ijsrkthe prediction of disulphide bonding in hiv and other lenti-viruses by machine learning...

IJSRK International Journal of Scientif ic Research in Knowledge

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Feb 2014

Volume 2, Issue 2

Pages 57 – 115

Table of Contents

Article Author(s) page

The Prediction of Disulphide Bonding in HIV and other lenti-viruses by Machine Learning Techniques

Anubha Dubey 57

Bioinformatics Prediction of Interaction Silver Nanoparticles on the Disulfide Bonds of HIV-1 Gp120 Protein

Shahin Gavanji, Hassan Mohabatkar, Hojjat Baghshahi and Ali Zarrabi

67

A Comparative Evaluation of Drug Release and Permeability of Ethylcellulose, Cellulose Acetate and Eudragit RS100 Microspheres

Prakash Katakam, Saousen R. Diaf, Baishakhi Dey, Shanta K. Adiki, Babu R. Chandu and K.P.R. Chowdary

75

Investigation of a Proposed Four Storey Building Sites Using Geophysical and Laboratory Engineering Testing Methods in Lagos, Nigeria

Oyedele Kayode Festus, Adeoti, Lukman, Oladele Sunday and Kamil Akintunde

83

Nutritional and Anti-Nutritional Composition of Bridelia Ferruginea Benth (Euphorbiaceae) Stem Bark Sample

Adesina Adeolu Jonathan, Akomolafe Seun Funmilola

92

A Study on the Relationship between Accounting Conservatism and Earnings Management in Teheran Stock Exchange Listed Companies

Abbas Ramezanzadeh Zeidi, Zabihollah Taheri and Ommolbanin Gholami Farahabadi

105

International Journal of Scientific Research in Knowledge, 2(2), pp. 57-66, 2014

Available online at http://www.ijsrpub.com/ijsrk

ISSN: 2322-4541; ©2014 IJSRPUB

http://dx.doi.org/10.12983/ijsrk-2014-p0057-0066

57

Full Length Research Paper

The Prediction of Disulphide Bonding in HIV and other lenti-viruses by Machine

Learning Techniques

Anubha Dubey

Research Scholar, Department of Bioinformatics, MANIT BHOPAL (M.P), INDIA

Email: [email protected]

Received 01 November 2013; Accepted 28 December 2013

Abstract. The introduction of disulphide bonds into proteins is an important mechanism by which they have evolved and are

evolving. Most protein disulphide bonds are motifs that stabilize the tertiary and quaternary protein structure. These bonds also

thought to assist protein folding by decreasing the entropy of the unfolded form. Amino acid cysteine plays a fundamental role

in formation of disulphide bonds. In the present study, proteomics of disulphide bonding in HIV is studied through a machine

learning model which has been developed to classify disulphide bonds from different species of lentiviruses like bovine

immunodeficiency virus (BIV), simian immunodeficiency virus (SIV), Feline immunodeficiency virus, murine infectious virus

(MIV) and equine infectious anaemia virus (EIV) and Human immunodeficiency virus (HIV). Phylogenetic relationship is also

studied by the prediction of disulphide bonding among these viruses. Hence by different algorithms of WEKA classifier J48

predicts better classification with an accuracy of 89.6104%.

Keywords: Disulphide bond, motifs, lentiviruses, Phylogenetic, WEKA.

I. INTRODUCTION

Disulfide bonds play an important role in the folding

and stability of some proteins, usually proteins

secreted to the extracellular medium (Savier and

Kaiser, 2002).Since most cellular compartments are

reducing environments; in general, disulfide bonds are

unstable in the cytosol, with some exceptions as noted

below, unless a sulfhydryl oxidase is present (Hatahet

et al., 2010).

Fig. 1: Cysteine is composed of two cysteines linked by a

disulfide bond (shown here in its neutral form)

Disulfide bonds in proteins are formed between the

thiol groups of cysteine residues. The other sulphur-

containing amino acid, methionine cannot form

disulfide bonds. A disulfide bond is typically denoted

by hyphenating the abbreviations for cysteine, e.g.,

when referring to Ribonuclease A the "Cys26-Cys84

disulfide bond", or the "26-84 disulfide bond", or most

simply as "C26-C84" (Ruoppolo et al., 2000). The

structure of a disulfide bond can be described by its

dihedral angle between the

atoms, which is usually

close to ±90°.

The disulfide bond stabilizes the folded form of a

protein in several ways:

1) It holds two portions of the protein together,

biasing the protein towards the folded topology. That

is, the disulfide bond destabilizes the unfolded form of

the protein by lowering its entropy.

2) The disulfide bond may form the nucleus of a

hydrophobic core of the folded protein, i.e., local

hydrophobic residues may condense around the

disulfide bond and onto each other through

hydrophobic interactions.

3) Related to #1 and #2, the disulfide bond link

two segments of the protein chain, the disulfide bond

increases the effective local concentration of protein

residues and lowers the effective local concentration

of water molecules. Since water molecules attack

amide-amide hydrogen bonds and break up secondary

structure, a disulfide bond stabilizes secondary

structure in its vicinity (Thorton, 1981; Wetzel, 1987).

mailto:[email protected]

Dubey


58

For the protein folding prediction, a correct

prediction of disulfide bridges can greatly reduce the

search space (Skolnick et al., 1997; Huang, 1999).

The prediction of disulfide bonding pattern helps, to a

certain degree, predict the 3D structure of a protein

and hence its function because disulfide bonds impose

geometrical constraints on the protein backbones.

Some recent research works had shown the close

relation between the disulfide bonding patterns and

the protein structures (Chuang, 2003; Vlijmen, 2004).

By stabilizing protein structure, disulphide bond can

protect proteins from damage and their half-life. Once

the disulphide bond is formed they remain unchanged

for the life of the protein.

In the realm of the disulfide bond prediction, four

problems are addressed. The first is the protein chain

classification: to classify if the protein contains

disulfide bridge(s) or not, the second is the residue

classification: to predict the bonding state of

cysteines, the third is the bridge classification and the

last is the prediction of the disulfide bonding pattern.

Over the past years, significant progress has been

made on the prediction of the disulfide bonding states

(Fariselli, 1999; Fiser and Simon, 2000; Martelli,

2002; Chen, 2004)) and the disulfide bonding pattern

(Vullo, 2004; Ceroni, 2006; Song, 2007; Rubinstein,R

2008). For disulfide bonding pattern prediction, with

the exception of the methods proposed by (Ferre,

Clote 2005, 2006; Chen et al., 2006) others are also

used with or without bonding state known.

A method for predicting disulphide bonds from

genomic data which organisms are rich in disulfide

bonds has been described in (Mallick, 2002;

O'Connor, 2004). In the present study, a similar

strategy was utilized in which proteomic sequences

are used first to generate phylogenetic relation

between HIV and other species of lentivirus and then

disulphide bond prediction is done among the species

to see the disulphide richness across the species. HIV

(Human Immunodeficiency Virus) is a member of

genus lentivirus, part of the family retroviridae.

Lentiviruses have many common morphologies and

biological properties. Many species are infected by

lentiviruses, which are characteristically responsible

for long-duration illnesses with a long incubation

period lentiviruses are transmitted as single-stranded,

positive-sense, enveloped RNA viruses. Here in this

paper we have introduced a disulphide bonding

relationship of HIV with Other six species of

Lentivirus like bovine immunodeficiency virus (BIV),

simian immunodeficiency virus (SIV), Feline

immunodeficiency virus, murine infectious virus

(MIV) and equine infectious anaemia virus (EIV) and

two types of HIV- HIV1 & HIV2.

Table1: The comparative features of HIV with other related viruses

S.N

o.

Featur

es

FIV BIV MLV EIAV SIV HIV

1. Occur Cats Cattles Cancer in

mouse

Horse African

green

monkey

Human

2. Genom

e size

80-100 nm

and

pleomorphic,d

iploid

genome

Mature

virus,110-

130 nm

with 8.4 kb

90 nm in

diameter

- - 120 nm

3. Enzym

es

RTase,integras

e, protease

RTase,integ

rase,

protease

RTase,integ

rase,

protease

RTase,integ

rase,

protease

RTase,integ

rase,

protease

RTase,integrase,protease,ri

bonuclease

4. Structu

ral

genes

Gag,pol,env Gag,pol,env Gag,pol,env Gag,pol,env Gag,pol,env Gag,pol,env

5. Open

reading

frames

absent Regions

between pol

& env

absent absent present Present

6. Access

ory

genes

Vif,vpr,rev Nif,tat,rev absent Tat, vif - Vif,vpr,nef,vpu,vpx

(HIV2),tat,rev,tev(fusion of

tat,rev,and env)

7. Envelo

pe and

core

Env codes for

surface

glycoprotein

and

transmembran

e glycoprotein

Envelope

present and

core

contains

gag,gag-pol

polyprotein

Gag,gag-

pol poly

protein

Gag poly

protein

Gag,pol,

polyprotein

Gag-pol polyprotein

8. Conser

ved

RNA

absent absent Present

called core-

encapsidati

on signal

absent Present

called core

encapsidati

on signal

Present in SR proteins,

RNA interface etc.


59

One of the most important contributions of

biological sequences to evolutionary analysis is that

the sequences of different organisms are often related.

Hence role of disulphide bond is studied among

lentivirus species.

2. MATERIALS and METHODS

2.1. Data Preparation

The analysis has been done on the basis of protein

sequence data of BIV, FIV, EIAV, MLV, SIV, and

HIV which has been obtained from UNIPROT [30].

2.1.1 Phylogenetic methods

To study evolutionary relationship it is important to

do multiple sequence alignment (MSA). MSA is a

sequence alignment of three or more biological

sequences, generally protein, DNA, or RNA. In many

cases, the input set of query sequences are assumed to

have an evolutionary relationship by which they share

a lineage and are descended from a common ancestor.

Of the various software’s of MSA, CLUSTAL W2

(Chenna, 2003) is found to be suitable. In this

neighbour-joining method is used. Neighbour-joining

(NJ) is a bottom-up clustering method used for the

construction of phylogenetic trees. Usually used for

trees based on DNA or protein sequence data, the

algorithm requires knowledge of the distance between

each pair of taxa (e.g., species or sequences) in the

tree.

Phylogenetic methods play an important role in

evolutionary analysis and to obtain the evolutionary

relationship of HIV. The sequences taken as

S1,S2,S3,S4,S5,S6,S7,S8 represents

HIV1,HIV2,MLV,BIV, Lentivirus,Murine virus,

Feline immunodeficiency virus, Equine infectious

anaemia virus, Simian immunodeficiency virus.

Following figures are obtained by CLUSTAL-W2.

FFiigg.. 22:: ((aa)) NNeeiigghhbboouurr JJooiinniinngg UUnnrrooootteedd ttrreeee FFiigg.. 22:: ((bb)) NNeeiigghhbboouurr JJooiinniinngg RRooootteedd ttrreeee

Fig. 3: (a) Dendogram Unrooted tree Fig. 3: (b) Dendogram Rooted tree

Here the cladogram and NJ tree shows the HIV 1

& 2 is related with Simian Immunodeficiency Virus.

The alignment of a query sequence to a

homologous sequence infers a likely three-

dimensional mapping of the protein sequence in

question, yielding homology-based structural

predictions for many proteins. Considering all such

protein sequences from a given genome as a group,

Dubey


60

the tendency of each amino acid type to appear in

spatial proximity to every other type was then

analyzed, taking into account the overall abundances

of the 20 amino acid types. Enrichment in cysteine–

cysteine proximity above the expected value was

taken to indicate an enrichment of disulfide bonding.

Since cysteine–cysteine proximity can also indicate

metal-binding motifs, proteins were first filtered to

remove proteins with metal-binding sites that would

otherwise produce false-positive results.

2.1.2. Disulphide Bond Prediction

Of the various software’s available for disulphide

bond prediction, Disulphide Bonding Connectivity

Pattern (DBCP) server (Hsuan-Hung and Lin-Yu,

2010) is used as it predicts better disulphide bonding

positions with cysteines positions and also capable to

relate disulphide bonding with metal binding sites.

The working of server is as follows:

(1) Run Basic Local Alignment Search Tool

(BLAST) to get the template sequence of the input

sequence. The parameters of BLAST are set as

follows: the Expectation value (E) threshold for

saving hits is set to a very large value 10 000 and the

database is set to PDB that contains sequences derived

from the 3D structure records from the Protein Data

Bank. If the E-value of the template sequence is >10

or the template sequence shares identity <25% to the

input sequence, instead of going to Step 2, the method

previously developed by (20) to predict the disulfide

bonding pattern is used.

(2) Align the input sequence and the template

sequence.

(3) Feed the alignment file into MODELLER and

run the procedure to evaluate the model of the input

sequence using the template sequence.

(4) get the coordinate (X, Y, Z) of the Ca (a

Carbon) of each residue.

(5) Coding each cysteine pair as the NPD

(normalized pair distance), this will be the input to the

SVM (Hsuan-Hung and Lin-Yu, 2010).

(6) Feed the coding file into the Support Vector

Machine (SVM) to predict the bonding probability of

each cysteine pair with the trained model. The

multiple trajectory searches (Tseng and Chen, 2008)

are tightly integrated with the SVM training. For more

details, please refer to the Supplementary Data on the

DBCP web server.

(7) Coding the input file with the probabilities

from the SVM output and using the modified

weighted perfect matching algorithm to get the first

level disulfide bonding connectivity.

(8) Justify the first level disulfide bonding

connectivity with the thresholds to get the final result.

(9) Display the result on the web page or send the

result to the user. In Step 1, if the E-value of the

template sequence is >10 or the template sequence

shares identity <25% to the input sequence, a

previously proposed method (Lin, H.H., and Tseng,

L.Y. 2009) is used for prediction. In this method, the

position specific scoring matrix, the normalized bond

lengths, the predicted secondary structure of protein

and the physicochemical properties index of the amino

acid were used as features. The multiple trajectory

searches and the SVM training were tightly integrated

to train the predictor. More details can be obtained

from Lin and Tseng, 2009).

The DBCP server is free and open to all users.

2.1.2.1. Evaluation

After taking four websites of disulphide bond

connectivity pattern without prior knowledge of

bonding state of cysteine (Ferre et al., 2006; Song,

2007). We have tested our prediction by 10-fold cross

validation on the data set of FIV, BIV, MLV, EIAV,

SIV, HIV jointly named as VIRUS. And disulphide

bonds were observed with cysteine residues and some

of them are also shows metal binding sites. This was

again evaluated/ classified by J48 WEKA 3.7

algorithm. J48 is a decision tree classifier (Pfahringer

IHW, 1999).

The number of ways of forming p disulfide bonds

from n cysteine residues is given by the formula

2.1.2.2. Measurement of accuracy

A necessary step to the prediction of disulphide

connectivity is the prediction of the disulphide

bonding state of cysteines in proteins. In order to

evaluate the accuracy of the prediction two indexes

can be used: Qp and Qc.

For a protein PQp is defined as:

Qp= δ (Correct pattern, predicted pattern)

(1)

Where δ(x,y) is 1 if and only if the predicted

pattern coincides with the correct pattern.

Alternatively, Qc is defined as:

C

numberofcorrectlypredictedpairsQ

numberofpossiblepairs (2)


61

The two indexes are equally suited and

complimentary for measuring the accuracy of the

prediction: Qp is a measure of the predictive

performance on each protein (either 1 or 0) and can be

averaged over a number of predicted proteins to give a

global measure of the accuracy of the method. Qc

quantifies the accuracy of the method based on the

number of pairs correctly predicted with respect to the

total number of possible pairs.

In order to score the method its performance was

also compared with that of a random predictor. The

probability of a predictor randomly performing (Rp)

on the prediction of the connectivity pattern can be

computed. In general, given 2B cysteines, the number

of possible connectivity pattern is:

Np= (2B-1)

( )(2 1) (2 1)i B iNp B (3)

The corresponding probability of Rp is:

1( )Qp Rp

Np (4)

For the random predictor (Rp), Qc is

1( )

(2 1)c pQ R

B

(5)

Evaluation of predictive accuracy:

The prediction accuracy was calculated by following

the standard conventions accuracy for prediction:

2c

o

NQ

N (6)

Where Nc is the total number of correctly predicted

cysteines and No is the total number of cysteines.

Specificity of the prediction:

X

X X

TNSpecificity

TN FP

(7)

Where x denotes the bonded cysteines or non-

bonded cysteines XFP is the number of false

negatives in the prediction and XTP is the number of

true positive predictions for bonding state x.

Sensitivity of the prediction was calculated as:

X

X X

TPSensitivity

TP FN

(8)

Where XFN is the number of false negatives for

bonding state x. The Matthews correlation

coefficient:

MCC is calculated as:

Mathews Correlation coefficient( ) ( )

( )( )( )( )

TP TN FP FNMCC

TP FN TP FP TN FP TN FN

Where XTN the true negatives of bonding state are

X. The value of MCC is an indication of how good is

the prediction. The closer the MCC is to 1, the closer

the prediction is to a perfect prediction.

2.1.3. Prediction of oxidation state of cysteines

Knowledge of the oxidation state of cysteines infer a

lot of information about the protein such as local

sequence environment the possible 3D structure of

protein and in some cases, the function and working

mechanisms of the protein. In this paper position of

oxidized cysteines was observed by DBCP software

(Hsuan-Hung and Lin-Yu, 2010).

2.1.4. Prediction of connectivity pattern of

cysteines

Connectivity pattern prediction is a challenging and

yet very biological meaningful task. It is challenging

because there are too many possibilities of disulphide

bonding for a given protein and many factor influence

the final connection pattern. The correct predictions of

disulphide bond provide in order to have a stabilized

three dimensional protein structure. Research is going

on for prediction of connectivity pattern of cysteines

(Hsuan-Hung and Lin-Yu, 2010)

2.1.5. Prediction of number of disulphide bridges

Analysis of prediction results shows that there is a

relationship between the sum S(p) of all the

probabilities of cysteines and the total number of

bonded cysteines (as predicted by DBCP serwer). The

Dubey


62

total number of bonded cysteines using linear

regression approach shows that the total number of

bonded cysteines is even and does not exceed the total

number of cysteines in sequence. When the number of

disulphide bridges increases in chains, the

performance decreases in general. The overall

specificity and sensitivity using four different input

schemes are around 51% to 55%. The variations of the

performance for chains with many disulphide bridges

(K>6) is large because there is few in the dataset.

