01 phd thesis.pdf

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Study on the cognitive changes in STZ-induced diabetes with special reference to

glial changes and immune activation in rat hippocampus

A thesis submitted to

Jiwaji University

For the award of the degree of

Doctor of Philosophy in Neuroscience

By

Aarti Nagayach

Under the supervision of

Prof. I. K. Patro

School of Studies in Neuroscience, Jiwaji University, Gwalior (M.P.)

2015

36

Acknowledgements

At this moment of accomplishment I wish to express my sincere acknowledgements to

all those who have contributed to this thesis and supported me in one way or the

other during this amazing journey.

First and foremost, I would like to thank my supervisor Prof. I. K. Patro, School

of Studies in Neuroscience/ Zoology, Jiwaji University, Gwalior for encouraging my

research instincts and allowing me to grow as a research scientist. His treasured

advice, practical criticism and discussions helped me a lot in developing a researcher

perspective inside me. During the most difficult times of my thesis writing, he gave me

the support and freedom I needed to move on. I appreciate all his contributions of

timing and ideas to make my Ph.D. experience productive and stimulating.

My profound gratitude are reserved for Dr. Nisha Patro, Scientist, School of

Studies in Neuroscience, Jiwaji University, Gwalior. Her invaluable suggestions in

immunohistochemical technique have aided me well. I owe her my wholehearted

appreciation.

I express my gratitude to Hon’ble Prof. Sangeeta Shukla, Vice-chancellor, Jiwaji

University, Gwalior for providing all the necessary help and encouragement to our

department.

My deep sense of respect is due for Prof. P.K. Tiwari, Coordinator-Head, School

of Studies in Neuroscience, Jiwjai University, Gwalior for providing me the moral

support and encouragement during this tenure.

This work would not be possible without the fellowship of Indian Council of

Medical Research-Senior Research Fellowship (ICMR-SRF), New Delhi. Facilities and

support provided by Department of Biotechnology-Bioinformatics Information Facility

(DBT-BIF) and Department of Biotechnology-Human Resource Development (DBT-

HRD), Govt. of India, New Delhi is acknowledged.

I take this opportunity to genuinely acknowledge all my seniors who guided and

supported me from the early days of my research. Dr. Sarika Kuswaha, Dr. Kapil

Saxena, Dr. Meghna Saxena, Dr. Surya Awasthi, Dr. Amit Awasthi, Dr. Arpita Sharma,

Dr. Kamendra Kumar and Shashank sir, were among those whom friendly attitude and

elderly guidance kept me going at the beginning. I am extremely thankful to Dr. Vinay

Lomash, whose distinguished helping nature and ingenious suggestions helped me

immensely while doing histopathological studies and research paper writing.

Appreciations are due to my juniors Kavita, Brijendra, Aijaz, Deepika, Shrestha,

Nisar and Priya for being the most delightful lab-mates, providing a great working

environment and for their ‘anytime’ help, discussions and pleasing chats.

I am also indebted to my hostel friends (Samta di, Rohinika, Hrillekha, Preeti,

Aaliya, Shilpi, Manvi, Pooja and Preeto), not only for all their support, love and

concern but also for being there to listen whenever I needed an ear (amazingly

37

untiring listeners!!). My friends in hostel and other parts of the world (Trapti, Leena,

Naveen, Bhaskar, MAK, Arojit, Varun, Deepak and Abhilasha) were the sources of

laughter, joy and esteem support during the tough times of Ph.D. pursuit. EXTENDED,

HUGE and WARM thanks to you all!

I am thankful to Mr. Vishnu, Mr. Mahesh, Mrs. Seema and Mrs. Kavita our

departmental administrative staff members, who have always been kind enough to

advise and help me at the office front.

I am also thankful to our animal house keepers, Udaybhan and Awadesh for

routinely maintaining and taking care of the animals, I worked upon. I would also wish

to acknowledge Sureshji, for always keeping the working place clean and tidy,

undeniably needed for the good experimentation.

Last but not the least, I warmly thank and appreciate my family for their love

and encouragement. My deep and lasting gratitude is due to my ma and pa for their

unconditional love, faith and support that encouraged me to work hard and to

continue pursuing a research career. Their support without any complaint or regret

has enabled me to complete this Ph.D. tenure. I owe you my eternal appreciation and

affection. They are the reason I thrive to be better.

I must offer my thankfulness to the experimental rats who sacrificed their lives

for the accomplishment of this work.

Utmost of all, I praise the God, the Almighty for providing me this opportunity

and granting me the capability, indispensable to proceed with and complete this work

successfully.

Lastly, I would like to thank all the people, who are somehow, were involved in

this work and provided me with the necessary help and made it possible for me to

write this thesis.

Aarti Nagayach

38

ABBREVIATIONS

AD Alzheimer’s disease

AGE Advanced Glycation End products

ApoR3 apolipoprotein receptor-3

ATP Adenosine tri phosphate

BBB Blood Brain Barrier

BDNF Brain derived neurotrophic factor

BDV Borna disease virus

BSA Bovine serum albumin

CA1 Cornu Ammonis 1

CA2 Cornu Ammonis 2

Ca2+ Calcium ion

CA3 Cornu Ammonis 3

Caspase-3 Cystein aspartate protease-3

CNS Central Nervous System

COX-2 Cyclooxygenase 2

DAB 3’3- diaminobenzidine tetrahydrochloride

DAPI 4’6,- diamidino-2-phenylindole

DG Dentate Gyrus

DNA Deoxyribonucleic acid

DPX Distrene tricresyl phosphate xylene

EGL External granular layer

FITC Fluorescein isothioscynate

GFAP Glial fibrillary acidic protein

GLT-1 Glutamate transporter-1

GLUT-2 Glucose transporter-2

H2O2 Hydrogen peroxide

i.p Intraperitoneally

39

Iba-1 Ionized calcium binding adaptor molecule-1

IFN-ү Interferon-ү

IGIF Interferon Gamma Inducing Factor

IGL Internal granular layer

IL-10/12/15/18 Interleukin-10/12/15/18

IL-1β Interleukin-1β

IL-3/6 Interleukin-3/6

iNOS Inducible nitric oxide synthase

IP-10 IFN-γ-inducible protein-10

Jak/Stat Janus kinase/ Signal Transducer and Activator of Transcription

JNK c-Jun N-terminal Kinase

K+ Potassium ion

LPS Lipopolysaccharide

LTD Long term depression

LTP Long term potential

mAChR Muscarinic acetylcholine receptors

MAPK Mitogen-Activated Protein Kinase

MCP-1 Monocyte chemoattractant protein-1

M-CSF Macrophage colony – stimulating factor

MGluR2 Metabotrophic glutamate receptor 2

MHC class-I/II Major histocompatibility complex I/II

MIP-1α/β Macrophage-Inflammatory Protein-1α/β

MIP-2 Macrophage-Inflammatory Protein-2

ML Molecular layer

NF-kβ Nuclear factor kappa-light-chain-enhancer of activated B cells

NGF Nerve Growth factor

NGS Normal goat serum

NMDA N- methyl D- aspartate

40

NO Nitrous Oxide

NOS2 Nitric oxide synthase 2

NOX1/2 NADPH oxidase 1/2

NT-3 Neurotrophin-3

PBS Phosphate buffer saline

PD Parkinson’s disease

PKC Protein kinase C

RAC1 Ras-related C3 botulinum toxin substrate 1

RAGE Receptor for advanced glycation end products

ROS Reactive Oxygen Species

STZ Streptozotocin

TBS Tris buffer saline

TGF-β Transforming Growth Factor-β

TLR Toll-like receptors

TNF Tumor necrosis factor

TRITC Tetra methyl rhodamine isothiocynate

TrK A Tropomyosin receptor kinase A

41

SYMBOLS

cm Centimetre

g Gram

hr Hour(s)

L Litre

kg Kilogram

m Metre

μl Microlitre

μM Micomolar ( mole/litre)

μm Micrometre

mg Milligram

ml Milliliters

mm Millimeters

min Minute(s)

mM Milli molar (m mole/litre)

M Molar (mole/litre)

rpm Revolution per minute

sec Second(s)

wt. Weight

β beta

α alpha

γ gamma

42

CONTENTS

Introduction 1-4

Review of Literature 5-34

Materials and Methods 35-60

Results 61-86

Discussion 87-106

Summary and conclusions 107-118

Photomicrographs & graphs 119-181

References 182-223

Appendix I 224-226

Publications & presentations 227-228

43

INTRODUCTION

Diabetes is the most prevalent heterogeneous endocrine disorder characterized by

hyperglycemia due to the absolute and relative insulin deficiency that results from

inadequacies in insulin secretion or action or both. According to the world health organization

(WHO) 2014 fact sheets, diabetes mellitus is one of the non-communicable diseases that will

be the 7th

leading cause of death in 2030 globally. The ramification of diabetes associated

impediments is not just limited to the insulin dependent organs. Irrespective of its two major

forms, i.e., type 1 and type 2, diabetes mellitus is associated with several comorbid

complications including structural and functional dysfunctions in central nervous system (Mc

Call, 1992; Biessels et al., 1994; Coleman et al., 2004; Guven et al., 2009) and end organ

damage via many diverse mechanisms. In so far, the cellular mechanisms affecting the brain

functioning during diabetic state are still not well understood. Accordingly, the diagnostic

approaches or therapeutic tools to comprehend and treat the cognitive and behavioural deficits

in diabetes are in vain.

Studies have depicted that the prevalence of cognitive deficits and emotional alterations

are two times more in diabetic patients than in the non-diabetic population. Cognitive and

behavioural dysfunctions are being the most apparent CNS impairments well-reported in both

humans (Petrofsky et al., 2005; Kodl and Seaquist, 2008; Alvarez et al., 2009) and animal

models of diabetes (Biessels, 1994; Coleman et al., 2004; Guven et al., 2009). These

dysfunctions were resulted in impaired cognitive and psychiatric ability, dementia and

alterations in learning and memory (Gispen and Biessels, 2000; Popoviç et al., 2001; Allen et

al., 2004; Arvanitakis et al., 2006; Zavoreo et al., 2014; Nagayach et al., 2014a). Patients with

diabetes and hyperglycemia also reported with poor motor coordination and reduced motor

activity (Daneman, 2001; Petrofsky et al., 2005; Cox et al., 2005; Nagayach et al., 2014b).

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The causative factors for these alterations are presumed as dysregulated glucose utilization via

glucose transporters (Duelli et al., 2000), oxidative stress (Sharma et al., 2010; de M Bandeira

et al., 2013) and deposition of advanced glycated end products (Wang et al., 2009) etc.

The hippocampal formation, an elemental hub for the various aspects of cognition and

behavioural processes is particularly sensitive to the glucose homeostatic alterations (Routh,

2002; Huang et al., 2007). Hyperglycemia supplies additional substrate for anaerobic

glycolysis in the brain, which further results in lactic acidosis and enhanced damage to both

glial and neuronal cells (Biessels et al., 1994). Concomitantly hyperglycemia also augment

the formation of oxygen free radicals following lipid peroxidation in the brain tissues which

later contributes to increased neuronal death (Hawkins and Davis, 2001; Hernández-Fonseca

et al., 2009; Guven et al., 2009) and astrocytic glial reaction (Barber et al., 2000). Diabetes

not only affects the cell proliferation associated neurogenesis but also restricts the synaptic

plasticity in hippocampal neurons (Saravia et al., 2004; Zhang et al., 2008; Alvarez et al.,

2009; Mardirossian et al., 2009) which possibly leads to the deterioration of hippocampal

functioning.

In the nervous system, neurons do not exist in isolation; they are accompanied by a

heterogeneous group of cells known as glial cells. Several researchers have evidenced that

glial cells were endowed with a wide range of indispensable regulatory and immune functions

in the CNS. Glia (astroglia and microglia) have a wide range of tasks in CNS ranging from

the regulation of innate immunity, scavenging dead cell debris, scaffolding and protecting

neurons to the regulation and maintenance of synaptic transmission and putative integration of

information with neurons. Following any brain insult or immune breaching, glial cells get

activated and exhibit morphological transformations from resting to activated, increase in

their cell population and secrete an array of inflammatory molecules to combat the baleful

condition (Patro et al., 2005; Luo and Chen, 2012; Boche et al., 2013; Verkhratsky et al.,

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2014a). Glial activation based on the progression of insult and severity of stimulus, imposes

contrasting features of brain curator (Morgan et al., 2004; Luo and Chen, 2012; Wang et al.,

2013; Peng et al., 2014) and/or executioner (Heneka et al., 2010; Verkhratsky et al., 2014a,c;

Verkhratsky and Parpura, 2014). Conclusively, the multifarious attribute of glial cells had

made them an ideal target for therapeutic interventions during various neurodegenerative

diseases and disorders.

Despite of universal acceptance, of glial participation in cerebral health and disease, the

information regarding functional and structural stature of glial cells and allied changes

following diabetes are still ineffectual. Thus, a pertinent research is needed to clarify the

impact of diabetes on glial cells per se or their rejoinder effects on neuronal cells with special

reference on associated brain functions. Concomitantly, the neuro-immunological aspects of

neurodegeneration and neuroregulation following diabetes also require specific attention.

Evidences are also instigating an insight on possible role of oxidative stress following

diabetes in perpetuation of glial activation, neuronal cell death and associated immune

response. Thus, an associative reciprocity between metabolic stress, cell death and gliosis in

hippocampus also deserve consideration as they have never been studied and will provide an

effective window to understand the underlying cellular mechanism following diabetes in

brain.

Thus, the present study was intended to elucidate the scenario of glial activation,

cellular degeneration and associated immune response either neuroprotective/ degenerative in

consort with subsequent behavioural and cognitive alterations during experimentally induced

diabetes in rats. This information will provide an insight which not only help in understanding

the aura of consequent complications of diabetes but also in establishing a concrete strategic

therapeutic approach for developing the treatment of diabetes associated cognitive and

behaviour deficits.

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Therefore, the main objectives of the present study are:

a) To study the glial response following STZ-induced diabetes state and associated neuronal

damage with special reference to neuroimmunological changes.

b) To record the phenotype changes in microglia and astrocytes following STZ-induced

diabetes.

c) To correlate the cognitive changes following induced hyperglycemia to the allied glial

response in terms of immune activity.

47

REVIEW OF LITERATURE

1. Diabetes mellitus: Global health havoc

Diabetes mellitus is a global health problem swiftly attaining the status of a potential

epidemic. According to a report of world health organization (WHO), there are 347 million

people worldwide suffering from diabetes (Danaei et al., 2011), and this number is estimated

to double by 2030 (WHO, 2013). In India, about 62 million people are facing the prevalent of

diabetes, and presumably this number will become 79.4 million in the next fifteen years

(Kaveeshwar and Cornwall, 2014).

Diabetes mellitus is a heterogeneous endocrine disorder mainly categorized in two

forms, i.e., type 1 and type 2. Type 1 diabetes is an autoimmune disorder resulting from the

absolute or relative destruction of the pancreatic beta cells leading to depletion in insulin

production. It is also defined as insulin-dependent diabetes mellitus (IDDM). Type 2 diabetes

is non-insulin-dependent diabetes mellitus (NIDDM) characterized by the reduced insulin

sensitivity or relative insulin deficiency. Irrespective of its form, diabetes mellitus associated

chronic hyperglycemia trails various micro- and macro-vascular complications. Diabetes

alters the blood-glucose homeostasis which further affects the end-organs like kidney, eyes,

brain, etc. In addition to this, diabetes has also been associated with many structural and

functional complications in both central and peripheral nervous system (Biessels, 1994;

Baydas et al., 2005; Guven et al., 2009). The underlying mechanism(s) causing these

alterations are not fully understood. The presumed causative factors are (i) variations in the

cerebral energy homeostasis and metabolism possibly through fluctuation in blood-glucose

level (Horani and Mooradian, 2003; Brands et al., 2004; Scherbakov et al., 2012); (ii) changes

in osmolar gradients in hyperglycemia (Stevens et al., 1993; Wang et al., 2012); (iii)

dysregulated glucose utilization via glucose transporters (Duelli et al., 2000; Lacombe, 2014);

(iv) acute and/ or chronic metabolic and vascular impairment, such as deficits in cerebral

48

blood flow, changes in osmolytes (Biessels et al., 2002; Brands et al., 2004) as well as

oxidative stress (Sharma et al., 2010; Wang et al., 2011; Soares et al., 2012; de M Bandeira et

al., 2013), deposition of advanced glycated end products (Yan et al., 2008; Wang et al., 2009;

Vlassara and Striker, 2013) and the altered levels of ketone bodies (Felig, 1974; Balasse and

Fery, 1989; Umpierrez et al., 2002) may cause functional and structural cerebral changes in

diabetic patients (Biessels et al., 2002; Brands et al., 2004).

1.1. Type 1 diabetes

Type 1 diabetes is a common and chronic disorder with notable incidence in children

and adolescents. It is due to the auto-immune destruction of pancreatic beta cells leading to an

absolute loss of endogenous insulin production (Atkinson, 2001; Bluestone et al., 2010). This

results in elevation of blood-glucose level (hyperglycemia) trailing the characteristic

symptoms of type-1 diabetes i.e., polydipsia, polyuria and body weight loss. In a diabetic state

as body run out of the insulin, the energy extraction from blood glucose gets depleted and

then frequent need of energy causes the breakdown of fats (through lipolysis and release

glycerol and free fatty acids) and other stored energy reservoir which further results in sudden

body weight loss. Furthermore, the increased level of free fatty acids get converted into

ketones and resulted in elevated ketone level and decreased hydrogen ion concentration (pH)

in the body fluids. The accretion of ketones in body fluids, reduced pH and electrolyte level

and dehydration from excessive urination, and alterations in the bicarbonate buffer system

result in diabetic ketoacidosis (DKA). Uncontrolled severe hyperglycemia is prone to develop

DKA that can result in coma or death. Similarly, the increased glucose content in blood also

causes osmotic effect and starts pulling out water from the body to dilute the excess of

glucose that causes the excessive thirst or polydipsia and subsequently resulted in the state of

polyuria in order to dampen the superfluous glucose water in form of urine. The abrupt body

weight loss due to low energy conversion and conservation by the cells leads to hunger state

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and resulted in polyphagia to compensate the energy loss required for normal body

functioning and maintenance.

1.1.1. Pathophysiological mechanism

Diabetes-related impediments are not just limited to the insulin dependent organs like

muscle and adipose tissue but also extended upto the other vital organs, i.e., kidney, liver,

eyes and brain. These organs are directly affected by the glucose toxicity allied

hyperglycemia during the diabetes mellitus.

Hyperglycemia dramatically alters the function of various cell types and their

extracellular matrix causing changes in structure and functions of the affected tissue.

Hyperglycemia trailed diabetes causes glycation of proteins, fats and nucleic acids. The

advanced glycation end products (AGEs) accumulate in renal glomerulus, endoneurial areas,

microvasculature of the retina and at the walls of the larger blood vessels.

The invariant critical participation of various cellular pathways generated and/ or

stimulated by diabetes allied hyperglycemia is well known in reinforcing the possible reasons

of diabetic complications (Fig. 1; Brownlee, 2001; Vlassara and Palace, 2002). During

diabetic state excess of glucose get converted into sorbitol and fructose through polyol

pathway and generate a milieu of osmotic stress inside the cell which further resulted in the

oxidative stress and cell death. Similarly formation of advanced glycation end products

(AGEs) and increased glucose shunting in the hexosamine pathway stimulate the

inflammatory signals which later on ensues the diabetic complications. Furthermore

superfluous AGEs production increases the level of circulating AGEs and affects the normal

protein functions of the cell which ultimately causes the alterations in renal, vascular and

connective tissues. Stress signalling via MAPK, Jak/Stat, p38 and NF-kβ pathway is an

another marked consequent of hyperglycemia resulting in elevation of cytokines and iNOS

level developing the state of vascular damage and cell death. Hyperglycemia also leads to the

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mitochondrial dysfunctions leading to the activation of protein kinase C isoforms which

further leads to oxidative stress allied, alterations of structural proteins and damage the

relative organ via causing alterations in gene expression and enzyme functions. Thus, type 1

diabetes resulted in long-term complications, which develop gradually and even increase the

risk of other life-threatening and disabling syndromes.

1.2. Effect of diabetes on brain

Diabetes associated hyperglycemia induces multiplying changes in vascular and

neuronal cells, as well documented in both animal model of diabetes and diabetic patients.

The changes at both cellular and functional level following diabetes are pleotypic in nature as

the flow of glucose and its metabolites is well-known to affect several cellular pathways. As

glucose is the prime source of energy in brain, and its consistent functioning is reliant on the

continuous supply of glucose (Clarke and Sokoloff, 1999; Mergenthaler et al., 2013), so any

alteration in glucose content or supply would possibly affect the cerebral functions (Ryan et

al., 2004; Oddo et al., 2008). The well-recognized diabetic impediments in CNS are listed as:

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impaired cognition (Gispen and Biessels, 2000; Allen et al., 2004; Arvanitakis et al., 2006;

Biessels et al., 2008; Kodl and Seaquist 2008; Nagayach et al., 2014a; Mayeda et al., 2015),

dementia (Biessels et al., 2002; Wessels et al., 2008; Cheng et al., 2012; Crane et al., 2013),

altered learning and memory processes (Popovic et al., 2001; Baydas et al., 2003; Choi et al.,

2009; Capiotti et al., 2014), stroke (Tiehuis et al., 2008; Eriksson et al., 2012; Hägg et al.,

2014), cerebrovascular disorders (Mankovsky et al., 1996; Yan et al., 2013) and Alzheimer‟s

disease (Ahtiluoto et al., 2010; Kim et al., 2013; Wang et al., 2015).

1.2.1. Mechanism and consequent effect of cellular damage following diabetes in brain

During diabetes increased level of glucose reacts with oxygen and generates a series of

oxidative radicals. The state of oxidative stress caused by these free radicals increase the

polyol pathway activation, formation of advanced glycation end products (AGEs), enhance

the activation of protein kinase C and glucose shunting in the hexosamine pathway that could

ultimately damage the cell constituents and resulted in cell death (Yamagishi et al., 2003; Van

Harten et al., 2006). Hyperglycemia instigated through reduced level of insulin provides

substrate for the anaerobic glycolysis that resulted in brain lactic acidosis and dehydration

which further involved in diminished cerebral blood flow and ischemia (de Kloet et al., 1998;

Chan et al., 2003).

Long term studies on STZ-induced rodent model characterized the diabetic

encephalopathy in relevant regions of the brain i.e., cerebral cortex, cerebellum and

hypothalamus. Diabetes trigger various morphological changes in brain cells like increased

area of myelinated neurons, disarrangement of myelin sheath, perivascular and mitochondrial

swelling, presynaptic vesicle dispersion in swollen axonal boutons and fragmentation of

neurofilaments (Hernández-Fonseca et al, 2009). Interestingly the oxidative and nitrosative

stress milieu in the brain of STZ-induced diabetes rats was imposed by the mitochondrial

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swelling and vacuolation (Mastrocola et al., 2005) caused by increased intracellular glucose

level or via other damaging inducers following diabetes (Hernández-Fonseca et al, 2009).

