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Record W2000918832 · doi:10.1063/1.3339773

Modeling of dielectrophoretic transport of myoglobin molecules in microchannels

2010· article· en· W2000918832 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiomicrofluidics · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMyoglobinDielectrophoresisElectrokinetic phenomenaElectric fieldMicrochannelFinite element methodDielectricElectrophoresisField (mathematics)PhysicsMaterials scienceChemistryMechanicsNanotechnologyThermodynamicsOptoelectronicsMathematics

Abstract

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Myoglobin is one of the premature identifying cardiac markers, whose concentration increases from 90 pgml or less to over 250 ngml in the blood serum of human beings after minor heart attack. Separation, detection, and quantification of myoglobin play a vital role in revealing the cardiac arrest in advance, which is the challenging part of ongoing research. In the present work, one of the electrokinetic approaches, i.e., dielectrophoresis (DEP), is chosen to separate the myoglobin. A mathematical model is developed for simulating dielectrophoretic behavior of a myoglobin molecule in a microchannel to provide a theoretical basis for the above application. This model is based on the introduction of a dielectrophoretic force and a dielectric myoglobin model. A dielectric myoglobin model is developed by approximating the shape of the myoglobin molecule as sphere, oblate, and prolate spheroids. A generalized theoretical expression for the dielectrophoretic force acting on respective shapes of the molecule is derived. The microchannel considered for analysis has an array of parallel rectangular electrodes at the bottom surface. The potential and electric field distributions are calculated using Green's theorem method and finite element method. These results also compared to the Fourier series method, closed form solutions by Morgan et al. [J. Phys. D: Appl. Phys. 34, 1553 (2001)] and Chang et al. [J. Phys. D: Appl. Phys. 36, 3073 (2003)]. It is observed that both Green's theorem based analytical solution and finite element based numerical solution for proposed model are closely matched for electric field and square electric field gradients. The crossover frequency is obtained as 40 MHz for given properties of myoglobin and for all approximated shapes of myoglobin molecule. The effect of conductivity of medium and myoglobin on the crossover frequency is also demonstrated. Further, the effect of hydration layer on the crossover frequency of myoglobin molecules is also presented. Both positive and negative DEP effects on myoglobin molecules are obtained by switching the frequency of applied electric field. The effect of different shapes of myoglobin on DEP force is studied and no significant effect on DEP force is observed. Finally, repulsion of myoglobin molecules from the electrode plane at 1 KHz frequency and 10 V applied voltage is observed. These results provide the ability of applying DEP force for manipulating nanosized biomolecules such as myoglobin.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.188
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it