Thus for proteins with a large number of disulphide

bridge (K>6), prediction must be used as caution. It is

very difficult to correctly predict the entire disulphide

connectivity pattern because the number of

connectivity pattern increases exponentially with K.

2.2. J48 algorithm

The disulphide bond prediction will be classified by

machine learning algorithm. J48 proves better for

small biological data. J48 is a decision tree

classifier.J48 is a Machine learning algorithm, a

branch of artificial intelligence, is a scientific

discipline concerned with the design and development

of algorithms that allow computers to evolve

behaviours based on empirical data, such as from

sensor data or databases. A learner can take advantage

of examples (data) to capture characteristics of interest

of their unknown underlying probability distribution.

Data can be seen as examples that illustrate relations

between observed variables. A major focus of

machine learning research is to automatically learn to

recognize complex patterns and make intelligent

decisions based on data; the difficulty lies in the fact

that the set of all possible behaviours given all

possible inputs is too large to be covered by the set of

observed examples (training data).

3. RESULTS AND DISCUSSIONS

Phylogenetic methods play an important role in

evolutionary analysis and to obtain the evolutionary

relationship of HIV with other species of lentivirus i.e.

MLV, BIV, Lentivirus, Murine virus, Feline

immunodeficiency virus, Equine infectious anaemia

virus, Simian immunodeficiency virus. CLUSTAL-

W2 result shows the cladogram and NJ tree of the

species which presents that HIV 1 & 2 is related with

Simian Immunodeficiency Virus. Disulphide bond is

predicted for these sequences to find out the similarity

among lentivirus species and then disulphide bond

based classification is studied by J48 a machine

learning technique.

3.1. Analysis of DBCP server

A web-based application system called the DBCP is

provided for the prediction of the disulfide bonding

connectivity pattern without the prior knowledge of

the bonding state of cysteines. To the best of our

knowledge, the best accuracy of disulfide connectivity

pattern prediction (Qp) and that of disulfide bridge

prediction (Qc) are found 81% and 82%, respectively,

on the data set of HIV and other related to HIV

molecular sequences with 10-fold cross validation.

Env gene plays a significant role in disulphide bond

prediction. Env, gag in FIV, env- pol in MLV, pol in

EIA, Env in SIV & HIV correctly predicts disulphide

bonds. Table 2 shows the species with position of

disulphide bond and this proves that disulphide bond

is conserved among species.

Table 2: Species with position of disulphide bonds

Species gene Position of disulphide bonds

FIV Env & gag 328-348

EIA POL 322-342

MLV ENV & POL 81-95,112-129,121-134,165-184: 536-538,561-576,

SIV ENV 99-207,106-198,180-193,230-242,300-333,382-457,389-

430,412-422

HIV ENV 118-200,125-191,213-242,223-234,291-328,374-435,381-

408

Stabilization of the native Env complex by disulfide

bond linkage is likely to impose constraints on Env

function because a certain degree of flexibility is

probably essential for Env to undergo the

conformational changes that eventually lead to fusion

of the viral and cellular membranes. The gp120 –

gp41 interface is considered to be structurally flexible,

so constraining its motion might have adverse effects.

3.2. J48 based classification

Again disulphide bond based classification of HIV

and other related viruses is done by machine learning

J48 algorithm which gives the accuracy of 89.6104%.

After 10 fold cross validation of training data (Virus)

the result obtained is shown as follows:

In the field of machine learning, a confusion

matrix is a specific table layout that allows

visualization of the performance of an algorithm,


63

typically a supervised learning one (in unsupervised

learning it is usually called a matching matrix). Each

column of the matrix represents the instances in a

predicted class, while each row represents the

instances in an actual class.

Table 3: Statistics of J48 algorithm

Correctly Classified Instances 69 89.6104 %

Incorrectly Classified Instances 8 10.3896 %

Kappa statistic 0.8359

Mean absolute error 0.0528

Root mean squared error 0.1845

Relative absolute error 56.0893 %

Root relative squared error 56.0893 %

Total Number of Instances 77

Table 4: Detailed accuracy by class

TP

RATE

FPRATE PRECISION RECALL F-MEASURE ROC CLASS

0 0 0 0 0 0.474 EIA

0 0 0 0 0 0.48 BIV

0.833 0.042 0.625 0.833 0.714 0.893 FIV

1 0.032 0.875 1 0.933 0.99 MLV

0.714 0 1 0.714 0.833 0.814 SIV

0.976 0.083 0.93 0.976 0.952 0.918 HIV

0.896 0.053 0.885 0.896 0.884 0.899 Weighted

average

Table 5: Confusion Matrix between predicted and actual class Predicted class (column)

a b c d e f Classified as

0 0 1 0 0 0 a=EIA

0 0 1 0 0 0 b=BIV

0 0 5 1 0 0 c=FIV

0 0 0 14 0 0 d=MLV

0 0 0 1 10 3 e=SIV

0 0 1 0 0 40 f=HIV

The table 4 shows precision and recall which

actually are two widely used metrics for evaluating

the correctness of a pattern recognition algorithm.

They can be seen as extended versions of accuracy, a

simple metric that computes the fraction of instances

for which the correct result is returned. In a

classification task, the precision for a class is the

number of true positives (i.e. the number of items

correctly labeled as belonging to the positive class)

divided by the total number of elements labeled as

belonging to the positive class (i.e. the sum of true

positives and false positives, which are items

incorrectly labeled as belonging to the class). Recall in

this context is defined as the number of true positives

divided by the total number of elements that actually

belong to the positive class (i.e. the sum of true

positives and false negatives, which are items which

were not labeled as belonging to the positive class but

should have been).

Fig. 4: ROC for J48 Classifier

Dubey


64

3.3. Reciever Operating Curve (ROC)

It is a graphical technique for evaluating data mining

schemes, which are used in such a way the learner is

trying to select samples of test instances that have a

high proportion of positives a term used to

characterize the tradeoff between hit rate and false

rate.ROC curves depicts the performance of a

classifier without regard to class distribution or error

costs. They plot the number of positives included in

the samples on the vertical axis, expressed as a

percentage of the total number of positives, against the

total number of negatives on the horizontal axis. For

each fold of a 10 fold cross validation ,weight the

instances for a selection of different cost ratios train

the scheme on each weighted set ,count the true

positives and false positives in the test set, and plot the

resulting point on the ROC axes.

The correlation between MLV, SIV and HIV is

predicted as their data is sufficient for analysis of

correlation between these species, but the data of EIV,

FIV, BIV are less for any analysis. Let MLV is X3,

SIV is X2 and HIV is X1, then from correlation

coefficient r12= 0.98551, r13=0.30182, r23=0.47188.

This correctly shows that HIV is highly related to

SIV. Hence Pearson correlation coefficient has been

widely for the analysis of proteomic data. Its

popularity is likely due to its simplicity and

interpretability; therefore it essentially computes the

strength of the linear relationship between the two

quantities/ species.

4. CONCLUSION

Here a framework for disulphide bond prediction and

classification is presented with an accuracy of

89.6104%. Furthermore, DBCP is better for prediction

of disulphide bond with cysteines positions and also

this web server is able to find metal binding sites.

Other methods that can predict both the disulfide

bonds and the metal binding sites will be more

suitable for prediction. The high metal binding site

score (e.g. >0.5) indicates that there may be cysteines

involved in the metal binding sites. For protein

sequence analysis it was found that Env envelope

glycoprotein shows disulphide bond conservation

among all the species of retroviruses. The correlation

between HIV and SIV was also found to be 0.98551.

Hence disulphide bonds are evolutionary conserved

throughout the species.

The knowledge of disulfide richness in certain

organisms suggests practical applications, including

engineering enhanced protein stability and facilitating

protein-fold recognition. Disulfide-rich organisms

should allow the development of novel tools and

approaches for attacking such problems of current

interest. This work depends upon the availability of

sequenced proteomes, and the availability of

additional other proteomes has enabled the

identification of an enigmatic protein family as a

potential player in the biochemistry of cytoplasmic

disulfide bonds. We hope this study will promote

continued interest in sequencing more proteins from

diverse organisms so as to further enhance the scope

and resolution of comparative proteomics techniques.

As more proteomes become available, we anticipate

that the ease of discovery of specific proteomic

adaptations to the environment will improve and yield

further insights into molecular evolution and cell

biology.

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Dubey


66

Anubha Dubey has submitted her PhD in Bioinformatics at Maulana Azad National Institute of

Technology, Bhopal. She received her first degree in Rani Durgawati University Jabalpur in 2005

awarded with Bachelors of Science in Biotechnology. She obtained degree in Master of Science in

Biotechnology from Barkatullah University Bhopal in 2007 with dissertation An Approach to

Investigate the Phenomenon of Genomic Instability in Cultured Human Foetal Lung Fibroblast cells by

modern Technologies. Her current research is focus on extracting information from HIV molecular

sequences by Machine learning techniques. To date, she has published several scientific articles related

to machine learning field.



ISSN: 2322-4541; ©2014 IJSRPUB


67


Bioinformatics Prediction of Interaction Silver Nanoparticles on the Disulfide Bonds

of HIV-1 Gp120 Protein

Shahin Gavanji1*

, Hassan Mohabatkar2*

,Hojjat Baghshahi3, Ali Zarrabi

2

1Young Researchers and Elite Club, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran

2Department of Biotechnology, Faculty of Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran

3Department of Animal Sciences, College of Agriculture, Isfahan University of Technology, Isfahan, Iran

*Corresponding Author: [email protected], [email protected]

Received 25 November 2013; Accepted 01 January 2014

Abstract. Silver nanoparticles have anti-HIV features in early stages of virus amplification. The two existing disulfide bonds

in carboxyl half of the HIV-1 GP120, which cooperate in conjugation of CD4 receptor, interact with silver nanoparticles.

Studies on protein disulfide bonds were done using Metal Detector Predicts V2.0 software. All Cys and His residues in amino

acid sequences were identified. Protein denaturation decreases disulfide bonds when silver ions couple with sulfhydryl groups.

CTRPNNNTRKRIRIQRGPGRAFVTIGKIGNMRQAHC amino acid sequence in GP 120 plays a key role. Breaking this bond

can alter spatial structure of the protein and prevents this part from connecting to CD4. Ultimately, nanosilver can prevent HIV

from connecting to CD4.

Key words: Metal binding sites, silver, GP 120, Bioinformatics

1. INTRODUCTION

Nanoparticles are defined as structures with a

dimension in the range of 1–100 nm. The widely

technological use of nanoparticles in commercial

industry will cause a great increase in price by 2015

(up to $3 trillion) (Ahamed et al., 2010). Silver is

often found in form of metal silver nanoparticles.

Since the particles are small in size, the exposure of

their surface in solution peaks, which leads to the

maximum possible effect per unit of silver. All the

interacting silver nanoparticles with the bacteria were

between 1 and 10 nm (Morones et al., 2005). This

dependency in size probably exists because the

combination of these particles can pass and react with

the cell membrane and their surface-to-volume ratio is

higher.

The smaller is the size of the silver nanoparticles,

the higher is the interaction between atoms. This

explains the reason for small (1−10nm) silver

nanoparticles’ interaction with the bacteria (Feng et

al., 2000). The existence of silver in this minute

amount doesn’t have any adverse effect on human

body (Berger et al., 1976). Nanoparticles have been

applied in medicine in order for experts to trace,

diagnose and cure different diseases. However, the

biological features of these particles are yet to be

studied (Bhattacharya and Mukherjee, 2008). In the

nineteenth century scientists discovered the use of

silver in medicine and local antibacterial agents

(Tokumaru et al., 1974). Studies run on anti-microbial

potential of silver nanoparticles have shown that these

nanoparticles are antibacterial agents against Gram-

negative and Gram positive bacteria (Shahverdi et al.,

2007). And are antiviral agents against HIV-1 (Sun et

al., 2005), hepatitis B virus (Lu et al., 2008),

respiratory syncytial virus (Sun et al., 2008), herpes

simplex virus type 1 (Baram-Pinto et al., 2009) and

monkey pox virus (Rogers et al., 2008). Many

biological processes in micro organisms can be

attacked by silver, namely the alteration of cell

membrane structure and functions (Pal et al., 2007).

This fact makes the application of silver very useful in

developing many biological and pharmaceutical

processes, products and devices some of which are

coating materials for medical devices (Raad and

Hanna, 2002), orthopedic or dental graft materials

(Hotta et al., 1998), wound repair topical aids

(Dowsett, 2004), water sanitization (Lin et al., 2002),

textile products (Takai et al., 2002) and washing

machines (Jung et al 2007). Everyday new forms of

silver nanoparticles are being produced. Parts of

clothing, food containers, wound dressings, ointments,

implant coating ant etc. are some of these products


Gavanji et al.


68

(Arora et al., 2008; Kumar et al., 2008). Silver modes

of inhibitory action to microorganisms are

various(Clement and Jarrett, 1994), therefore,

compared to synthetic fungicides, the use of it in

controlling different forms of plant pathogens might

be safer (Choi, 2006).

This effect seems to be caused by those

mechanisms that are the cause of bactericidal effect of

silver ions. There are two groups of bactericidal

effects of silver: silver ions or silver nanoparticles.

Ions and particles have to be distinctively identified.

Silver ions are charged atoms (Ag+) while silver

nanoparticles are single crystals of nanosize

dimensions. Structural changes in the cell membrane

have been proven to be made by silver ions. The

enzyme-containing sulfate in the membrane of the

bacteria is in interaction with silver ions and. This

changes the membrane morphology by pacifying the

enzymes. Silver ions can easily penetrate the

membrane because of the mentioned inactivation

which makes the membrane vulnerable. The

interaction between silver ions and sulfate groups

located in the active site of the enzyme inside the cell

causes the destruction of the different parts of the cell

to continue. An inactivation of enzymes happens as a

result of this interaction with the active site. Another

interaction, which is proved to have severe effects, is

the interaction between silver ions and phosphorus

groups. The interaction between silver ions and DNA

backbone is an example of this, which is the reason

for bacteria’s inability in replicating itself or

transcribing mRNA for new proteins. All above-

mentioned changes cause a decrease in the speed of

bacteria growth and eventually lead to its death

(Alcamo, 1997). It was shown by another study that,

on the surface of cellular membrane, monovalent

silver ions (Ag+) replace hydrogen cations (H

+) of

sulfhydryl or thiol (S-H) groups.

This disables the production of proteins required to

sustain the cell, which finally kills the cell (Feng et

al., 2000). In addition, studies have suggested that

when silver ions enter the cell they intercalate into

bacterial DNA, and that prevents more pathogen

proliferation. The effectiveness of silver particles as

antimicrobial agents has been increased by

nanotechnology in recent years. The contact between

silver nanoparticles and microbes increases because of

the larger area-to-volume ratio of silver nanoparticles,

which results in the increase of their ability to

permeate cells, and that prevents more pathogen

proliferation. It is thought that silver’s mode of action

depends on Ag+ ions. These ions prevent bacterial

growth greatly by suppression of respiratory enzymes

and electron transport components and through

interference with DNA functions (Li et al., 2006).

Life is believed to be sustained in bacteria through

using an enzyme to metabolize oxygen. This enzyme

gets crippled by silver ions therefore oxygen

metabolizing gets stopped which suffocates the

bacteria and kills it. Virus growth happens when they

invade living cells and then produce replicas of

themselves. Since cell’s life depends on oxygen

metabolizing enzymes, silver ions kill viruses by

killing the cell by suffocation (Alvarez-Puebla et al.,

2004). The interactions between silver nanoparticles

and the bacteria are quite similar to the interactions

between silver ions and bacteria. This might mean that

silver nanoparticles and silver ions are similarly able

to interact with the same types of chemical groups,

and therefore can damage the bacteria in the same

form (Morones et al., 2005). More than any other

inorganic antibacterial agent, the antimicrobial

property of silver has been investigated and employed

extensively (Russell et al., 1994).

The slow and continual release of silver that

prolonged the antimicrobial effect is supposed to be

reason for this. Ionic or nanoparticle silver can

potentially be used for controlling spore-producing

fungal plant pathogens because of their antifungal

activity. In comparison with synthetic fungicides,

silver might have less toxicity for humans and

animals. Antibiotic and preservative qualities of silver

nanoparticles bring them close to human beings.

Bacteria play a key role in human digestion, and if

nanoparticles could eliminate the bacteria, it would

have a fatal effect. Some recent studies have shown

that silver nanoparticles have the ability to attach to

HIV-1virus and avoid it from making bonds with cells

(Elechiguerra et al., 2005). World Health

Organization has currently listed silver sulfadiazine as

an essential anti-infective topical medicine (Lara et

al., 2010). Virus adsorption tests were used to prove

that anti HIV activity of silver nanoparticles prevents

this virus from binding or fusion to the cells. AIDS

happens because of HIV-1infection (Lara et al., 2010;

Allan et al., 1985).

Since the binding between HIV and the target cell

surface, and therefore the cellular and viral membrane

fusion, is mediated by the envelope, its role is critical

in infection. Because preventing HIV from entering

the target cell abandons viral infectivity, replication,

and the cytotoxicity caused by virus-cell interaction,

fusion or entry inhibitors should be remarkably noted.

Also the presence of virucidal agents is necessary for

HIV/AIDS prevention because of their deactivating

quality against viral particle (virion), with which the

completion of viral replication cycle can be prevented

(Salzwedel et al., 1999). Silver nanoparticles act like

virucidal agent or viral entry inhibitor and therefore

deploy anti-HIV activity at early stages of viral

replication. Remarkable differences in antiviral


69

activities of silver nanoparticles against different

drug-resistant strains were not found; therefore

changes made in antiretroviral HIV strains that confer

resistance do not have any influence on the efficacy of

silver nanoparticles (Al-Jabri and Alenzi, 2009).