Among various brain regions hippocampus is more susceptible to diabetes. Previous

studies conducted on both spontaneous model of autoimmune T1D (NOD mice) and STZ-

induced model depicted the deleterious effect of diabetes. Diabetes dramatically decreases the

cell proliferation (Saravia et al., 2004; Revsin et al., 2009; Piazza et al., 2011), altered the

neurogenesis (Beauquis et al., 2006, 2008; Bachor and Suburo, 2012) and causes neuronal

apoptosis in hippocampus (Beauquis et al., 2006, 2008; Nagayach et al., 2014a) and damaged

the dendrites and synaptic structures of CA3 neurons (Jackson-Guilford et al., 2000; Li et al.,

2002; Zhang et al., 2008). Diabetes also reduced the dendritic growth of newly formed

neurons in dentate gyrus that severely affect the neurogenesis (Alvarez et al., 2009; Choi et

al., 2009). The deleterious effects of diabetes not only limited to the malfunctioning of the

hippocampal cells but also affecting the synaptic plasticity (Mardirossian et al., 2009; Detka

et al., 2013) and associated learning memory (Stranahan et al., 2008; Revsin et al., 2009;

Piazza et al., 2011). The above discussed consequent of diabetes on hippocampus provides an

iota of explanation for the cognitive impairment following diabetes.

2. Experimental animal models of diabetes mellitus

For the advancement of information and to explore the facts, several animal models

have been established to study the diabetes mellitus and related consequences more precisely.

These models are not just providing evidence regarding pathogenesis of the disease but also

helping to a great extent in developing therapeutic preventive strategies to combat the diabetic

state and associated complications. These animal models were developed using chemical,

genetic, surgical (pancreatectomy) and other techniques. Success of these animal models

relies on their depiction of various clinical features and related phenotypes of diabetes

mellitus.

53

Chemicals used to create the diabetic animal models are aimed to selectively destroy the

pancreatic beta cells partially or completely and retain the hyperglycemic state for a

sustainable duration without causing unsolicited syndromes other than diabetes. Studies over

the past 70 years considered, alloxan and Streptozotocin (STZ) as the most used chemical

substances for developing successful animal models for both Type 1 and Type 2 diabetes

mellitus (Mc Neill, 1999; Rees and Alcolado, 2005; Ventura-Sobrevilla et al., 2011). The

universal proclaim regarding alterations in pancreatic beta cells as well as in the animal

physiology following alloxan (Lenzen and Patten, 1988; Kikumoto et al., 2010) and

streptozotocin (Rakieten et al., 1963; Balamurugan et al., 2003; Eleazu et al., 2013) induced

diabetes made them a well-accepted diabetogenic drug even today. The metabolic

disturbances in rats caused by these diabetogenic drugs (Szkudelski et al., 1998, 2013) and

their mechanisms of cytotoxic action on the pancreas are thoroughly illustrated by various

studies (Lenzen and Patten, 1988; Szkudelski, 2001; Hayashi et al., 2006; Lenzen, 2008).

Streptozotocin and alloxan exert their effect via administrating parentally (intravenous,

intraperitoneal or subcutaneous) at specific dose depending upon the animal species and

nutritional status of the animal (Federiuk et al., 2004; Etuk and Muhammed, 2010).

Intriguingly, besides having similar diabetogenic action, streptozotocin is widely opted

over alloxan for developing the animal model for diabetes (Islas-Andrade et al., 2000; Lee et

al., 2010; Eleazu et al., 2013). Streptozotocin is not only capable of inducing an irreversible

long-term effect of diabetes (Gaulton et al., 1985; Méndez and Ramos, 1993; Eleazu et al.,

2013) but also has a low mortality rates in comparison to alloxan (Mansford and Opie, 1968;

Lenzen, 2008; Chatzigeorgiou et al., 2009; Deeds et al., 2011).

3. A brief account on Streptozotocin: A diabetogenic drug

In 1963, Rakieten and his co-workers claimed that streptozotocin is a diabetogenic drug.

It is a naturally occurring broad-spectrum, cyto-toxic chemical isolated from a mould

54

streptomycetes achromogenes. Streptozotocin is popularly used to induce both insulin-

dependent and non-insulin dependent diabetes mellitus.

Chemical name: 2-deoxy-2-([(methylnitrosoamine) carbonyl] amino)-D glucopyranose

Structure:

Cytotoxic methylnitrosourea moiety (N-methyl-N-N-Nitrosourea) attached to the glucose

(2-deoxyglucose) molecule.

Mechanism of Action

Streptozotocin induces diabetes in mammals via inhibiting insulin production in pancreas by

killing beta cells.

Streptozotocin (through i.p. or i.v. injection)

Pancreatic beta cell

Streptozotocin selectively accumulates in the pancreatic beta cells through low affinity

GLUT-2 transporters (Tjälve et al., 1976). The DNA alkylating methylnitrosourea moiety

(especially at o6 position of guanine) of STZ causes DNA fragmentation (Bennett and Pegg,

1981; Murata et al., 1999; Szkudelski, 2001) alongwith a defined chain of damaging events

55

like protein methylation (Bennett and Pegg, 1981; Wilson et al., 1988), nitric oxide (NO)

generation that inhibits aconite activity (Kröncke et al., 1995) and reduced level of cellular

NAD+ and ATP (Uchigata et al., 1982) that conclusively causes necrotic cell death and

hamper the insulin biosynthesis and secretion (Yamamoto et al., 1981; Uchigata et al., 1982).

Furthermore, the diabetogenic toxicity of streptozotocin is also accompanied and accelerated

by the resultant oxidative stress caused due to a low level generation of ROS, counting

superoxide and hydroxyl radical generation from hydrogen peroxide dismutation during

hypoxanthine metabolism following enhanced ATP dephosphorylation.

4. The brain cells

Cellular organization of central nervous system (CNS) is mainly constituted of about

10% neurons and 90% of glial cells. Despite of dissimilarity in cellular excitability the

reciprocal communication between neurons and glial cells, accomplish the appropriate

functioning and maintenance of CNS.

4.1. Neuroglia

One hundred and fifty years ago i.e., on 3rd April 1858, the whole neuroscience world

came to know about the term „neuroglia‟ (nerve glue) when a German pathologist, Rudolf

Ludwig Karl Virchow described them. For Virchow, neuroglia was a connective material

around the neuron just binding them together. Although these glial elements were also

recognized even before Virchow‟s proclaim, but Virchow‟s nimble description made them a

confrontational entity to study and explore in the brain. Soon after, many different forms of

glial cells were described and images published by Otto Deiters (1850s), Jacob Henle (1869),

Camillo Golgi (1898), Gustav Retzius (1894) and many others.

There are different types of glial cells, i.e., astrocytes, microglia, oligodendrocytes,

Schwann cells and radial glial cells. Each of these glial cell types has its own specific

attributes, tasks and characteristics. It was speculated that there are at least 10 glial cells for

56

every single neuron. As their size is much smaller than neurons, they occupy about 50% of

the total volume of nerve tissue. Glia were involved in several functions ranging from

scavenging debris, scaffolding and protecting neurons, facilitating the synaptic transmission,

to putatively integrate the information with neurons. Thus, there have been many

groundbreaking studies that are devoted to the structure and functions of glial cells and

establish their important and beneficial roles in brain functioning and disorders (Verkhratsky

et al., 2014a). An article in Forbes Magazine (July 13, 2009) asserted that glial cells may even

be more imperative than neurons for treating neurodegenerative diseases.

4.1.1. Astrocyte

Astrocytes (also known as astroglia) are characteristic star-shaped glial cells in the

nervous system. The term „astrocyte‟ a greek word stands for the star-shaped cell („Astar‟

means star and „cyte‟ means cell), which was first proposed by Michael von Lenhossek in

1893, and subsequently, it gained universal acceptance. Astrocytes have been observed as an

intricate community of cells. True and the largest group of astrocytes share a similar stellate-

shaped architecture, multiple extended thin processes, interface connection with blood vessels

and close communications with both neighbouring neurons and mesenchymal elements of the

brain (Volterra and Meldolesi, 2005).

Astrocytes are the most abundant macroglial cells in the CNS, having numerous

projections. Astrocyte is a parasol term for a heterogeneous population of cells that is highly

vulnerable to its local environment. In addition to their vastly different territorial organization

across brain regions and species, astrocytes also differ in their physiological properties such

as membrane potential, potassium conductance, glutamate transporter, receptor expression

and the expression of proteins such as glial fibrillary acidic protein (GFAP; Kalman, 1998;

Doetsch, 2003; Oberheim et al., 2012).

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4.1.1.1 Functional properties of astrocytes

Astrocyte functions are grouped into three main categories: guidance and support of

neuronal migration during development (Peretto et al., 2005; Bozoyan et al., 2012),

maintenance of the neural microenvironment (Stitt et al., 1991) and modulation of immune

reactions by serving as antigen-presenting cells (Dong and Benveniste, 2001; Girvin et al.,

2002; Barcia et al., 2013). The star-shaped cells are regarded as crucial homeostatic cellular

element in the brain as it controls the brain environment by regulating the volume and

composition of extracellular space (Kettenmann and Verkhratsky, 2008) and controls the

extracellular ion- metabolite- and neurotransmitter homeostasis (Haydon and Carmignoto,

2006; Verkhratsky and Butt, 2007; Verkhratsky and Parpura, 2010). They also play an

important role in secretion or absorption of neural transmitters (Perea et al., 2014) as well as

in the maintenance of the blood-brain barrier (Bundgaard and Abbott, 2008; Alvarez et al.,

2013). Both in vivo and in vitro studies revealed that astrocytes mediate neurotrophic signals

and ardently promote the neuronal survival in the CNS (Wagner et al., 2006). The astrocytes

express, both ligand-gated and voltage-dependent ion channels (Sontheimer, 1994; Porter and

McCarthy, 1997; Verkhratsky and Steinhauser, 2000), and are proposed to have the general

function of clearing neurotransmitters and ions away from the synapse (Henn and Hamberger,

1971; Perdan et al., 2009). Astrocytes interact with essentially all other cellular elements of

the brain. They contain high affinity glutamate transporters that are critical in maintaining the

extracellular glutamate concentration at sub-excitotoxic levels and thereby preventing

neuronal cell death (Rothstein et al., 1994, 1996; Anderson and Swanson, 2000; Verkhratsky

et al., 2014b). Furthermore, astrocytes also play an active role in modulating the neuronal

activity and behaviour (Perea and Araque, 2007; Navarrete and Araque, 2008; Halassa and

Haydon, 2010). Metabolically, astrocyte supports the neurons by providing them lactate as a

nutrient (Cakir et al., 2007; Brown and Ransom, 2007; Magistretti, 2008). Experimentally

58

activated astrocytes express some metabolic enzymes and transporters, which supports in

boosting the resistance towards metabolic injuries and facilitates the neuronal survival

(Escartin et al., 2007). This plethora of functions makes these cells as an ideal concierge of

neurons.

4.1.1.2. Astrogliosis

Astrogliosis is another popular term used for the astrocytic activation. Astrocytes‟

customary functioning may be enhanced by its activation via pharmacological agents or

induction of astrocyte reactivity in various pathological conditions. On activation, astrocytes

exhibit discernible morphological and functional changes (Figure 2). In response to any stress,

injury or pathological conditions, quiescent astrocyte having fine processes transform into

activated state that comprises thick hypertrophic processes and soma with the upregulation of

cytoskeletal components like glial fibrillary astrocytic protein (GFAP), vimentin, nestin and

S100β (Pekny and Nilsson, 2005; Buffo et al., 2010). Activated astrocytes migrate towards

the infected region and demarcate it from the healthy part by forming glial scar, a type of

anisomorphic gliosis (Kalman, 2004). Astrogliosis as an emblem of neuroinflammation

generally considered as a pathological reaction that further instigate a negative influence on

the brain pathology. In contrast to this general view, customized astrocyte activation based on

the progression of insult and severity of stimulus, may also imposes a defensive and beneficial

effect upon the brain cells (Sofroniew and Vinters 2010; Verkhratsky et al. 2012; Colangelo et

al., 2014).

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Furthermore, astrocytes secrete several inflammatory molecules that directly or

indirectly help in the general improvement of brain cell functions like enhanced glutamate

uptake, reorganization of metabolic pathways, modulation of synaptic transmission, etc.

(Liberto et al., 2004; Sofroniew, 2005; Vesce et al., 2007; Pekny et al., 2007 ; Claycomb et

al., 2013). Astrogliosis has also been implicated in the pathogenesis of a variety of

neurodegenerative diseases, including Alzheimer‟s disease, Parkinson‟s disease, Huntington‟s

disease, inflammatory demyelinating disease, cerebral ischemia and Prion-associated

spongiform encephalopathy (Mena and García, 2008; Takano et al., 2009; Sofroniew and

Vinters 2010; Verkhratsky et al., 2012; Verkhratsky et al., 2014c). This intrinsic ability of

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astrocytes makes them important therapeutic targets as they stringently retort to every sort of

brain injury and act as saviour via developing a broad range of defence mechanisms against

injury or insult.

4.1.2. Microglia

Microglia were first recognized by Nissl in 1880 and thoroughly portrayed by a Spanish

neuroanatomist, Pio-del Rio-Hortega as resting ramified cells by light microscopy and silver

staining methods. Microglial cells constitute about 5-20% of glial population in central

nervous system. As immunocompetent nomadic cells of the brain, microglia continuously

survey the CNS microenvironment with their highly motile extensions for any kind of brain

insult or injury. As resident immunocompetent phagocytic cells, they perform functions

similar to those of tissue macrophages present in other organs and comprise the first line of

defence against any baleful invasion. The well-accepted notion of microglia structural

plasticity in response to the adverse conditions and its dual action following various

pathological conditions, were vastly studied in both in vivo and in vitro models of animal and

humans. Moreover, in addition to the defensive role, microglia also takes part in the

maintenance and regulation of various vital processes of brain functions throughout the

lifespan, which have been neglected so far.

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In normal healthy brain „resting (ramified) surveillent‟ microglia resides at strategic

locations throughout the entire brain and spinal cord. The rationale of this state is to maintain

a constant level of available microglia to detect and fight the infections (Aloisi, 2001;

Christensen et al., 2006). In the resting or ramified state, microglial cells release neurotrophic

growth factors to promote neuronal survival and enhance the neurogenesis (Kim and de

Vellis, 2005; Ekdahl et al., 2009; Shigemoto-Mogami et al., 2014; Sierra et al., 2014). During

various neurodegenerative diseases and brain insults resident/ resting microglia turn into

activated or reactive microglia (Streit et al., 1999; Ling et al., 2001; Minghetti et al., 2005;

Lull and Block, 2010). Under adverse circumstances microglia release myriad of

inflammatory molecules, growth factors, matrix proteins, chemokines, prostanoids and

reactive free radicals (Fig. 3) which contribute in dual form i.e., either impose neuronal

dysfunction and cell death or provide support in the healing of damaged tissues (Block et al.,

2007; Colton, 2009; Gomes-Leal, 2012; Hellwig et al., 2013). The biphasic (detrimental or

beneficial) role of microglia depends upon the progression of insult and severity of the

stimulus.

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4.1.2.1. Microglial structural plasticity

Morphologically, three major types of microglial forms appear: amoeboid, ramified or

resting and reactive or activated. These different transition stages make them effectively

perform varied functions in the brain (summarized in Table 1).

Table 1: Functions of microglia during different transition phases

Amoeboid microglia Ramified microglia Activated microglia

Regulate gliogenesis

(Giulian et al., 1988).

Phagocyte the degenerating

cells (Ling et al., 2001).

Remodeling of nervous

tissue (Ling, 1976).

Tissue histogenesis via

removing inappropriate and

superfluous axons (Marín–

Teva et al., 2004).

Promotes axonal growth and

migration (Polazzi and

Contestabile, 2002).

Astroglial proliferation

Vigilant surveyor of function

and integrity of brain (Davalos

et al., 2005).

Precursors for active

macrophages (Davis et al.,

1994).

Virtual scavenger during

normal remodeling of

neocortex (Streit, 2001).

Mitigate excitotoxicity-

induced degeneration (Vinet et

al., 2012).

Prevent diffusible

neurotransmitters activity

(Booth and Thomas, 1991).

Major source of

pleiotropic cytokines

(Tambuyzer et al., 2009).

Helps in regeneration

(Rapalino et al., 1998).

Contribute in the

maintenance of chronic

pain (Hains and Waxman,

2006).

Secrete neurotrophic

factors (Streit, 2002).

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(Giulian and Baker, 1985).

Determinant of cell fate

during development

(Vilhardt et al., 2005).

Function as antigen

presenting cell in developing

brain (Ling et al., 1991).

Protect against glutamate

excitotoxicity (Kaur et al.,

2006; Vinet et al., 2012).

Promote maintenance of neural

stem cells (Zhu et al., 2008).

Provide neurotrophic support

to other brain cells (Streit,

2002).

Contributes to metabolite

removal and debris clearance

following injury (Fetler and

Amigorena, 2005).

Amoeboid microglial cells are round or irregular in shape and are prevalent during

development and rewiring of the brain. Morphologically, they closely resemble with the

macrophages. Amoeboid microglia seeds via primitive myeloid/ haematopoietic progenitor

cells during the embryonic and perinatal stage and sustain upto the early postnatal stages

(Ginhoux et al., 2010; Prinz and Mildner, 2011; Kierdorf et al., 2013). Later at postnatal

stages of development these amoeboid microglia transform into ramified (resting) microglia

(Kaur et al., 1985; Kaur and Ling, 1991).

Ramified or resting microglial cells are the monitoring immune cells of the adult CNS.

Ramified microglia have a small cell body with short, wispy and fine processes extending into

the brain microenvironment and creating a matrix like structure to better perceive the CNS

milieu. The term resting is a misnomer as these microglial cells in a healthy brain

continuously survey the CNS for any damage or insult, so they are not resting but active

64

(Ransohoff and Cardona, 2010; Kettenmann et al., 2011; Aguzzi et al., 2013; Kettenmann et

al., 2013). In vivo time-lapse video microscopy in mouse has confirmed that the fine

processes and protrusions of ramified or resting microglia cells constantly sample the CNS

microenvironment (Nimmerjahn et al., 2005). As such they are never in a resting state in the

brain.

Reactive Microglia

In response to any unfavourable stimuli ramified microglia are transformed into a

reactive or activated state characterized by thick and retracted processes with a large and

irregular shaped cell body (Gehrmann, 1995). Reactive microglial cells during the disparaged

condition starts proliferating to better screen and fight back against the sabotage (Niquet et al.,

1994; Huttmann et al., 2003). The population increment and morphological transformation of

such reactive cells in affected site is considered as the hallmark of microglial activation (Perry

et al., 1985; Castano et al., 1996).

The intricacy to identify the microglial function is eclipsed by the differential

phenotypes of the cells, as microglial activation generally acts in two ways either help in

efficacious restoration of injured brain cells or generates a threatening environment which

causes subsequent brain alterations depending upon the stimulus and progression of the

diseased state. To overcome the situation, an activation spectrum was exemplified to

characterize the activity-dependent microglial activation. The spectrum was developed on the

basis of cytoactive factors released by the reactive microglia.

The “classical activation (popularly known as M1 phase)” is the initial innate immune

response induced by TLR ligand and IFN-ү followed by the generation of pro-inflammatory

cytokines (Luo and Chen, 2012; Boche et al., 2013). This state of microglial activation

promote the protection of damaged tissue via defending against the pathogens by releasing a

plethora of pro-inflammatory molecules (like TNF-α, IL-6, IL-1β, IL-12; Benoit et al., 2008),

65

superoxide anions, nitric oxide synthase and proteases etc.), redox (NOX2, NOX1, RAC1,

iNOS, NOS2 etc.) and excitotoxic molecules (MGluR2, GLT-1, P2X7-R etc.). Another phase

of microglial activation is “M2 or alternate activation” phase. This is considered as a

protective phase as it is characterized by the production of anti-inflammatory molecules such

as TGF-β, IL-10, scavenging receptors and extracellular matrix. The cytoactive molecules of

this phase down-regulate the generation of pro-inflammatory molecules and accelerate the

process of wound healing and damaged tissue repair (Martinez et al., 2008). The third or

subtype of M2 phase is termed as “acquired deactivation”. It is associated with deactivation of

glial inflammation and uptake of apoptotic cells or oxidized lipids via the release of anti-

inflammatory cytokines (Elenkov and Chrousos, 2002; Luo and Chen, 2012; Boche et al.,

2013) and glucocorticoid hormones (Mantovani et al., 2004).

5. Role of glial activation in CNS

In the central nervous system, glial cells as a heterogeneous group of cells perform varied

functions, i.e., to shape the microarchitecture of the brain, provide support and protection,

control extracellular ion- metabolic- and neurotransmitter homeostasis, form myelin, destroy

and remove the carcasses of dead neurons, and help in signal transmission, etc. Several

studies have elucidated the functions performed by activated microglial and astroglial cells

following stringent pathological conditions, injuries and stress in the brain. Glial cells are the

dynamic entities that exhibit morphological changes reliant upon their cellular

microenvironment. The morphological alterations in both astroglia and microglia are

considered as a reliable marker of their activated state, which further trailed by the severe

influence on brain cells and associated functions.

5.1. Microglial activation

Microglial cells being resident and as immunocompetent phagocytic cells perform

functions similar to those of tissue macrophages present in other organs and constituting the

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first line of defence against invading pathogens (Streit, 2002; Vilhardt, 2005). In response to

neurodegenerative stimuli either via any infection (Voorend et al., 2010; Mutnal et al., 2011;

Tripathi et al., 2014), injury (Galiano et al., 2001; Patro et al., 2005, 2010b), inflammation

(Riazi et al., 2008; Patro et al., 2004; Patro et al., 2010a), blood brain barrier (BBB) damage

(Davies et al., 1998; Stoll and Jander, 1999) or metabolic disorder (Nagayach et al., a,b),

microglia get activated and release an incredible array of immunocompetent molecules, which

comprise numerous chemokines like KC, MIP-1α, MIP-1β, MIP-2, MCP-1, RANTES, IP-10,

and IL-8 (Hanisch, 2002) and interleukins like IL- 1α/β (Peterson et al., 1997; Meda et al.,

1999; Nagai et al., 2001), IL-3, IL-6 (Pulliam et al., 1995; Nagai et al., 2001), IL-10

(Ledeboer et al., 2002), IL-12 (Stalder et al., 1997), IL-15, IL-18 (Suzumura, 2002), tumour

necrosis factor α (TNF-α; Chabot et al., 1997), interferon gamma inducing factor (IGIF),

inflammatory proteins, transforming growth factor (TGF-β; Pratt and McPherson, 1997) etc.

Collectively, these molecules not only control the inflammatory processes but also help in the

regulation of immune response of the brain (Glabinski and Ransohoff, 1999) and contribute to

neuropathogenesis in CNS inflammation. Concurrently activated microglia also phagocytose

the debris of apoptotic cells (Reichert and Rotshenker, 2003; Djukic et al., 2006; Neher et al.,

2012) that helps in facilitating the reorganization of neuronal circuits and triggers the repair

mechanism (Kim and Vallis, 2005; Hanisch and Kettenmann, 2007; Neumann et al., 2009;

Salter and Beggs, 2014). In conclusion, microglial cells as immune regulators of the nervous

system secrete several types of molecules or express various receptors that facilitate the

integration of microglial response towards the changing microenvironment.

