Concentration Control in

Microfluidics for Neuroscience Applications

Presenter: Ali Hashmi

Advisor: Jie Xu

Date: 04.03.2014

School of Engineering and Computer Science, Washington State University

Outline Background

Neurons

Traditional research methods in neuroscience

The need for chemical concentration control

Concentration control with microfluidics

Piezoelectric actuation

Synchronized pumps

Comparison and suggested improvements

2

Outline Background

Neurons

Traditional research methods in neuroscience

The need for chemical concentration control

Concentration control with microfluidics

Piezoelectric actuation

Synchronized pumps

Comparison and suggested improvements

3

Introduction: Neurons

Neurons transmit information use both chemical and electrical impulses

Electrical signals travel along axons

Neurotransmitters are released at axon terminals

Neurotransmitters either chemically excite neighbouring neurons or repress their activity upon

absorption at the dendrites

Frequency of chemical/electrical impulse are critical

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Source: wikipedia

Traditional research methods in neuroscience

Almost all traditional techniques for neural stimulation involve electrical stimulation

e.g. The first patch clamp technique

Recent techniques in neuroscience such as optogenetics involve light as stimuli to induce neuronal activity Special protein called channel-rhodopsin

Chemical stimulation remains largely ignored !

Challenging to achieve precise and rapid chemical concentration control in petri-dishes

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Source: NY times

Source: wikipedia

The need for chemical concentration control The effects of neurotransmitters remain a mystery

More than 100 neurotransmitters exist

Acetylcholine associated with learning

Endorphins with emotions

Functions of many are not known

The imbalance in neurotransmitter concentration can be studied with precise concentration control

Might help in deciphering the cause of various diseases

Platforms to test the effects of drugs and other externally administered substances over long durations

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Can microfluidics help? Microfluidics can enable precise control of small volumes

of liquids in microchannels

The flows are extremely slow (low Reynolds number) and laminar

makes manipulation of fluids easy

Concentration gradients can be conveniently generated

local chemical concentration can be varied

7Quake lab (Stanford)Xu and Attinger (2008)

Microfluidics & Neuroscience

Concentration gradients generated for stimulating neurons have mostly been steady-state

Co-culture chambers provide chemical cues to study axon/cell-bodies independently

8Folch Lab

Taylor et al (2006)

Outline Background

Neurons

Traditional research methods in neuroscience

The need for chemical concentration control

Concentration control with microfluidics

Piezoelectric actuation

Synchronized pumps

Comparison and suggested improvements

9

Objectives To dispense individual packets of chemical (neurotransmitters

or drugs) in a microchannel

To achieve absolute control over spatiotemporal concentration profile

Develop dynamic chemical clamp to study the effects of chemicals on cellular activity

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Dynamic clamp : an artificial neuronal environment

A step toward developing a novel dynamic clamp 11

Concentration gradients: piezoelectric actuation

Piezoelectric transducers can enable faster actuation

The shape, amplitude and frequency of the input can be conveniently altered

Ease of device fabrication (micromilling and softlithography)

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Fabrication - micromilling

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Micro milling

roughness ~500 nm

resolution ~5 mm

suitable for channel > 50 mm

Soft lithography

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roughness < 100 nm

resolution < 5 mm

Suitable for channel

< 100 mm(Whitesides, Harvard, 1998)

our device

Preliminary design

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Chemical waveform

The graph shows a measure of the ink concentration profile. The

duty cycle (50%) is apparent by a slower increase in pixel intensity 16

Analysis

The figures show a count of pixels representing the plume for dilatation

(left image) and compression (right image) of chamber.

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Chemical waveform contd.

The chemical plume expands rapidly at higher actuation frequencies.

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inferences

chemical waveform may be generated for low actuation frequencies and smaller time periods

diffusion causes the plume to disperse

concentration of chemical in the chamber can vary in time

constant perfusion is necessary to refresh the chemical plume

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1st design iteration

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Chemical waveform

The figures show the intensity profile for the periodic shift in boundary

at an input frequency of 1 and 5 Hz and the respective spectrogram 21

inferences

concentration gradients were generated via shifting boundaries

No individual chemical packets were observed

Negligible difference between surface tension

Possible ways to break the flow

Modify nozzle geometry

Tune the input signal

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Photomask design

4 cm

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Pulsed chemical switch

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Chemical waveform

The plot represents the chemical waveform obtained from the pulsed

input.