Furthermore, an interaction between silver

nanoparticles and the two disulfide bonds located in

the carboxyl half of the HIV-1 gp120 glycoprotein

might happen. This mentioned area has been shown in

binding to the CD4 receptor (Lekutis et al., 1992).

The binding between sulfhydryl groups causes the

protein denaturation through reducing disulfide bonds.

Because silver nanoparticles have antiviral activity,

they are able to prevent HIV-1 infection from binding

to gp120. This inhabitation prevents CD4-dependant

viron binding, fusion and infectivity and inhibits HIV-

1 cell-free and cell-associated infection. This happens

because they act as virucidal agents (Borkow and

Lapidot, 2005). It is concluded that, through stopping

the activity of HIV particles at an early stage of viral

replication, silver nanoparticles act as effective

virucides by inactivating HIV particles in a short

period of time.

The aim of the study was to investigate the

bioinformatics prediction of interaction silver

nanoparticles on the disulfide bonds of HIV-1 Gp120

protein

2. MATERIALS AND METHODS

2.1. Preparing 3 dimensional structure GP120

protein

In the first step, amino acid sequences of GP120

protein with an accession number of p03378.1 were

taken from NCBI website (www.ncbi.nlm.nih.gov).

The GP120 protein consists of 478 amino acids

(Figure 1) and its molecular weight is 23.469Da .Then

the GP120 viral protein with the number of 1GC1

linked to CD4 protein was taken from Protein Data

Bank website. The CD4 and additional ligands were

separated from that GP120 viral protein through

Molegro software and this protein was prepared for

research, without having any other protein or ligand

linked to it (Figure 2) (www.rcsb.com). In the next

step, and silver with Ag formula (number 22394) were

provided from ChemSpider website

(www.chemispider.com).

Fig. 1: Amino acid sequence of GP120 protein

Fig. 2: Structure of GP120 protein

2.2. Studying disulphide bonds in proteins

2.2.1. Metal Detector Web Server

The web server Metal Detector classifies histidine

residues in proteins into one of two states (free or

metal bond) and cysteines into one of three states

(free, metal bond or disulfide bridged). It is freely

available at (http://metaldetector.dsi.unifi.it/v2.0).

This web server takes the protein sequence as input

and outputs predictions of transition-metal binding for

cysteine and histidine residues; for cysteines it also

predicts disulfide bonding bridges. Residues predicted

to coordinate the same ion will share the same

identifier. Every identifier is an integer ranging from 1

to 4. Its value has no special biochemical semantics

http://www.rcsb.com/

http://www.chemispider.com/

http://metaldetector.dsi.unifi.it/v2.0

Gavanji et al.


70

but lower values correspond to a higher level of

confidence for the predictor.

2.2.2. Studying disulphide bonds

Studies on disulfide bonds were performed using

Metal Detector Predicts v2.0 software. All Cys and

His residues in amino acid sequences were identified.

(http://metaldetector.dsi.unifi.it).

Fig. 4: disulfide bonds and metal binding site in GP120 protein


3.1. Protein Structure Analysis

The GP120 protein consists of 478 amino acids, and

its molecular weight is 23.469 kD. This location is in

extracellular form, and the location of CD4-binding

loop is from amino acids 366 to 376 which contain 11

amino acids. According to the results taken from

Metal Detector Predicts v2.0 online server, the

disulfide bonds in GP120 protein amino acid sequence

are sited between cysteine amino acids in locations

186, 173, 164, 125, 99, 94, 87, 42, 22, 413, 386, 353,

346, 299, 264, 215, 207 and 196 as they are shown in

figure 4. The 346 location is the most important site of

this sequence, which is the site for metal group bonds.

Therefore, the sequence of

CTRPNNNTRKRIRIQRGPGRAFVTIGKIGNMRQA

HC in GP120 protein plays a key role (Figure 5). This

sequence is in the first and most important part of this

protein to bind GP120 and CD4 proteins. In Molegro

software the basis of the three dimensional structure

of this protein is positioned between 264 to 299 amino

acids where sulfide bonds are located. Breaking this

binding can change the spatial structure of this

protein, therefore prevents this part from binding to

CD4.

http://metaldetector.dsi.unifi.it/


71

Fig. 5: The structure of sequence amino acid in GP120 protein

Penetration and distribution inhibitors are

considered remarkable since inhibiting HIV from

penetrating the target cell will in turn lead to

prevention from viral infections, duplication, and

cytotoxicity caused by virus-cell interaction (Borkow

and Lapidot, 2005). The antivirus activity of

nanosilver particles let us inhibit HIV1 infections

regardless of virus types or resistant profiles against

GP120 binding. This inhibition is done so that viral-

particle-dependant CD4 cannot bind and there will not

be any infection and propagation, and it prevents

HIV-1 free cells and infected cells. Thus, nanosilver

particles are effective antivirus particles since they are

short term HIV deactivators. These particles act at the

beginning stages of viral propagation (penetration or

spread) and at pre-penetration stages (Lara et al.,

2010). The binding of silver ions to sulfhydryl groups

causes protein denaturation through reducing disulfide

bonds (McDonnell, 2007). Results of our research

show that the first and most important part of this

protein binds GP120 and CD4 proteins. In Molegro

software the basis of the three dimensional structure

of this protein is positioned between 264 to 299 amino

acids where sulfide bonds are located. Breaking this

binding can change the spatial structure of this

protein, therefore prevents this part from binding with

CD4.

4. CONCLUSION

At the first stages of HIV proliferation, silver nano

particles can act as antivirus agent for deactivation of

the virus in a short period of time. This process is

done through interaction of nano silver with 2

disulfide bonds located in carboxyl )HIV-1 gp120) so

that silver ions, through interaction with thiol group,

decrease disulfide bonds leading to protein

denaturation. Considering other similar scientific

investigations, one can conclude that the mentioned

process is fulfilled through substitution of single

valence Ag+ with H+ existed in thiol group.

Bioinformatic results using software and servers show

that silver ions make interaction with thiol group

through which the disulfide bonds decrease and the

virus will be destroyed.

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Shahin Gavanji graduated in Biotechnology at MSc at the Department of Biotechnology, Faculty of

Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran. He has over 10 international

medals in invention. Shahin Gavanji's research has focused on Pharmacy and Pharmacology, Nano

Biotechnology, Bioinformatics, Biotechnology - Medical Biotechnology. He is editor in chief of

International Journal of Scientific Research in Inventions and New Ideas.

Dr. Hassan Mohabatkar is a faculty member at Department of Biotechnology, Faculty of Advanced

Sciences and Technologies, University of Isfahan, Isfahan, Iran. His research has focused on

Bioinformatics.

[email protected]

Hojjat Baghshahi graduated in Animal Science at MSc at the Department of Animal Sciences, College of

Agriculture, Isfahan University of Technology (IUT), Isfahan, IRAN.

Dr. Ali Zarrabi, Assistant Professor of Nano-biotechnology, Department of Biotechnology, Faculty of

Advanced Sciences and Technologies, University of Isfahan, Isfahan, Iran.

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ISSN: 2322-4541; ©2014 IJSRPUB


75


A Comparative Evaluation of Drug Release and Permeability of Ethylcellulose,

Cellulose Acetate and Eudragit RS100 Microspheres

Prakash Katakam1*, Saousen R. Diaf

1, Baishakhi Dey

2, Shanta K. Adiki

3, Babu R. Chandu

1, K.P.R. Chowdary

4

1Faculty of Pharmacy, University of Zawia, Libya

2School of Medical Science and Technology, IIT Kharaghpur, India

3Nirmala College of Pharmacy, Guntur, India

4College of Pharmaceutical Sciences, Andhra University, India

*Corresponding Author: [email protected]

Received 01 December 2013; Accepted 11 January 2014

Abstract. Present study aims at comparative evaluation of drug release and permeability of diclofenac sodium loaded

ethylcellulose (EC), cellulose acetate (CA) and eudragit (EU) microspheres. Microspheres of EC, CA and EU containing

diclofenac sodium were prepared by an emulsification-solvent evaporation (oil-in-oil, o/o) method and were investigated for a

comparative evaluation of various parameters. The microspheres were found discrete, free flowing, multinucleate, monolithic

and spherical. About 5560% of all microspheres prepared were in the size range of –20+30 (715 m) mesh size. The

encapsulation efficiency was in the range of 97.1106.4% with various polymers. The wall thickness of microspheres was in

the range of 13.69-74.97m which depended on polymer employed and was directly proportional to polymer concentration.

Diclofenac release from the microspheres was slow over longer periods of time and depended on the polymer used and

coat:core ratio. Release was diffusion controlled and followed first order kinetics. Good linear relationships were observed

between percent coat, wall thickness and release rate constant with all the three polymers. The slopes of percent coat vs release

rate (k1) plots were found to be 0.4117, 0.2351 and 0.9762; and those of wall thickness (h) vs drug release rate (k1) plots were

found 0.2549, 0.1863 and 0.7850 respectively for EC, CA and EU microspheres. The lower the slope the better is the

controlling effect. Cellulose acetate exhibited better release-controlling effect than that of ethylcellulose and eudragit. The

increasing order of diclofenac release rate and permeability observed with various microspheres was, cellulose acetate <

ethylcellulose < eudragit RS100. The possible permeability of drug from the prepared porous micrsopheres could be due to

osmotic pressure generated by diclofenac.

Keywords: Diclofenac sodium, Microspheres, Ethylcellulose, Cellulose acetate, Eudragit RS100 Release kinetics

1. INTRODUCTION

Microspheres are solid, approximately 1 to 1000 m

in size and are made of synthetic and natural

polymeric, waxy or other protective materials both

biodegradable and non-biodegradable (Vyas and

Khar, 2002). The internal structure of microspheres

varies as a function of polymer and the process

employed to prepare them (Brannon-Peppas, 1992).

Reservoir microcapsules have a core of drug coated

with a polymer. Whereas in monolithic microspheres,

the drug is distributed homogeneously throughout the

polymeric matrix. Microspheres have been widely

accepted as a means to achieve oral and parenteral

controlled release (Sau-hung et al., 1987).

Microspheres provide several advantages over other

sustained release systems, especially matrix type

tablets. They can be widely distributed throughout the

gastrointestinal tract, improve drug absorption and

minimize side effects due to localized buildup of

irritating drugs against the gastrointestinal mucosa (Li

et al., 1988).

The rate of drug release from microspheres dictates

their therapeutic action. Release is governed by the

molecular structure of the drug and polymer, the

resistance of the polymer to degradation and the

surface area and porosity of microspheres (Izumikawa

et al., 1991; Pitt and Schindler, 1983). Drug release

from polymeric systems with a variety of geometries

has been described (Cheung et al., 1988). Zero order

release kinetics may be more easily achieved with slab

or rod geometries than spheres. The rate of release

from spheres may result from polymer diffusion or

erosion (Cartensen, 1984; Crank, 1975).

Ethylcellulose, cellulose acetate and eudragit

RS100 are non-toxic, biocompatible polymers with

Katakam et al.


76

good film-forming properties and have been

extensively used in coating (Kent and Rowe, 1978)

and microencapsulation (Porter, 1989) to prepare

microspheres. Though they have been studied

(Prakash et al., 2007; Padala et al., 2009; Chowdary

and Ratna 1993; Kawashima, 1989; Hasan, 1992;

Lorenzo-Lamon et al., 1998) individually for

microspheres and controlled release, no reports on

comparative evaluation of their drug release and

permeability characteristics for diclofenac are

available. In the present study a comparative

evaluation of drug release and permeability of

ethylcellulose (EC), cellulose acetate (CA) and

eudragit (EU) microspheres has been made employing

diclofenac sodium as core. Oral controlled release

formulations are needed for diclofenac because of its

short biological half-life of 2.0 hr and gastrointestinal

irritation if present in larger concentrations (Gilman,

1991). In the present investigation a comparative

evaluation of drug release and permeability of

ethylcellulose (EC), cellulose acetate (CA) and

eudragit (EU) microspheres was made by employing

diclofenac sodium as core.

2. MATERIALS AND METHODS

2.1. Materials

Diclofenac sodium was a gift sample from M/s

Roland Pharmacetuicals, Berhampur, India.

Ethylcellulose (Loba Chemie, Mumbai, with an

ethoxy content of 47.5% by weight and a viscosity of

22 cps in a 5% concentration by weight, in a 80:20

toluene-ethanol solution at 25 oC), cellulose acetate

(Loba Chemie, Mumbai with a viscosity of 100140

cps in a 6% solution in 95% acetone-water mixture at

20 oC), eudragit RS100 (with a viscosity of 15 mPa s

in a 2% acetone-ethanol (1:1) solution at 25 oC), n-

hexane (Ranbaxy), acetone (Merck) and liquid

paraffin I.P. were procured from commercial sources.

All other reagents used were of analytical grade.

2.2. Preparation of microspheres

Microspheres of ethylcellulose, cellulose acetate and

eudragit containing diclofenac sodium were prepared

by an emulsification-solvent evaporation (oil-in-oil,

o/o) method. The polymer (EC, CA or EU) (2.0 gm)

was dissolved in acetone (100 mL) to form a

homogeneous polymer solution. The core material,

diclofen

added to the polymer solution (20 mL) and mixed

thoroughly. The resulting mixture was then added in a

thin stream to 200 mL of liquid paraffin contained in a

450 mL beaker, while stirring at 1000 rpm to emulsify

the added dispersion as fine droplets. A Remi medium

duty stirrer with speed meter (Model RQT 124) was

used for stirring. The solvent was then removed by

continuous stirring at room temperature (28 oC) for 3

hr to produce spherical microspheres. The

microspheres were collected by vacuum filtration and

washed repeatedly with n-hexane to remove adhering

liquid paraffin. The product was then air dried to

obtain discrete microspheres. Different proportions of

coat:core materials namely 1:9 (MC1), 2:8 (MC2), 3:7

(MC3), 4:6 (MC4) and 5:5 (MC5) were used in each

case to prepare microspheres with varying coat

thickness.

2.3. Evaluation of microspheres

Diclofenac sodium content in the microspheres was

estimated by using UV-spectrophotometric method

(The United States Pharmacopoeia, 1999) based on

measurement of absorbance at 276 nm in phosphate

buffer of pH 6.8. The method was validated for

linearity, accuracy and precision. The method obeyed

Beer-Lambert’s law in the concentration range 1-20

μg/mL. When a standard drug solution was assayed

repeatedly (n=6), the mean error (accuracy) and

relative standard deviation (precision) were found to

be 1.2% and 2% respectively. The encapsulation

efficiency was determined by estimating the drug

content in the microspheres and using the formula:

For size distribution analysis, different sizes in a

batch were separated by sieving using a range of

standard sieves. The amounts retained on different

sieves were weighed. Theoretical mean wall thickness

of the microspheres was determined by the method of

Luu et al (1973) using the equation:

12

1

d P1Pd 3

d P1 rh

where, h = wall thickness (m); r = mean radius of

microspheres (m); d1 = density of core material

(g/cm3); d2 = density of coat material (g/cm

3) and P =

proportion of medicament in the microspheres.

The microspheres prepared along with their

diclofenac content, encapsulation efficiency and wall

thickness measurements are given in Table 1. The

microspheres were observed under a scanning electron

microscope (SEM-LEICA, S430, UK). For SEM, the

microspheres were mounted directly on the sample

stub, using double-sided sticking tape, and coated

with gold film (thickness 200 nm) under reduced

pressure (0.001 torr).


77

2.4. Drug release study

Release of diclofenac sodium from the microspheres

of size 20/30 was studied in phosphate buffer of pH

6.8 (900 mL) at 37 oC using an USP XXIV 6-stage

dissolution test apparatus (M/s. Campbell Electronics,

Mumbai) with a paddle stirrer at 100 rpm. A sample

of microspheres equivalent to 100 mg of diclofenac

sodium was used in each test. Samples were

withdrawn through a filter (0.4 m) at different

intervals of time and were assayed at 276 nm for

diclofenac sodium using an Elico UV-visible double

beam spectrophotometer. The drug release

experiments were conducted in triplicates.

From the drug release data, the permeability

coefficient (Pm) for various microspheres was

calculated using the equation as described by Koida et

al (1986).

s

app

A.C

.V.HKPm

where, Pm = permeability coefficient

(cm2/min), Kapp = apparent dissolution rate constant

calculated as mg/min from, the slope of the early

linear portion, V = volume of dissolution medium

(cm3), H = wall thickness of microspheres (cm), A =

surface area of the microspheres (cm2) and Cs =

solubility of the core in the dissolution medium (mg).

3. RESULTS AND DISCUSSION

Ethylcellulose, cellulose acetate and eudragit

microspheres of diclofenac sodium could be prepared

by the emulsification and solvent evaporation method

using acetone as solvent for the polymer as reported

by us (Prakash et al., 2007). The microspheres were

found to be discrete, spherical and free flowing.

Scanning electron microscogram (SEM) showed that

the microspheres prepared by all the three polymers

were nearly spherical with rough microporous surface

(Fig. 1). Regarding the internal structure the nature of

the method indicates that the microspheres produced

were of multinucleate monolithic type.

The sizes could be separated and a more uniform

size range of microspheres could readily be obtained

by sieving. The size distributions were normal in all

the batches with a large proportion, overall about

5560%, in the size range of –20+30 (715 m) mesh

size.

Fig. 1: Scanning electron micrograms of ethylcellulose (A), cellulose acetate (B) and eudragit RS100 (C) microspheres loaded

with diclofenac sodium.

Low coefficient of variation (< 4.7%) in percent

drug content indicated uniformity of drug content in

each batch of microspheres prepared with different

polymers (Table 1). The encapsulation efficiency was

found in the range 97.1103.8% with ethylcellulose,

99.4106.4% with cellulose acetate and

101.4104.2% with eudragit. As the microspheres

were spherical, the theoretical mean thickness of the

wall that surrounds the core particles in the

microspheres was calculated as per Luu et al (1973).

Microspheres prepared employing various ratios of

coat:core in each case (polymer) were found to have

different wall thickness.