5.2. Astrocytic activation

Similarly, astrocytes are being increasingly believed to act as immunocompetent cells

within the brain (Shrikant and Benveniste, 1996; Kettenmann and Ransom, 2005). They

rapidly react to various neurodegenerative insults leading to vigorous astrogliosis. Such

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reactive gliosis is associated with alteration in morphology and structure of activated

astrocytes along with their functional characteristics (Mucke and Eddleston, 1993; Ridet et al.,

1997). Astrocytes being the predominant “building blocks” of the blood-brain barrier (BBB)

play a crucial role in sealing the barrier upon brain injury (Bush et al., 1999; Bundgard and

Abbott, 2008) and infections (Barres et al., 2008). Upon activation, astroglia not only release

a plethora of factors (cytokines, chemokines, prostanoids, etc.) mediating the tissue

inflammatory response but also recapitulate stem cell/ progenitor features after damage and

prove as a promising target for reparative therapies following brain damage (Buffo et al.,

2010; Verkhratsky et al., 2012; Verkhratsky et al., 2014c).

Recently, there have been many groundbreaking studies that are devoted to the structure

and functions of activated glial cells and established their imperative and beneficial role in

various brain disorders. Given their functions, glial activation following brain damage

represents targets for therapeutic interventions.

6. Glial changes following STZ –induced diabetes

The imperious role of glial cells in brain disorders was remarkably evident in the

diabetic state, which further underpins the possible reasons of brain dysfunction following

diabetes. Diabetes causes the generation of free radicals which actively assault

macromolecules within neuron and glial cells, resulting in structural and functional changes in

proteins. Various studies revealed that oxidative stress following diabetes on brain cells,

causes a selective decrease in astrocyte GFAP levels in the cerebral cortex, cerebellum,

hippocampus (Coleman et al., 2004; Hernὰndez-Fonseca et al., 2009; Guven et al., 2009) and

spinal cord (Renno et al., 2008) with apparent neurodegeneration at 4-8 weeks of diabetic

duration. The diabetic allied decreased GFAP levels, without altering the relative astrocyte

number, may be linked to insulin secretion, which essentially takes part in the modification of

phenotypic appearance of astrocytes and increases the expression of GFAP mRNA and

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protein (Toren-Allerand et al., 1991). A study depicted that microglial activation in the optic

nerve in diabetic retinopathy might be an additional pathogenic factor in diabetic optic

neuropathy (Zeng et al., 2008). Likewise, there is only one report in the literature

demonstrating the response of microglia to STZ-induced diabetes by assessing the reduction

in the number of Iba-1 positive microglia in the dorsal horn of the spinal cord following

gabapentin treatment in diabetic neuropathy (Wodarski et al., 2008). The impact of

hyperglycemia on glial cells per se or their response to neuronal damage remains to be studied

in detail. Particular attention needs to be taken on neuro-immunological aspects of

neurodegeneration and neuroregulation under diabetic conditions.

Studies on animal models have also shown that diabetes induced GFAP alteration has

been linked to other central nervous system disturbances like distorted learning and memory

processes and further increased risk of dementia and cognitive dysfunction. With regard to the

functional importance of microglial cells in brain following any stress or degenerative

changes, it would be quite interesting to study the microglial activation following diabetes in

the brain regions, responsible for behaviour and cognition. On activation, microglia secretes

plethora of cytokines and chemokines initiating neuroinflammation, which in turn influence

neuronal functions and even some of them also play a critical role in learning, memory

(Goshen et al., 2007; McAfoose et al., 2009) and motor activity (Patro et al., 2010a). Such

microglial activation and related neuroinflammation have never been studied in the diabetic

brain hippocampus, neither their expression nor the immune response developed by these

cells. Glial cell research is actively addressed today on various aspects of their involvement in

neuronal health and disease, but their response to diabetic states has not been studied in large

details and thus requires precise investigation.

7. Brain immune response: Neuroinflammation

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Our central nervous system and immune system share a bi-directional collaborative

relationship, assumed to be imperative in establishing a pertinent physiological, behavioural

and immunological response against any injury or disorder. Central nervous system has been

considered as “immune privileged” due to the lack of humoral immune response constituting

draining lymphatics as seen in the periphery (Barker and Billingham, 1977; Carson et al.,

2006). Immunologically insulated and protected through blood-brain barrier (BBB), CNS

innate immune system as first line of defence constitutes macrophages, resident microglia and

antigen presenting cells. Cellular molecules of innate immune system of CNS in response to

any insult or damage, get activated, mobilize towards the site of insult, phagocytose the

detrimental factors, present antigens, release and synthesize a varied range of inflammatory

molecules such as tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, and IL-6 that serve as

major mediators of the immune response. Interestingly, immune privileged nature of CNS is

still intricate and under relevant exploration (Wekerle, 2006; Galea et al., 2007; Harris et al.,

2014).

The secretion of inflammatory molecules regarded as “double-edged sword” because of

its potential to both protect and harm the tissue. Glial cells as foremost cell population and

functionally concierge to the CNS intensely contribute in neuroinflammation (summarized in

section 2.2.1 and 3). Neuroinflammation is a dynamic process in which both microglia and

astroglia may migrate, proliferate, release potentially harmful factors (i.e. cytokines and

reactive oxygen species), display different surface proteins (i.e., MHC-I/II etc.) and bind in

functions such as antigen presentation and phagocytosis in response to signals such as protein

aggregates, neuronal degeneration and glial products (i.e. colony stimulating factor and

cytokines etc.). Under normal conditions, neuroinflammatory response remains transient and

non-damaging at both tissue and functional level. But if sustain for prolong duration it

probably becomes damaging extended to both tissue and region-specific functions. Several

70

studies have reported that following pathological conditions the protective role of

inflammation switches to the detrimental phase resulted in synaptic impairment, cell death

and neurotoxicity that finally become the possible perpetrators of neuronal damage within the

brain (Cunningham et al., 1996; Aktas et al., 2007; Frank-Cannon et al., 2009; Bjorkqvist et

al., 2009; Lyman et al., 2014).

7.1. Effect of neuroinflammation on behaviour and cognition

Neuroinflammatory mechanism is comprised of an organized set of interaction between

varied mediators like cytokines, chemokines and prostaglandins, etc. Rather than pathological

conditions the secretion of inflammatory molecules is highly influenced by the glial activation

also. In response to any injury, insult or disparaged conditions the apparent activation of glial

cells (both microglia and astroglia) trigger the secretion of inflammatory molecules that

circumstantially become superfluous at chronic glial activation (Block et al., 2007). Various

studies found that excessive expression of cytokines mainly IL-1β, TNF-α and IL-6 induce

non-specific symptoms of diseases like lethargy, low activity and reduced social interaction

(Kelly et al., 2003). Even elevation in TNF-α and IL-1β level found to be involved in the

cognitive impairment and dementia in AD patients (Magaki et al., 2007; Holmes et al., 2009).

Studies have shown that exogenous administration of IL-1β or TNF-α to rodents induces the

full spectrum of behavioural signs of sickness in a dose- and time-dependent manner while

IL-6 could cause fever like symptoms (Dantzer, 2001; Dantzer et al., 2008). Likewise, IL-1β

is also capable in directly affecting the hippocampal neurons causing impairment in long term

potentiation (LTP; Schneider et al., 1998; O'Connor and Coogan, 1999; Vereker et al., 2000;

Lynch, 2014). Experiments showed that prolong exposure of IL-1β reduces the BDNF and

TrK B concentration in hippocampus and up-regulates TrK A and p75 expression. Enhanced

expression of p75 receptors in cholinergic neurons causes neuronal apoptosis and

degeneration of hippocampal cells leading to cognitive deficits (Barrientos et al., 2004;

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Coulson et al., 2009). Excessive cytokine secretion as exaggerated immune response is

believed to be involved in several neuropsychiatric conditions like depression (Howren et al.,

2009; Dowlati et al., 2010; Blume et al., 2011), autism (Ashwood et al., 2011; Depino, 2013)

and anxiety behaviour (Pitsavos et al., 2006; Arranz et al., 2007; Vogelzangs et al., 2013).

It had been shown that neuroinflammatory mediators are capable in causing cognitive

alterations via various mechanisms that could possibly affect the neuronal properties and cell

survival. Several studies are conducted to conceptualize the possible cause and link between

neuroinflammation and behavioural and cognitive impairments. Such studies proposed that an

associative interplay between cellular excitoxicity, neuronal cell death, chronic glial

activation and oxidative stress trigger the state of cognitive and behavioural deficits. During

pathological condition, cellular damage causes activation of glial cells which initiate and

perpetuate the state of excitoxicity and oxidative stress within the brain. Furthermore,

oxidative stress leads to the excessive dicarbonyl glycation which further activates the calpain

expression and degrades the brain-derived neurotrophic factor (BDNF). This contributes to

retard the process of neurogenesis and synaptic plasticity and stimulates NFkB-dependent

inflammation and secretion of inflammatory molecules. Recurrent increment in cytokine

levels increases the permeability of BBB to peripheral immune molecules and prolongs the

central immune inflammatory response that generates an inordinate environment of oxidative

and inflammatory stresses, accelerating CNS oxidative damage and elicits adverse

behavioural and cognitive consequences.

8. Cortical zone of cognition and behaviour: Hippocampus

Hippocampus is an anatomical structure forming a part of limbic system in CNS. It is

mainly responsible for the collection, consolidation and retrieval of various aspects of

learning, memory and spatial navigation (Scoville and Milner, 1957; O‟Keefe and Nadel,

1978; Rolls, 1996). The term hippocampus arises from the Greek words hippos mean horse,

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and kampos means sea monster. From 1729, onwards, considering its structural resemblance

the name of this structure was wavered between seahorse and silkworm (german anatomist

Duvernoy). Later, in 1932, a Danish group proposed the term "Ram's horn" or "cornu

Ammonis" (horn of ancient Egyptian God Amun). Anatomically, it is a bilobule structure

extended in both right and left lobes of the cerebral cortex of both human and other

vertebrates. Through both septotemporal (longitudinal) and transversal axis, hippocampus is

mainly divided into two divisions i.e., dentate gyrus (DG) and three sub regions of Cornu

Ammonis (CA1, CA2 and CA3). The Cornu Ammonis region is also known as the

hippocampus proper having pyramidal neurons as the prime neurons that comprises 90% of

the neuron population in CA region of the hippocampus formation where the DG region is

mainly consisted of granule cell and molecular cells.

8.1. Hippocampal circuitry and processing

Hippocampus is an elemental hub for the cognition and behavioural processes (Sweatt,

2004). Purview of these functions depends upon the conjunctive relationship between the

hippocampal sub-regions, i.e., CA1, CA2, CA3 and DG and their synaptic connections with

other cortical areas. Hippocampus receives all the prime subcortical inputs from perirhinal,

parahippocampal, posterior cingulate, insular, orbitofrontal and superior temporal cortices

(Insausti et al., 1987; Amaral and Witter, 1995; Pikkarainen et al., 1999).

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Hippocampal circuitry forms a trisynaptic loop that receives and transmits the cortical

information throughout the CNS (Figure 4). Highly processed cortical inputs from the

entorhinal cortex (EC) enter into the dentate gyrus through the perforant path projection.

Granule cells dendrites in DG make excitatory synaptic contact with perforant path axons.

The proximal apical dendrites of CA3 pyramidal neurons receive input through the mossy

fibres of granule neuronal cells, which in turn, through Schaffer collaterals pathway projected

to the ipsilateral CA1 pyramidal neurons and to contralateral CA3 and CA1 pyramidal

neurons via commissural connections. CA1 and CA3 pyramidal neurons also receive direct

input from the entorhinal cortex via layer III and layer II cells of entorhinal cortex

respectively. Deep layers of EC receive the exclusive output from the hippocampus. Besides

EC, some other additional outputs from the hippocampus are also received by other cortical

areas like the prefrontal cortex and lateral septal area.

Accordingly, the possible effect of oxidative stress following diabetes on neuronal and

glial cell death and the interconnected feedback loop between oxidative stress, cell death and

gliosis have never been studied in the hippocampus. Therefore, a detailed study on glial

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activation and immune response either neuroprotective/degenerative, produced by glial cells

following diabetic exposure along with subsequent behavioural and cognitive impairment

with respect to gliosis needs to be carried out in a more organized manner. Thus, the present

study will help in assessing the effect of diabetes on: glial activation, cell death and the

possible immune response produced by microglial and astroglial cells along with their effects

on behaviour and cognition changes in a rat model.

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MATERIALS & METHODS

1. Animals

Wistar rats bred and raised in the animal house facility of School of Studies in Neuroscience,

Jiwaji University, Gwalior were used in this study. The animals were maintained at controlled

temperature of 25±2˚C and 50-65% humidity with a fixed 12:12 hour light dark cycle.

Animals were housed, in pairs, in polypropylene cages (52cm x 28cm x 22cm) with clean dust

free husk bedding. Water and standard rat pellet diet (Ashirwad Industries, Chandigarh, India)

were provided ad libitum. Animal house maintenance practices were carried out as per the

guidelines of Committee for the Purpose of Control and Supervision on Experiments on

Animals (CPCSEA), and all the procedures were pre-approved by Institutional Animal Ethics

Committee, Jiwaji University, Gwalior (M. P.).

2. Diabetes Induction

A pool of healthy rats weighing between 180-230 g and blood-glucose level of 90-140 mg/dl

was selected for developing type 1 diabetes animal model (McNeill, 1999). Animals were

fasted overnight, but had free access to drinking water prior to STZ-injection. Type 1 diabetes

was induced by a single intraperitoneal (i.p.) injection of Streptozotocin (STZ; Sigma) at a

dose of 45 mg/ kg body weight, dissolved in 0.1M citrate buffer (pH=4, preparation discussed

in Appendix I; Stevens et al., 2007; Lebed et al., 2008; Waer and Helmy, 2012). Rats injected

with vehicle alone served as control. Blood-glucose level (non-fasting) was determined at

72hrs post STZ injection, through tail snipping (Kamal et al.,2000; Lechuga-Sancho et al.,

2006) using AccuChek Sensor Comfort (Roche Diagnostics, Berlin, Germany). Animals

having the blood-glucose level of 250 mg/dl or above were considered as diabetic.

Diabetic animals were randomly divided into following groups, i.e., 2nd

week post

diabetic confirmation (2nd

week), 4th

week post diabetic confirmation (4th

week), 6th

week post

76

diabetic confirmation (6th

week), 8th


week), 10th

week

post diabetic confirmation (10th

week) and 12th


week).

Blood glucose level (non-fasting) and body weight were checked once a week throughout the

study duration to ensure the diabetic stature. Animal‟s food and water consumption was also

measured daily to further confirm the diabetic symptoms like polyphagia and polydipsia.

3. Behavioural and Cognitive Assessment

The behavioural and cognitive assessments were done at 2nd

, 4th

, 6th

, 8th

, 10th

and 12th

week

post diabetes confirmation (n=8/group) with their respective control groups. A wide range of

behavioural and cognitive studies were performed to analyse the spatial cognition, working

memory, locomotor activity, motor coordination and muscular strength of the animals

following STZ-induced diabetes.

Notably, the experimental room conditions (light, temperature, humidity and noise

intensity) and timing (9:00am to 2:00pm) were consistent and similar to the animal house

environment in all the behavioural and cognitive studies to avoid any procedural anomalies.

To minimize the novel-environment associated variance, animals were taken into the

experimental room one hour before the test.

3.1. Open field test

3.1.1. Principle

Open field test is popularly used to assess the locomotor activity of the rodents and serve as a

good preliminary test to determine the motor deficits (Qianet al., 2010; Hong et al., 2014). It is

also used as an indicator of unconditioned emotionality in response to the novel environment

with limited complexity (Hall and Ballechey, 1932; Henderson, 1970). The basic outcome of

the study is based on „subject‟s movement‟ which is influenced by the motor output, novelty

fear or freezing and exploration, etc.

3.1.2. Instrumentation

77

The test was performed on a computerized Optavarimax Autotrack activity monitoring system

(Columbus Instruments, Columbus, OH, USA). A testing chamber of the transparent acrylic

box with an area of 43cm x 43cm x 17cm and preinstalled software Auto-track version 4.41

was used to record and measure the animal‟s locomotor and non-locomotor activity. The

testing chamber has two arrays of infrared beams perpendicular to each other to measure both

horizontal and vertical activity of the animal. Instrument is based on photobeam interruption

principle. An arrangement of 30 infrared photocells (15 per row) were located every 2.5cm

from side-to-side and 4cm above the arena to record the horizontal activity. On the other side,

an array of similarly distributed 16 infrared photocells were placed 10 cm above the arena

floor to measure the vertical activity.

3.1.3. Experimental procedure

Test animals were provided with a prior exposure of 5 min of the test chamber to minimize

novel-environment fear in the animal. With the help of the software (Auto-track version 4.41)

behaviour variables were recorded for 20 min continuously for each animal. Each animal was

tested once. After every trial, the chamber was cleaned with 10% alcohol to remove the animal

odour from the chamber. Notably, lethargic or abnormally behaved animals were not included

in the study and eliminated as outliers. The measured variables were as follows:

78

1. Distance travelled (cm): Total distance covered by the animal after moving from the centre

position.

2. Resting time (sec): Total time when the animal is not moving in the testing device.

3. Ambulatory time (sec): Total time taken by the animal to change its position in the testing

area either by walking, circling or rearing.

4. Stereotypic time (sec): Time taken by the animal to perform non-locomotor activities like

grooming, scratching, etc.

All the pre-described variables were recorded by the sensors and displayed on the screen

with their tracking plots and hence was saved for further data analysis (section 4).

3.2. Motor coordination test

3.2.1. Principle

Dependable assessments of motor function essentially require the evaluation of the motor

disability in the rodent model of disease (Brooks and Dunnett, 2009). Rotarod is the most

popular and widely used test to study the motor coordination as motor function in rodents

(Jones and Roberts, 1968; Rustayet al., 2003). Initially, rodents are trained or acclimatized to

walk on the rotating rod at a certain speed for specific time duration and after training,

animal‟s motor coordination is assessed on the basis of their abilityto coordinate the balance

and movementon the rotating rod with exceeding speed. Animals which are unable to cope

with the faster moving rotating rod will drop off early are testified as having impaired motor

coordination. The assessment is based on the animals‟ falling latency, recorded when the

animal fall off and breaks the photo-beam detection over the time.


Rotamex 5 (Columbus Instruments, Columbus, OH, USA), a motor-driven treadmill was used

to evaluate the effects of diabetes on the motor coordination of the rats. Rotarod apparatus has

a plastic semi-enclosed box shaped chamber having row of infrared photo-cells (diameter

79

3cm, width 5cm) on two parallel facing sides. A rotating spindle at the middle of the apparatus

between the beams is suspended at a height of 35cm above the floor. The rotating ridged

spindle provides optimal grip to the animal. The apparatus is provided with round plates on

either side of the separated section to prevent animal from escaping. The latency to fall was

recorded automatically by the photocells as the total length of time spent by the animal on the

rotating rod with the help of software Rotamex version 1.2.3 installed with the apparatus.


Animals from each group were acclimatized for 3 days consecutively at start acceleration

speed minimum of 2 rpm to maximum of 8 rpm for a total duration of 100 sec, three trials for

each animal. Final reading was taken post 24 hour of last acclimatization, at a start

acceleration speed of minimum 2 rpm to maximum of 40rpm for a total duration of 420 sec.

An animal fall is detected by infrared photocells, which cross the space just above the spindle.

Once the photocells loose the detection of the animal, the falling latency of that animal was

recorded. Test animals were given 3 trials each, with a resting time interval of 5 min was

given between each successive trial. If any animal behaved abnormally (i.e., data generated

80

varied dramatically from the animals of similar states), then it was considered as outlier. Data

compilation and analysis is described in section 4.

3.3. Neuromuscular strength test

3.3.1. Principle

Grip strength meter is popularly used to measure the neuromuscular strength of the rodents

(Meyer et al., 1979). It determines the peak force value applied by the rodent to hold the grip.

The device works under the principle of compression and tension. For the forelimb muscular

strength assessment, the tension mode was considered.


Grip strength meter (Columbus Instruments, Columbus, OH, USA) consisted of a force gauge

digital display (sensor range: 0-5kg) is connected with a specially designed forelimb grasping

pull bar assemblies (76mm x 50mm) made of steel wire. The values of grip strength were

recorded automatically via a RS-232 interface connected to the computer and a software Grip

strength version 1.19. The unit of measurement of the sensor is delivered in grams mode.


For measuring the grip strength the test animal was placed over the metallic grid and allowed

to hold the grid through its forelimbs. Through a gentle force, the animal was pulled back

carefully by the tail until its grip was released. Each animal was retested after three successive

readings followed by 2 min interval, total six readings per animal were recorded.

81

The maximum strength value animal takes to release the grid was recorded by the sensors and

displayed on the screen and hence was saved for further data analysis (section 4). Notably,

lethargic or abnormally behaved animals were not included in the study and eliminated as

outliers.

3.4. Test for spatial memory

3.4.1. Principle

Barnes circular maze is a spatial memory task for rodents that involves the learning of the

position of a hole that can be used to escape from the open surface of the maze (Barnes, 1979).

The task relies on subject‟s learning and memory to locate the escape box using spatial

reference points that either is fixed in relation to the maze (extra-maze cues) or are on the

maze itself fixed in relation to the escape hole (proximal cues).


Barnes circular maze is consisted of a black circular platform of 120 cm in diameter with 18

holes of 10 cm diameter evenly spaced around the circumference. An escape box (20x10x10

cm) was placed under one of the holes. For recording the test, a camera connected to the

82

Escape box

computer interface with preinstalled Any Maze software version 4.82 (Stoelting, USA) was

mounted directly over the maze.


Test animals were acclimatized for 3 consecutive days to locate the escape box prior to the

final reading. Experimental animals those behaved abnormally and were unable to locate the

escape box in the provided time duration were excluded from the study as outliers. For the

final test, animal was placed in the middle of the platform away from the experimenter face

and allowed to explore the maze. Timing of the session ended when the animal found the

escape box or after 120s had elapsed. Variables like duration to find the escape box, path

efficiency and speed were assessed from the final 3 trials test reading for each animal. Final

data as a mean value per animal was statistically calculated and analysed (described in section

4). After each trial, the maze was cleaned with 10% ethanol to remove possible biasing effects

due to odour cues left by previous rats.

3.5. Test for anxiety and depression

3.5.1. Principle

Elevated plus maze is a widely used test for measuring the fear and anxiety-like behaviour in

rodents (Pellow et al., 1985; Walf and Frye, 2007). The test is based on the animal‟s

unconditioned preference between a comparatively safe and comfortable environment (the

83

closed arms) and a risky environment (elevated open spaces) and their innate behaviour to

explore the novel environment. An anxious animal avoids the entry in open space (Pellow et

al., 1985; Walf and Frye, 2007; Mizunoya et al., 2013) and present higher anxiety index, an

integrated value of total number of entries in the arms (open and closed) and number of entries

in open arms (Cohen et al., 2013; Contreras et al., 2014).


