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HUMBOLDT STATE UNIVERSITY (CA) B.A. 1985 INDUSTRY FOR 4 YEARS PENN STATE PH.D. 1993 UNIVERSITY OF CALIFORNIA, RIVERSIDE POSTDOC 1996 PROFESSOR ASU 1996-CURRENT.

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Presentation on theme: "HUMBOLDT STATE UNIVERSITY (CA) B.A. 1985 INDUSTRY FOR 4 YEARS PENN STATE PH.D. 1993 UNIVERSITY OF CALIFORNIA, RIVERSIDE POSTDOC 1996 PROFESSOR ASU 1996-CURRENT."— Presentation transcript:

1 HUMBOLDT STATE UNIVERSITY (CA) B.A INDUSTRY FOR 4 YEARS PENN STATE PH.D UNIVERSITY OF CALIFORNIA, RIVERSIDE POSTDOC 1996 PROFESSOR ASU 1996-CURRENT Mark A. Hayes

2 WE TRY TO BREAK THINGS DOWN INTO THEIR SIMPLEST COMPONENTS, UNDERSTAND THOSE AND BUILD BACK TOWARDS COMPLEXITY. What would you need to provide the earliest possible detection of disease? We are all chemists here, and therefore are reductionists-

3 Differential Diagnostics What are typical diagnostic strategies?  ‘black box’ guesses  Symptoms (T, BP, visual cues), some chemical/biological measurements  Fit to a model  Educated but—by definition—guesses  Patient used as test bed – treatments attempted, when fail—move to next treatment  We simply do not yet understand ‘normal’ biology, much less ‘abnormal’ or ‘disease’ biology

4 Analytics and Medical Science Premise: if we can measure all the cells and molecules (and tissue?) in the ‘system’ we could predict (and diagnosis precisely) disease state. [and a lot of other things: pathways ID, enzymatic quantification, PTMs, etc.] Works pretty well for 747s (Hartwell quote) sensors, early warning systems in place. None have fallen out of the sky. But…

5 Analytics and Medical Science Three problems: 1) we don’t even know all the molecules & cells 2) we don’t have tools to measure these at the right timescales, cost and sensitivities 3) we don’t know how useful this would be (and can’t until we do it!)

6 Analytics and Medical Science Here’s where we come in: Building the best tools to 1) Independently identify biomolecules in a short timeframe, in a cost efficient manner that is relevant to medical science (and fundamental biological studies) 2) To augment other analytics (mass spectrometry, molecular recognition, spectroscopy, electrochemistry) to accomplish the same goals 3) To learn exactly how sensitive and precise these measurements need to be (more later on this topic)

7 Our work We focus on microfluidics, separations science and immunoassay (and other fundamental physical processes – not discussed today) Because biomolecules all look the same (spectroscopically speaking) or will compromise the operation of instruments, they must be purified or isolated prior to analysis The separation itself can be an identifier (retention time, location on an array, signal from an immunoassay)

8 Our work What’s different or new compared to all the other microfluidics out there?  1) we are generating unprecedented resolution (the ability to quickly or efficiently (space) separation wanted from unwanted)  2) broad range of targets (10 microns to small molecules) – bacteria, cells, viruses, proteins, metabolites  3) building a format for programmable parallel array-base separations  4) all can be coupled to traditional bio-detection systems (immuno./molec. rec., MS, EC, spectrscp.)

9 Overall Technical Paradigm Lysing or disruption chamber Flow Flow stream shift or valve Fraction Collection from Dielectrophoresis

10 Overall Technical Paradigm Lysis and Pattern Generation (separation or array) Lysing or disruption chamber or and (some circumstances) Array readout: molecular recognition & spectroscopy Linear or multi-dimensional separations

11 Overall Technical Paradigm: Today’s Presentation Gradient Dielectrophoresis Electrophoretic Capture (Array) and (some circumstances)

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15 F EK F DEP

16 F EK F DEP A new dual-force gradient focusing technique similar in form to IEF: IEF: f( d +z/d pH * E) f( d -z/d pH * E) D R = f (dpH/dx, dz/dpH, E, D) IGDEP: f(  DEP *  E 2 ) f(  EK * E) D R = f (dE/dx, d  E 2 /dx, D)* *other factors also…

17 Chen et al DC-iGDEP: Particle Separations F EOF F DEP EK Linear separation device, similar to isoelectric focusing or other gradient techniques.

18 F EOF F DEP PDMS Buffer solution Assuming nDEP

19 Surface plot:local electrical potential, V Contour lines:magnitude of electric field, |E| Normalized arrows:direction of DEP force, proportional to |E| 2 ∆ DEP Force (Centerline, Log Scale) COMSOL Calculation Seven ‘teeth’ narrowest on right

20  Live & dead Bacillus subtilis, Escherichia coli, & Staphylococcus epidermidis  Three different design, based on sawtooth theme  Consistent separation between physiologic states  Suggests ability to resolve both species, sub-species and metabolic state (see ‘C’, top left) ‏ Pysher 2005: Hayes 2007 DC-iGDEP Particle Separations: Bacteria

21  Blood diluted in phosphate buffer  Cells located in specific zones  Cell debris trapped separately Jones, 2010 DC-iGDEP : Red Blood Cells

22 Staton, 2010, in press Electrophoresis DC-iGDEP: Particle Separations A-beta Amyloid Fibrils 1 x 20 nm courtesy Gilman/Kheterpal 1 micron and 200 nm polystyrene

23 ➡ Cells ➡ Narrowest Gate: 20 µm ➡ Widest Gate: 500 µm ➡ Change in gate height (Δh) varies along channel Δh (µm) = ➡ Proteins/Virions ➡ Narrowest Gate: 1 µm ➡ Widest Gate: 30 µm Δh (µm) = 21

24 ➡ Max value |E| 2 : ➡ 2.1x10 15 V 2 /m 3 – 20 µm gate ➡ Min value : ➡ 1.9x10 13 V 2 /m 3 – 500 µm gate ➡ Rate of change : ➡ 1.3x – narrow gates ➡ 1.1x – wide gates ∆

25 What does this all mean? We develop revolutionary tools, tightly coupled to needs in the medical sciences  Collaborations with pathologists, surgeons, instrument companies, defense industry (along with physicists, mathematicians, engineers, biologist, other chemists) Need to get to the biologically fluctuations in concentration to extract interpretable data Sometimes that means pushing the detection limit or temporal resolution (cost) Other times that means monitoring a large number of targets looking or patterns (meadow/ecology model)

26 What is it like to work with Dr. Hayes? Good question! Please ask my current students. My students average 5 years to graduation  Earliest is 2.7 years, latest is 6.5 Work hard, play hard  Not much in the way of micromanaging  Expect a lot, gentle corrections  You will know more about your project than I by the time you graduate. Most students tell me when they are ready. Social group Attend Conferences 3-5 first-author publications Highly supported: NSF, Fulbright & NIH fellows earned while in group Looking for 1-2 students


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