Diclofenac release from the microspheres of size

20/30 was studied in phosphate buffer of pH 6.8 for a

period of 12 hr. Diclofenac release from all the

microspheres was slow and spread over extended

periods of time (Table 2). Plots of log percent drug

remaining vs time (Fig. 2) were found to be linear

(r>0.9516) with all the microspheres indicating that

the drug release from these microspheres was

according to first order kinetics with all the three

polymers. In a monolithic microsphere the path length

does not remain constant, since the drug in the center

has a longer path or travel than the drug near the

surface and therefore the rate of release decreases

exponentially with time. The release rates of various

microspheres are given in Table 2. At all coat:core

ratios the release rates were higher with eudragit and

the order of increasing release rates with various

Katakam et al.

A Comparative Evaluation of Drug Release and Permeability of Ethylcellulose, Cellulose Acetate and Eudragit RS100

Microspheres

78

polymers was CA < EC < EU. In each case the

release was depended on the percent of coat and wall

thickness of the microspheres.

Table 1: Coat:core ratio, drug content, encapsulation efficiency and wall thickness of the microspheres prepared.

Microspheres Coat:Core ratio Percent drug content Encapsulation

efficiency (%)

Wall thickness

(m) Theoretical Practical*

ECMC1 1:9 90 88.4 (1.6968) 98.2 18.90

ECMC2 2:8 80 77.7 (1.5444) 97.1 35.50

ECMC3 3:7 70 71.2 (3.6516) 101.7 50.16

ECMC4 4:6 60 61.5 (4.1951) 102.5 63.24

ECMC5 5:5 50 51.9 (2.3121) 103.8 74.97

CAMC1 1:9 90 93.5 (2.139) 103.8 13.69

CAMC2 2:8 80 83.1 (2.0457) 102.1 26.93

CAMC3 3:7 70 69.6 (3.8793) 99.4 39.76

CAMC4 4:6 60 62.3 (4.6548) 103.3 52.17

CAMC5 5:5 50 53.2 (4.1353) 106.4 64.20

EUMC1 1:9 90 93.2 (2.253) 103.5 14.18

EUMC2 2:8 80 81.9 (2.3199) 102.4 27.78

EUMC3 3:7 70 72.6 (2.8925) 103.7 40.83

EUMC4 4:6 60 62.5 (2.72) 104.2 53.35

EUMC5 5:5 50 51.7 (4.091) 101.4 65.39

* Figures in parentheses are coefficient of variation (cv) values.

Fig. 2: Log percent of drug remaining vs. time plots of ethylcellulose (A), cellulose acetate (B) and eudragit RS100 (C)

microspheres. MC1 (□), MC2 (), MC3(◊), MC 4 (Ο) and MC5(* ).


79

Table 2: Release characteristics of microspheres prepared.

Microspheres Mean percent drug released at different time intervals (hr) (%±SD), n=3 T50

(hr)a k1 (hr-1)b

1.0 2.0 4.0 8.0 10.0 12.0

ECMC1 76.81±4.25 80.15±5.18 85.03±5.29 100.00±5.13 - - 7.09 0.3246

ECMC2 56.90±3.44 65.77±3.79 79.11±4.29 100.00±4.62 - - 7.37 0.3125

ECMC3 53.44±3.79 62.50±4.31 73.46±4.37 100.00±5.36 - - 8.21 0.2805

ECMC4 52.08±2.53 60.96±4.33 68.96±4.77 90.03±4.22 - - 8.74 0.2635

ECMC5 42.67±2.94 50.77±3.79 62.43±3.21 79.11±4.16 85.01±4.66 89.78±4.55 13.91 0.1656

CAMC1 63.56±4.19 79.23±3.61 88.48±4.45 100.00±4.97 - - 9.63 0.2392

CAMC2 54.36±3.88 64.46±4.34 70.36±5.49 86.87±4.37 100.00±5.14 - 11.98 0.1923

CAMC3 50.30±2.59 61.02±3.28 68.26±4.62 83.17±4.14 89.12±4.62 100.00±5.12 14.47 0.1591

CAMC4 48.35±3.18 56.49±3.46 65.40±5.18 80.94±3.85 86.39±4.26 91.78±4.52 14.58 0.158

CAMC5 39.15±3.31 45.22±3.11 56.36±4.73 74.45±4.28 82.71±4.76 86.17±5.18 16.52 0.1394

EUMC1 81.99±4.75 89.16±4.39 98.45±5.35 - - - 3.84 0.5995

EUMC2 76.93±6.39 83.70±5.44 94.61±5.97 - - - 4.86 0.4738

EUMC3 58.65±3.86 70.38±4.71 81.67±3.82 96.38±3.92 - - 6.54 0.3521

EUMC4 41.98±3.64 61.19±3.88 75.56±4.26 90.08±4.51 97.57±5.33 - 9.08 0.2535

EUMC5 38.93±2.71 56.34±3.29 63.39±3.74 80.58±4.89 96.26±4.27 - 11.02 0.2089 aTime for 50% release;

bFirst order release rate constant

Good linear relationships were observed between

percent coat (or) wall thickness and release rate

(Fig. 3). The relationships could be expressed by the

following linear equations.

y = 0.4117 x + 39.23 for ethyl cellulose

y = 0.2351 x + 24.26 for cellulose acetate

y = 0.9762 x + 64.72 for eudragit

where, x is percent coat and y is first order release rate

(k1 hr-1

) of the microspheres.

y = 0.2549 x + 39.31 for ethyl cellulose

y = 0.1863 x + 25.09 for cellulose acetate

y = 0.7850 x + 69.39 for eudragit

where, x is the wall thickness (m) and y is first order

release rate (k1 hr-1

) of the microspheres.

Fig. 3: Relationship between (A) percent coat and release rate and (B) wall thickness and release rate of ethyl cellulose (Ο),

cellulose acetate (□) and eudragit RS100 () microspheres.

The slope of the linear regression between percent

coat and release rate (k1) indicates the release

controlling effect of the polymer. The lower the slope

the better is the controlling effect. The slopes were

found to be 0.4117, 0.2351 and 0.9762 respectively

for the coat materials ethylcellulose, cellulose acetate

and eudragit. Similarly from the plots of wall

thickness (h) vs drug release rate (k1), the slopes

Katakam et al.

A Comparative Evaluation of Drug Release and Permeability of Ethylcellulose, Cellulose Acetate and Eudragit RS100

Microspheres

80

obtained for ethylcellulose, cellulose acetate and

eudragit microspheres were 0.2549, 0.1863 and

0.7850 respectively. Thus cellulose acetate was found

to have better release controlling effect than the other

two polymers (Pratap et al., 2012). The order of their

effectiveness in controlling drug release was found as

CA > EC > EU. Plots of amount released vs square

root of time (Fig. 4) were found to be linear with all

the three polymers indicating that the drug release

from these microspheres was diffusion controlled.

Fig. 4: Amount released vs. square root of time plots of ethylcellulose (A), cellulose acetate (B) and eudragit RS100 (C)

microspheres. MC1 (□), MC2 (), MC3(◊), MC 4 (Ο) and MC5(*).

Permeability of the microspheres was calculated

based on the release data as described by Koida et al

(1986). Permeability values of various microspheres

are summarized in Table 3. At all ratios of coat:core,

the microspheres of cellulose acetate were less

permeable than those of ethyl cellulose and eudragit

RS100. The order of increasing permeability of the

microspheres was CA < EC < EU. The permeability

of microspheres having porous surface occurs when

drug release is driven by osmotic pressure (Ozturk et

al., 1990). The possibe permeability of drug from the

prepared porous micrsopheres could be due to osmotic

pressure generated by diclofenac.

Table 3: Permeability coefficient (Pm) values of various microspheres prepared.

Microspheres Coat : core ratio Permeability coefficient, Pm (cm2/min) of microscpheres

EC CA EU

MC1 1:9 8.93 5.35 7.15

MC2 2:8 12.43 9.01 13.15

MC3 3:7 16.50 12.32 14.74

MC4 4:6 20.26 15.53 13.78

MC5 5:5 19.68 15.47 15.67

4. CONCLUSION

Ethylcellulose, cellulose acetate and eudragit RS100

microspheres containing diclofenac sodium could be

prepared by the emulsification-solvent evaporation

method using acetone as solvent for the polymer with

an encapsulation efficiency varying between

97.1106.4%. The microspheres were discrete, free

flowing, multinucleate, monolithic and spherical.

Diclofenac release from the microspheres was slow

over longer periods of time and depended on the

polymer used and coat:core ratio. Release was

diffusion controlled and followed first order kinetics.

Good linear relationships were observed between

percent coat, wall thickness and release rate constant

with all the three polymers. Cellulose acetate

exhibited better release-controlling effect than

ethylcellulose and eudragit. The order of increasing

diclofenac release rate and permeability observed with

various microspheres was cellulose acetate <

ethylcellulose < eudragit.

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Katakam et al.


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Prakash Katakam, M.Pharm., Ph.D., has done his Ph.D. (Pharmaceutical Sciences) from Berhampur

University, Orissa, India. Research contribution includes design and biomedical evaluation in vitro and in

vivo, of various controlled release drug delivery systems like subgingival delivery films, microcapsules

and matrix tablets and conventional dosage forms. Other areas of research interest are biomaterials,

bioanalytical method development and natural medicine. He has guided two Ph.D. students and several

M.Pharm students. He has 80 peer reviewed research articles and four Indian patents to his credit. He is a

member of various professional bodies and editorial board member of several international journals.

Presently he is working on biomaterials and their novel modifications for pharmaceutical application.

Saousen R. Diaf, has completed her MSc Pharmaceutical Technology and Pharmacy Science in 2009 from

School of Pharmacy, University of Complutense, Madrid, Spain. She has completed her Master degree in

Pharmacognosy and Natural products in 2006 from College of Pharmacy, University of Alfateh, Tripoli,

Libya. She has been a recipient of Fulbright Exchange Libya Scholarship 2013, University of Nebraska

Medical Center, College of Public Health, Omaha, Nebraska, USA. Her areas of research interest are

Novel Drug Delivery systems and Industrial Pharmacy.

Ms Baishakhi Dey, M.Pharm., is a Faculty of Pharmacy, pursuing her PhD. Her research interests are

mostly in herbal anti-diabetic bio-actives, Nanotechnical approaches to drug delivery, Formulation of

nutraceuticals via innovative process technologies and pharmacoepidemiological surveys on disease

pattern. Currently she is having 12 peer reviewed journal articles, 5 conference papers, 2patents. Ms Dey is

the co-author of two books, and four book chapters.

Shanta Kumari Adiki, PhD, has done her PhD (Pharmaceutical Sciences) from Berhampur University,

India. She has completed her Master degree from Andhra University, India. She has 12 years of rich

experience Research and Teaching and published over 35 research articles in various international journals

and has two Indian patents. Her primary research area is Analytical chemistry and Bioanalytical Method

Development. Her other areas of research interest are formulation development, novel drug delivery

systems and natural products. She is presently guiding two PhD students and has guided several M.Pharm

projects.

Babu Rao Chandu, M.Pharm., Ph.D., has done his Ph.D. (Pharmaceutical Sciences) from Andhra

University, India. During his highly noticeable research experience over 20 years he has published over

140 papers in various international impact journals and one Indian patent. His research areas of interest

include, Phytochemistry, Natural medicine, Drug design and synthesis, Bioanalytical method development

and Formulation of dosage forms. He is a member of various professional bodies and editorial member of

several international journals. He has guided five Ph.D. students and several M.Pharm students.

Chowdary, KPR, M.Pharm., PhD., PGDAS, is a retired professor from University College of

Pharmaceutical Sciences, Andhra University. His primary area of research is Controlled Drug Delivery

Systems. He is well known for his research in the field of Microencapsulation and polymer science. He is

highly specialized in modification of drugs to improve their solubility by complexation. He has produced

over 60 PhDs and guided over 100 M.Pharm research projects.



ISSN: 2322-4541; ©2014 IJSRPUB


83


Investigation of a Proposed Four Storey Building Sites Using Geophysical and

Laboratory Engineering Testing Methods in Lagos, Nigeria

Oyedele Kayode Festus*, Adeoti, Lukman, Oladele Sunday and Kamil Akintunde

Department of Geosciences, University of Lagos, Lagos, Nigeria

*Corresponding Author: Email: [email protected]


Abstract. The spate of engineering structures collapse in Lagos metropolis with its attendant loss of lives and properties has

assumed an alarming proportion in recent times. Efforts to mitigate such incidence has necessitated an integrated geophysical

and geotechnical investigation of a proposed four storey building sites with a view to determine the suitability of the site for

the proposed project. Resistivity investigation, un-drained multi-stage triaxial compression and oedometer consolidation tests

were carried out to determine the engineering properties of the subsurface. The results revealed peaty clay to silty sand

materials characterized by 35kN/m2 - 75kN/m

2 cohesion values, (5°-13°) internal friction, 29.3% - 64.5% natural water content

and 1.652 – 1.972 Mg/m3 bulk density. The allowable bearing capacity of 50 kN/m

2, volume compressibility from 0.115

m2/MN to 0.666 m

2/MN, initial void ratio and consolidation coefficient of 0.779 - 1.381 and 2.7 m

2/year - 8.3 m

2/year

respectively on the pressure range of 0 to 400 kN/m2

and estimated settlement values of 114 to 273 mm were obtained for the

site materials. These results are indicative of soft to stiff clays and presence of sands and silts in the essentially clayey deposit.

The study area is thus underlain by extensive zone of ductile and low strength founding materials having medium to high

compressibility and settlement value that exceeds the tolerable limit suitable for founding a four storey building and should

therefore be avoided. These characteristics preclude the use of conventional shallow foundations, piles or vibro-replacement up

to a depth of 30 m.

Keywords: Resistivity, vibro-replacement, multi-stage triaxial, geotechnical, uncomformably

1. INTRODUCTION

The incessant incidence of building failures is

becoming alarming in Nigeria and Lagos metropolis

in particular and has led to loss of life and properties

worth millions of dollars. These failures have been

attributed to factors such as inadequate information

about the subsurface geological material, poor

foundation design and poor building materials. Prior

to the commencement of design of a construction

project, investigations are traditionally carried out in

line with existing guides and codes regarding the

property and quality of the proposed site. Such

investigation is carried out in order to avert structural

failures, as these failures could lead to disasters which

pose serious threats to public safety. The ultimate goal

of site investigation is to have appreciable

understanding of the behaviour of the soils that will

bear load to be transmitted by the proposed structure.

More often than not, site investigation in Nigeria is

achieved by use of traditional geotechnical methods

such as boring and cone penetration testing while

undermining the growing importance of the

geophysical methods (Soupios et al., 2007) for the

geotechnical site chatacterization.

Geotechnical tests usually reveal discreet

information about the subsurface. However, to obtain

a clearer picture, geophysical methods are essential to

establishing lateral and vertical variations between the

points under investigation. The need to address the

lateral variations informed the integration of

geophysical and geotechnical methods in this study. In

the last decade, the involvement of geophysics and

geotechnical methods in civil engineering has become

a promising approach (Adepelumi et al., 2009; Al

Omosh et al., 2008; Schoor, 2002; Adepelumi and

Olorunfemi, 2000). However, it should be noted that

the use of geophysical methods in site investigation is

intended to supplement geotechnical methods and not

to serve as substitutes for the drilling, sampling, test

pitting and in-situ laboratory testing (Rowe, 2001).

For economic reasons, boreholes cannot be placed

close enough to one another to give an accurate

picture of subsoil conditions. The role of geophysics

is usually to describe the properties and geometry of

the subsurface (Sheriff, 2002) and to provide data

Festus et al.

Investigation of a Proposed Four Storey Building Sites Using Geophysical and Laboratory Engineering Testing

Methods in Lagos, Nigeria

84

between borings and at the same time reduce the

number of boreholes. Thus, combination of

geophysical data and geotechnical measurements may

greatly improve the quality of construction in civil

engineering as it will focus on the behaviour and

performance of soils and rocks in the design and

construction of civil engineering structures (Oyedele

et al., 2009). In this study, geophysical and field/

laboratory geotechnical methods were integrated with

a view to determining the suitability of subsoil at a

proposed four storey building development sites in

Ebute Metta (near Iponri), Lagos Nigeria, which will

serve as a guide for the design of the foundation for

the proposed structure.

2. GEOLOGIC SETTING

The Dahomey Basin is a combination of

inland/coastal/offshore sedimentary basin in the Gulf

of Guinea (Obaje, 2009). The lithology based

stratigraphic classification of Dahomey basin by Jones

and Hockey (Brownfield and Charpentier, 2006) is

suitable for this study in that lithology is a key

parameter in determining suitability of materials for

engineering purposes. The Ewekoro Formation, which

conformably overlies the Abeokuta formation is

Palaeocene in age and consists of limestone, shale and

clay members. The Ilaro formation overlies the

Ewekoro Formation and is of Eocene age. It is

composed of poorly sorted sandstone with clay

fractions and subordinate shale. The Coastal Plains

Sands unconformably overlies the Ilaro Formation and

is Pleistocene to Oligocene in age. The lithology

consists essentially of sands, silts and clay deposits

with traces of peat in parts. It directly underlies the

study area and is composed of deposits which can be

divided into the littoral and lagoonal sediments of the

coastal belt and the alluvial sediments of the major

rivers. They essentially of consist of unconsolidated

sands, clays and mud with a varying proportion of

vegetative matter.

3. METHODOLOGY

3.1. Geophysical Survey

A multi - electrode 2- D resistivity survey was carried

along four 200m traverses spaced approximately 30 m

from each other (Figure 1) with sixty-four electrode

SAS 4000 Terameter. A 5 m inter-electrode spacing

Wenner array was utilized owing to its high sensitivity

to lateral in homogeneities to provide a good idea of

variation of materials in a continuum around the site.

The acquired 2D data was inverted using the software

package RES2DINV (Loke, 1997).

3.2. Borehole Drilling

Eleven bore holes, distributed along the four traverses

were drilled on the site to a maximum depth of 30 m.

The drilling was carried out employing the shell and

auger drilling method with a fully equipped motorized

Pilcon Wayfarer drilling rig. Samples were collected

for inspection, description and laboratory analysis.