Elevated plus maze is a metallic plus “+” shaped apparatus, elevated 75 cm above the floor

supported with four metallic stands. The apparatus is consisting of two open and two closed

arms of same dimensions, i.e., 50 cm long and 10 cm wide. The closed arms were covered by

the 40 cm long metallic sheet walls. At the conjunction of four arms, a central square platform

(10 x 10 cm) was present. A camera setup mounted just over the maze and connected to the

computer interface with preinstalled Any Maze software version 4.82 (Stoelting, USA) was

used to record the animal tracking.


Prior to the final test, animals were acclimatized for 3 consecutive days on elevated plus maze

for 2 min each. Final trial was conducted 24 hour after the last acclimatization session. Test

animal was placed at the square platform and allowed to roam inside the maze for upto 120s.

Three trials were tested for each animal for the number of entries and time spent in the closed

or open arm.

84

To analyse the data following were calculated: percentage of open arm entries = ([open

entries]/[total entries] × 100), percentage of time spend in open arms = ([time in the open

arms/ (time in the open arms + time in the closed arms)] x 100) and anxiety index = 1 −

[([Open arm time/Test duration] + [Open arms entries/Total number of entries])/2] were

calculated (Walf and Frye, 2007; Mizunoya et al., 2013; Cohen et al., 2013; Contreras et al.,

2014). Data collection and analysisis described in section 4.

3.6. Test for working memory

3.6.1. Principle

T maze test is a well-known task for studying the working memory of the rodents (Wenk,

2001). In this task, animal learn to find the baited arm (arm having eatable reward) based on

their memory of previously visited arms (Nasuti et al., 2013).


The maze is a „T‟ shaped structure consisted of black metallic one start arm (60 x 10 x 10 cm)

joined to two identical reward arms (45 x 10 x 10 cm). A camera connected to the computer

interface with preinstalled Any Maze software version 4.82 (Stoelting, USA) help in recording

the track details.


85

Test animals were acclimatized for 3 consecutive days 3 trials per day to learn the baited arm.

The trial was completed when the animal reached the baited arm or after 5 min had elapsed.

Animals those failed to explore the baited arm in the provided time duration (5 min) or

behaved abnormally were excluded from the study as outliers. On the final test day, animals

were tested for 6 trials successively to assess the time duration animal takes to choose the

rewarded arm and path efficiency to reach this arm. Trials were carried out using 10-min

resting intervals. Data assessment and evaluation for the difference between the path

efficiency and test duration of diabetic animals in comparison to controls is explained in

section 4.

4. Data collection and statistical analysis

For every cognitive and behavioural assessment,final readings of each study were calculated

for a single mean value per animal on an excel file, and from the mean of readings of every

animal group, standard error was calculated within the mean of different animals (Coolidge,

2002). SigmaStat software (version 3.5; Systat Software, Inc., Point Richmond, CA, USA)

was used to analyse the significance between the various experimental groups, assessment was

done by one-way ANOVA followed by the Tukey‟s posthoc test. The threshold for statistical

significance was set at p≤0.05.

5. Tissue collection and processing

Animals (n=6/group) from both diabetic and control groups were sacrificed on 2nd

, 4th

, 6th

, 8th

,

10th

and 12th

week and animal tissues were preserved and processed for further analysis.

5.1. Perfusion-Fixation

5.1.1. Principle

The aim of whole-body perfusion-fixation is to use the vascular system of a deeply

anesthetized animal to deliver the fixatives to the tissues of interest (Jonkers et al., 1984). This

is an ideal method of tissue preservation as it fixed the tissues before autolysis begins and

86

retains the tissue in life-like condition. Perfused tissues are less susceptible to the damage

caused by handling.

5.1.2. Procedure

A well-designed and approved perfusion set-up was used to achieve the purpose (Figure 1).

Animal was first anesthetized with diethyl ether vapours inside a glass desiccator with closed

lid. After proper deep anaesthesia, animal was placed dorsally downward over the dissecting

tray. An incision of 4-5 cm was made through the integument and abdominal wall just beneath

the rib cage. Then with the help of a curved and blunt scissor another small incision was made

in the diaphragm and continued along the entire length of the rib cage to expose the heart.

Parallel cuts were made on either side of the rib cage up to the collarbone. Sternum was lifted

upwardly towards the animal‟s head with the help of artery forceps and tissues attached with

the heart were carefully removed by a blunt scissor for the better view of heart. Subsequently,

a 15 gauge blunt butterfly needle running with buffered saline flow (PBS; 0.01M; pH=7.4,

Appendix I) was inserted into the left ventricle of the heart and successively a small nick was

made on the right auricle with the help of scissor to allow the flushing of whole-body blood

via circulatory system. When the blood was completely flushed out from the body and the

fluid exiting the auricle was clear, the fixative valve was opened to uninterruptedly replace the

saline flow with buffered fixative (Appendix I), i.e., 2% paraformaldehyde (for

immunohistochemical study) and 10% buffered formalin (for histological study). The fixative

was allowed to run until the rat‟s body became stiff or fixed properly.

87

5.2. Tissue processing

5.2.1. Principle

Tissue processing is achieved to provide the enough solid medium support to the tissue that

offers sufficient rigidity to enable the thin sections to be cut. It also prevents the distortion

while performing the sectioning. The processing method not only preserves the morphological

integrity but also retains the cellular changes of the tissue. According to the sectioning method

directed, i.e., cryotomy or microtomy different procedures of tissue processing were applied.

5.3. Tissue processing for cryotomy

5.3.1. Procedure

After perfusion-fixation cerebral cortex through occipito-temporal region (to expose the

hippocampal area) and cerebellum were dissected out carefully, weighed and post-fixed in the

same fixative overnight at 4°C. The tissues were then cryoprotected in Phosphate buffered-

Sucrose gradients, i.e., 10%, 20% and 30% at 4°C until tissue settled at the bottom.

After processing the coronal sections of hippocampus and sagittal sections of cerebellum

were sequentially cut using cryostat (Microm HM 525, Thermo Scientific), at a thickness of

14µm. The sections were collected serially on chromalum-gelatin coated slides and stored at

-20˚C till they were used for immunocytochemical studies.

88

5.4. Tissue processingfor microtomy

5.4.1. Procedure

Histological studies were done for hippocampus, cerebellum, kidney, liver and pancreas.

Following method was employed for the paraffin tissue processing:

Post-fixation: Following perfusion-fixation, tissues were kept in same fixative for 48 hrs at

room temperature for the efficient fixation of tissues.

Washing: Washing was done thrice with distilled water for 1½ hour each to remove the excess

of fixative from the tissue.

Dehydration: Through a graded series of alcohol, i.e., 30%, 50%, 70%, 90%, 100% I and

100% II sequentially for 1 hour each at room temperature, tissues were dehydrated to extract

out the water molecules that would hamper the paraffin impregnation and embedding.

Clearing: Tissues were cleared in 2 changes of toluene for ± 45 min each (until the tissues

became transparent in appearance). The purpose of clearing is to remove the dehydrating

solution from the tissue and making the tissue permissible for the subsequent paraffin

impregnation.

Wax impregnation: Cleared tissues were kept in paraffin wax twice for ± 2hr each in hot oven

(56-58°C) for the proper impregnation of wax inside the tissues. After paraffin impregnation,

tissues were embedded in wax and paraffin tissue blocks were made with the help of

Leukhart‟s „L‟ pieces.

The sectioning was performed on a microtome (Leica Rotary Micotome, RM 2135).

Serial sections of cerebrum (10µm thickness), pancreas, liver and kidney (8µm thickness)

were collected on chromalum-gelatin coated slides, stretched in hot water bath (50°C), dried

on hot air oven (37°C) and stored at room temperature for further histological studies.

6. Immunohistochemical study

6.1. Principle

89

Immunohistochemistry is a technique to identify or localize the specific protein antigen

through antigen-antibody interaction that can be visualized by some specific markers like,

fluorescent dye, enzyme or colloidal gold. Immunohistochemical study using enzyme-

substrate reaction producing a specific colour to label the antigen-antibody interaction is

termed as immunoenzymatic labeling. In this study the immunohistochemical labeling was

employed to assess the stature of various brain proteins following STZ-induced diabetes.

6.2. Procedure

Cryocut sections were brought to room temperature and air dried for 1 hour at 37°C.

Afterwards, sections were washed thrice with washing buffer (as shown in Table 2) for 5 min

each, and then permeabilised with 1% Triton X-100 for 30 min at room temperature followed

by three washings (5 min each) with buffer again. To quench the endogenous peroxidase

activity sections were treated with 1% hydrogen peroxide for 30 min at room temperature.

Then the sections were preblocked with 1% normal serum (prepared in washing buffer) of

same species as secondary antibody, for 90 min in a humid chamber. Next to blocking the

sections were incubated with primary antibody (Table 2) overnight at 4°C. Next day after

three buffer washes, the sections were then incubated with secondary antibody (Table 2), for

90 min at room temperature. Afterward, rinsed in buffer, sections were subsequently incubated

in streptavidin-biotin-peroxidase complex (Table 2) for 90 min at room temperature.

Following buffer wash the colour was developed with chromogen solution containing 3, 3′-

diaminobenzidine tetrahydrochloride (0.025%) and hydrogen peroxide (0.006%) dissolved in

the buffer for 20 min at room temperature. Later on trailed by distilled water wash, slides were

dried at 37°C, dehydrated in 100% alcohol, cleared in xylene and mounted with DPX. To

ensure comparable immunostaining, sections were processed together at the same time in the

same conditions. Omission of primary antibodies served as negative control.

90

Table 2. Antibody Details:

Antibody/

Source

Specificity Raised in/

Concentration

Secondary

(Biotinylated, Sigma)/

Concentration

Tertiary (SABC,

Amersham)/

Concentration

Colour

Visualization

Washing

Buffer

GFAP

(Dako, Denmark)

For labeling the

astroglia

Rabbit Polyclonal/

1:2000

Anti-rabbit (1:100) 1: 200 DAB PBS

Iba-1

(Wako, Japan)

For labeling the

microglia

Rabbit Polyclonal/

1:1500


Caspase-3

(R&D Systems)

Detection of cell

death

Rabbit Polyclonal/

1:1000

Anti-rabbit (1:150) 1: 200 DAB + NiSo4 TBS

OX-6

(Serotec)

MHC-II presenting

cells

Mouse Monoclonal/

1:100

Anti-mouse (1:100) 1: 200 DAB + NiSo4 TBS

S-100β

(Sigma)

Astrogliosis Rabbit Polyclonal/

1:200


OX-42

(Serotec)

Complement

receptor-3 activation

Mouse Monoclonal/

1:100


ED-2

(Serotec)

Macrophagic marker Mouse Monoclonal/

1:200


TNF-α

(R&D Systems)

Pro-inflammatory

cytokine

Goat Polyclonal/

1: 200

1:100,

Biotin labelled

(VectastainElite ABC

Kit, Universal)

1: 200

(VectastainElite

ABC Kit,

Universal)

DAB

PBS

IL-1β

(R&D Systems)

Pro-inflammatory

cytokine

Goat Polyclonal/

1: 200

1:100,

Biotin labelled

(VectastainElite ABC

Kit, Universal)

1: 200

(VectastainElite

ABC Kit,

Universal)

DAB

PBS

Note: All the antibodies were diluted in 1% BSA dissolved in washing buffer.

91

7. Histological staining

7.1. Principle

Histology is aimed to study the cellular organization and structure of the tissue and cell. It

also helps to understand the physiological importance and relationship between cellular

structures under various conditions. Histological staining is the eminent and prime tool of

the histological study based on the principle of ion-ion and acid-base interactions.

Haematoxylin and Eosin staining is used to study the histopathological changes in both

nuclei and the cytoplasm of the cell. Haematoxylin is a cationic dye; that stains the nuclei

in blue-black colour while eosin stains the cytoplasm in pink colour.

7.2. Procedure

Paraffin sections were first deparaffinised with two changes of xylene for 15 min each.

Then sections were rehydrated through descending series of alcohol i.e., 100%, 90%,

70%, 50%, 30% sequentially for 10 min each followed by 2 changes of distilled water for

5 min each. Afterwards, sections were placed in the Delafield‟s haematoxylin (Fisher

Scientific, India) stain for 4 min. This was followed by washing under running tap water

for 20 min for removing the excess of stain. Differentiation was done with 0.5% HCl (1-2

dips), and the slides were again washed in running tap water for 20 min to remove the

acid. After a 5 min wash in distilled water sections were placed in ascending series of

graded alcohol, i.e., 30%, 50% and 70% for 5 min each to dehydrate the sections. Then

the sections were kept in the 1% eosin stain prepared in 90% alcohol for 2 min. This was

followed by 1-2 dips in 90% alcohol for differentiation, and then the sections were placed

in 100% alcohol for 20 min with 2 changes (10 min each) trailed by clearing in xylene for

15min. And finally, the sections were permanently mounted with DPX.

8. Morphological analysis

92

Images were captured using Leica DM 6000 microscope equipped with Leica DFC 310

RX digital camera and Leica Application Suite (LAS) software in order to have

magnified images showing fine structural details for more demarcated morphological

analysis.

9. Cell quantification and analysis

9.1 Cell counting using Leica Qwin software

Cell quantification was done on the sections stained through standard HRP-conjugated

immunohistochemistry method. The cell population was estimated in CA1, CA2, CA3

and DG regions of the hippocampus. The hippocampal regions for quantification were

delineated as twelve frames per area in the two sections per animal in all the groups. In

order to count equal areas (mm2) in every subject, a 21670.9µm

2 frame comprising

exclusively the anatomical areas of interest was applied to ensure that counts were

representative of the analysed areas. Photomicrographs of the regions located between

bregma 3.8 mm and intraural 5.2 mm (Paxinos and Watson, 1982) were photographed

with Leica DM6000 microscope fitted with digital camera (DFC 420C, Leica, Germany).

Only tissue sections corresponding to these coordinate were included in the

quantification, ensuring that the regions of interest were equivalent among animals and

experiments. Cell counting was performed on the digital pictures using Leica Qwin

software (version 3.1) and interactive measurement application tool and presented as the

total number of cells/ mm2.

93

Immunolabelled image

was opened through

Open option in main

tool bar. Image was

opened and

„Interactive‟ mode

was chosen in the

„Measure‟ option

panel of the main menu

tool bar.

After opening the

„Interactive

Measurement‟ box,

cell counting was done

manually by clicking

on the immunolabelled

cells.

As the manual cell

counting precedes, the

data was recorded and

displayed in „Manual

Results‟ box as cells

present in per frame

area of 21670.9µm2.

Values were copied in

separate excel sheet

and converted to mm2

and averaged for a

single mean value.

9.2. Quantification of area fraction using Image J software: "Image J" is a freely

available java-based public-domain image processing and analysis program developed at

the National Institute of Health (NIH). This program is a reliable, well-accepted and

94

accessible laboratory tool for the scientific image analysis for a very long time (Girish

and Vijayalakshmi, 2004; Schneider et al., 2012). In the present study Image J was used

to study the area fraction (percentage of staining) of the specific immunolabelling. Images

of the same magnification were used for the cell counting to ensure the consistency of the

data.

Through File option in main tool

bar new image was opened.

Measurement scale was calibrated

by drawing a line over the scale bar

with straight line tool and Set Scale

option from Analyze tool bar was

selected. In Set Scale window,

entries were made as value 100 in

„Known distance‟ box, µm in unit

of measurement box and Global

option was marked. Analyze Set Scale

Image was converted into grayscale

through following path:

Image Type 8-bit

95

Adjust option was selected from

the main tool bar Image section

and threshold was adjusted as:

Image Adjust Threshold

Image background and particles

were converted into white and

black colour respectively via

following path:

Process Binary Make Binary

Analyze Particles option was

selected from Analyze panel of

menu tool bar as:

Analyze Analyze Particles

96

In Analyze Particles window, 100

value was selected as the minimum

particle size and options „Display

Results‟, „Summarize‟, and

„Record States‟ was opted.

Area fraction was counted from the

Summary window. The Summary

window also enlisted the count,

total area and average size for

every image. Provided data was

copied to the excel sheet for further

statistical analysis.

10. Statistical analysis

Results were statistically analysed with SigmaStat software (version 3.5; Systat Software,

Inc., Point Richmond, CA, USA) and were reported as mean ± SEM. In experiments, to

assess the significance between the multiple groups one-way ANOVA followed by the

Tukey‟s posthoc test was done. The threshold for the statistical significance level was set

at p≤0.05.

11. Biochemical study

Biochemical study was done to evaluate the level of oxidative stress in rat following

diabetes.

97

Lipid peroxidation (LPO): Lipid peroxidation (LPO) was assessed by measuring

malondialdehyde (MDA) levels based on the reaction of MDA with thiobarbituraric acid

using Buege and Aust (1978) method. The reaction of malondialdehyde (MDA), a

degradation product of peroxidized lipids with thiobarbituric acid (TBA) to produce TBA

malondialdehyde chromophores has been taken as the index of lipid peroxidation. LPO

estimation serves as preliminary tests to determine the oxidative stress in diabetic rats.

Reagents:

• Potassium chloride (0.15 M): 1.1184 g was dissolved in 100 ml of D.H2O.

• Trichloroacetic acid (30%): 30 g TCA was dissolved in 100 ml of D.H2O.

• Thiobarbituric acid (0.8%): 0.8 g was dissolved in 100 ml of D.H2O.

11.1. Procedure

For LPO estimation, animals (n=6) from both diabetic and control groups were sacrificed

and tissue of interest i.e., kidney, liver and hippocampus were surgically removed and a

10% (w/v) tissue homogenate was prepared in 0.15M KCl solution. Then, 0.5 ml of 30%

TCA and 0.5ml of 0.8% TBA was added sequentially into the homogenate with 2min

vortex after the TCA addition. After the reagent addition, test tubes mouth was covered

with parafilm and aluminium foil to prevent the spillage. The tubes were then kept in

boiling-water bath for 30 min. After cooling the tubes, the homogenate was centrifuged at

3000rpm for 10min and afterwards, the optical density was read at λ 535 nm. The value

of absorbance was converted as MDAµmol/gm of tissue with the following formula:

MDAµmol/gm of tissue = Absorbance x 10

0.156

12. Statistical analysis

Computation of the statistical analysis was carried out with the help of the Microsoft

Excel program (Microsoft Office XP Professional, Microsoft Corporation, USA) and

98

SigmaStat software (version 3.5.; Systat Software, Inc., Point Richmond, CA, USA).

One-way analysis of variance (ANOVA) followed by the Tukey‟s posthoc test was done

to compare the mean levels of various experimental groups. The threshold for the

statistical significance level was set at p≤ 0.05.

99

RESULTS

Streptozotocin (STZ)-induced diabetic animal model was used in this study as

streptozotocin is not only capable of inducing an irreversible long-term effect of diabetes

(Gaulton et al., 1985; Méndez and Ramos, 1993; Eleazu et al., 2013) but also has low

mortality rate as compared to the other diabetogenic agents (Mansford and Opie, 1968;

Lenzen, 2008; Chatzigeorgiou et al., 2009; Deeds et al., 2011). The effect of STZ in

experimental animals was checked post 72 hrs of STZ-injection and animals having blood

glucose level of 250mg/dl or above were considered as diabetic. Further diabetes

associated effects (cognitive, behavioural, biochemical and cellular) were assessed from

2nd

to 12th

week post diabetes confirmation (PDC). The model was validated through the

assessment of cardinal signs of diabetes mellitus i.e., high blood glucose level, body

weight loss, polydipsia, polyphagia, absolute pancreatic beta cell loss and acute

degenerative changes in vital organs like kidney and liver.

1. STZ-induction causing symptomatic diabetes

Streptozotocin (STZ)-injected animals exhibited characteristic signs of diabetes with

blood glucose level consistently high at 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week

(p≤0.001), 8th

week p≤0.001), 10th

week p≤0.001) and 12th

week (p≤0.001) of post

injection diabetic durations (post-diabetes confirmation; PDC) as compared to their

respective controls (Fig. 1/i). Furthermore, the water intake of diabetic animals was also

increased significantly at all the PDCs i.e., 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th

week (p≤0.001) and 12th

week (p≤0.001) as

compared to their respective controls (Fig. 1/ii). Similarly, the food consumption of the

animals also increased at 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week PDC (p≤0.001) as compared to their

respective controls (Fig. 1/iii). The increment in food and water intake in STZ-induced

100

animals also confirmed the symptomatic signs like polyphagia and polydipsia observed

in type 1 diabetes.

2. Diabetes induced reduction in body and brain weight

Body weight of diabetic rats reduced significantly after 2nd

week (p≤0.001) and

continued to remain low till the end of the experiment i.e., 4th

week (p≤0.002), 6th

week

(p≤0.001), 8th

week (p≤0.001), 10th


week PDC (p≤0.001) of

diabetic animals (Fig. 2/i). Similarly, the brain weight of diabetic animals was also

decreased significantly after 2nd

week (p≤0.001) and continued to remain low till the end

of the experiment i.e., 4th

week (p≤0.002), 6th

week (p≤0.001), 8th

week (p≤0.002), 10th


week PDC (p≤0.013) as compared to the respective controls

(Fig. 2/ii). A cumulative resultant of reduced body and brain weight, the brain weight/

body weight ratio of diabetic animals was escalating at all the diabetic time points i.e.,

2nd

week (p≤0.005), 4th

week (p≤0.024), 6th

week (p≤0.003), 8th

week (p≤0.008), 10th


week PDC (p≤0.008) as compared to their age-matched controls

(Fig. 2/iii).

3. Histological changes in kidney, liver and pancreas following STZ-induced

diabetes

3.1. Pancreas

In controls the pancreatic tissue was observed with normal architecture having compact

arrangement of beta cells and non-beta cells. The pancreas of control rats showed a clear

demarcation of lobes by the means of fibrous connective tissue (Fig. 13). It consisted of

exocrine region consisting acinar cells lined by cuboidal epithelium with eosinophilic

secretions in the lumen and endocrine region illustrated by the presence of groups of cells

lying within each lobule and these cells are known as the island of islets of Langerhans

(Fig. 13/a). In the pancreatic tissue of diabetic rats degenerative changes were clearly

evident (Fig. 13/b-g). The insulin producing beta cells were successively decreasing both

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in numbers and volume with the advancing diabetic state confirming the severe

permanent insulin deficiency following STZ-injection. The insulin deficiency is in

correlation with the increased blood glucose level of the animals which is gradually

increasing from 2nd

to 6th

week PDC and remained at higher than normal level

afterwards. Islet cells were also atrophied (Fig. 13/ b-d; red arrowhead) and their number

was reduced from 2nd

to 8th

week of diabetes. However, a gradual and complete loss of

islet cells was evidenced from 6th

week post diabetes (Fig. 13/d-g). From 10th

week

onwards the vacant island of islets of Langerhans was started surrounding by fibrous

tissue that clearly observable by 12th

week PDC (Fig. 13/d-g). There was no sign of any

regenerative changes upto the 12th

week of diabetes. Marked necrosis of the exocrine

pancreas was also noticed. Severity of necrosis was increased with the time duration and

was evidently depicted by the presence of eosinophillic acinar cells showing karyolysis

and atrophy (Fig. 13/d-g; red arrow). Histopathological investigation of pancreas reveals

persistent loss of beta cells and tissue damage with almost no regenerative changes as

observed following STZ-induction, validating the type 1 diabetes animal model. The

sustained severity of diabetes upto the 12th

week of study was also confirmed. Details of

histopathological findings are presented, in the summary incidence table 1.