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Inferences

Concentration waveform does not span the entire width of the channel

Might be helpful for single cell chemical stimulation

Not reliable for stimulating a larger neuronal culture

some further improvements

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Concentration gradients: synchronized pumps

Two programmable syringe pumps can be used in conjunction

generate a chemical waveform

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Analytical analysis

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= . .

Concentration profile for 1st half cycle

setup validation

concentration profile least square fit 29

Ca2+ ion nanosensor

(A)schematic showing the calcium ion nanosensor, with carbon

nanotubes as the sensing elements (B) image showing the actual

device

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Experimental test-rig

Image showing the apparatus: syringe-pumps, probe station and

semiconductor device analyzer31

Experimental results

Graph showing the resistance change of CNTs for a 1 Hz ramp

Input to the synchronized pumps for a total flow-rate of 0.3 mL/min 32

Fourier Analysis

Fourier transform of the signal showing the frequency distribution 33

Filtered signal

Filtered signal to compensate for the moving average34

Comparison of systems

Piezoelectric based actuation

high frequency waveforms

not robust for long durations of operation mainly due to mechanical cracks developing in piezoelectric transducer

Chemical concentration not distributed across channel

Synchronized pumps

cannot generate chemical waveforms at higher frequencies stepping period for the servo motors is limited

difficult to change input signal in real-time

robust operation for long time durations

uniform concentration across channel

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Suggested improvements

Piezoactuator based chemical switch

transducer with higher blocking force and free displacement can be used

relaxation time for PDMS can be varied

Synchronized pump based chemical switch

use pumps with smaller stepping time period

a mixer can be installed before CNT sensors

Further design alterations

piezoelectric pumps can be used to generate chemical waveforms at higher actuation frequencies

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Journal PublicationsH-index = 5, citations = 46

1. A. Hashmi*, G. Heiman*, G. Yu, M. Lewis, H. J. Kwon, and J. Xu. Oscillating Bubbles in Teardrop Cavities for Microflow Control. Microfluidics and Nanofluidics, 14, Issue 3-4, p. 591-596 (2013).

2. Y. Xu*, A. Hashmi*, G. Yu, X. Lu, H.J. Kwon, X. Chen, and J. Xu. Microbubble Array for On-Chip Worm Processing. Applied Physics Letters 102, p. 023702 (2013).

3. A. Hashmi, G. Yu, M. Reilly-Collette, G. Heiman, and J. Xu. Oscillating Bubbles: a Versatile Tool for Lab on a Chip Applications. Lab on a Chip 12(21), p. 4216-4227 (2012).

4. J. Zhao, A. Hashmi, J. Xu, and W. Xue. A Compact Lab-on-a-Chip Nanosensor for Glycerol Detection. Applied Physics Letters 100(24), p. 243109 (2012).

5. A. Hashmi, A. Strauss, and J. Xu. Freezing of a Liquid Marble. Langmuir 28(28), p.10324-10328 (2012).

6. A. Hashmi*, Y. Xu*, B. Coder*, P. A. Osborne, J. Spafford, G. E. Michael, G. Yu, and J. Xu. Leidenfrost Levitation: Beyond Droplets. Scientific Reports 2, article number: 797 (2012).

7. A. Bajwa*, Y. Xu*, A. Hashmi, M. Leong, L. Ho, and J. Xu. Liquid Marbles with In-flows and Out-flows: Characteristics and Performance Limits. Soft Matter 8, p. 11604-11608 (2012).

8. C. M. R. Mesias, G. Yu, H.-J. Kwon, J. Zhao, A. Hashmi, J. Gao, W. Xue, J. Xu and A. Dimitrov. Towards a Dynamic Clamp for Neuro-chemical Modalities (under review).

9. J.W. Jeon, L. Zhang, D. D. Laskar, M. I. Nandasiri, A. Hashmi, J. Xu, R. K. Motkuri, C. A Fernandez, J. Liu, J. L. Lutkenhaus, M. P. Tucker, B. Yang and S. K. Nune, Lignin Derived Nanoporous Carbon for Supercapacitor Applications (under review).

10. A. Hashmi, and J. Xu. On the Quantification of Mixing in Microfluidics (under review).

* represents equal contributors 37

Awards and Achievements 10 publications (3 under review) with 5 as the first author and 2 as the

second author

H-index of 5 with 46 citations in the past 2 years of study

Fellowship and assistanceship from Stanford Universitys Bioengineering Program for PhD

2 prestigious NSF travel grants worth 1750 $

Best presentation award for ASME IMECE Microfluidics Symposium

Institutional travel grants and presentation award

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