Sampling and in situ tests were carried out

progressively with the advancement of the drilling

activity through the sediments from which a number

of geotechnical samples intended for triaxial

compression and oedometer testings were collected.

3.3. Undrained Multi-Stage Triaxial Compression

Testing

Triaxial Compression Test is a test in which a

cylindrical specimen of soil or rock encased in an

impervious membrane is subjected to a confining

pressure and then loaded axially to failure in

compression. The triaxial apparatus has been

described in great detail by Bishop and Henkel

(1962). To prepare a triaxial specimen, field samples

were removed from its plastic sleeve and trimmed to a

length of about 200 mm.

The multistage triaxial test (Kovari and Tisa,

1975), as specified in BS1377: part 8:1990 and

described in Head (1992), was carried out to measure

the shear strength parameters of soils namely cohesion

and internal friction angle. In this multi-stage element,

a single specimen was compressed at three effective

stress stages, rather than using the more familiar three

individual specimens. The reason for using the multi-

stage approach is that fewer samples require less time

in the field, and that issues of non-uniformity between

samples were removed.

3.4. Oedometer Consolidation Test

The specimens were loaded and unloaded in several

steps. At each loading stage the change of the height

was recorded at suitable intervals while consolidation

takes place. At the end of the test, the final dial gauge

readings were taken. After removing the dial gauge

and the top plate, the measurements of the final height

of the specimen were determined by the calipers.

Immediately after that, the free water was removed

from the soil surface and specimen weighed. The

water content and void ratio were then determined.

The compressibility and cohesive values were

compared with the guidelines proposed by Bell

(2007).


85


4.1. 2D Resistivity and borehole logs

Results from the resistivity surveys show that much of

the subsurface beneath the site is underlain by a

simple nearly horizontal stratification which is

constituted essentially of clayey deposits. The

resistivity sections AA' to DD' (Figures 2, 4, 6 and 8)

generally shows alternation of Peaty Clay (<10 Ωm),

Silty Clay (approx 10 - 40 Ωm ) and Silty Sand (>40

Ωm) that completely submerged in water. These

materials are viewed as incompetent engineering

materials. Similar lithologies were delineated by

Oyedele et al. (2012), Adepelumi et al. (2009) and

Adepelumi and Olorunfemi (2000) using resistivity

measurements around the Lagos metropolis.

Considering the borehole lithology logs, two sets of

logs were observed. The first set having

predominantly clayey materials from ground surface

to the terminal depths of the boreholes at 30 m, while

the second set have more sandy contents within the

uppermost 10 m (Figures 3, 5, 7 and 9).

Fig. 1: Base Map of the Study Area.

Fig. 2: 2-D resistivity section along traverse AA'

Festus et al.



86

Fig. 3: Sections of Borehole Logs along traverse AA'

Fig. 4: 2-D resistivity section along traverse BB'

BH3 along traverse AA' (Figure 2) shows the

presence of silty sand between 4.5 m to 10 m which

was confirmed by the 2-D resistivity section. Though,

the 2 D shows that this layer is laterally continuous

but the resistivity of the silty sand greatly fluctuates

westward suggesting inhomogeneity (e.g at 55 – 90 m,

120 m) of the sandy material. This inhomogeneity

suggests changes in the quality and integrity of the

sandy material, implying unsuitability of the sandy

material for engineering foundation of a four storey

building.

Along traverse BB' (Figure 4), a BH6 at 40 m

mark encountered sandy materials at depth of about 9

m, indicating the presence of good founding medium

at that depth. However, the 2-D resistivity section

shows that the sandy medium which dipped steeply

easterly was replaced by peaty clay at 9 m so that it

was encountered at about 20 m. This is inimical to

engineering foundation.

Along traverse CC' (Figure 6), a borehole

drilled at lateral distance 90 m from the start of the

traverse (BH 8) appears to be underlain by sandy

materials from a depth of about 20 m, giving a wrong

notion of presence of good founding medium at that

depth. However, the 2-D resistivity section shows that

the sand medium is localized with much of the

subsurface beneath that traverse being constituted

essentially of clay materials.

Beneath traverse DD' (Figure 8), BH 10 and

BH 11 encountered peaty clay and silty sand

materials respectively at the shallow depth which are

in turn underlain by sandy/silty clay. The 2-D section

along this traverse shows that the sandy materials at

shallow depth beneath BH 11 is localized and lacks

lateral continuity and thus incongruous to bear

uniform load. The lateral continuity of silty sand at

about 25 m depth cannot be ascertained due to

discontinuity of data sets.


87

Fig. 5: Sections of Borehole Logs along traverse BB'

Fig. 6: 2-D resistivity section along traverse CC'

Fig. 7: Sections of Borehole Logs along traverse BB'.

Festus et al.



88

Fig. 8: 2-D resistivity section along traverse DD'

4.2. Laboratory Results

Laboratory testing results obtained from multistage

triaxial compression and oedometer consolidation

tests are shown in tables 1 and 2 respectively.

4.3. Undrained Triaxial Compression Tests

Following the triaxial compression tests carried out on

retrieved samples from the boreholes, strength

parameters were obtained. A range of cohesion

values of 35 kN/m2 - 75 kN/m

2 was obtained for these

samples which are indicative of soft, firm to stiff

clays. The values of angles of internal friction (5°-

13°) is quite high for clayey deposits but can be

attributed to the presence of sands and silts in the

essentially clayey deposit. These strength parameters

typify low strength founding materials up to 30m

which are unsuitable for a four storey building. This is

at variance with Oyedele et al (2011) which

established the presence of competent materials at

16m depth in the southeastern part of the study area.

The natural water content of the samples ranges from

29.3% - 64.5%. These high values are due to

submergence of all materials in water because

groundwater level was encountered at 0.10 m from the

boreholes. This factor will contribute to the weakness

of the subsurface materials. Furthermore, considering

the essentially clayey nature of the subsurface

materials, settlement rate for structures placed on such

high water content material is expected to be high.

The bulk density result varies from 1.652 – 1.972

Mg/m3 which pinpoint a slightly compacted clayey

material.


89

Table 1: Result of Multistage Triaxial Compression Test.

Table 2: Result of Oedometer Consolidation Test

Considering the cohesion and angle of internal

friction obtained from triaxial tests, the computed net

allowable bearing capacity of the soils within the

uppermost 1.2 m was found to be 50 kN/m2 without

using a safety factor of 3, this is grossly inadequate

for a four-floor building with an estimated load of 50

kN/m2.

4.4. Oedometer Consolidation Test

This coefficient of volume compressibility varies

between 0.115 m2/MN and 0.666 m

2/MN an indicative

of medium to high compressibility. Therefore such

materials will be unable to bear a four storey building.

The initial void ratio and consolidation coefficient

varies between ranges from 0.779 - 1.381 and 2.7

m2/year - 8.3 m

2/year on the pressure range of 0 to

400 kN/m2 respectively. Although settlement in

clayey materials may be slow because they drain

slowly, the settlement (subsidence) in the study area

will be eventually be large due to high initial void

ratio and consolidation coefficient. The estimated

settlement values obtained for the proposed four-floor

building using typical single and double wings range

from 80 to 192 mm and 114 to 273 mm respectively.

Festus et al.



90

These settlement values are far higher than the

tolerable limit of 50 mm for raft (shallow) foundation.

5. CONCLUSIONS

Geophysical method integrated with field and

laboratory geotechnical testing have shown that

electrical resistivity correlate well with engineering

strength parameters of the subsurface soils of a

proposed four storey building site. 2-D resistivity

sections proved useful in providing information

continuity between borings, depth and position of

changes in strata over large area and reduced the

number of boreholes necessary. The sections revealed

incompetent founding materials beneath the study

area. Laboratory tests conducted on the materials

obtained from boreholes at the site indicated materials

of grossly inadequate net allowable bearing capacity

and estimated settlement values that are higher than

the tolerable limit for the proposed four-floor

building. Therefore, the results of the various

investigations conducted in the study area prohibit the

use of conventional shallow foundation, piles or

vibro-replacement up to a depth of 30 m. It is

recommended that, for the proposed load, further

investigations be carried out by drilling more test

boreholes beyond 30 m with a view to establish the

strata with adequate bearing capacity.

REFERENCES

Adepelumi AA, Olorunfemi MO, Falebita DE,

Bayowa, OG (2009). Structural mapping of

coastal plain sands using engineering

geophysical technique: Lagos Nigeria Case

Study. Natural Science, 1: 2-9.

Adepelumi AA, Olorunfemi MO (2000). Engineering

geological and geophysical investigation

investigation of the reclaimed Lekki Peninsula,

Lagos, Southwest Nigeria. Bulletin of

Engineering, Geology and the Environment, 58:

125-132.

Bell FG (2007). Engineering Geology. Second

Edition. Elsevier Ltd. Oxford, U.K. 222, 223.

Bishop AW, Henkel DJ (1962). The measurements of

soil properties in the triaxia test. 2nd

edition

Edward Arnold (Publishers) LTD., London.

Brownfield ME, Charpentier RR (2006). Geology and

total petroleum systems of the West Central

Coastal Province (7203), W/Africa: U.S.

Geological Survey Bulletin 2207, 52 p.

BS1377 (1990) Method of test for soils for civil

engineering purposes. British Standards

Institution, London.

Head KH (1992). Manual of soil laboratory testing.

Vol. 3, effective stress tests, Wiley.

Kovari K, Tisa A, Einstein H, Franklin JA (1983).

Suggested methods for determining the

strength materials in triaxial compression. Int. J.

of Rock Mech. & Min. Sci. & Geomechs Abs.,

20: 283-290.

Loke MH (1997). RES2DINV ver. 3.3 for Windows

3.1, 95 and NT Advanced Geosciences Inc. 66

Obaje NG (2009). Geology and Mineral Resources of

Nigeria, Lecture Notes in Earth Sciences.

221p, Springer Dordrecht Heidelberg London

New York.

Oyedele K.F, Ayolabi EA, Adeoti L, Adegbola RB

(2009). Geophysical and Hydrogeological

Evaluation of Rising Groundwater Level in the

Coastal Areas of Lagos, Nigeria. Bull. Eng.

Geol. Environ. , 68: 137 - 143.

Oyedele KF, Oladele S, Adedoyin O (2011).

Application of Geophysical and Geotechnical

Methods to Site Characterization for

Construction Purposes at Ikoyi, Lagos, Nigeria.

Journal of Earth Sciences and Geotechnical

Engineering, 1(1): 87-100

Oyedele KF, Oladele S, Okoh C (2012). Geoassement

of Subsurface Conditions In Magodo Brook

Estate, Lagos Nigeria. International journal

of advanced scientific and technical research,

2(4): 731-741

Rowe RK (2001). Geotechnical and

Geoenvironmental Engineering Handbook,

Kluwer Academic Publishing, Norwell,

Mass., USA. 82.

Soupios P, Georgakopoulos P, Papadopoulos N,

Saltas V, Vallianatoss F, Sarris A, Makris J

(2007). use of engineering geophysics to

investigate a site for a building foundation. J.

Geophys. Eng, 4: 94-103.

Sheriff RE (2002). Encyclopedic Dictionary of

Applied Geophysics, Fourth Edition. The

Society of Exploration Geophysicists (S.E.G)

Tulsa OK USA. 323.


91

DR Oyedele Kayode Festus, He is an Associate Professor. He is interested in Groundwater Exploration,

Geotechnical Investigation, Environmental Pollution, Petroleum Geophysics researches.

Dr. Lukumon Adeoti, He is a Senior Lecturer. He received his BS degree in Applied Physics-

Geophysics, 1997. He received his MSc degree in Exploration Geophysics, 2000. Also He received PhD

degree in Geophysics, 2007. He is interested in Exploration Geophysics / Borehole Geophysics.

Oladele Sunday, He is an Assistant Lecturer. He received MSc degree in Applied Geophysics. He is

interested in Petroleum geophysics, forensic geophysics, Earth imaging and modeling.



ISSN: 2322-4541; ©2014 IJSRPUB


92


Nutritional and Anti-Nutritional Composition of Bridelia Ferruginea Benth

(Euphorbiaceae) Stem Bark Sample

Adesina Adeolu Jonathan1*

, Akomolafe Seun Funmilola2

1Department of Chemistry, Ekiti State University, PMB 5363, Ado Ekiti, Nigeria

2Department of Biochemistry, Ekiti State University, PMB 5363, Ado Ekiti, Nigeria

*Corresponding Author: Email: [email protected]


Abstract. Nutritional composition of Bridelia ferruginea Benth (Euphorbiaceae) stem bark sample was evaluated. The

percentage protein, fat, fibre and carbohydrate contents were: 15.7 ± 0.30, 5.45± 0.05, 4.35 ± 0.06 and 60.7 ± 0.71 respectively

while the total gross energy was 1501kJ/100g. The mineral composition ranged from 0.25 to 74.2 mg/100g, with phosphorus

being the most concentrated. The K/Na ratio (1.80) was higher than 1.0 recommended. The mineral safety index computation

showed only Zn to be in excess based on the recommended daily allowance (RDA). The amino acid contents ranged between

0.597 – 13.1 g/100g. All the essential amino acids were present in varying amount with Isoleucine being the most

concentrated. The % TEAA and % TNEAA were: 47.8 and 52.2 respectively. The P-PER (predicted protein efficiency ratio),

pI (Isoelectric point) and EAAI (essential amino acid index) values were: 1.69, 5.14, 1.18 respectively. Based on the whole

hen’s egg amino acid scoring pattern, methionine was limiting while with respect to FAO/WHO provisional amino acid

scoring pattern and essential amino acid scoring pattern based on the requirements of pre-school child Met + Cys was limiting.

The anti-nutritional factors analyzed; phytates, tannins, oxalates, phenolic content, saponins, phytin phosphorus and alkaloids

in the sample were lower than the range of values reported for most vegetables. This study revealed that the Bridelia

ferruginea stem bark consumed in Ekiti State and other states in the South-western part of Nigeria can contribute useful

amount of nutrients to human diet.

Keywords: Nutritional, anti-nutritional composition, Bridelia ferruginea stem bark

1. INTRODUCTION

Forage trees and shrubs play an essential and multiple

roles in the balance of the Sahelian and Sudanian

ecosystems exploited by man and his animals. This

role becomes more important as the dry season grows

longer, and decreases as the mean annual rainfall

increases. It therefore grows less important from north

to south according to the rainfall gradient, which is

about 1 mm per km, or 110 mm per each degree of

latitude. Throughout West Africa, especially in areas

prone to drought, previous studies demonstrate the

importance of edible wild plants as food sources

(Grivetti et al., 1987; Sena et al., 1998). Commonly,

drought is associated with inadequate food intake and

disease, where food scarcity and inadequate dietary

intakes clearly have led to increased incidence of

malnutrition and famine (Franke and Chasin, 1980).

Use of edible wild species in combination with

domesticated foods has remained a hallmark of many

African agro-pastoral societies (Grivetti, 1978, 1979;

Grivetti et al., 1987). Traditional medicine practiced

in rural Nigeria, reveals well-documented uses of

plant barks and bark extracts, fruits, leaves, nuts and

seeds, and tubers, but with few exceptions, dietary-

medical uses of edible wild plants as components of

West African traditional medicine have not been

widely documented (Ogugbuaja et al., 1997).

Bridelia ferruginea Benth (Euphorbiaceae) is a

medicinal plant that is widely used in African

folkloric medicine. In Nigeria, it is commonly called

Kirni, Kizni (Hausa); Marehi (Fulani); Iralodan

(Yoruba), Ola (Igbo), Kensange abia (Boki). Its

habitat is the savannah especially in the moister

regions extending from Guinea to Zaire and Angola.

The tree is 6-15m high, up to1.5m in girth and bole

crooked branching low down. The bark is dark grey,

rough and often markedly scaly (Kolawole and

Olayemi, 2003). The stem bark decoction is used in

African traditional medicine to treat diarrhea,

dysentery and gynaecological disorders (including

sterility). A decoction of the leaves is used to treat

diabetes. It has even been evaluated for antimalarial

(Kolawole and Adesoye, 2010), antimicrobial

Jonathan and Funmilola

Nutritional and Anti-Nutritional Composition of Bridelia Ferruginea Benth (Euphorbiaceae) Stem Back Sample

93

(Kareem et al., 2010), analgesic (Akuodor, et al.,

2011) and antidiabetic (Bakoma et al., 2011)

activities. B. ferruginea bark is used for treatment of

bacterial infections on wounds (Irobi et al., 1994). A

decoction of the leaves is used as a purgative and also

in the treatment of diabetes (Cimanga et al., 1999).

Roots and leaves extracts are used to cure piles,

diarrhea and dysentery (McNeely, 1990) and also

confirmed for anti-inflammation activities (Olajide et

al., 1999). Galocatechin has been isolated from the

bark (De Bruyne et al., 1997).

In western Nigeria, B. ferruginea is used as a

mouthwash and remedy for candidal oral thrush;

whereas in Northern Nigeria, the bark is used for

treatment of infections caused by poisoned arrow

wounds (Irobi et al., 1994). A decoction of the bark

extract has also been proven to have antibacterial

effect (Kolawole et al., 2006). It is also used as

purgative and a vermifuge. A macerated extract of the

bark is used in Northern Nigeria to harden beaten

laterite and mud floors (Kolawole and Olayemi,

2003). The chemical constituents of Bridelia

ferruginea have not been thoroughly examined. The

present study is therefore aimed at exploiting the

proximate, minerals, anti-nutritional and amino acid

profile of the back of Bridelia ferruginea as this

would promote its dietary-medical uses.

2. MATERIAL AND METHODS

2.1. Collection and preparation of samples

The sample was collected from local farms around

Iworoko- Ekiti, Irepodun-Ifelodun local Government

area of Ekiti State. It was properly sorted, washed,

dried, milled into fine powdered form and kept in an

air-tight plastic bottle prior to analysis.

2.2. Proximate analysis

Moisture, total ash, fiber and ether extract of the

samples were determined by the methods of the

AOAC 2005. Nitrogen was determined by a micro-

Kjeldahl method and the crude protein content was

calculated as N x 6.25 (Pearson, 1976). Carbohydrate

was determined by difference. All the proximate

results were reported in g/100 g dry weight. The

energy values obtained for carbohydrates (x 17 kJ),

crude protein (x 17 kJ) and crude fat (x 37 kJ) for each

of the samples. Determinations were in duplicate.