3.2. Kidney

The kidney of control rat showed the normal architecture upto the 12th

week of study

(Fig. 14/a). The histopathology of kidney presented normal glomerulus, Bowman‟s space

and renal parenchyma supported with proximal and distal convoluted tubules and Vasa

recta. Renal tubules in the parenchyma showed clear lumen and were lined with cuboidal

cells. Following STZ-injection the degenerative changes were clearly evident in the renal

tubules as depicted by necrosis of cuboidal cells (Fig. 14/b-g; black arrow) and severity

of tubular necrosis from 2nd

to 12th

week post STZ induction (Fig. 14/b-g). In the later

diabetic stage there was complete loss of renal parenchyma leading to the formation of

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cyst (Fig. 14/d-g; black arrowhead). Renal parenchyma also showed wide spread

glomerular atrophy and its severity was evidenced at 2nd

week PDC and continued till the

end of the experiment. Additionally, few focal areas showing hyperplasia of mesengial

cells in the glomerulus were also noticed in kidney upto the 12th

week of diabetes.

Furthermore, transmigration of inflammatory cells was also evident at 2nd

week of

diabetes. However severity of inflammatory foci was reduced at later time points. Details

of histopathological findings are presented, in the summary incidence table 1.

3.3. Liver

Liver of control rats showed a normal lobular architecture with hepatocytes arranged in

cord like pattern radiating from the central canal. Hepatic cords were lined

circumferentially by endothelial cells to form hepatic sinusoids that showed a normal

pattern in control rats (Fig. 15/a). In the diabetic rats hepatocytes were found to be

hypertrophied, that resulted in narrowing the sinusoidal space. Focal area of necrosis and

mild hepatocellular degenerative changes were also observed from 2nd

week PDC

onwards (Fig. 15/b-g). Additionally, hepatocytes also showed the increasing severity of

these lesions from 2nd

to 12th

week of diabetic duration. Foci of inflammatory cell

migration surrounding necrotic hepatocytes were also noticed with hypertrophied kupffer

cells in sinusoidal space in diabetic liver throughout the study (Fig. 14; hollow arrow)

depicting a consistent severe alteration in liver following STZ-induced diabetes. Details

of histopathological findings are presented, in the summary incidence (Table 1).

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4. Effect of diabetes on cognitive ability

4.1. Diabetes resulted in reduced spatial learning and memory

Barnes maze was used to assess the spatial learning and memory of the animals. The test

is based on the time duration and path efficiency taken by the animal to locate the escape

box that can be used to escape from the open surface of the maze. Diabetic animals

presented reduced spatial cognitive ability as compared to the controls. They took more

time to reach the escape box in barnes maze test (Fig. 4). The increment in test duration

was significant at 2nd

week (p≤0.023), 4th

week (p≤0.006), 6th

week (p≤0.001), 8th

week

(p≤0.018), 10th


week PDC (p≤0.047) of diabetic duration (Fig.

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3/i). The average speed of the diabetic animals was also found to be reduced at 2nd

week

(p≤0.023), 4th

week (p≤0.010), 6th

week (p≤0.001), and 8th


week

PDC (p≤0.001) as compared to their respective controls (Fig. 3/ii). Additionally,

following STZ-induction animals also presented poor path efficiency in locating the

escape box at all the diabetic time points (Fig. 3/iii) i.e., 2nd

week (p≤0.002), 4th

week

(p≤0.006), 6th

week (p≤0.001), 8th

week (p≤0.011), 10th


week

PDC (p≤0.001) as compared to their respective controls depicting a continual and

persistent spatial cognitive deficit in diabetic animals.

4.2. Diabetes caused alteration in working memory

The working memory of the experimental animals was tested on T-maze by assessing the

test duration and path efficiency taken by each animal in exploring the baited arm. STZ-

injected animals performed poor while exploring the baited arm (Fig. 6) as the test

duration was significantly higher and consistent upto the 12th

week of diabetes as

compared to their age-matched control animals (Fig. 5/i) i.e., 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week PDC (p≤0.001). Diabetic animals were also presented poor path efficiency in

reaching the baited arm at 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week PDC (p≤0.001) as compared to the

respective age-matched controls (Fig. 5/ii) confirming impaired spatial working memory

in diabetic conditions.

5. Diabetes caused anxiety like behaviour in animals

Elevated plus maze was used to assess the anxiety like behaviour. The test relies upon the

rat‟s preference toward enclosed, dark space (approach) and an unconditioned fear of

heights and/or open spaces (avoidance). Diabetic animals from the 2nd

week PDC were

presenting anxiety-like behaviour as compared to the age-matched controls (Fig. 8). The

percentage of time spend in open arm of diabetic rats were significant reduced in 2nd

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week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th

week

(p≤0.001) and 12th

week PDC (p≤0.001) as compared to their respective controls (Fig.

7/i). Simultaneously, the percentage of open arms entries was also significantly reduced

at all the diabetic time points (Fig. 7/ii) i.e., 2nd

week (p≤0.01), 4th

week (p≤0.01), 6th

week (p≤0.01), 8th

week (p≤0.01), 10th


week PDC (p≤0.01) as

compare to their controls. Furthermore the anxiety index was significantly increased in

diabetic animals (Fig. 7/iii) i.e., at 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week

(p≤0.001), 8th

week (p≤0.001), 10th



compared to their age-matched controls indicating the diverse effect of diabetes on the

emotionality of the animals.

6. Decreased motor coordination following STZ-induced diabetes

Motor coordination was assessed as total length of time spent by the animals on the

rotating rod. The test measures the riding time of the animal on the accelerating rod as

falling latency. The falling latency of diabetic animals were significantly decreased at 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th

week

(p≤0.001) and 12th

week PDC (p≤0.001) as compared to their respective controls (Fig.

9/i). Therefore, it is evident that diabetes resulted in reduced motor coordination and this

alteration was sustained for a longer duration.

7. Altered neuromuscular strength following diabetes

Forelimb muscular strength was measured by the grip strength meter to assess the effect

of diabetes on the neuromuscular strength of the animals. A significant reduction was

observed in the grip strength of diabetic animals at 2nd

week (p≤0.001), 4th

week

(p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week

PDC (p≤0.002) as compared to their respective controls (Fig. 9/ii) indicating the adverse

and long term effect of diabetes in terms of reduced muscular strength.

8. Diabetic animals presented altered motor activity

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Animal‟s locomotor activity in open field test is explained in terms of motor output,

freezing, grooming, rearing and exploration behaviour of the animal at novel

environment. Diabetic animals presented hyperactivity with significantly increased

distance travelled consistently at all the PDCs as compared to their respective controls

(Fig. 10/i, 11) i.e., 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week

(p≤0.001), 10th


week PDC (p≤0.002).

The resting time duration of the diabetic animal as a resultant of hyperactivity

was significantly reduced at 2nd

week (p≤0.005), 4th

week (p≤0.001), 6th

week (p≤0.001),

8th

week (p≤0.001), 10th


week (p≤0.002) of diabetes as compared

to their controls (Fig. 10/ii).

On exposure to the novel environment diabetic animals were doing more non-locomotor

activities (Stereotypic movements) like grooming, scratching, etc. Thus, the stereotypic

time was significantly increasing from the 2nd

week onwards i.e., 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week (p≤0.001) PDCs (Fig. 10/iii) as compared to their age-matched control animals.

Similar trend of increment was also observed in the ambulatory time of the diabetic

animals they were doing more ambulatory movements like walking, circling or rearing

behaviour in the testing area (novel environment). Accordingly, STZ-induced animals

presented significantly increased ambulatory time at 2nd

week (p≤0.017), 4th

week

(p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week

(p≤0.001) PDCs as compared to their controls (Fig. 10/iv).

9. Diabetes causing oxidative stress in various vital organs

Assessment of oxidative stress not only explains the level of cytotoxicity in terms of free

radicals generation but also reveal the dysregulation of essential cell membrane

functions. Following STZ-induced diabetes the tissue lipid peroxidation (LPO) end

product concentration i.e., malondialdehyde (MDA) was significantly higher (15-20%) in

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all the vital tissues i.e., hippocampus, kidney and liver as compared to the respective

controls. The stature of oxidative stress in hippocampus was persistent throughout the

12th

week of diabetic duration (Fig. 12/i). At 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p=0.001), 10th


week PDC (p≤0.001)

the level of MDA is significantly higher as compared to their respective controls.

Furthermore in kidney also the tissue MDA concentration was significantly higher in all

the diabetic time points i.e., at 2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week

(p≤0.001), 8th

week (p≤0.001), 10th



compared to their respective controls (Fig. 12/iii). Similar effect of diabetes was also

observed in liver as the MDA tissue concentration was increased at 2nd

week (p≤0.001),

4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week (p≤0.001) of diabetes as compared to their respective controls (Fig. 12/ii).

10. Histoarchitectural alterations in brain following diabetes

Neuronal integrity was assessed in the CA1, CA2, CA3 and DG sub regions of

hippocampus and cerebellum of control and diabetic rat using haematoxylin and eosin

staining.

10.1. Histoarchitectural alterations in hippocampus

Control rats showed regular arrangement of neurons and various types of glial cells in the

cell layers of all the hippocampal subfields (Fig. 16-19/a). However, in diabetic

hippocampus neurons and glial cells showed various degenerative changes noted at

different time points in all the hippocampal subfields i.e., CA1 (Fig. 16/b-g), CA2 (Fig.

17/b-g), CA3 (Fig. 18/b-g), and DG (Fig. 19/b-g). From 2nd

weeks onwards diabetic rat

hippocampus showed minimal to mild degenerative changes characterized by the

ballooning of neuronal and glial cells in all the hippocampal subfields. Focal area

showing a very few necrotic and pyknotic (dark cells) neurons in stratum pyramidale

layer of CA1, CA2 and CA3 (Fig. 16-18/b) and in granule cell layer of DG region (Fig.

108

19/b) were also clearly evident at 2nd

week PDC. A substantial number of neurons

showed necrosis/ apoptosis and severity of this episode got increased with time and was

at the peak during 12th

week PDC as observed in all the hippocampal subfields. Mild to

moderate chromatolysis with cellular acidophilia was observed in the neurons in 4th

to 6th

week PDC (Fig. 16-19/c, d) and its severity got exacerbated at 8th

to 12th

week following

diabetes (Fig. 16-19/c, d). At this stage (8th

to 12th

week PDC) hippocampal parenchyma

showed vacuolation due to increase in the number of lost cells. An extensive gliosis was

also evidenced in all the hippocampal subfields. Incidence of gliosis was mainly

observed around the necrotic and apoptotic cells. Details of histopathological findings are

presented, in the summary incidence table (Table 2).

109

10.2. Histoarchitectural changes in the cerebellum during diabetes:

Cerebellum of control rats stained with haematoxylin and eosin showed intact

arrangement of molecular, Purkinje and granular cell layers with normal distribution of

glial cells (Fig. 20/a). Purkinje cell monolayer was continuous with a centrally placed

nucleus in the cell body. STZ-induced diabetic rats also showed intact arrangement of all

the three layers. In contrast to control most of the Purkinje cells of the diabetic

cerebellum were swollen, showing chromatolysis and vacuolation, suggesting necrotic

cell death. This focal area of necrosis was surrounded by activated glial cells depicting

the typical histomorphology of neuronophagia (Fig. 20/b-g). In addition, some Purkinje

110

neurons presented shrunken and pyknotic appearance suggestive of apoptotic cell death

(Fig. 20/b-g). Severity and incidence of dying or degenerating cerebellar cells increased

with the advancing stage of diabetes. Activation of astroglia and microglia was evident

from 2nd

week and remained consistent till 12th

week of the diabetic rat cerebellum. In the

later stages activated, glial cells were circumscribing the necrotic/ apoptotic neurons (Fig.

20/c-g). Interestingly, a discontinuity in the Purkinje cells monolayer indicates a

correlation with the severity of degenerative histoarchitectural alterations following

diabetes. Details of histopathological findings are presented, in the summary incidence

table (Table 3).

11. Cell death following diabetes

To investigate the diabetes associated apoptotic cell death, active caspase-3

immunolabelling was performed in both hippocampus and cerebellum. Caspase-3 has

been accepted to be the major executioner of the cell death mechanism. Any brain injury

or disorder activates the caspase-3 and its profuse expression validates the severity of the

brain disorder.

111

11.1. Cellular death in hippocampus during STZ-induced diabetes

A very few cells were presented caspase-3 immunopositivity in controls (Fig. 21/a.i-iv).

The apoptotic cells were more pronounced in DG region than in CA1, CA2 and CA3

regions of the diabetic rat hippocampus (Fig. 21/a-g.iv). While arbitrating the

morphology of the stained cells, the active caspase-3 expression was mainly present in

the cytoplasm and processes of the degenerating cells. On 2nd

week PDC onwards the

dying caspase-3 positive cells were more pronounced in stratum radiatum and stratum

pyramidal cell layer of CA1, CA2 and CA3 region. While in DG region the apoptotic

cells were scattered in both granular and polymorphic layer in all the diabetic time points.

Quantitatively, the apoptotic cell population was increasing in all the diabetic time points

consistently in all the hippocampal fields (Fig. 22/i) i.e., in CA1 (p≤0.001), CA2

(p≤0.001), CA3 (p≤0.001) and DG region (p≤0.001) as compared to the respective

controls suggesting a severe cellular degeneration in the hippocampal tissue following

diabetes. Volumetric fraction (area fraction) assessment also showed a significant

increment in the percentage of active caspase-3 expression in CA1, CA2, CA3 and DG

region at all the diabetic time points as compared to the respective controls (Fig. 22/ii).

11.2. Cell death in cerebellum following diabetes:

Similar pattern of cellular damage was also observed in cerebellum as a reflective cell

death was observed following STZ-induced diabetes upto 12 weeks from active caspase-

3 immunolabelling. Active caspase-3 positive cells were clearly evident in molecular

layer, Purkinje cell layer and granule cell layer of the diabetic cerebellum (Fig. 23/b-g) as

compared to the controls having minimal presence of active caspase-3 labelled cells (Fig.

23/a). Interestingly, active caspase-3 expression was more prominent in the nuclei of

Purkinje cells and in surrounding Bergmann glial cell bodies in comparison to the

molecular and granule cell layer (Fig. 23/b-g). The inclination in Purkinje and Bergmann

cell degeneration was constant at all the diabetic time points as compared to the controls.

112

Quantitatively, caspase-3 positive cells were significantly increasing with advancing

diabetic state i.e., 2nd

week (p≤ 0.001), 4th

week (p≤ 0.001), 6th

week (p≤ 0.001), 8th

week

(p≤ 0.001), 10th


week PDC (p≤ 0.001) as compared to their

respective controls (Fig. 24/i) suggesting a severe cellular degeneration in the cerebellar

tissue. Percentage of area fraction of caspase-3 expression was also showing the similar

trend. The increment of caspase-3 expression was consistent at all the diabetic time

points i.e., 2nd

week (p≤ 0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week

(p≤0.001), 10th


week PDC (p≤0.001) as compared to their

respective controls (Fig. 24/ii).

12. Glial activation and proliferation following STZ-induced diabetes

To examine the glial activation, we gauged and compared the distribution of cells

immunoreactive for the astrocyte (GFAP) and microglial (Iba-1) markers in the

hippocampus of STZ-induced diabetic and age-matched control rats. The activated state

was judged by phenotypic changes, increase in cell number and glial cell scoring. The

activation stature was further confirmed by the immunoexpression of OX-6 and OX-42

for microglia and S100β for astrocyte. Glial activation assessment was also done in

cerebellar tissue to investigate and compare the further effect of diabetes on other brain

regions.

12.1. Glial phenotypic switching

12.1.1. Astroglial activation following diabetes

GFAP (Glial fibrillary astrocytic protein) is an intermediate filament protein in astroglia,

popularly used to study the astroglial structure and associated functions.

12.1.1.1. Hippocampus: Immunohistochemical analysis showed an elevated expression

of GFAP protein following diabetes in hippocampus alongwith an alteration in the

morphology of GFAP-labelled astroglia in CA1, CA2, CA3 and DG regions of

hippocampus from 2nd

week onwards (Fig. 26/b-g.i-iv). Resting astroglia in controls

113

presented thin, fine, intact processes with small cell body (Fig. 24/a. i-iv). The presence

of resting astroglia was consistent in all the control groups upto the 12th

week of diabetic

duration.

At 2nd

and 4th

week of diabetes the GFAP immunolabelling was more intense and

hypertrophied astroglia with activated phenotype, i.e., thick, dense, bushy and

extensively overlapping processes with enlarged darkly stained cell body were present

(Fig. 25/b-d). Such cells were more common in CA1, CA2, CA3 and DG regions of the

hippocampus (Fig. 26/b, c. i-iv). Interestingly, hypertrophied astroglial cells at 4th

week

of diabetes were also having fragmented processes (Fig. 25/c,d; 26/c.i-iv). From 6th

week

onwards, the unevenly distributed reactive astroglia having thicker, fragmented and

overlapped processes, with deeply stained cell body, were clearly observed indicating the

astroglial dystrophy in all the aforementioned hippocampal regions (Fig. 26/d, g. i-iv).

Interestingly, the scenario of astroglial activation is regular in all the neuronal cell layers

of the hippocampus suggesting a long term effect of STZ-induced diabetes on

hippocampus astroglial population.

12.1.1.2. Cerebellum: An increased GFAP expression in the diabetic cerebellum upto

12th

week of diabetes was immunohistochemically observed. The GFAP labelled

Bergmann glial fibres in controls were presented intact, thin and erect morphology (Fig.

28/a) while in diabetic animals Bergmann glial fibres became hypertrophied, fragmented

and disorganised at all the time points (Fig. 28/b-g). The astroglia in the white matter and

granule cell layer also presented activated morphology having thick, dense and

fragmented processes with the darkly stained cell body (Fig. 29/b-g) as compared to the

resting astroglia with thin processes and lightly stained cell body in controls (Fig. 29/a).

12.1.2. Microglial response during diabetes

12.1.2.1. Hippocampus: Microglial alterations in hippocampus during diabetes were

studied with the immunoexpression of Iba-1 (Ionized calcium binding adaptor molecule-

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1). It is a calcium binding protein that not only participates in membrane ruffling but also

regulates the functioning of microglia. In brain, Iba-1 protein expression is specifically

restricted to the microglial cells.

Following STZ-induced diabetes, Iba-1+ cells in the entire hippocampus were

presenting activated morphology as compared to the controls (Fig. 31, 32). The

microglial cells were showing phenotypic transformation, i.e., from ramified to activated

states bearing retracted, thick processes and large irregular cell body (Fig. 31/b-d; Fig.

32/b-g). In controls resting microglia cells processes exhibited ramified wispy

appearance with round lightly stained cell body (Fig. 31/a) throughout the hippocampus

subfields upto the 12th

week PDC (Fig. 32/a.i-iv).

In diabetic hippocampus, by 2nd

week PDC the resting/ramified microglia get

transformed into intermediate activated state having thick processes with enlarged cell

body mainly in CA1 and CA3 regions of the hippocampus (Fig. 32/b.i, iii) while in CA2

and DG regions microglial cells were showing mild activation (Fig. 32/b.ii, iv). Fourth

week onwards, the intermediate activated microglial cells became fully activated with

intense labeling, thicker and retracted processes and larger irregular or rod shaped cell

body undergoing hypertrophy that was preceded by hyperplasia (Fig. 32/c-g). The

activation state of microglia was consistent in CA1, CA2, CA3 and DG regions of the rat

hippocampus upto the 12th

week PDC depicting an austere and long term response of

microglial cells, as first line of defense following diabetes.

12.1.2.2. Cerebellum: STZ-induced diabetes resulted in intense microglial activation and

morphological transformation to activated phenotype in the cerebellum as shown by Iba-

1 immunolabelling. In controls, microglia were seen with resting morphology having

small, thin, multiple processes and round small cell body (Fig. 34/a). Following diabetes,

an increase in Iba-1 expression was clearly evident in the cerebellar microglia. With the

advancing diabetic duration, the resting microglia got transformed into activated state

115

exhibiting thick and fewer numbers of processes with darkly stained Iba-1 positive

irregular cell body (Fig. 34/b-g).

12.2. Glial proliferation in response to STZ-induced diabetes

12.2.1. Astrocyte proliferation during diabetes

12.2.1.1. Hippocampus: Cell proliferation and associated glial activation in all the

regions of hippocampus was not only prominent but also accentuated on successive time

duration following diabetes. GFAP labelled cell quantification showed that there was a

considerably steep increment in the number of astroglia in all the hippocampal subfields.

The population of reactive astroglia was significantly dense in CA1 (p≤0.001), CA2

(p≤0.05), CA3 (p≤0.001) and DG (p≤0.001) region as compared to the respective

controls (Fig. 27/i). Volumetric fraction (area fraction) assessment also showed a

significant increment in the percentage of GFAP expression in CA1, CA2, CA3 and DG

region during the 2nd

(p≤0.001), 4th

(p≤0.001), 6th

(p≤0.001), 8th

(p≤0.001), 10th

(p≤0.001)

and 12th

(p≤0.001) week of diabetic duration as compared to the respective controls (Fig.

27/ii).

12.2.1.2. Cerebellum: Quantification of GFAP positive cells showed a significant gradual

increment (p≤0.001) in astroglia population at all the diabetic points i.e., 2nd

week

(p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th

week

(p≤0.001) and 12th

week (p≤0.001) as compared to their respective controls. A

progressive escalation was also observed in the cerebellar astroglial population following

diabetes (Fig. 30/i). Volumetric fraction (area fraction) assessment also showed a

significant increment in the percentage of GFAP expression at all the diabetic points i.e.,

2nd

week (p≤0.001), 4th

week (p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week (p≤0.001) as compared to their respective controls (Fig.

30/ii).

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12.2.2. Diabetes leads to the microglial proliferation

12.2.2.1. Hippocampus: Cell quantification of Iba-1 immunopositive cells revealed a

gradual increase in microglial population indicative of cell proliferation in brain

following STZ-induced diabetes. There was a significant (p≤0.001) increment in

microglial population throughout the hippocampus i.e., in CA1, CA2, CA3 and DG

region on every subsequent diabetic time point i.e., at 2nd

(p≤0.01), 4th

(p≤0.01), 6th

(p≤0.01), 8th

(p≤0.01), 10th

(p≤0.01) and 12th

week (p≤0.01) PDCs as compared to their

respective controls (Fig. 33/i). Volumetric fraction (area fraction) assessment also

showed a significant increment in the percentage of Iba-1 protein expression in CA1,

CA2, CA3 and DG region during the 2nd

(p≤0.01), 4th

(p≤0.01), 6th

(p≤0.01), 8th

(p≤0.01),

10th

(p≤0.01) and 12th

(p≤0.01) week of diabetic duration as compared to their respective

controls (Fig. 33/ii).