Table1: Proximate and some calculated parameters in the sample of Bridelia ferruginea stem bark

PEP = Proportion of total energy due to protein

PEF = Proportion of total energy due to fat PEC = Proportion of total energy due to protein

UEDP = Utilizable energy due to protein

2.3. Mineral analysis

The mineral elements were determined in the

solutions obtained above-Na and K by flame

photometry, Model 405 (Corning, Halstead Essex,

UK) using NaCl and KCl to prepare standards.

Minerals were analysed using the solutions obtained

by dry ashing the samples at 550 oC and dissolving it

in 10 % HCl (25 ml) and 5 % lanthanum chloride (2

ml), boiling, filtering and making up to standard

volume with deionized water. Phosphorus was

determined colorimetrically using a Spectronic 20

(Gallenkamp, London, UK) instrument, with KH2PO4

as a standard. All other elements (Ca, Mg, Zn, Fe, Mn,

Cu and Cr) were determined by atomic absorption

spectrophotometry, Model 403 (Perkin-Elmer,


94

Norwalk, Connecticut, USA). All determinations were

made in duplicate. All chemicals used were of

analytical grade, and were obtained from British Drug

House (BDH, London, UK).

The detection limits for the metals in aqueous

solution had been determined just before the mineral

analyses using the methods of Varian Techtron, giving

the following values in µg/ml: Fe (0.01), Cu (0.002),

Na (0.002), K(0.005), Ca(0.04), Mg(0.002), Zn

(0.005), Mn (0.01) and Cr (0.02) (Varian Techtron,

1975). The optimal analytical range was 0.1 to 0.5

absorbance units with coefficients of variation from

0.9-2.2 %.

The coefficients of variation per cent were

calculated (Steel and Torrie, 1960). The percentage

contribution to energy due to protein (PEP), due to

total fat (PEF) and due to carbohydrate (PEC) as PEP

%, PEF % and PEC % respectively were calculated.

The percentage utilizable energy due to protein

(UEDP %) was also calculated. Ca/P, Na/K, Ca/Mg

and the millequivalent ratio of [K/(Ca +Mg)]; the

mineral safety index (MSI) of Na, Mg, P, Ca, Fe and

Zn were also calculated (Hathcock, 1985). To

calculate MSI, we have: RAI is recommended adult

intake; CV in the Table will represent calculated value

(CV) of calculated MSI from research results. The

differences between the standard MSI and the MSI of

the samples were also calculated.

2.4. Determination of Anti-nutritional factors

2.4.1. Determination of tannin

200mg of the sample was weighed into a 50ml sample

bottle. 10ml of 70% aqueous acetone was added and

properly covered. The bottles were put in an orbital

shaker and shaken for 2 hours at 300C. Each solution

was then centrifuged and the supernatant stored in ice.

0.2ml of each solution was pipetted into test tubes and

0.8ml of distilled water was added. Standard tannic

acid solutions were prepared from a 0.5mg/ml stock

and the solution made up to 1ml with distilled water.

0.5ml folin reagent was added to both sample and

standard followed by 2.5ml of 20% Na2CO3. The

solutions were then vortexed and allowed to incubate

for 40 minutes at room temperature after which

absorbance was red against a reagent blank

concentration of the sample from a standard tannic

acid curve (Makkar and Goodchild, 1996).

Table 2: Composition and some calculated mineral ratios in the Bridelia ferruginea bark sample

*milliequivalent ratio

2.4.2. Determination of oxalate

1g of the sample was weighed into 100ml conical

flask. 75ml of 1.5N H2SO4 was added and the solution

was carefully stirred intermittently with a magnetic

stirrer for about 1 hour and then filtered using

Whatman filter paper. 25ml of sample filtrate was

collected and titrated hot (80-900C) against 0.1N

KMnO4 solution to the point when a faint pink colour

appeared that persisted for at least 30 seconds (Day

and Underwood, 1986).

2.4.3. Determination of alkaloid

Alkaloid determination was carried out following the

procedure of Harborne(Harborne, 1973). 5.0g of the



95

sample was weighed into a 250ml beaker and 200ml

of 10% acetic acid in ethanol was added and covered

and allowed to stand for 4h. This was filtered and the

extract was concentrated on a water bath to one

quarter the original volume. Concentrated ammonium

hydroxide was added drop wise to the extract until the

precipitation was complete. The whole solution was

allowed to settle and the precipitate was collected and

washed with dilute ammonium hydroxide and then

filtered. The residue is the alkaloid which was dried

and weighed.

2.4.4. Determination of saponin

The method used was that of Obadoni and Ochuko,

2001). 5g of the sample was put into a conical flask

and 100cm3 of 20% aqueous ethanol were added. The

sample was heated over a hot water bath for 4h with

continuous stirring at about 550C. The mixture was

filtered and the residue re-extracted with another

200ml 20% ethanol. The combined extracts were

reduced to 40ml over water bath at about 900C. The

concentrate was transferred into a 250ml separating

funnel and 20ml of diethyl ether was added and

shaken vigorously. The aqueous layer was recovered

while the ether layer was discarded. The purification

process was repeated. 60ml n-butanol was added. The

combined nbutanol extracts were washed twice with

10ml of 5% aqueous sodium chloride. The remaining

solution was heated in a water bath after evaporation;

the sample was dried in the oven to a constant weight.

The saponin content was calculated as percentage.

2.4.5. Determination of flavonoid

The method of Boham and Kocipai-Abyazan (Boham

and Kocipai-Abyazan, 1974) was followed in the

determination of flavonoid. 5g of the sample was

extracted repeatedly with 100ml of 80% aqueous

methanol at room temperature. The whole solution

was filtered through whatman filter paper (125ml).

The filtrate was later transferred into a crucible and

evaporated into dryness and weighed to a constant

weight.

2.4.6. Oxalate determination

The titration method as described by Day and

Underwood (1986) was followed. 1g of sample was

weighed into 100 ml conical flask. 75 ml 3M H2SO4

was added and stirred for 1 h with a magnetic stirrer.

This was filtered using a Whatman No 1 filter paper.

25 ml of the filtrate was then taken and titrated while

hot against 0.05 M KMnO4 solution until a faint pink

colour persisted for at least 30 s. The oxalate content

was then calculated by taking 1ml of 0.05 M KMnO4

as equivalent to 2.2 mg oxalate (Chinma and Igyor,

2007; Ihekoronye and Ngoddy, 1985).

2.4.7. Phytate content determination

This was determined by the method of Wheeler and

Ferrel (1971).100 ml of the sample was extracted with

3% trichloroacetic acid. The extract was treated with

FeCl3 solution and the iron content of the precipitate

was determined using Atomic Absorption

spectrophotometer (Pye Unicam 2900). A 4:6 Fe/P

atomic ratio was used to calculate the phytic acid

content (Okon and Akpanyung, 2005). Phytin

phosphorus (Pp) was determined and the phytic acid

content was calculated by multiplying the value of Pp

by 3.55 (Young and Greaves, 1940). Each milligram

of iron is equivalent to 1.19 mg of Pp.

Phytin phosphorus as percentage of phosphorus (Pp %

P) = Pp/P × 10

2.5. AMINO ACID ANALYSIS

The amino acid profile was determined using the

method described by Sparkman et al. (1958). Each

sample was dried to constant weight, defatted,

hydrolyzed, evaporated and loaded into the techno

sequential multi-sample amino acid analyzer (TSM).

Following the steps described below: 2 g of the dried

sample was weighed into extraction thimble and the

fat extracted with chloroform: methanol (2:1) mixture

using soxhlet extraction apparatus (AOAC, 2005).

Then, 1 g of the defatted sample was weighed into

glass ampoule. 7 ml of 6 N HCl were added and

oxygen expelled by passing nitrogen into the ampoule.

The glass ampoule was sealed and placed in an oven

preset at 1050C for 22 h. The ampoule was allowed to

cool before breaking open at the tip and the content

filtered. The filterate was then evaporated to dryness

and the residue dissolved with 5 ml acetate buffer (pH

2.0) and stored in plastic specimem bottles. 10 μl was

dispensed into the cartridge of the analyser which is

designed to seperate andanalyse free, acidic, neutral

and basic amino acids of the hydrolysate. The amount

of each amino acid present in the sample was

calculated in g/100 g protein from the chromatogram

produced.


96

Table 3: Mineral safety index of Na, Mg, P, Ca, Fe, and Zn for the Bridelia ferruginea stem bark sample

TV = table value, CV = calculated value

D = difference (TV - CV)

Table 4: Anti-nutritional content of the Bridelia ferruginea stem bark samples

2.5.1. Determination of quality parameters

2.5.1.1. Determination of amino acid scores

Determination of the amino acid scores was fir

st, based on whole hen’s egg (Paul et al., 1976). In

this method, both essential and nonessential amino

acids were scored. Secondly, amino acid score was

calculated using the following formula (FAO/WHO,

1973):

Amino acid score = (amount of amino acid per test

protein (mg/g)) / (amount of amino acid per protein in

reference pattern (mg/g)).

In this method, Met + Cys and Phe + Tyr were

each taken as a unit. Also, only essential amino acids

determined were scored. Amino acid score was also

calculated based on the composition of the amino

acids obtained in the samples compared with the

suggested pattern of requirements for pre-school

children (2-5 years). Here, Met + Cys and Phe + Tyr

were each taken as a unit. Also, only essential amino

acids with (His) were scored.

2.5.1.2. Determination of the essential amino acid

index

The essential amino acid index (EAAI) was calculated

by using the ratio of test protein to the reference

protein for each of the eight essential amino acid plus

histidine in the equation that follows (Steinke et al.,

1980):

Methionine and cystine are counted as a single amino

acid value in the equation, as well as Phe + Tyr.

2.5.1.3. Determination of the predicted protein

efficiency ratio

The predicted protein efficiency ratio (P-PER) was

determined using one of the equations derived by

Alsmeyer et al. (1974), i.e.

P-PER = –0.468 + 0.454 (Leu) – 0.105 (Tyr).

2.5.1.4. Other determinations

Determination of the total essential amino acid

(TEAA) to the total amino acid (TAA), i.e.

(TEAA/TAA); total sulphur amino acid (TSAA);

percentage cystine in TSAA (% Cys/TSAA); total

aromatic amino acid (TArAA), etc; the Leu/Ile ratios

were calculated while the isoelectric point (pI) was

calculated using the equation of the form

(Olaofe and Akintayo, 2000):



97

pIm IPiXi

Where pIm is the isoelectric point of the mixture of

amino acids, IPi is the isoelectric point of the ith amino

acid in the mixture and Xi is the mass or mole fraction

of the ith amino acid in the mixture (Finar, 1975).

Table 5: Amino acids profile of the Bridelia ferruginea

bark samples (g/100g cp)

3. RESULTS AND DISCUSSION

The results of proximate composition of the Bridelia

ferruginea back sample are shown in Table 1. The

crude protein content (15.7 ± 0.30 %) was comparably

higher than the values reported for some vegetables

consumed in Nigeria: 5.91 % (Cnidoscolus

chayamansa), 3.31 % (Solanium nodiflorum), 3.03 %

(Senecio biafrae) (Adeleke and Abiodun, 2010);

4.60% (A. hydridus), 4.30 % (T. occidentallis)

(Fafunso and Basir, 1977) but favourably compared

with the values reported for C. maxima (18.6 %), A.

viridis (19.2 %) and B. alba (18.0%) (Adesina, 2013)

and S. indicum (18.59%), B.aegypiaca (15.86 %)

(Kubmarawa et al., 2008).

The ash content (6.54 %) of Bridelia ferruginea

back sample is an indication of the levels of minerals

or inorganic component of the sample. These minerals

act as inorganic co-factors in metabolic processes

which mean in the absence of these inorganic co-

factors there could be impaired metabolism

(Iheanacho and Udebuani, 2009). Table 1 still

contains other parameters calculated from the

proximate values. It shows the various energy values

as contributed by protein, fat and carbohydrate. The

daily energy requirement for an adult is between

2500-3000 kCal (10455-12548 kJ) depending on his

physiological state while that of infants is 740 kCal

(3094.68 kJ) (Bingham, 1978). This implies that while

an adult man would require between 590-709 g

(taking the calculated energy of 1501 kJ/100 g) of his

energy requirement, infants would require 174.9 g

(taking the calculated energy of 1501 kJ/100 g). On

the whole this meant that samples with higher energy

value would require lower quantity of sample to

satisfy the energy needs of man and infants. The

utilizable energy due to protein (UEDP %) for the

sample (assuming 60 % utilization) 10.7 %. The

UEDP % compared favourably with the recommended

safe level of 8 % for an adult man who requires about

55 g protein per day with 60 % utilization. The PEF %

values were generally low in the sample (13.4 %) and

far below the recommended level of 30 % (NACNE,

1983) and 35 % (COMA, 1984) for total fat intake;

this is useful for people wishing to adopt the

guidelines for a healthy diet.

Table 6: Concentrations of essential, non-essential, acidic,

neutral, sulphur, aromatic, basic, etc. (g/100g crude protein)

of Bridelia ferruginea stem bark samples (dry matter of

sample)


98

Table 2 gives the list of the nutritionally important

minerals as well as the computed mineral ratios in

Bridelia ferruginea back sample. Minerals are

important in human nutrition. It is well known that

enzymatic activities as well as electrolytic balance of

the blood fluid are related to the adequacy of Na, K,

Mg and Zn. Potassium is very important in

maintaining the blood fluid volume and osmotic

equilibrium. Metal deficiency syndrome like rickets

and calcification of bone is caused deficiency.

Appreciable levels of all the essential minerals were

present in the the sample. The sample was apparently

high in phosphorus (74.2 ± 0.105 mg/100g), a value

which was comparably higher than what was reported

for F. asperifolia and F. sycomorus (Nkafamiya et al.,

2010). The levels of K, Na, Ca and Mg were

comparably higher than Mn and Cu levels. The Ca/P

(0.326) was comparably lower than 0.5 which is the

minimum ratio required for favourable calcium

absorption in the intestine for bone formation

(Nieman et al., 1992) although the level of Ca/P has

been reported to have some effects on calcium in the

blood of many animals (Adeyeye et al., 2012). The

value of ratio (0.556) was lower than 0.6, the value

that favours non-enhancement of high blood pressure

disease in man. Although for normal retention of

protein during growth and for balancing fluid a K/Na

ratio of 1.0 is recommended (Helsper et al., 1993), the

high value of K/Na ratio (1.80) obtained in the present

report suggests that bringing the ratio down would

require the consumption of food sources rich in Na.

the Ca/Mg value obtained for the present sample

(1.14) was fairly higher than the 1.0 recommended. It

means both that both Ca and Mg would need

adjustment for normal for normal health.

The milliequivalent ratio of [K/(Ca+Mg)] (1.31)

was comparably lower than 2.2 recommended, which

means the sample would not promote

hypomagesaemia in man (NRC, 1989; Adeyeye and

Adesina, 2012). Iron and Zinc are among the required

elements for humans and their daily requirements for

adults are 10 and 15 respectively. Levels obtained in

the present report (4.55 ± 0.02 mg/100g) (Fe) and 25.7

mg/100g (Zn)) compared favourably with the values

reported for F. asperifolia and F. sycomorus

(Nkafamiya et al., 2010). However zinc requirements

can easily be met by consuming this sample (25.7

mg/100g). Generally from the recommendation set out

by NRC/NAS, the daily requirement of Zn, Mn and

Cu can easily be met while the diets may need be

supplemented with foods high in K, Na, Ca and P.

The mineral safety index (MSI) values of the

sample are shown in Table 3. The standard MSI for

the elements are Na (4.8), Mg (15), P (10), Ca (10), Fe

(6.7) and Zn (33). For Ca, P, Mg, Fe, Cu and Na, the

MSI values ranged from 0.16 – 2.75, with all the

differences between the standard and calculated MSI

values being positive.

Let us take Na for an example, the calculate MSI

value is 0.16 and the difference is +4.64, this meant

that no amount of the sample might be overloading

the body with sodium that can lead to secondary

hypertension. For Ca, Mg and P all the calculated MSI

were lower than standard MSI and hence within the

USRDA (Hathcock, 1985). For Zn, the odd sample

out, was 56.5 and the difference was -23.5. The

implication of the above is that abnormally high level

Zn was present in the sample. The sample could cause

the reduction of Zn absorption in the small intestine in

children. The Zn MSI greater than 33 are above the

recommended adult intake. The minimum toxic dose

is 500 mg, or 33 times the RDA (Hathcock, 1985).

High doses of Zn can be harmful. Zinc supplements

can decrease the amount of high density lipoprotein

(HDL) circulating in the blood, increasing risk of

heart disease. Excess Zn interacts with other minerals,

such as Cu and Fe, decreasing their absorption. In

animals, Zn supplements decrease the absorption of

Fe so much that anaemia is produced (Adeyeye et al.,

2012).When patients are given 150 mg of Zn per day,

Cu deficiency results. Intakes of Zn only 3.5 mg/day

above the RDA decrease Cu absorption (Nieman et

al., 1992). In animals, Cu deficiency causes scarring

of the heart muscle tissue and low levels of Ca in the

bone (Adeyeye et al., 2012).

The antinutrient content of the sample are listed in

Table 4. These are compounds that limit the wide use

of many plants due to their ubiquitous occurrence of

them as natural compounds capable of eliciting

deleterious effect in man and animals (Kubmarawa et

al., 2008).

The antinutrient factors; oxalate, tannin, saponin,

phytate, alkaloids, phenolic content, phytin

phosphorus and flavonoids were present in varying

amounts in the sample.

These anti nutritional factors tend to bind to

mineral elements there by forming indigestible

complex (Nkafamiya and Manji, 2006). Oxalate for

instance tends to render calcium unavailable by

binding to the calcium ion to form complexes

(calcium oxalate crystals). These oxalate crystal

formed prevent the absorption and utilization of

calcium. The calcium crystals may also precipitate

around the renal tubules thereby causing renal stones

(Ladeji et al., 2004; Nkafamiya and Manji, 2006). In

general the levels of antinutrients in Bridelia

ferruginea bark sample are low to significantly

interfere with nutrients utilization. They are below the

established toxic level (Nkafamiya and Manji, 2006).

The amino acid profile of the Bridelia ferruginea

back sample is shown in Table 5. The levels of the



99

amino acid ranged between 0.597 ± 0.001 – 13.1±

0.450 g/100g.

All the essential amino acids were present in the

sample, with Isoleucine having the highest

concentration (6.20 ± 0.014 g/100g).

Table 6 shows the concentrations of total AA

(TAA), total essential AA (TEAA), total acidic AA

(TAAA), total neutral AA (TNAA), total sulphur AA

(TSAA), total aromatic AA (TArAA) and their

percentage values. The Leu/Ile ratios, their differences

and percentage differences are contained in Table 6.

Non- essential amino acids have the highest %

concentration (52.2) while TEAA total essential

amino acids had a % concentration of 47.8. The

content of TEAA of 43.1 g/100g crude protein was

close to the value for egg reference protein (56.6

g/100g cp) (Paul et al., 1976); comparably close to the

values reported for soya bean (44.4 g/100g cp)

(Altschul, 1958).

The TAA in the current report was 90.1 g/100g cp,

this value was comparably close to the values of

reported for the dehulled African yam bean (AYB)

(70.3 – 91.8 g/100g cp) (Adeyeye, 1997) but

comparably higher than the values reported for raw

and processed groundnut seeds (Adeyeye, 2010). The

content of TSAA (1.42 g/100g) was lower than the 5.8

g/100g cp recommended for infants

(FAO/WHO/UNU, 1985) The ArAA range suggested

for ideal infants protein (6.8 – 11.8 g/100g cp )

(FAO/WHO/UNU, 1985), the present report has its

value better than the minimum, i.e 8.96 g/100g cp.

The ArAA are the precursors of epinephrine and

thyroxin (Robinson, 1987). The % ratios of TEAA/

TAA in the sample was 47.8 % which was well above

39 % considered to be adequate for ideal protein food

for infants ; 26 % for children and 11 % for adults

(FAO/WHO/UNU, 1985). The TEAA/ TAA was

strongly comparable to that of egg (50 %)

(FAO/WHO, 1990), and 43.6 % reported for pigeon

pea flour (Oshodi et al., 1993).

Most animal protein are low in Cys and hence in

Cys in TSAA (Adeyeye and Adamu, 2005). In

contrast many vegetable proteins contain substantially

more Cys than Met. The reverse is the case in the

present in which the % Cys in TSAA was 42.0 %.

Information on the agronomic advantages of

increasing the concentration of sulphur-containing

amino acid in staple foods shows that Cys had

positive effects on mineral absorption, particularly

zinc (Mendoza, 2002).

The P-PER value (1.69) was higher than 1.21

(cowpea), close to (Salunkhe and Kadam, 1989); 1.62

(millet ogi) and 0.27 (sorghum ogi) (Oyarekua and

Eleyinmi, 2004). A common feature of sorghum and

maize is that the proteins of these grains contain a

relatively high proportion of leucine. It was therefore

suggested that an amino acid imbalance from excess

leucine might be a factor in the development of

pellagra (FAO, 1995). Clinical, biochemical and

pathological observations in experiments conducted in

humans and laboratory animals showed that high

leucine in the diet impairs the metabolism of

tryptophan and niacin and is responsible for niacin

deficiency in sorghum eaters (Ghafoorunissa and

Narasinga Rao, 1973). High leucine is also a factor

contributing to the pellagragenic properties of maize

(Belavady and Gopalan, 1969). These studies

suggested that the leucine/isoleucine balance is more

important than dietary excess of leucine alone in

regulating the metabolism of tryptophan and niacin

and hence the disease process. The present Leu/Ile

ratios were low in value. The pI value was 5.14. The

pI of any organic matter is important when the protein

isolate is to be prepared. The EAAI can be useful as a

rapid tool to evaluate food formulations for protein

quality. The EAAI for soy flour is 1.26 (Nielsen,

2002) which is better than the current result of 1.18.

Table 7 showed that Met had the lowest score with

a value of 0.26. to correct for the AA needs from the

sample, it becomes 100/26 or 3.85 times as much raw

sample protein to be taken (eaten) when they are the

sole source of protein in the diet (Bingham,1977). In

Table 8 two different scoring patterns were presented:

Scorea

= Essential amino acid scores based on

FAO/WHO (1973) scoring pattern, Scoreb

= Essential

amino acid scores based on requirements of pre-

school child (2-5 years)(FAO/WHO/UNU, 1985).

In both patterns Met + Cys had the lowest score

(limiting amino acid), with values 0.41 and 0.57. and

would need a correction of 100/41 or 2.44 according

to the essential amino acid scoring pattern 100/57 or

1.75 times as much raw sample protein to be taken

(eaten) when they are the sole protein in the diet

(Bingham, 1977).


100

Table 7: Amino acid score of the Bridelia ferruginea stem

bark samples based on whole hen's egg amino acid

4. CONCLUSION

This study has revealed that the Bridelia ferruginea

back consumed in Ekiti State and other states in the

South-western part of Nigeria can contribute useful

amount of nutrients including amino acids to human

diet. Interestingly, the anti-nutritional content of the

sample was low, much lower than is obtainable in

most Nigerian vegetables. This implies that, its overall

nutritional value will not be affected. Indeed, this part

of the plant consumed largely by the rural populace in

Ekiti State is not inferior to the conventional popular

Nigerian vegetables. There is need, however, to

determine the vitamins and fatty acids present in the

sample. Understandably, nutrient loss is of great

concern during blanching and cooking of vegetables,

therefore there is need to study the effects of cooking

and processing procedures on nutrient availability of

the Bridelia ferruginea back sample. This will help to

adequately establish their importance in human

nutrition and provide basis for maximum utilization of

the plant’s part.

Table 8: Essential amino acid scores of the Bridelia ferruginea stem bark samples

Scorea = Essential amino acid scores based on FAO/WHO (1973) scoring pattern, Scoreb = Essential amino acid scores based on requirements of pre-school

child (2-5 years)(FAO/WHO/UNU, 1985)

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104

Adesina, Adeolu, J. is a Ph.D candidate in Food/ Analytical Chemistry of the Department of

Chemistry, Ekiti State University, Ado Ekiti, Nigeria. He received his first degree from

University of Ilorin, Kwara State, Nigeria 2001 awarded with Bachelor of Science in Pure

Chemistry. He obtained degree in Master of Science in Analytical Chemistry from University of

Ibadan, Nigeria in 2006. His current research focuses on Food chemistry and quality. To date, he

has published several scientific journal articles related to Food chemistry and quality evaluation

field.

Akomolafe Seun Funmilola is a Ph.D candidate in Food biochemistry and toxicology of the

Department of Biochemistry, Federal University of Technology, Akure, Nigeria. She received her

first degree from Ekiti State University, Ado Ekiti Nigeria. 2005 awarded with Bachelor of Science

in Biochemistry. She obtained degree in Master of Science in Biochemistry from University of

Ibadan, Nigeria in 2009. Her current research focuses on Food Biochemistry and quality. To date,

she has published several scientific articles related to food Biochemistry and toxicology field.



ISSN: 2322-4541; ©2014 IJSRPUB


105


A Study on the Relationship between Accounting Conservatism and Earnings

Management in Teheran Stock Exchange Listed Companies

Abbas Ramezanzadeh Zeidi1*

, Zabihollah Taheri2, Ommolbanin Gholami Farahabadi

3

1Department of Accounting, Neka Branch, Islamic Azad University, Neka, Iran

2Department of Accounting, Payamenour University, Sari, Iran

3Department of Accounting, Payamenour University, Neka, Iran

*Corresponding Author: E-mail: [email protected]


Abstract. The present study focuses on the link between accounting conservatism and earnings management in Teheran Stock

exchange listed companies. To this aim, the researches selected a statistical sample consisting of 154 companies and gathered

statistical data for time period from 1385 to 1390. Using multiple variable combinational regressions, the researchers extracted

the proper research model and examined the research hypothesis. The models developed for conservatism and earnings

management were respectively book value to market value ratio of the stockholders' equity, and Jones's adjusted model.

Primarily, research findings indicated that the models are insignificant and a significant link between conservatism and

earnings management does not exist. However, when the researches fitted the examination based on logarithm of conservatism,

they found out that there is significant and negative link between conservatism and earnings management.

Keywords: conservatism, earnings management, discretionary accruals

1. INTRODUCTION

Regarded as the basic providers of companies'

resources, investors always require accurate and

comprehensive databases from the companies.

Accounting information appears in financial

statements and investors regularly refer to such

information without adjustingitto the changes in

accounting methods or the way those information

were calculated (Hendriksen et al., 1982). Income

statements are a key tool among the financial

statements for evaluating the performance as well as

the profitability of the business enterprise. The

information needs to be shared in a way that itenables

the investors to evaluate preceding performance and to

effectively assess and forecast the profitability of the

business enterprise. As a result, the profit reported in

the statements helps the investors evaluate the

performance and profitability of the firm and fulfill

their expectations about theiridealreturn profit.

Therefore, boththe reported profitand the qualitative

characteristics of the profit mean a lot to the investors

(Francis et al., 2004). Earnings management is a

means managers take advantage of to manipulate

reported profit. It is, in effect, a targeted interference

bypersonal motives of managers in the process of

financial reporting to the individuals outside the

business enterprise and is achieved by manipulating

the information of the current period. In other words,

managers let their personal judgments meddle in the

process of financial reporting and manipulate the

mechanism of transactions to make changes in the

financial reports.

Conservatism has been a controversial premise

from the outset and plays an important part in the

practice of Accounting. A conservative approach

defines a level of caution in forecasting the profit;

however, itdoes the same with the possible lossesonly

if it is risk-free for the upcoming cash flow. Preparing

conservative financial statements heightens reliability

of accounting data and indicates the ability of

accounting profit to illustrate financial profit (positive

dividend yield) and financial loss (negative dividend

yield). Conservative approach stresses on

distinguishing between positive and negative dividend

yield (financial profit and loss) (Basu, 1997). The

notions of profit management and conservatism in

accounting have other functions in financial reporting,

and each of them solely is capable of influencing

immensely the quality of financial reporting and

consequently the efficiency of capital market and also

the behavior of investors, creditors and in general the

Zeidi et al.

A Study on the Relationship between Accounting Conservatism and Earnings Management in Teheran Stock Exchange

Listed Companies

106

users of financial statements. Therefore, the

researchers believe that studying the correlation

between these two parameters can be a step forward

and contribute significantly to the literature on this

subject. The researchers seek to answer the following

questions: does conservatism in accounting procedure

have any influence on profit management? Is there

any correlation of any kind between conservatism and

profit management?

2. THEORETICAL FRAMEWORK AND

RELATED LITERATURE

2.1. Defining conservatism

Basu (1997) defines conservatism as the necessity to

gainhigh degree of certainty to differentiate between

desirable news e.g. profit from undesirable ones e.g.

loss. Such a definition views conservatism from a

profit/loss standpoint. However, other definitions

(Feltham and Ohlson, 1995) examine conservatism in

the balance sheets. Based on this, where there is an

actual uncertainty in selecting from among a number

of reporting methods, that method is preferable which

has the least desirable effect on the rights of the

shareholders. The third definition (Givoly and Hayn,

2000) combines the two aforementioned methods of

balance sheets and profit / loss. In this third approach,

conservatismis defined as an accounting notion and

results in a reduction in reported cumulated

dividendcaused by belated acknowledgement of profit

and prompt acknowledgement of expenses, low

evaluation of assets and high evaluation of debts.

Ryan (2006) draws another category to define

conservatism i.e. conditional and unconditional

conservatism. Conditional conservatism is obligated

by accounting standards. This translates into prompt

recognition of the losses in case of any undesirable

news and not acknowledging the profit in case of any

desirable news. For instance, applying the law of

minimum cost or that of net sales value in inventory

evaluation is an example of conditional conservatism,

also called profit / loss or retrospective conservatism.

On the other hand, unconditional conservatism is not

obligated by the widely accepted accounting

standards. This type of conservatism does not go

beyond indicating net book value of the assets through

traditional accounting procedures. It is also known as

balance sheet or futuristic conservatism.

2.2. Literature Review

Many studies have ever been conducted on topics

related to profit management and conservatism. Basu

(1997) studied the link between earnings and dividend

using regression to estimate the conservatism index.

He realized that in companies whose dividend yield is

negative, the dividend yield has higher correlation

with earnings compared with companies whose

dividend yield is positive. He also found out that in

periods of judicial and court trials, conservatism

increases. Watts and Zimmerman (1978) hold that

companies with higher political costs tend to apply

more conservative accounting procedures. Just to

prove this fact, Ahmed et al. (2002) showed that big

companies apply conservative accounting procedures

more than other companies. Their study also revealed

that in case of any discrepancies between the interests

of the loaners and those of the shareholders

concerning distribution of the income, the managers

of the borrowing companies are more likely to apply

conservative accounting procedures. He also

discovered that there is negative relation between

conservatism and profit management. In another study

(2007), Ahmed concludes that conservative

accounting discourages managers from investing on

projects with negative return.

In addition, Nikolav (2008) examined the relation

between conservative accounting and the limitations

of debt covenants. He found out that the more limited

the debt covenant is, the more the conservatism

grows. This fact had already been reached at in Ball et

al. (2007). Watts (2003), believes that if a company's

contract with different groups e.g. investors and

creditors should be based on accounting figures, then

the companies' managers, due to discrepancies

between their own interests and those of the groups,

will try to unfairly manipulate the figures in their own

favor. For example, they may increase the profit or

asset and on the other hand decrease the debts. In such

cases, conservatism, as an effective regular

mechanism, neutralizes the manager's unfair

manipulations by postponing the acknowledgement of

profit and helping a prompt recognition of the debt

and loss. In their research Zhou and Lebov (2006)

found out that companies that offer conservative

financial statement are able to handle profit

management more efficiently. However, as Zhou

discovered, such companies normally do not get

involved in earning management. Richardson (2005)

claims that accrual items have proven to be more

reliable and can predict loss and profits of the coming

year as well.

Bur Gestaller et al. (2006) concluded in their

research that private companies make bigger profits

compared with state-run companies and in countries

with more efficient judicial system, these companies

have a smaller share in profit management. Lafond

and Wattz (2007) showed that informational

asymmetry between aware and unaware investors

gives rise to conservatism in financial statements.

Conservatism lowers managers' motiveand ability to


107

manipulate accounting figures and consequently,

informational asymmetry and great losses it is

responsible for are reduced and the value of the

company increases. Moreover, in another study (2008)

Lafond and Watz pointed out that conservative

financial reporting is part of a regulation system that

makes managers less able to manipulate profit and to

raise cash flow in the company. Ball and Shivakumar

(2006) believe that once the managers realize that they

can no longer postpone loss recognition to the coming

years, they appreciate conservative accounting since it

helps solve potential issues and restricts company's

investments on projects with negative Net Present

Value (NPV).

3. THESIS HYPOTHESIS

Based on the primary studies that were already carried

out in the field, the hypothesis of the research is as

follows: There is a meaningful link between

accounting procedures and profit management

4. MTHODOLOGY

4.1. Statistical population and sample volume

Statistical population of the present research includes

Tehran Stock Exchange listed companies. The

statistical sample has been narrowed down using a

systematic omission method regarding the following

requirements:

(1) The business enterprise must not be an

investment company, a leasing company or a bank,

due to their field of activity

(2) The end of fiscal year of the business enterprise

must coincide the end of Esfand

(3) The business enterprise must not experience a

shift in fiscal year during the study period

(4) Financial data of the business enterprise must

be available during the study period

Considering these requirements, the researchers

selected 154 companies for a study period from 1385

until 1390.

4.2. Research Methodology

The present study is categorized as a descriptive-

explorative research. It studies the status quo and

describes it regularly trying to examine its different

features in relation to the variables. Such a research is

significant both for applied and theoretical areas. The

findings may well be put into use in decision and

policy making, and the explorations can contribute

substantially to theories since they have been reached

at through deductive methods.

4.3. Research parameters

4.3.1. Independent variable

In the present study profit management has been

considered as the independent variable. Based on the

study, the proper variable to indicate profit

management is the accrual items. These items may be

subcategorized into non-discretionary and

discretionary accrual items. The former is determined

by activity levels and is out of the control of the

managers; the latter is within the control of the

managers and may simply be manipulated. The

researchers hold that the residual of accrual items

model is a criterion of discretionary accrual items and

may be considered as profit management, meaning

that after estimating the model and ensuring that its

statistical qualities are effective, the residual amount

of the model is considered as profit management

variable. Dechow et al. (1995) and Guay et al. (1996)

argued that Jonse's adjusted model is the most

practical one among the existing models to estimate

discretionary accrual items. Because of this, the

researchers have applied this model in the present

study. The model is formulated as follows:

Where, TACit = total accruals for company i in year t;

TAit-1 = Lagged total asset for company I; ΔREVit =

change in operating revenues for company i in year t;

ΔRECit = change in net receivables for for company i

in year t; PPE it = gross property, plant and equipment

for company i in year t; α0j - α3j = regression

parameters; E = error term

4.3.2. Dependent variable

Conservatism is the dependent variable in this study.

According to other studies ever carried out on the

topic (Ahmed et al., 2002; Zang, 2007; Lebov et al.,

2008; Jean and Rezaee, 2004) the ratio of book value

to the market value of stockholders' interest has been

chosen to represent conservatism. Therefore, if the

ratio of book value to the market value of

stockholders' interest is less than one, then it can

indicate accounting conservatism.

Zeidi et al.