12.2.2.2. Cerebellum: A significant increase was observed in microglial population in the

diabetic rat cerebellum at all the time point studied i.e., 2nd

week (p≤0.001), 4th

week

(p≤0.001), 6th

week (p≤0.001), 8th

week (p≤0.001), 10th


week

PDC (p≤0.001) as compared to their respective controls indicating microgliosis in

response to the alterations following diabetes (Fig. 35/i). Percentage of Iba-1 expression

as area fraction in diabetic cerebellum was also significantly increasing throughout the

study i.e., at 2nd

week (p=0.044), 4th

week (p=0.002), 6th

week (p=0.001), 8th

week

(p≤0.001), 10th


week (p≤0.001) of diabetic cerebellum as

compared to their respective controls (Fig. 35/ii).

13. S100β positive cells in diabetic rat hippocampus

S-100β, a calcium binding protein is well-accepted astrocytosis marker that particularly

associated with astrocytic activated states and functions. S100β immunolabelling was

performed to further verify the astroglial activation.

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Immunolabelling confirmed the presence of S100β positive cells in all the

hippocampal regions (Fig. 36/b-g) following diabetes. Hippocampal cells

immunolabelled with S100β had round or irregular shaped cell body with thick

processes. These S100β+ cells in diabetic hippocampus were showing stellate

morphology having large cell body and thick processes similar to the activated

astrocytes. Such S100β+ astrocytes were common in all the hippocampal regions i.e.,

CA1, CA2, CA3 and DG throughout the 12th

week PDC (Fig. 36/b-g. i-iv). While in

controls very mild S100β positivity was recorded in all the hippocampal subfields (Fig.

36/a.i-iv). The S100β labelled cell population was gradually increasing following

diabetes and consistent upto the 12th

week of diabetic duration displaying the adverse

effect of increased blood glucose level as astrogliosis in hippocampus.

14. Antigen presenting cells in diabetic hippocampus

OX-6 (MHC-II) immunolabelling was performed to detect the antigen presenting cells in

hippocampus following STZ-induced diabetes. In brain, microglial cells are the primary

mediators of MHC-II antigen presentation and processing. OX-6 is also regarded as an

activation-specific microglial marker.

Immunolabelling revealed a profound expression of OX-6 positive cells in all the

subregions of the diabetic hippocampus from 2nd

week PDC (Fig. 37/b-g). The OX-6

expressing cells were common in both pyramidal and granular layer of all three

hippocampal subregions. In controls the expression was very low in all the hippocampal

subfields (Fig. 37/a.i-iv). Cell quantitation results revealed a significant and gradual

elevation in MHC-II expressing cells in the entire hippocampus upto the 12th

week PDC,

i.e., in CA1 (p≤0.001), CA2 (p≤0.001), CA3 (p≤0.001) and DG region (p≤0.001) as

compared to their respective controls (Fig. 38/i). Volumetric fraction (area fraction)

assessment also showed a significant increment in the percentage of OX-6 expression in

CA1, CA2, CA3 and DG region during the 2nd

(p≤0.01), 4th

(p≤0.01), 6th

(p≤0.01), 8th

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(p≤0.01), 10th

(p≤0.01) and 12th

(p≤0.01) week of diabetic duration as compared to their

respective controls (Fig. 38/ii). The significant expression of OX-6 not only depicted the

activation of microglial cells but also evidenced the state of inflammation following

diabetes in hippocampus as MHC-II signalling plays an imperative role in inflammation

retorting to both endogenous and exogenous antigenic proteins.

15. Effect of diabetes on OX-42 expressing cells in hippocampus

OX-42 recognizes the type 3 complement receptors (CR3) in mononuclear phagocytes.

Thus, OX-42 immunolabelling was performed to assess the microglia/macrophages

activation following diabetes.

A robust microglia/macrophages activation was observed at 2nd

week PDC till the

12th

week of diabetic state, the aftermost time point investigated in our study (Fig. 39/b-

g). In controls, however resting/ ramified microglia morphology having small, thin

processes and small round cell bodies expressing CR3 (OX-42 positive) were seen (Fig.

39/a.i-iv). Such resting/ramified microglial cells were homogenously distributed in all the

hippocampal subfields.

During diabetic state OX-42 positive microglial cells were intensely labelled,

thicker and possessed retracted processes with larger irregular or rod shaped cell body

indicating austere microglial activation in hippocampus (Fig. 39/b-g.i-iv). These

activated cells were mainly present in stratum radiatum and stratum oriens while fewer in

stratum pyramidale. Accumulation of activated microglia near pyramidal neurons

indicated the moniker protecting approach of microglia cells via enfolding the

degenerating neuronal cells. The scenario of microglial activation was consistent upto

12th

week PDC. Quantitatively, the population of OX-42 immunolabelled cells was

significantly dense and sequentially increasing in CA1 (p≤0.001), CA2 (p≤0.001), CA3

(p≤0.001) and DG (p≤0.001) region as compared to their respective controls (Fig. 40/i).

Volumetric fraction (area fraction) assessment also showed a significant increment in the

119

percentage of OX-42 expression in CA1, CA2, CA3 and DG region during the 2nd

(p≤0.001), 4th

(p≤0.001), 6th

(p≤0.001), 8th

(p≤0.001), 10th

(p≤0.001) and 12th

(p≤0.001)

week of diabetic duration as compared to their respective controls (Fig. 40/ii). The

plethoric presence of OX-42 (CR-3) positive activated microglial cells in hippocampus

confirmed the incidence of neuroinflammation-related brain disorder following diabetes.

16. Macrophagic cell stature in hippocampus following diabetes

ED-2 or CD-163 is a glycoprotein of class B of the scavenger receptor cysteine rich

superfamily exclusively expressed on the perivascular (PV) and meningeal macrophages.

It is a phagocytic marker which also performs immunoregulatory functions.

Immunoexpression of CD-163 is associated with the resolution phase of inflammation

and the alternative activation of macrophages. Thus, it is useful in the assessment of

prolific microglial activation (express more in perivascular microglia, than in

parenchymal microglia) and resulted inflammation following diabetes.

The ED-2 immunolabelling revealed an increased presence of macrophagic cell

population in hippocampus following STZ-induced diabetes (Fig. 41). In controls, the

immunoexpression was weak in terms of both labelling and quantification indicating the

negligible incidence of phagocytic activity and inflammation following microglial

activation (Fig. 41/a.i-iv).

From 2nd

week PDC the presence of ED-2 positive cells increased sequentially upto the

6th

week PDC (Fig. 41/b-d.i-iv). Afterwards, a decrement was observed from 8th

week

PDC, but significantly higher than the respective controls upto the 12th

week PDC and

remained steady (Fig. 41/e-g.i-iv). Quantitatively, the population of ED-2 positive cells

were consistent and significantly higher in all the hippocampal fields i.e., in CA1

(p≤0.001), CA2 (p≤0.001), CA3 (p≤0.001) and DG region (p≤0.01) as compared to their

respective controls (Fig. 42/i). Volumetric fraction (area fraction) assessment also

presented a significant increment in the percentage of ED-2 positive cells in CA1, CA2,

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CA3 and DG region during the 2nd

(p≤0.01), 4th

(p≤0.01), 6th

(p≤0.01), 8th

(p≤0.01), 10th

(p≤0.01) and 12th

(p≤0.01) week PDC as compared to their respective controls (Fig.

42/ii).

17. Neuroinflammation in hippocampus following diabetes

To assess whether oxidative stress, cell death and glial activation following STZ-induced

diabetes promotes the neuroinflammation, we have evaluated the expression levels of

pro-inflammatory cytokines, i.e., IL-1β and TNF-α in the hippocampus.

17.1. IL-1β expression in hippocampus following diabetes

An increased and pronounced immunoexpression of IL-1β was observed in hippocampus

following diabetes (Fig. 43). The IL-1β positive cells were clearly observed in stratum

radiatum and stratum oriens layer of CA1 and CA3 region of the diabetic hippocampus

(Fig. 43/b-g. i,iii), while in CA2 region the IL-1β positive cells were more in stratum

pyramidale as compared to the other neuronal layers (Fig. 43/b-g. ii). In DG region the

expression was consistent in both granular and polymorphic layer (Fig. 43/b-g. iv).

Similar stature of IL-1β expressing cells was observed throughout the 12th

week PDC.

However, in controls the population of IL-1β positive cells was very low in all the

hippocampal subfields throughout the study (Fig. 43/a.i-iv). Cell quantification also

presented a significant and regular appearance of IL-1β positive cells in the entire

hippocampus upto the 12th

week of diabetes i.e., in CA1 (p≤0.001), CA2 (p≤0.001), CA3

(p≤0.001) and DG region (p≤0.001) as compared to their respective controls (Fig. 44/i).

Volumetric fraction (area fraction) assessment also showed a significant increment in the

percentage of IL-1β expression in CA1, CA2, CA3 and DG region during the 2nd

(p≤0.01), 4th

(p≤0.01), 6th

(p≤0.01), 8th

(p≤0.01), 10th

(p≤0.01) and 12th

(p≤0.01) week of

diabetic duration as compared to their respective controls (Fig. 44/ii). The data indicated

the occurrence and persistent stature of neuroinflammation in hippocampus for a long

duration following STZ-induced diabetes.

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17.2. TNF-α expression in hippocampus following diabetes

Tumor-necrosis factor-α (TNF-α) is a pro-inflammatory cytokine with potent stimulatory

actions in immune and vascular responses. It plays a major role in stimulation and

propagation of neuroinflammation following brain insults.

Throughout the study the TNF-α immunolabelling in controls was negligible both

in terms of expression (Fig. 45/a.i-iv) and quantification (Fig. 46/i,ii). In diabetic

hippocampus the immunoexpression of TNF-α positive cells was significantly higher and

consistent in all the hippocampal subfields upto the 12th

week PDC (Fig. 45/b-g.i-iv). The

TNF-α expressing cells were more in stratum oriens and stratun radiatum neuronal layers

than in stratum pyramidale layer of CA1, CA2 and CA3 region of hippocampus (Fig.

45/b-g.i-iii). Similarly, in DG region the expression of TNF-α positive cells was regular

in both granular and polymorphic layer (Fig. 45/b-g.iv). Quantitatively, the population of

TNF-α immunolabelled cells was significantly dense and increased in CA1 (p≤0.001),

CA2 (p≤0.01), CA3 (p≤0.001) and DG (p≤0.001) region as compared to their respective

controls (Fig. 46/i). Interestingly, the TNF-α expressing cells sequentially increased from

2nd

week PDC onwards. The significant presence of pro-inflammatory cytokine TNF-α,

directs towards the long term neuroinflammatory state in hippocampus following

diabetes. Volumetric fraction (area fraction) assessment also showed a significant

increment in the percentage of TNF-α positive cells in CA1, CA2, CA3 and DG region

during the 2nd

(p≤0.001), 4th

(p≤0.001), 6th

(p≤0.001), 8th

(p≤0.001), 10th

(p≤0.001) and

12th

(p≤0.001) week PDC as compared to their respective controls (Fig. 46/ii).

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DISCUSSION

Diabetes mellitus (DM) is one of the most severe metabolic disorders in humans

characterized by the hyperglycemia due to relative/an absolute lack of insulin or the

action of insulin on its target tissue or both. It is now a global health concern with a

affected population of 347 million worldwide (IDF, 2014). Diabetic patients seem to

have more risk of developing Alzheimer‟s disease and other dementias as such DM

associated alterations in CNS and resulted neurological consequences have become

priorities in neuroscience research (Biessels et al., 1994, 2008; Arvanitakis et al., 2004;

Northam et al., 2006; Kawamura et al., 2012; Cardoso et al., 2013; Wang et al., 2014).

Impairments of cognitive deficits (Popoviç et al., 2001; Baydas et al., 2003a; Biessels et

al., 2008; Alvarez et al., 2009; Choi et al., 2009; Zavoreo et al., 2014; Nagayach et al.,

2014a), reduced muscular strength (Andersen et al., 2005; Nagayach et al., 2014b),

behavioural deficits (Sweetnam et al., 2012; Nagayach et al., 2014b), anxiety (Lustman

and Clouse, 1990; Grigsby et al., 2002; Herzer and Hood, 2010) and depression (Talbot

and Nouwen, 2000; Egede and Ellis, 2010) are well documented in both type 1 and type

2 diabetes mellitus. Besides, information on the systematic mechanisms explaining the

associative reciprocity among the various brain regions and cells to DM is deficient till

date. There are only few studies explaining the diabetic encephalopathy in terms of

cognitive and behavioural dysfunctions with limitations (Mc Call, 1992; Biessels et al.,

1994; Coleman et al., 2004; Kodl and Seaquist, 2008; Guven et al., 2009; Choi et al.,

2009; Alvarez et al., 2009). The pathophysiological and/or cellular mechanisms

explaining diabetes allied impediments is limited to the causative factors like poor

glycemic control, insulin dependency and oxidative stress (Egede, 2006; Liu et al., 2008;

Gupta et al., 2014). Diabetes associated alterations range from structural, cellular to

neurochemical changes leading to direct neuronal damage, oxidative stress, cell death

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and loss of information processing (Thorré et al., 1997; Alvarez et al., 2009; Nagayach et

al., 2014a, b).

The structure and functions of glial cells in healthy and diseased brain is always

been a matter of debate and deliberate research. Glial cells are now recognized as an

elementary contributor in the pathogenesis of various neurological disease and disorders

(Heneka et al., 2010; Parpura et al., 2012; Verkhratsky et al., 2014). Understanding of the

imperative and multitasking attribute of glial cells in brain, its stature and response

following diabetes allied cognitive and behavioural impairments deserves pertinent

investigation. The present study is an approach to fulfil the lacunae on the role of glial

cells and associated immune response in cognitive and behavioural deficits in

experimentally induced diabetes models.

The hippocampus plays major role in several cognitive aspects linked to emotional,

learning, memory and sensorimotor functions (Bast, 2007). Furthermore, cerebellum is

associated with emotion, cognition and behaviour (Rapoport et al., 2000; Schmahmann

and Caplan, 2006) and any alterations to the cerebellum lead to motor deficits, dementia,

schizophrenia and other psychiatric disorders (Baldaçara et al., 2008; Sui and Zhang,

2012). Hence we have studied these two tissues.

Long term physiological changes as a consequent of increased blood glucose level

following STZ-induction

The consequences of type 1 diabetes are well studied in the STZ-induced experimental

animal models. Similar to the previous studies (Choi et al., 2009; Coleman et al., 2004,

2010) the STZ-induced animals were showing increase in blood glucose level, food and

water intake, brain-body weight ratio and decreased body weight, directing towards the

marked destruction of insulin secreting pancreatic β-cells by STZ (Junod et al., 1969).

During diabetes, the glucose utilization in the brain gets decreased (McCall, 1992), due

124

to reduction in BBB glucose transporters (Choi et al., 1989; Pardridge et al., 1990),

which further makes the brain more vulnerable to the critical pathological events. The

consequence of diabetes was well manifested by the decreased brain weight which might

be due to the increased cell death (Jakobsen et al., 1987) in brain has also been evidenced

in this study.

Pancreatic and other vital organs damage grounded the confirmation for STZ-

induced diabetic model

In our study we have observed a persistent damage in pancreas, kidney and liver upto the

12th

week PDC. In both STZ and alloxan- induced type -1 diabetes models there is an

irreversible pancreatic damage that includes decrease of secretory granules, fusion of

some granules and pyknotic nuclei, adipose tissue infiltration and localized lymphocytic

cell accumulations are reported (Li et al., 2000; Jelodar et al., 2005; Abdel Aziz et al.,

2013). Similar irreversible degeneration was also observed in the histopathological

evaluation of pancreas. This was initiated from the 2nd

week PDC and sustained upto the

12th

week PDC. Enhanced AGEs production, oxidative stress and increased level of

cytokines following type 1 diabetes, resulting in exocrine pancreatic atrophy that

includes the severe loss of the islet of Langerhans in exocrine pancreatic tissue (Gepts,

1965), swollen, necrotic and vacuolated beta cells having condensed nucleus with loss of

cytoplasmic granularity has been observed (Mir et al., 2008). Such changes have also

been recorded in the present investigation.

Effect of STZ-induced diabetes was clearly evidenced in kidney and upto the 12th

week PDC the alterations in renal structure and function was consistent and severe. Most

presumptive symptoms of diabetes include polyuria (excess of urination) that in

uncontrolled diabetic state resulted in severe kidney damage or diabetic nephropathy

(Mauer et al., 1984; Makino et al., 1996). Diabetes associated hyperglycemia trigger

125

multiple mechanisms that instigates not only the development but also extend the

outcomes of nephropathy (Ziyadeh, 2004). Hyperglycemia activates vasoactive systems

(renin–angiotensin–aldosterone and endothelin systems) which further interact with

metabolic system and genetic predisposition and aggravate the kidney damage

(Dronavalli et al., 2008). We observed similar alterations in experimentally induced

diabetic kidney that resulted in functional and structural changes of nephron like

glomerular infiltration and hyperfusion, thickening of the glomerular basement

membrane, glomerular hypertrophy, decreasing the width of Bowman‟s space, thickening

of the parietal layer of Bowman‟s capsule, hyalinisation, glomerulosclerosis and

mesangial expansion, etc. This is in agreement with the findings of Şen et al. (2002),

Öztürk et al. (2005), and Ozdemir et al. (2009).

Furthermore, the necessary function of balancing the blood glucose homeostasis

makes the liver more vulnerable to any blood glucose fluctuation. Thus, during diabetes

the increment in blood glucose level resulted in imbalance of oxidation-reduction

reactions in hepatocytes, which further triggers the generation of AGEs and lead to the

state of oxidative stress. Histopathologically, the accumulation of fatty molecules or

hyperlipidemia is a most apparent observation in type 1 diabetic liver (Ohno et al., 2000;

Zafar et al., 2009). Alike previous studies there were many pathological changes also

observed in our study of diabetic liver including dilated sinusoids, periportal fatty

infiltration, degenerated or necrotic hepatocytes with polymorphic nuclei, hyperplasia of

bile duct, etc. (Cameron et al., 2005; Zafar et al., 2009; Ozdemir et al., 2009).

The irreversible pancreatic damage (Abdel Aziz et al., 2013), renal (Finne et al.,

2005; Reutens, 2013) and liver (Martin and Tomlinson, 2014) pathogenesis are

considered as major complications of type 1 diabetes. The severe destructions of insulin

producing pancreatic beta cells upto the 12th

week PDC validates the increased blood

glucose level following STZ-induction. Furthermore, renal and liver damage as observed

126

in the study not only confirms the incidence of polyuria, body weight loss and subsequent

polyphagia to reimburse the energy loss during diabetes.

Diabetes resulted in cognitive and behavioural alterations

Manifestations of diabetes related cellular changes in brain believed to cause reduced

cognitive ability (Alvarez et al., 2009) and high susceptibility for dementia and

Alzheimer‟s disease (Biessels et al., 1994; Ristow, 2004; Northam et al., 2006). The

degenerative changes in neurons (Suh et al., 2007) and declined neurogenesis (Choi et

al., 2009; Alvarez et al., 2009) resulted in significant cognitive impairment. In

coincidence with these reports we found that STZ-induced animals were performing

poorly on Barnes maze and T maze tasks revealing a reduced spatial learning and

working memory. Similar alterations were also observed in the motor behaviour and

muscle strength of the diabetic animals as they were showing reduced falling latency on

Rotarod and poor or weak muscular strength in grip strength meter indicating impaired

motor/ muscle activity upto the 12th

week PDC. Alterations in motor behaviour following

diabetes was previously well reported both in human and animal models with underlying

causes of increased blood glucose level associated micro- or macrovascular

complications (Demirbüken et al., 2012) and altered neurotransmission (Sherin et al.,

2012). On elevated plus maze STZ-injected diabetic animals present anxiety behaviour as

they had higher and consistent anxiety index than the controls upto the 12th

week PDC.

The anxiety index of the diabetic animals coalesces various variables (like percentage of

entries in the open arm and total number of entries in both the arms) assessed during

exploration in the elevated plus maze and specifies an inclusive tendency of emotionality

of the animal (Cohen et al., 2013). A similar anxiety-like behaviour in type 1 diabetic

patients in relation to the poor glycemic control has been evidenced (Collins et al., 2009;

Herzer and Hood, 2010).

127

Open field test was generally intended as a test of exploration, locomotor activity

and anxiety (Walsh and Cummins, 1976; Prut and Belzung, 2003; Ramos et al., 2008). In

open field test diabetic animals presented increased locomotor activity, stereotypic time

(grooming, rearing etc.) and ambulatory time indicating the altered motor activity and

aberrant exploratory behaviour in the novel environment as has been reported in earlier

studies (Ramanathan et al., 1998; Belviranli et al., 2012). Belviranli et al. (2012) have

shown that altered grooming behaviour is an index of anxiolytic activity that is frequently

performed by the rodents either to escape, resolve or to normalize the anxiety condition

(Gispen and Isaacson, 1981; Moody et al., 1988; Kalueff and Tuohimaa, 2004).

Additionally, the movement of diabetic animals were more in the corners of the open

field test apparatus as they were avoiding the arena centre. In the studies following

anxiolytic drug administration it was observed that an anxious animal usually avoids the

arena centre as it assumed to be threatening for the rodents than its periphery (Treit and

Fundytus, 1988; Simon et al., 1994). The pathophysiological and/or cellular mechanisms

related to the above listed motor deficits and anxiety behaviour following diabetes is still

limited to the causative factors like poor glycemic control, insulin dependency and

oxidative stress (Egede, 2006; Liu et al., 2008; Ho et al., 2012; Gupta et al., 2014).

Persistent cell death in brain due to STZ-induced diabetes

It was previously reported that increased blood glucose level could lead to the elevation

in brain glucose level within 2-3 days of STZ induction (Mäkimattila et al., 2004; Criego

et al., 2005; Heikkilä et al., 2009) and that it persists for months was recorded by

Ruderman et al. (1974), Folbergrová et al. (1992), and Shram et al. (1997). Such altered

brain glucose level causes increased glycogenolysis, impaired glucose transport across

the membranes, reduced glycogenesis and excessive cell death. This has also been well

128

documented in case of hypoglycemia that altered glucose homeostasis triggers the

neuronal death in CNS (Singh et al., 2004).

In our study we found a significant cellular degeneration and/ or cell loss in both

hippocampus and cerebellum of STZ-induced diabetic animals with

immunohistochemical and histological studies consistently upto the 12th

week of diabetic

duration. Histological study revealed marked cell destruction both in hippocampus and

cerebellum following diabetes. Cardinal signs of cell degeneration like, necrosis/

apoptosis, vacuolation, chromatolysis, nonalignment of cells, neuronophagia and gliosis

were clearly visible in all the subfields of hippocampus and cerebellar layers. The

incidence of continual cell degeneration and/or loss is in accordance with the increased

level of oxidative stress (level of LPO) in hippocampus upto the 12th

week PDC.