Listed Companies

108

4.3.3. Control variables

In this research, variables such as company size,

financial leverage and shareholders' dividend yield

have been used as control variables in an attempt to

control the effects of other factors. Zimmerman

(1983) states that, because of more political

sensitivities, bigger companies tend to apply

conservatism more than other companies. Previous

researches prove that we may use common logarithm

of total asset at the end of each fiscal period (Derashid

AND Zang, 2003) and also logarithm of the total sales

income (Zimmerman, 1983) as a criterion to measure

a company size. Since the total sales income has direct

effect on the profit, it can influence the results of the

study in a way that are not desirable, therefore, the

researchers have decided that common logarithm of

total asset at the end of each fiscal period is an

acceptable criterion to indicate the company size.

Besides, the study conducted by Chen et al. (2007)

proved that companies with lower profitability tend to

manage profits more cautiously and effectively.

Kowthari et al. also believe that discretionary accrual

items are connected with a company's performance

which was calculated and evaluated through Return on

Equity (ROE).

On the other hand, accounting methods relate to

financial leverage, since one of the essential criteria of

the creditors in Iran (banks mainly) is the company's

debt ratio. Therefore the higher the company's debt

ratio is, the less it tends to apply conservative

methods. As a result, managers are expected to apply

less conservative methods in their financial statements

in a bid to minimize the risk that their offer to receive

loans from the banks may not be granted, and to stop

to be imposed a burden of higher interest

rates.Therefore, the researchers have decided that debt

ratio represents financial leverage. The ratio is

estimated by dividing the total debt by total asset.

4.4. Research model

The following regression model has been applied in

the research to study the links between the use of

conservatism in accounting procedures and earnings

management:

EM = β0 + β1 CON + β2 Size + β3 ROE + β4 Lev +e

Where, EM: Earnings management / CON:

Conservatism / SIZE: Company's Size / REO: Return

On Equity; LEV: Financial Leverage / β: fixed

parameter / e: error term

5. STATISTICAL METHODS AND

TECHNIQUES

Since the objective of the present study is to examine

the links between conservatism and earnings

management, multiple variable regression models has

been used based on mixedmethod data analysis to test

the research hypothesis. In this analysis, the proper

models were fitted based on the results from Chaw

test and Hausman test. To run significant test for the

fitted regression model, Fischer statistic was used in

95% assurance level. Respectively, the researchers

used T-student statistic to studyvariable coefficient of

regression model; Durbin-Watson test to study auto-

correlation among observations; and finally adjusted

determining variable statistic to examine how

explainable the model is.

6. DATA ANALYSIS AND EXAMINATION OF

THE RESEARCH HYPOTHESES

In the present research, the ratio of book value to

market value of the stockholders' equity has been

considered as a criterion of conservatism in

accounting procedures. The reason why such a

criterion was chosen was that notable researches such

as Ahmad et al. (2002), Zhang (2007) and Lobo et al.

(2008) also took advantage of this criterion in their

studies. They found out that there is a meaningful

negative link between conservatism and discretionary

accruals. Jain & Rezaee showed in their research that

when the ratio of book value to market value of the

stockholders' equity is less than one, it can indicate

accounting conservatism. Besides, as once mentioned

earlier, residual sum of adjusted Jones's discretionary

accruals model has been used to estimate earnings

management. To examine the research core model, the

researchers embedded the variable of book value ratio

to market value of the stockholders' equity as an

indicator of accounting conservatism asindependent

variable. On the other hand, they embedded residual

sum of adjusted Jones's discretionary accruals model

that is the same as discretionary accruals as

independent variable to indicate earnings

management. Moreover, control variable such as

company size, company leverage and return on equity

have been exerted to control the undesirable effects.

6.1. Descriptive statistics of research core model

variables

Descriptive statistics of research variables include

central tendency, variability and distribution

indicators. In this research, the relevant data related to

mean and median have been presented in category of

central tendency, standard deviationin category of


109

variability, and finally elongation and skewness in

category of distribution. Moreover, Jarko-bra statistic

and relevant significant level have been presented in

this chart to test normality of distribution of research

variables. Descriptive statistics of research core model

variables have been presented in Table 1.

Table 1: Descriptive Statistics of the Main Model Variables

variable Mean Median Standard

deviation

Skewness Elongation Jarco-bra

statistic Probability

Con 0.880815 0.550846 4.854001 22.24455 591.4461 13218915 0.000000

Em -7.49E-19 0.003025 0.233599 -6.818365 154.5776 857948.6 0.000000

Size 13.38333 13.17000 1.483872 0.808653 4.018428 137.1351 0.000000

ROE 0.405161 0.261357 5.445384 4.407300 131.4621 624521.4 0.000000

Lev 0.765846 0.649520 1.332373 15.5463 288.6741 624521.4 0.000000

The observations indicate that in average, book

value of the sample companies is about 88% of their

market value. As mentioned earlier, Jain & Rezaee

believe that when the ratio of book value to market

value of the stockholders' equity is less than one, it

can indicate accounting conservatism. Since this ratio

is below one in the sample companies, therefore on

may conclude that conservative accounting exists in

these companies. The ratio for half of the companies

is above 0.55 and for the second half it is below 0.55.

According to the observations, earnings management

in the sample companies is on average -7.49E-19. The

negative mark implies that the companies either have

adopted an earnings reduction policy or have not

taken any measure at all to manage the earnings.

However, this does not suggest any lack of earnings

management in those companies. This might be due to

the fact that the average accrual items are negative.

These items have already been referred earlier in this

paper. In other words, companies on average possess

negative accrual items.

The mean size of the sample companies according

to asset logarithm is 13.38. The median of this

variable decreased by 0.21 unit and amounted to

13/17. Mean ROE of the sample companies are 40.5

percent, which means that net profit is on average 40.5

percent of shareholders' equity. In half of the

companies the equity is above 26 percent and in the

other half it is below 26 percent. The observations

suggest that the sample companies' debts make up an

average of 76.5 percent of their assets. In half of the

companies, this ratio is above 65 percent and in the

other half it is less than 65 percent. All the research

variables have positive skewness except for earnings

management indicator. Positive skewness implies that

distant samples from central tendency indicator are

located on the right domain of the measurement scale.

When earnings management indicator has negative

skewness then distant samples from central tendency

indicator are located on the left domain of the

measurement scale. Besides, all the research variables

have positive elongation which means that variable

distribution curve is longer than normal distribution

curve. As Jarco-Bra statistic and its corresponding

significant level suggests, not all the research

variables have normal distribution.

6.2. Examining correlation among the research

variables

In this section, researchers examine the correlation

among the core model variables of the research

applying Pearson correlation coefficient. Table 2

presents correlation coefficient matrix.

Table 2: Correlation coefficients between the variables of the main model

con Size ROE Lev

Con : Pearson Correlation

Sig.

1.000000

Size: Pearson Correlation

Sig.

0.003540

0.9175

1.000000

ROE: Pearson Correlation

Sig.

-0.010421

0.7604

-0.043804

0.1996

1.000000

Lev: Pearson Correlation

Sig.

-0.025484

0.4557

0.068145

0.0459

-0.017358

0.6114

1.000000

As the table shows, the only significant correlation

regarding level of significance of correlation

coefficient among the variables (below 0.05) is the

correlation between size and leverage, being about

0.068. This means that the correlation is affirmative;

however, the correlation intensity between them is

evaluated as weak. Therefore, applying the variables

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to the model at the same time will not cause any

interference concerning collinearity.

6.3. Examination of research core models

6.3.1. Examining the model on links between

conservatism and earning management

The researchers primarily examined required tests in

each case to select a proper pattern. According to F

statistic ofChaw test and the sum of related probability

(above 0.05) the model lacks required effects. Since

this test does not recommend applying mixed data

along with the effects, therefore there is no need to

Hausman test and the model is immediately fitted. The

results are presented in Table 3. Table 3: The Results of Choosing a Model for Model Test of Relation between conservatism and earning management

Test type Sample

statistic

Statistic

quantity

df sig

Chow test F 0.008238 153,723 1.0000

Table 4: Estimating the model of relation between conservatism index and earning management

Dependent variable: discretionary accruals

Explanatory variable Coefficients Standard error T statistic sig

The width of source: (α0) 0.000168 0.002285 0.073643 0.9413

BV to MV ratio -0.000345 .0000800 -0.431327 0.6663

Fischer statistic: 0.083745 Adjusted coefficient of explanation statistic : 0.000043

Probability of Fisher’s Statistic: 0.772354 Durbin-Watson’s Statistic : 2.188045

The results from model estimation indicate that t-

statistic and its relevant probability show lack of (α0)

significance and book value to market value ratio in

the model. In other words, there is no evidence that

there is significant link between conservatism and

earnings management. The adjusted R2 model statistic

indicates that conservatism cannot explain earning

management efficiently. Since all the findings

suggested the inefficiency of the model to explain the

link between conservatism and earnings management,

once again another model was fitted based on

logarithm of book value to market value ratio to

examine the link more closely.

6.4. Testing the model of links between

conservatism and earning management

As it was earlier mentioned, to examine the links

between the variables more closely, another model

was fitted based on logarithm of book value to market

value ratio. In other words, logarithm of book value to

market value ratio has been considered as a criterion

of conservatism. To select a proper pattern, the

researchers examined required tests in each case.

According to F statistic of Chaw test and the sum of

related probability (above 0.05) the model lacks

required effects. Since this test does not recommend

applying mixed data along with the effects, therefore

there is no need to Hausman test and the model is

immediately fitted. The results are presented in Table

5. Table 6 introduces the results of model estimation

using combinational method without exercising the

effects.

Table 5: The Results of Choosing a Model for Model Test of Correlation between conservatism and earning management

Test type Sample statistic Statistic

quantity

df sig

Chow test F 0.992227 153,698 0.5139

Table 6: Estimating the model of correlation between conservatism index and earnings management



The width of source (α0) -0.003538 0.002619 -1.350927 0.1771

BV to MV ratio -0.005332 0.002352 -2.267174 0.0236

Fischer statistic: 4.641173 Adjusted coefficient of explanation statistic : 0.014601

Probability of Fisher’s Statistic: 0.031494 Durbin-Watson’s Statistic : 2.201023


111

Regression equation extracted from model estimation

is as follows:

EM = -0.003538 - 0.005332*LNCONS

Having studied the results from model estimation,

the researchers found out that t statistic and its related

probability (less than 0.05) indicates significance of

conservatism (logarithm of Book value to market

value ratio). Negative coefficient of the variable

proves that it has negative and significant effect on the

model. This means that there exists a negative and

significant link between conservatism and earnings

management. In other words, the higher the

conservatism index becomes, the less the earnings

management is exercised, and vice versa. (α0),

however, does not influence the model significantly.

Adjusted R2 statistic of the model indicates that only

1.4 percent of the earnings management may be

explained via conservatism. Of course, coefficient of

explanation of the model is too low. One may

conclude that the model is poorly explainable. Durbin-

Watson statistic of the model suggests that the

remaining model is still independent.


conservatism and earning management along with

control variables

To control the undesirable effects, researchers

involved other variables such as company size,

company leverage and performance as control

variables. First, Chaw and Hausman test were used to

select a proper model. The results of these tests have

been presented in Table 7. According to F statistic of

Chaw test and the sum of related probability (below

0.05) the model carries the required effects. Again,

with regard to X2 statistic of Hausman test the related

sum of the probability (higher than 0.05) the model

contains random effect. Table 8 introduces the results

of model estimation using random method

Table 7: The Results of Choosing a Model for Model Test of Correlation between conservatism index and Earnings

Management at the Presence of the Control Variables

Test Type Sample Statistic Statistic

Quantity

df sig

Chow Test F 1.423763 153,658 0.0018

Hausman Test X2 7.972217 4 0.0926

Table 8: Estimating the model of correlation between conservatism index and earning management at the presence of the

control variables



The width of source (α0) 0.0222000 0.028989 0.765811 0.4441

BV to MV ratio -0.028492 0.013198 -2.158818 0.0312

size -0.003145 0.001755 -1.792030 0.0736

ROE 4.72E-05 0.000508 0.092848 0.9261

Lev 0.012039 0.002036 5.913195 0.0000

Fischer statistic: 1.418300 Adjusted coefficient of explanation statistic: 0.074572

Fischer statistical probability: 0.001843 Durbin-Watson statistic: 1.714347


is as follows:

EM= 0.0222 – 0.028492 * Ln Cons – 0.003145 * Size

+ 4.72E-05* ROE + 0.012039* Lev+ [CX=R]


the researchers found out that F statistic and its related


the whole model. Negative coefficient of the variable

proves that it has negative and significant effect on the

model. This means that there exists a negative and

significant link between conservatism and earnings

management. In other words, the higher the

conservatism index becomes, the less the earnings

management is exercised, and vice versa. (α0),

however, does not influence the model significantly. T

statistic and the related probability (less than 0.05)

indicates significance of leverage variable. Positive

coefficient of the variable proves that it has Positive

and significant effect on the model. In other words,

the higher the leverage (debt to asset ratio) becomes,

the more the earnings management is exercised, and

vice versa. T statistic and the related probability (more

than 0.05) indicates lack of significance of size and

ROE variables.However, size variable up to 10

percent error has negative significance on the model.

In this case, as the size increases (assets logarithm)

earnings management increases, and vice versa.


conservatism and earning management along with

significant control variables

In this model, researchers involved only company size

variable, since it had significant effect on the model.

First, Chaw and Hausman test were used to select a

proper model. The results of these tests have been

presented in Table 9. According to F statistic of Chaw

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112

test and the sum of related probability (below 0.05)

the model carries the required effects. Again, with

regard to X2 statistic of Hausman test the related sum

of the probability (lower than 0.05) the model lacks

proper consistent effects. Table 10 introduces the

results of model estimation using consistent method.

Table 9: The Results of Choosing a Model for Model Test of Correlation between Earnings Management and Earnings

Response Coefficient at the Presence of the Control Variables

Test Type Sample Statistic Statistic

Quantity

df sig

Chow Test F 1.457958 153,683 0.0009

Hausman Test X2 8.323279 2 0.0156

Table 10: Estimating the model of correlation between conservatism index and earnings management along with significant

control variables



The width of source (α0) -0.020441 0.002852 -7.167389 0.0000

BV to MV ratio -0.029073 0.003773 -7.706612 0.0000

Lev 0.010837 0.000666 16.26696 0.0000

Fischer statistic: 8.231768 Adjusted coefficient of explanation statistic: 0.572214

Fischer statistical probability: 0.000000 Durbin-Watson statistic: 2.238676


is as follows:

EM= -0.020441 – 0.029073*Ln Cons + 0.010837*

Lev = [CX=F]


the researchers found out that F statistic and its related


the whole model. T statistic and the related probability

(less than 0.05) indicates significance of conservatism

(logarithm of book value to market value ratio)

Negative coefficient of the variable proves that it has

negative and significant effect on the model. This

means that there exists a negative and significant link

between conservatism and earnings management. In

other words, the higher the conservatism index

becomes, the less the earnings management is

exercised, and vice versa. T statistic and the related


the width of source, however, it influences the model

negatively and significantly. T statistic and the related


leverage variable. Positive coefficient of the variable

proves that it has Positive and significant effect on the

model. In other words, the higher the leverage (debt to

asset ratio) becomes, the more the earnings

management is exercised, and vice versa. Adjusted R2

statistic of the model indicates that about 57.2 percent

of the earnings management may be explained via

conservative variables in relation to leverage control

variable. It is noteworthy that coefficient of

explanation of the model has increased dramatically

compared with prior models, to the extent that the

model is explainable more than 50 percent.

7. CONCLUSION

With regard to the tests that were run, the findings

indicate that the whole model lacks significance. Book

value to market value ratio lacks significance, as well.

This means that no significant link was explored

between conservatism and earnings management.

Since all the cases that were examined showed

inefficiency of the model, therefore another model

was fitted based on logarithm of book value to market

value ratio. This time the findings proved that the

whole model as well as logarithm of book value to

market value ratio is significant. Negative coefficient

of this variable indicates negative and significant

effect of the variable on the model. Afterwards, to

control undesirable effects, other variables such as

company size, company leverage and ROE were also

involved in the study. Having fitted the model, the

researchers found out that the whole model as well as

logarithm of book value to market value ratio is

significant. The findings also indicate that leverage

variable is significant, since positive coefficient of the

variable signifies its positive and significant effect.

Next, the final model was fitted applying the leverage,

a significant control variable. Eventually, the final

findings of the study proved that the whole model as

well as logarithm of book value to market value ratio

is significant. Adjusted coefficient of determination of

the model indicates that about 57.2 percent of earnings

management by conservatism is explainable using

leveraging control variable.

7.1. Research implications

(1) As it was once mentioned in the descriptive

statistics chapter, the observations showed that on


113

average, book value of the sample companies are less

than their market value. That the ratio of book value to

market value of the stockholders' equity is below one

indicates accounting conservatism is very likely to be

there. Since this ratio is below one in sample

companies, therefore one may rightly conclude that

accounting conservatism is being exercised in these

companies. The researchers recommend the possible

users to refer to the findings and take this matter into

their consideration when making financial decisions.

(2) Since there is a negative and significant link

between conservatism and earnings management, it is

expected that as conservatism increases, earnings

management decrease. In some instances in which

earnings management takes a negative aspect, the

negative and significant link between conservatism

and earnings management can stop manipulating the

earnings. Therefore, analysts and possible users of the

research findings are recommended to take this matter

into consideration when making financial decisions.

7.2. Suggestions for further research

(1) The researchers suggest a similar study with an

emphasis on the notion of earnings quality.

(2) The researchers suggest that links between

conservatism and income smoothing be studied.

(3) The researchers suggest that links between

conservatism and diverse features of time series of

profit such as profit stability, profit predictability and

the like are studied.

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115

Abbas Ramezanzadeh Zeidi received his MA in Accounting from Tehran Branch, Islamic Azad

University. Currently, he is PhD Candidate at AMU India. He has more than 20 papers in the referees

journals and conferences. He is faculty member of Neka Branch, Islamic Azad University.

Zabihollah Taheri received his MA in Accounting from Tehran Branch, Islamic Azad University. He is

faculty member of Payamenour University, Sari, Iran.

Ommolbanin Gholami Farahabadi received her MA in Accounting from Payamenour University,

Behshahr, Iran. She is faculty member of Payamenour University, Neka, Iran.

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