Reactive oxygen and nitrogen species get reacted with polyunsaturated fatty acids present

in cell membranes and initiate the cascade of events leading to lipid peroxidation (LPO).

LPO via generation of reactive aldehydes either directly or indirectly cause damage to the

cell component. These cellular alterations cause oxidation of low density lipoprotein

(LDL) particles, fluctuations in permeability, alterations in ion flux and other toxic

constituents, damage to the cell matrix with consequent DNA injury, which ultimately

ensue the irreversible injury and finally cell death (Lima and Abdalla, 2001).

Additionally, higher oxygen consumption and abundant lipid content makes the brain

extremely vulnerable to the oxidative stress. A common notion regarding the

pathogenesis of brain dysfunction in diabetes, relates the cerebral cell damage to the free

radicals mediated oxidative stress (Kumar and Menon, 1993; Giacco and Brownlee,

2010; Muriach et al., 2014). Thus, oxidative stress reported in the present study is might

be a possible cause of cell death in hippocampus and cerebellum during diabetic state.

An increased and conspicuous active caspase-3 activity was evident in

hippocampal fields and cerebellar cell layers of the diabetic rats. The caspase-3 positivity

129

was significantly higher in degenerating neuronal cells and their processes. Active

caspase-3 expressing cells were more in stratum pyramidal and radiatum layers of CA

regions of hippocampus, while in the DG the cell death was more prominent in granule

cell layer suggestive of impaired information circuitry in hippocampus following

diabetes. Likewise, active caspase-3 positive cells were also successively increasing in all

the three layers of the cerebellum. Furthermore, the population of apoptotic (active

caspase-3 positive) cells were also successively rising in the subsequent weeks post

diabetes confirmation in both the brain tissues (hippocampus and cerebellum). Caspases

play an essential role in neuronal apoptosis (Bredesen, 2000; Yakovlev and Faden, 2001),

and caspase-3 has been accepted as a major executioner of the cell death mechanism.

Any brain injury or disorder activates the caspase-3 and its profuse expression validates

the severity of the brain disorder (Yuan and Yankner, 2000). The deleterious effect of

diabetes and hyperglycemia as cell death was previously well reported with underlying

mechanisms of activation of p53 transcription factor, intrinsic cell death pathway and

decreased IGF-I level due to increased blood glucose (Yamaguchi et al., 2001; Muranyi

et al., 2003; Lechuga-Sancho et al., 2006). Muranyi et al. (2003) showed that in transient

focal ischemia, diabetes activates the cell death pathway which might be due to caspase-3

activation via binding of initiator caspase-9 with Apaf-1 and mitochondrial matrix

component cytochrome c to form an apoptosome which further trigger the activation of

the downstream caspase cascade resulting in the cell death. Additionally, studies

suggested that p53 transcription factor is involved in the activation of caspase-3, 9 and 6

(Culmsee and Mattson, 2005) and also takes part in some forms of cerebellar cell death

(Inamura et al., 2000). In the present study an increase in caspase-3 expression and

number of caspase-3 positive cells in hippocampus following diabetes further confirms

the excessive cell death as a possible consequence of high blood glucose level noted post

diabetes confirmation. Similarly increased blood-glucose level as observed in this study

130

is expected to reduce the IGF-I (Insulin like growth factor) level in cerebellar granule

neurons (Linseman et al., 2002). Constitutively, the reduced IGF-I level due to high

blood-glucose level or activation of p53 transcription factors or intrinsic cell death

pathway might be the potential cause behind the sequential apoptotic cell death following

diabetes as reported in this study.

Long term glial (astroglia and microglia) activation and proliferation in brain

account for the severity of experimentally-induced diabetes

STZ-induced diabetes instigated a severe astroglial and microglial activation in both

hippocampus and cerebellum. During any brain insult microglial and astroglial cells get

activated through a paracrine signalling mechanism. Ample of studies have shown that

activated microglia and astroglia release various inflammatory molecules and secretory

proteins that not only instigate and promote the activation of each other but also take part

in the modulation of their activation via gliotransmission, generation of immune

molecules and cell-derived soluble factors, etc. (Davalos et al., 2005; Shih et al., 2006;

Liu et al., 2011; Pascual et al., 2012; Shinozaki et al., 2014). Our data directed a similar

inclination of glial activation in both hippocampus and cerebellum following STZ-

induced diabetes that continued upto the 12th

week PDC.

Persistent astroglial activation and proliferation grounds the deleterious effect of

diabetes in brain

Diverse features of glial activation like phenotypic switching, proliferation and

expression of activation cell surface markers to measure the extent of activation of

astroglia and microglia have been well reported in various models of injury (Pěkný and

Nilson, 2005; Patro et al., 2005, 2010b), inflammation (Patro et al., 2010a; Cerbai et al.,

2012) and disease (Heneka et al., 2010; Verkhratsky et al., 2012; Peng et al., 2014) in

both central and peripheral nervous system. Here, in response to STZ-induced elevated

131

blood glucose level and subsequent cell death, significant morphological heterogeneity

was observed in both type of glial cells i.e., astroglia and microglia in the hippocampus

and cerebellum.

Increased level of the astrocyte intermediate filament cytoskeletal protein i.e.,

GFAP with phenotypic transformation is a considerable marker of astroglial activation

caused by CNS injury, aging and neurodegeneration (Pěkný and Nilsson, 2005;

Sofroniew and Vinters, 2010; Burda and Sofroniew, 2014). However, astroglial response

during diabetic state varies according to the severity and duration of the diabetes (Saravia

et al., 2002; Lechuga-Sancho et al., 2006). Previous studies have revealed the selective

decrease in astrocyte GFAP levels in the cerebral cortex, cerebellum, hippocampus

(Coleman et al., 2004; Guven et al., 2009) and in spinal cord (Renno et al., 2008) with

least neurodegeneration at 4-8th

weeks of diabetic duration. Differing to the prior reports

of decrease GFAP level (Coleman et al., 2004; Hernὰndez-Fonseca et al., 2009; Guven et

al., 2009), we noted a progressive hyperactivation of astroglial cells upto the 12th

weeks

of diabetes in both hippocampus and cerebellum with profound cell death has been

recorded. The increased level of GFAP recorded is consistent with the findings of

Saravia et al. (2002) and Baydas et al. (2003b). Morphology of classically activated

astroglia with bushy, crumpled, extensively overlapping, deeply stained bold projections

and large cell nuclei, transformed from the resting astrocytes were present in all the

hippocampal subfields and cerebellar layers. Several mechanisms have been proposed to

explain the astroglial response in STZ-induced diabetes such as oxidative stress, protein

glycation, increases in the polyol pathway and altered calcium homeostasis (Brownlee,

2001). Excessive free radical generation following diabetes have been clearly

documented with the altered levels of the GFAP (Baydas et al., 2003b). In our study,

stature of oxidative stress in hippocampus upto the 12th

week of diabetes is comparable

with the altered astroglial response indicative of astroglial reactivity caused by diabetes-

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induced oxidative stress. Additionally, many astrocytes were also presenting fragmented

processes from 4th

week of diabetes onwards. Astrocyte confer a protective role in blood

brain barrier by encapsulating the brain capillaries with their long cytoplasmic processes.

They also play an imperative role in antioxidant defence producing antioxidant

molecules. Thus, fragmentation of the astrocytic processes could possibly compromise

functioning of the blood brain barrier (Huber et al., 2006) and oxidative stress

(Mastrocola et al., 2005) in brain following diabetes. As suggested that astroglia play an

imperative role in controlling the glucose supply and its metabolites to neurons, thus any

alterations in brain glucose level could foremostly affects the astroglia. Therefore, this

activation might be a customized approach to modulate the effect of excessive cell death

following diabetes as in response to adverse state glial cells transform their morphology

and proliferate to combat the baleful condition (Patro et al., 2005; Verkhratsky et al.,

2012) as documented in this study.

S100β is a reliable predictor of astrocytosis (Woods et al., 2010) and clinical

marker of brain damage (Netto et al., 2006; Patro et al., 2009). Thus, S100β

immunolabelling was performed to further verify the astroglia activation. Affirmatively,

S100β is involved in various intracellular and extracellular regulatory activities including

protein phosphorylation, transcription, Ca(2+) homeostasis, stimulation of neurite

outgrowth and astrocyte proliferation etc. (Zimmer et al., 1995, 2003; Sorci et al., 2013),

but the overexpression of this protein in brain is considered as a biomarker of astrocytic

damage in disorders like AD and Down‟s syndrome (Griffin et al., 1989; Zimmer et al.,

1995; Mrak and Griffin, 2001). As calcium binding protein, S100β responds to the cell

signalling induced calcium stimulus. Thus, in activated astroglia it might be possible that

the enormously increased calcium influx induces the overexpression or secretion of

S100β protein via astrocytes as evidently shown in previous studies of neurodegenerative

disorders (Steiner et al., 2011). Likewise in the present study, we have also observed the

133

pronounced expression of S100β cells in all the hippocampal fields following diabetes.

These S100β+ cells were showing stellate morphology having large cell body and thick

processes similar to the activated astrocyte. The augmented synthesis and overexpression

of S100β protein from activated astrocytes has been involved in the excessive growth of

dystrophic neurites in neuritic plaques contributing in the progression of AD (Sheng et

al., 1994; Mrak RE, Griffin, 2001). Thus, the incidence of astrocyte activation and

overexpression of S100β in diabetic hippocampus possibly explains the vulnerability of

diabetic brain more towards the pathogenesis of AD. Additionally, the elevated

concentration of S100β in serum or CSF has deleterious consequences like activating the

innate immune response in brain consequently causing inflammation (Koppal et al.,

2001; Sorci et al., 2011) and cell death (Hu et al., 1997; Rothermundt et al., 2003; Steiner

et al., 2011). Therefore, in conclusion the STZ-induced diabetes in hippocampus causes

astrogliosis alongwith fragmented processes, ensuing the release of S100β, which

possibly in turn, influence or exaggerate the process of cell death and inflammation.

Heteromorphic microglial activation and proliferation for the longer duration

intensifies the damaging magnitudes of diabetes in brain

Concomitant to the astroglial activation, the intense microglial expression was also

observed following diabetes in all the hippocampal fields (CA1, CA2, CA3, and DG) and

cerebellar cell layers upto the 12th

week PDC. Previously, microglial expression and

proliferation was also detected in diabetic retinopathy (Zeng et al., 2000), acute cerebral

infarction in presence of diabetes mellitus (Li et al., 2011) and in diabetic hyperalgesic

rat spinal cord (Daulhac et al., 2006). Similarly, our data showed an evident activation

directed morphological transformation in microglial cells i.e., from resting to reactive

phenotype consistently in all the hippocampal fields and cerebellar cell layers following

diabetes. During 2nd

and 4th

week of diabetes the microglial cells are in their intermediate

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activated state and from 6th

week onwards the presence of highly activated hypertrophied

microglial cells were clearly observed in both Iba-1 and OX-42 immunolabelling.

Quantitative data of both hippocampus and cerebellum also showed the marked

proliferation of microglial cell population following diabetes.

Microglia as affiliate of brain defence system, on any immune breaching or insult

become activated as well reported in our previous studies following peripheral nerve

injury (Saxena et al., 2007; Patro et al., 2010b) and in hippocampus (Patro et al., 2010a;

Patro et al., 2013; Nagayach et al., 2014). Through various pattern –recognition receptors

[like Toll-like receptors (TLRs), NOD-like receptors (NLRs), receptors of cell wall

components or DNA/RNA of pathogens), purinergic receptors, advanced glycation

endproducts (RAGE) receptors], scavenger receptors, microglia receive signals from

injured and dying cells and vascular damage (Block et al., 2007; Brown and Neher,

2010). Connexions of these receptors initiate a microglial activation cascade with the

expression of various proteins, comprising CD-45, COX-II, iNOS, MHC-II and various

co-stimulatory molecules etc. These molecules facilitate the microglial expression of

antigens to T cells, entered through the damaged BBB during neuroinflammation

(Gehrmann et al., 1995; Aloisi, 2001; Carson, 2005; Gertig and Hanisch, 2014). On

activation these immune cells get rapidly shifted into the reactive phenotype and slack

their highly ramified morphology not only to protect but also to repair the damaged tissue

via removing the dying cell debris and facilitating the healing process (Hanisch and

Kettenmann, 2007; Kettenmann et al., 2011). On the contrary, microglial activation is

also responsible in aggravating the neurodegeneration (Block and Hong, 2005; Venero et

al., 2011). Thus, microglia activation following diabetes in the hippocampus and

cerebellum as shown in this study might be in response of cell death, oxidative stress and

astroglial activation for providing the potential damage control or possibly microglial

135

activation was itself inducing the cell death and astroglial activation via generating

various immune mediators.

Additionally, the expression and sequential population rise of antigen surface

marker OX-6 (MHC-II) positive cells in hippocampal fields following diabetes further

reflect the persistent activation of microglial cells and its macrophagic state. MHC-II

(OX-6) labelling was undertaken to determine the extent at which diabetic condition can

increase the antigen presentation in brain. Under normal healthy conditions the

expression of these antigens on microglia is either low or absent (Sedgwick et al., 1993;

Bulloch et al., 2008) but can be dramatically augmented in adverse brain conditions.

Activated microglia in detrimental phase induces MHC-II expression (O‟Keefe et al.,

1999; Pabon et al., 2011). Furthermore the expression of ED-2 also accounts for the

incidence of alternate activation of macrophages and prolific perivascular microglial

activation (Balabanov et al., 1996) in diabetic hippocampus upto the 12th

week PDC. ED-

2 as a well-recognized marker not only used to define the macrophages and but also play

a major role in stimulating the generation of inflammatory molecules like TNFα, IL-1β

and IL-6 (Polfliet et al., 2006; Kowal et al., 2011). A recent study on AD has also shown

that the ED-2 positive cells were present in higher density around the compromised blood

vessels (Pey et al., 2014) might be indicating the BBB breakdown. This information

supports the functional aspect of ED-2 expression in the resolution phase of

inflammation (Zwadlo et al., 1987; Polfliet et al., 2006) due infiltration of inflammatory

molecules following BBB damage (Perry, 2004). Conclusively, it might also be possible

that intense expression was aggravated by activated microglia to further facilitate its role

in initiating the cascade of events of immune system. Similarly, presence of ED-2

positive cells was also supporting the phagocytic role of activated microglia and

associated inflammation following diabetes in hippocampus.

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Neuroinflammation as potent immune response resulted from the cell death,

oxidative stress and glial activation following STZ-induced diabetes

Neuroinflammation is an essential biological progression that stands as the foreground of

various acute and chronic neuropathological conditions. Any alteration in brain‟s cellular

and functional integrity grounds the incidence of neuroinflammation. Neuroinflammation

as a defending responder aims to refurbish the tissue homeostasis via inducing several

repair processes (Goldszmid and Trinchieri, 2012). However, if the regulation of this

mechanism remains uncontrolled then the initial inflammatory response amplifies

exceedingly and the protective mode shifts towards the collateral destruction that would

further result in severe disease progression.

The state of neuroinflammation is well reported in various studies on diabetes

(Mohamed et al., 1999; Patel and Santani, 2009; Srodulski et al., 2014) and other

neurodegenerative disorders (Pacher et al., 2007; Frank-Cannon et al., 2009; Najjar et al.,

2013). Analogous to these studies we have also observed the state the neuroinflammation

in diabetic hippocampus via profound immunoexpression of pro-inflammatory cytokines

(IL-1β and TNF-α) upto the 12th

week PDC. Secretion of pro-inflammatory cytokines

following glial (astroglia and microglia) activation is the classic theory of

neuroinflammation recognized and reviewed widely (Carson et al., 2006; Luo and Chen,

2012; Boche et al., 2013). Likewise, in this study consistent astroglial and microglial

activation in hippocampus might be considered as the possible perpetuator of the

neuroinflammation. Glial activation is generally accompanied by the proliferation of

cells, mobilization towards the damaged or dying cell, and the expression and secretion

of pro-inflammatory cytokines, like IL-6, TNFα and IL-1β. Later on, these cytokines

stimulate other astroglia and microglia leading to the exacerbation of glial (microglia and

astroglia) activation. Furthermost alterations in cytokines expression are a result of

stimulation of the transcription factor NF-κB (nuclear factor kappa enhancer of B cells)

137

via phosphorylation-induced activation of IκB kinase (Brown and Neher, 2010).

Additionally the oxidative stress and cell death are also contributing in the generation and

propagation of pro-inflammatory cytokines as documented in earlier studies of diabetic

neuropathy (Shi et al., 2013; Sandireddy et al., 2014; Muriach et al., 2014). Oxidative

stress activate the NF-κB and speciality protein-1 (SP-1) that further results in

neuroinflammation and vascular deficits (Cameron and Cotter, 2008; Sandireddy et al.,

2014). Similar pattern of immune response regarding inflammation, cell death and

oxidative stress was also observed in this study. The incidence of neuroinflammation in

hippocampus following STZ-induced diabetes was started from the 2nd

week PDC

parallel to the cell death and oxidative stress and sustained upto the 12th

week PDC

depicting a direct involvement of oxidative stress related cell death or vice versa.

Intriguingly, reciprocal relationship between neuroinflammation, cell death and glial

activation is popularly considered as a prerequisite for the onset and pathogenesis of

various psychiatric disorders like AD, PD, dementia and bipolar disorder etc. (Hojo et al.,

2004; Enciu and Popescu, 2013; Najjar et al., 2013; Watkins et al., 2014). Accordingly,

the stature of glial activation, cell death and neuroinflammation for a longer duration as

reported in this study also provides a cue on the vulnerability of diabetic brain more

towards the pathogenesis of severe psychiatric disorders.

Cytokine signalling is actively involved in the regulation of various brain

functions like synaptic signalling modulation, neurotransmission, neuroendocrine

functions and neural circuitry of behaviour and cognition (Camacho-Arroyo et al., 2009;

del Rey et al., 2013; Aprile-Garcia et al., 2013; Cuartas and Jorge, 2014). Therefore, it is

relatively apparent to presume an altered behavioural and cognitive outcome as a

consequence of a dysregulation in cytokine signalling which might be resulted in

depression, anxiety, behavioural deficits and cognitive dysfunction as observed in this

study as well. Reportedly, IL-1β and TNF-α is involved in the processing of learning and

138

memory (Lynch et al., 2002; Bains and Oliet, 2007; Baune et al., 2008; McAfoose and

Baune, 2009) and any alterations in the level of these cytokines in hippocampus lead to

AD, dementia and cognitive impairment as observed in various cross-sectional and

prospective population studies (Dik et al., 2005; Magaki et al., 2007; Holmes et al., 2009;

Brosseron et al., 2014). In concurrence with this we have observed alterations in the

spatial cognition, working memory, motor coordination, muscle strength locomotor

activity and emotionality (anxiety-like behaviour) in the animals following STZ-induced

diabetes that initiated from the 2nd

week PDC and remain affected upto the 12th

week of

diabetes. These deficits might be the consequences of increased level of pro-

inflammatory cytokines in hippocampus following diabetes. The present data revealing

longer term cognitive impairment parallel to the inflammation and glial activation

concrete the possibility of the advance susceptibility of diabetic patients to develop other

psychiatric illness than the non-diabetic population.

Counteraction between oxidative stress, cell death, glial activation and

neuroinflammation embark cognitive and behavioural decline following diabetes

The role of hippocampus was well elucidated in both cognition and mood

regulation. Several studies have proposed the involvement of hippocampus in spatial

learning, memory functions, anxiety and defensive behaviours (Ferbinteanu and

McDonald, 2001; Pentkowski et al., 2006; Czerniawski et al., 2009; Fanselow and Dong,

2010). Additionally, cerebellum is also involved in the control and execution of several

aspects of cognition, emotional behaviour and motor functions, comprising coordination

(Horne and Butler, 1995), muscle tone (Manto, 2010) and locomotion (Morton and

Bastian, 2004) which is possibly controlled and maintained by the neuron-glia shuttle.

Thus, alterations in hippocampal and cerebellar cells are possibly affecting the

homeostasis of the neuronal circuitry that further impairs the brain ability to acclimatize

139

and restructure the crucial behavioural and cognitive functions. Previous reports

suggested that in brain a proficient level of glucose is required to perform the

hippocampal-dependent cognitive tasks (McNay et al., 2000). Thus, any alteration in

blood glucose level necessarily affects the hippocampal function as well documented in

previous cognitive and behavioural studies.

This provides us an outline to consider the reciprocal relationship between various

hippocampal and cerebellar cells and associated mechanisms. Our data presenting

various glial and neuropathological changes resulting in alterations of hippocampal and

cerebellar function account for their contribution in the brain symptoms of diabetes-

linked impediments by deteriorating the regulation of hypothalamic-pituitary-axis,

maintenance of learning and memory, motor coordination and control of emotional

expression.

Conclusively, present data depicted the scenario of glial activation, cellular

degeneration and associated immune response in consort with subsequent behavioural

and cognitive alterations during experimentally induced diabetes in rats. The gliosis and

allied neuroinflammation in hippocampal region following diabetes unremittingly

induces the alteration in motor coordination, anxiety and reduce cognitive ability in

animals that sustained for a longer duration. Consideration of the associative reciprocity

between metabolic stress, cell death and gliosis in hippocampus will not only provide an

effective window to understand the underlying cellular mechanism following diabetes in

brain but also help us in developing the ideal targets for therapeutic interventions.

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SUMMARY & CONCLUSIONS

Diabetes mellitus is a heterogeneous endocrine disorder resulting from defects in insulin

secretion or action or both and characterized by the hyperglycemia linked to absolute and

relative insulin deficiency. In addition to others, diabetes mellitus increases the risk of

various cerebral disorders resulting in many structural and functional impediments

related to central and peripheral nervous system (Biessels, 1994; Baydas et al., 2005;

Guven et al., 2009). These complications are listed as impairment of cognitive functions,

dementia in older peoples, alterations in learning and memory (Gispen and Biessels,

2000; Popovic et al., 2001; Allen et al., 2004; Arvanitakis et al., 2006) and mood

disorders (Herzer and Hood, 2010; Egede and Ellis, 2010) etc. Diabetes leads to

neurochemical and structural abnormalities as well as degenerative changes in brain that

could be related to hyperglycemia-induced oxidative stress (Baydas et al., 2003a;

McCall, 2004; Mastrocola et al., 2005), poor glycemic control and insulin dependency

(Liu et al., 2008; Gupta et al., 2014). Hyperglycemia supplies additional substrate for

anaerobic glycosis in the brain, which further results in lactic acidosis and enhanced

damage to both glial and neuronal cells (Biessels et al., 1994). Concomitantly

hyperglycemia augment the formation of oxygen free radicals following lipid

peroxidation in the brain tissues which actively assault macromolecules within neuron

and glial cells that later causes structural and functional changes in proteins and

subsequent cell death (Hawkins and Davis, 2001; Hernández-Fonseca et al., 2009; Guven

et al., 2009) and astrocytic glial reaction (Barber et al., 2000; Kaneko et al., 2002).

Various studies revealed that oxidative stress following diabetes on brain cells,

causes a selective decrease in astrocyte GFAP levels in the cerebral cortex, cerebellum,

hippocampus (Coleman et al., 2004; Hernὰndez-Fonseca et al., 2009; Guven et al., 2009)

and spinal cord (Renno et al., 2008) with apparent neurodegeneration at 4-8 weeks of

141

diabetic duration. The diabetic allied decreased GFAP levels, without altering relative

astrocyte number, may be linked to insulin secretion, which essentially takes part in the

modification of phenotypic appearance of astrocytes and increases the expression of

GFAP mRNA and protein (Toran-Allerand et al., 1991). The impact of hyperglycemia on

glial cells (both astroglia and microglia) per se or their response to neuronal damage

remains to be studied in detail. Particular attention needs to be taken on neuro-

immunological aspects of neurodegeneration and neuroregulation under diabetic

conditions.

In the central nervous system, a heterogeneous group of cells known as glial cells

accompany the neuronal population. The major glial population in brain i.e., astroglia

and microglia shape the microarchitecture of the brain, provide support and protection,

control extracellular ion- metabolic- and neurotransmitter homeostasis, destroy and

remove the carcasses of dead neurons and help in signal transmission. Several studies

elucidate the affirmative functions of microglial and astroglial cells following stringent

pathological conditions, injuries and stress in brain. Microglial cells being resident and as

immunocompetent phagocytic cells perform functions similar to those of tissue

macrophages present in other organs and constituting the first line of defence against

invading pathogens (Streit, 2002; Vilhardt, 2005). In response to any detrimental

condition microglial cells become activated and release several cytokines (Hanisch,

2002), trophic factors (da Cunha et al., 1997; Nakajima and Kohsaka, 2004) and anti/pro-

inflammatory molecules (Nadeau and Rivest, 2000; Perry, 2004) and concurrently

phagocytose the debris of apoptotic cells (Reichert and Rotshenker, 2003; Makranz et al.,

2004; Djukic et al., 2006). This activity helps in facilitating the reorganization of

neuronal circuits and triggers the repair mechanism (Kim and Vallis, 2005; Hanisch and

Kettenmann, 2007; Neumann et al., 2009). Similarly, reactive astroglia not only release a

plethora of factors mediating the tissue inflammatory response but also recapitulate stem

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cell/progenitor features after damage and prove as a promising target for reparative

therapies following brain damage (Buffo et al., 2010). On the contrary, glial (astroglia

and microglia) activation is also responsible in aggravating the neurodegeneration via

releasing several inflammatory molecules (Venero et al., 2011; Verkhratsky et al.,

2014a). Depending upon the stimulus and progression of the diseased state glial cell

activation generally acts in two ways either help in efficacious restoration of injured

brain cells or generate a threatening environment that further results in subsequent brain

alterations. Recently, there have been many groundbreaking studies that are devoted to

the structure and functions of glial cells and establish their dual (beneficial/detrimental)

role in various brain disorders.

Studies on animal models have also depicted that diabetes induced GFAP

alteration has been linked to other central nervous system (CNS) disturbances like

distorted learning and memory processes and further increased risk of dementia and

cognitive dysfunction (McCall et al., 1996; Kamal et al., 2000). There are several reports

depicting that microglial activation in the optic nerve in diabetic retinopathy might be an

additional pathogenic factor in diabetic optic neuropathy (Zeng et al., 2008; Grigsby et

al., 2014). Likewise, literature also demonstrate the response of microglia in STZ-

induced diabetes by assessing the reduction in the number of Iba1 positive microglia in

the dorsal horn of the spinal cord following gabapentin treatment in diabetic neuropathy

(Wodarski et al., 2008; Daulhac et al., 2011). Furthermore with regard to the functional

importance of microglial cells in brain following any stress or degenerative changes, it

would be quite interesting to study the microglial activation following diabetes in the

brain regions, responsible for behaviour and cognition. On activation microglia secretes

plethora of cytokines and chemokines initiating neuroinflammation, which in turn

influence neuronal functions and even some of them also play critical role in learning,

memory (Goshen et al., 2007; McAfoose et al., 2009) and motor activity (Patro et al.,

143

2010a). Such microglial activation and related neuroinflammation have never been

studied in diabetic brain hippocampus, neither their expression nor the immune response

developed by these cells.

The functional ramification of glial activation (astroglia and microglia) following brain

damage and associated immune response embodies targets for therapeutic interventions. Glial

cell research being actively addressed today on various aspects of their involvement in neuronal

health and disease, their response to diabetic states has not been studied in large details.

Consequently, this study is expected to facilitate in getting information on the possible

influence of glial cells associated neuroinflammation and degeneration in the

hippocampus following diabetes in the CNS and the subsequent effects on behavioural

and cognitive abilities. The possible effect of oxidative stress following diabetes on

neuronal and glial cell death and the interconnected feedback loop between oxidative

stress, neuronal death, gliosis and neuroinflammation have never been studied in the

hippocampus. Therefore, a detailed study on glial activation and immune response either

neuroprotective/degenerative, produced by glial cells following diabetic exposure along

with subsequent behavioural and cognitive impairment with respect to gliosis needs to be

carried out in a more organized manner. Thus, present study will also help us in assessing

the effect of oxidative stress following diabetes on: glial activation vice-versa and the

possible immune response produced by microglial and astroglial cells along with their

effects on behaviour and cognition changes in a rat model. We analysed the hippocampus

tissue due to its role in several cognitive aspects linked to emotional, learning, memory

and sensorimotor functions (Bast, 2007). Additionally, we have also studied the

cerebellum following diabetes as cerebellum is associated with emotion, cognition and

behaviour (Rapoport et al., 2000; Schmahmann and Caplan, 2006) and any alterations to

the cerebellum lead to motor deficits, dementia, schizophrenia and other psychiatric

disorders (Baldaçara et al., 2008; Sui and Zhang, 2012).

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For developing diabetic animal model, a group of healthy male, adult rats having

normal blood glucose level (between 90-144 mg/dl) were kept on fasting overnight. Next

morning diabetes was induced by a single intraperitoneal (i.p.) injection of Streptozotocin

(STZ) at a dose of 45 mg/kg body weight, dissolved in 0.1M citrate buffer (pH=4). The

diabetic state was confirmed by measurement of non-fasting blood glucose level, 72 hrs

post STZ injection with the help of glucometer (Accu-Chek, Roche Diagnostics,

Germany). Blood drop sample was obtained from tail tip bleed. Animals having blood

glucose level above 250mg/dl were selected for diabetic study. Diabetic animals were

randomly divided into following groups i.e., 2nd

, 4th

, 6th

, 8th

, 10th

and 12th

week post

diabetes confirmation (PDC). Subsequently, animals‟ body weight, consumed food and

water were measured to confirm the diabetic symptoms like polyphagia, polydipsia and

weight loss.

Furthermore, all the experimental animals (diabetic and age-matched controls)

were subjected to the various behavioural and cognitive assessments at 2nd

, 4th

, 6th

, 8th

,

10th

and 12th

week post diabetes confirmation. A wide range of cognitive and behavioural

studies were performed to analyse the spatial cognition (Barnes maze), working memory

(T maze), anxiety-like behaviour (elevated plus maze), locomotor functions (open-field

test) , motor coordination (Rotarod) and muscular strength (grip strength meter).

Afterwards, all the experimental animals were sacrificed via transcardial

perfusion (using 2% Paraformaldehyde and 10% formaldehyde as fixative; Nagayach et

al., a,b) and the tissues like cerebral cortex (occipito-temporal), cerebellum, liver and

pancreas, kidney were dissected out carefully and weighed. The brain tissues for

immunohistochemical study were post-fixed in the same fixative (2% paraformaldehyde)

overnight at 4˚C and then cryoprotected in Phosphate buffered-Sucrose gradients i.e.

10%, 20% and 30% at 4˚C until tissues settled at the bottom. After processing the coronal

sections of cerebral cortex through occipito-temporal region and sagittal sections of

145

cerebellum were sequentially cut using cryostat (Microm HM 525, Thermo Scientific), at

a thickness of 14µm. The sections were collected serially on chromalum-gelatin coated

slides and stored at -20˚C till they were used for immunohistochemical studies. For

histological study a separate set of animals from each group were perfused and processed

for paraffin sectioning as per previously described method (Kumar et al., 2013;

Nagayach et al., 2014b). Briefly, after perfusion-fixation, tissues were thoroughly washed

with water and dehydrated with graded series of ethyl alcohol. Then, the tissues were

cleared in toluene and infiltrated in Paraplast (Sigma, m. p. 56–58°C) for proper

impregnation of wax. Tissue blocks were made in paraffin and serial coronal sections of

cerebellum were cut at a thickness of 6µm using Leica RM2135 microtome. To observe

the histological changes, tissue sections were stained with 0.1 % cresyl violet acetate

(Sigma certified stain, C-5042), prepared in acetate buffer (pH 3.5). For oxidative stress

assessment Lipid peroxidation (LPO) was assessed by measuring malondialdehyde

(MDA) levels based on the reaction of MDA with thiobarbituric acid using Buege and

Aust (1978) method.

STZ-induced animals exhibited the characteristic signs of diabetes as their blood

glucose level was consistently higher throughout the study as compared to their

respective controls and this plateau was maintained upto the 12th

week of diabetic

duration. Similarly, the food consumption and water intake were also significantly

increased in the diabetic animals presenting the symptoms of polyphagia and polydipsia.

Furthermore, the body weight and brain weight were found to be significantly reduced

during diabetic state. A cumulative resultant of reduced body and brain weight, the brain

weight/ body weight ratio of diabetic animals was also escalating at all the diabetic time

points as compared to their respective controls. The biochemical assessment of the level

of lipid peroxidation (LPO) in hippocampus, kidney and liver revealed a persistent state

146

of oxidative stress in all the respective tissues successively upto the 12th

week PDC as

compared to their respective controls.

Behaviour data indicated the reduced motor coordination and poor or weak

muscular strength of diabetic animals on rotarod and in grip strength meter respectively

indicating towards the impaired motor/muscle activity significantly comparable to their

age-matched controls. Similar altered locomotor activity was also observed in open field

test as diabetic animals were showing restless motion with increased distance travelled,

stereotypic time and ambulatory time and decreased resting time. Additionally, the

spatial cognitive ability of diabetic animals was also seem to be affected as in barnes

maze diabetic animals were taking more time to find the escape box with consequent

reduced path efficiency and average speed as compared to the controls. On T-maze task

also diabetic animals performed poorly while exploring the baited arm. The time duration

of diabetic animals on T maze was significantly increased and path efficiency was

reduced as compared to the controls showing altered effect of diabetes on spatial working

memory. STZ-induced diabetic animals were also showing the anxiety behaviour on

elevated plus maze as they had significantly increased anxiety index than the controls

upto the 12th

week PDC. The percentage of time spent and total number entries of

diabetic animals were less in open arms than in closed arms. The presence of anxiety

behaviour is in the support of the restless motion of diabetic animals in open field test.

Histopathological study revealed a persistent cellular damage in pancreas, kidney

and liver upto the 12th

week PDC. The irreversible severe destructions of insulin

producing pancreatic beta cells upto the 12th

week PDC validates the increased blood

glucose level following STZ-induction. Furthermore, renal and liver damage as observed

in the study not only confirms the incidence of polyuria, body weight loss and subsequent

polyphagia to reimburse the energy loss during diabetes.

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A significant cellular degeneration and/ or cell loss was observed in both

hippocampus and cerebellum of STZ-induced diabetic animals with

immunohistochemical and histological studies consistently upto the 12th

week of diabetic

duration. Histological study revealed marked cell destruction both in hippocampus and

cerebellum following diabetes. Cardinal signs of cell degeneration like, necrosis/

apoptosis, vacuolation, chromatolysis, nonalignment of cells, neuronophagia and gliosis

were clearly visible in all the subfields of hippocampus and cerebellar layers. The

incidence of continual cell degeneration and/or loss is in accordance with the increased

level of oxidative stress (level of LPO) in hippocampus upto the 12th

week PDC. The

active Caspase-3 immunolabelling results were clearly depicting the apoptotic neurons in

both hippocampal regions and cerebellar layers following diabetes in rat. The level of

active caspase-3 expression was consistent and increasing in all the hippocampal fields

i.e., CA1, CA2, CA3 and DG regions and cerebellar layers in terms of both quantification

and immunoexpression. This suggests a severe and long term cellular degeneration in the

hippocampal and cerebellar tissue following diabetes. Diabetes caused an alteration in

the morphology of GFAP-labelled astrocytes in CA1, CA2, CA3 and DG regions of

hippocampus and in cerebellum by the 2nd

week PDC onwards. Resting astrocytes in

controls presented thin, fine, intact processes with small cell body. While during diabetes

the GFAP immunolabelling was more intense and hypertrophied astrocytes with

activated phenotype, i.e., thick, dense, bushy and extensively overlapping, fragmented

processes with enlarged darkly stained cell body. Such cells were common all the

hippocampal subregions and purkinje cell layer of the cerebellum. Quantification also

revealed a pronounced proliferation of astroglial cells following diabetes in both

hippocampus and cerebellum as compared to their respective controls. Furthermore, the

S100β immunopositivity in hippocampus upto the 12th

week PDC also confirmed adverse

effect of increased blood glucose level as astrogliosis consistently for the long duration.

148

Similarly, the Iba-1+ microglial cells in diabetic hippocampus and cerebellum were also

presenting activated morphology as compared to their respective controls. The microglial

cells were showing phenotypic transformation, i.e., from ramified to activated states

bearing retracted, thick processes and large irregular cell body. In controls resting

microglia cells processes exhibited ramified wispy appearance with round lightly stained

cell body throughout the hippocampus subregions upto the 12th

week PDC. Cell

quantification and area fraction of Iba-1 immunopositive cells also revealed a gradual

increase in microglial population indicative of microglial proliferation in brain following

STZ-induced diabetes. Additionally, the expression and sequential population rise of

antigen surface marker OX-42 positive cells in hippocampal fields following diabetes

further reflects the persistent activation of microglial cells and its macrophagic state. The

significant escalation in expression of OX-6 (MHC-II) both in terms of cell population

and immunoexpression not only depicted the activation of microglial cells but also

manifested the state of inflammation following diabetes in hippocampus as MHC-II

signalling plays an imperative role in inflammation retorting to both endogenous and

exogenous antigenic proteins. The ED-2 immunolabelling revealed an increased

expression of macrophagic cell population in hippocampus following STZ-induced

diabetes. In controls, the immunoexpression of ED-2 positive cells was weak in terms of

both expression and quantification indicating the negligible incidence of phagocytic

activity and inflammation following microglial activation. While assessing the effect of

cell death and glial activation following STZ-induced diabetes we observed an increased

and pronounced expression of pro-inflammatory cytokines i.e., IL-1β and TNF-α in

hippocampus following diabetes. The IL-1β and TNF-α positive cells were equally

distributed in all the subfields of the diabetic hippocampus as compared to their

respective controls. Quantitatively, the population of pro-inflammatory cytokines i.e., IL-

1β and TNF-α immunolabelled cells was also significantly dense and increasing upto the

149

12th

week PDC directing towards the long term neuroinflammatory state in hippocampus

following diabetes. In conclusion the consistent stature of oxidative stress trailed

increased cell death in hippocampus following diabetes might be activating the astroglial

and microglial cells. Furthermore the long term persistent oxidative stress and cell death

as reported upto the 12th

week of diabetes possibly exaggerating the glial activation

angling phenotype and associated neuroinflammation that further instigate the significant

hippocampal and cerebellar atrophy followed by cognitive and behavioural impairments.

The study has elucidated the impact of diabetes on glial cells per se and/or their

rejoinder effects on neuronal cells with special reference on associated brain functions.

Evidences are also instigating an insight on possible role of diabetes allied oxidative

stress in perpetuation of glial activation, neuronal cell death and associated neuro-

immunological aspects of neurodegeneration and neuroregulation. Thus, this information

will provide an insight which not only help in understanding the aura of consequent

complications of diabetes but also in establishing a concrete strategic therapeutic

approach for developing the treatment of diabetes associated cognitive and behaviour

deficits.

In conclusion:

STZ-induced diabetes model was established with symptomatic signs of diabetes

including irreversible histopathological damage in liver, kidney, pancreas,

hippocampus and cerebellum.

An increased level of oxidative stress was noted in hippocampus following STZ-

induced diabetes.

Diabetes caused severe cell death in both hippocampus and cerebellum including a

decrease in brain weight.

150

STZ-induced diabetic animals showed reduced motor coordination, muscle strength,

spatial cognition, working memory, altered motor activity and anxiety behaviour.

Both in hippocampus and cerebellum diabetes resulted in persistent glial (astroglia and

microglia) activation. Glial activation was the consequent effect of profound cell death

and oxidative stress. It was also resulted from the paracrine signalling between both

astroglia and microglia.

STZ-induced diabetes caused astrogliosis alongwith fragmented processes, which

further stimulated the release and overexpression of S100β in hippocampus, which

possibly in turn, exaggerated the process of cell death and inflammation.

Activated microglia with macrophagic properties expressing antigen surface markers,

i.e., OX-6 (MHC-II) and OX-42 (CR-3) and a cascade of immune response molecules

(IL-1β and TNF-α) were prevalent in the hippocampus of diabetic rats.

IL-1β and TNF-α are well known for their austere impact on cognition and behaviour.

Thus, increased and prolonged expression of these cytokines following diabetes was

deleteriously affecting the cognitive and behavioural abilities of the animal as

observed.

Collectively, the sequential loss of neurons and activated glial reaction associated

neuroinflammation as reported in this study could be a contributing hinge to the

altered cognitive ability and behaviour following diabetes.

From therapeutic standpoint, efforts are required to better elucidate the

pathophysiological changes that underpin the progression and severity of brain disorders

following diabetes to develop the better treatments.

151

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APPENDIX I

Preparation of buffers, fixatives and stain

1. Citrate buffer (0.1M/pH=4)

Reagents (for 20ml of solution):

Sodium citrate ………………………………………. 0.5882gm

Citric acid…………………………..............................for maintaining the pH

Method:

Calculated amount of sodium citrate was added in 20ml of sterilised distilled

water on a magnetic stirrer. Finally, with the help of Citric acid, pH of the

solution was maintained upto 4.

2. Phosphate buffer saline (PBS; 0.01M/pH=7.2-7.4)

Reagents (For 1 litre solution):

Di sodium hydrogen phosphate (anhydrous)……… 1.149gm

Sodium phosphate Monobasic (anhydrous)………... 0.296gm

Sodium chloride……………………………………… 8.5gm

Method:

All the reagents were sequentially added in 800ml of distilled water on a

magnetic stirrer. Finally the solution was made upto 1litre with distilled water.

3. 2% Para formaldehyde (0.01M/pH=7.4)




Paraformaldehyde……………………………………………. 20gm

Method:

All the reagents were sequentially added in 800ml of warm distilled water on a

magnetic stirrer. Crystals of Sodium hydroxide was added in the solution, if the

solution was not clear. Finally the solution was made upto 1litre with distilled

water and filtered properly. Then, the solution was kept for cooling at 4˚C in a

tight cap bottle for further use. (Fresh solution was prepared every time for the

perfusion)

4. 10% Buffered formalin (0.01M/pH=7.4)




Formaldehyde…………………………………………100ml

Method:

192

Both the reagent salts were added in 900ml of distilled water on a magnetic stirrer

and then 100ml of formaldehyde solution added and mixed. The solution was

stored at room temperature.

5. Tris buffer saline (TBS; 0.05M/pH=7.4-7.6)


Sodium chloride………………………………………...……… 8.766gm

Tris base…………………………………………………………... 6.057gm

Method:

All the reagents were sequentially added in 800ml of distilled water on a

magnetic stirrer. Finally the solution was made upto 1litre with distilled water.

6. Tris-HCl (0.05M/pH=7.4-7.6)

Reagents (For 100ml solution):

Tris base…………………………………………………………... 0.6057gm

Method:

Tris base was added in 80ml of distilled water on a magnetic stirrer and finally

made upto 100ml with distilled water.

7. Cresyl violet stain

Reagents (for 100ml of working solution):

Cresyl violet…………………………………………….0.5 g

Distilled water…………………………………………100 ml

10% Glacial acetic acid…………………………………...0.8ml

Method:

a. Cresyl violet stock solution: 0.5 g cresyl violet was added in 100ml distilled water

and mixed well.

b. Working solution: For working solution 0.8 ml of 10% acetic acid was added to

100 ml of stock cresyl violet solution. Then it was filtered properly for use.

193

PUBLICATIONS & PRESENTATIONS

PUBLICATIONS:

Research article

Nagayach A, Patro N and Patro I (2014) Experimentally induced diabetes causes

glial activation, glutamate toxicity and cellular damage leading to changes in

motor function. Front. Cell. Neurosci. 8:355. doi:10.3389/fncel.2014.00355. (IP:

4.2; Citations: 1)

Aarti Nagayach, Nisha Patro, Ishan Patro (2014) Astrocytic and microglial

response in experimentally induced diabetic rat brain. Metab Brain Dis.

29(3):747-761 (IP: 2.398; Citations: 1)

Patro Nisha, Nagayach Aarti, Patro IK (2010) Iba1 expressing microglia in the

dorsal root ganglia become activated following peripheral nerve injury in rats.

Indian Journal of Experimental Biology. 48: 110-116. (IP: 1.195; Citations: 14)

Book Chapter

Ishan Patro, Kapil Saxena, Aarti Nagayach and Nisha Patro (2014) Involvement

of Glial Cells in Pathophysiology of Peripheral Nerve Injury. In Contemporary

Topics in Life Sciences, Ed., Prof. P.P. Mathur, Narendra Publishing House, New

Delhi, pp.153.

Review article

Aarti Nagayach, Nisha Patro, Ishan Patro (2015) Microglia in the physiology and

pathology of brain. Proceedings of the National Academy of Sciences, India

Section B: Biological Sciences (communicated).

Abstract

Ishan Patro, Aarti Nagayach, Nisha Patro (2011) “Role of glia in health and

disease” in proceedings of 98th

Indian Science Congress at SRM University,

Chennai, during 3rd

-7th

January, 2011. (Invited lecture).

194

PRESENTATIONS (ORAL & POSTER):

Poster entitled “Behavioural and glial alterations in STZ-induced diabetic rats” in

XXXI Annual conference of Indian Academy of Neurosciences and International

symposium on Emerging Trends and Challenges in Neuroscience at NASI,

Allahabad during 25th

-27th

October, 2013.

Poster entitled “Role of glial activation in cognitive and behavioral impairment in

diabetic rats” in XXX Annual conference of Indian Academy of Neurosciences

and International symposium on Translational Neuroscience: Unravelling

mysteries of brain in health and disease at Guru Nanak Dev University, Amritsar

during 27th

-30th

October, 2012.

Oral Presentation on “Microglia type cells exist in DRG and upregulate Iba1

when activated following sciatic nerve injury: A novel finding” in 26th

M.P.

Young Scientist Congress, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Jabalpur

during February 28 - March 01, 2011.

Poster entitled “Existence of Iba1 expressing cells in dorsal root ganglion”

presented in International Conference on Advances in Neuroscience and 26th

Annual Meeting of Indian Academy of Neuroscience at Cochin University,

Cochin (India) from 12th

-14th

Dec. 2008.

01 phd thesis.pdf

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