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Dielectric study of biological phenomena at the single cell level: Electroporation and starvation

2017· article· en· W2770800152 on OpenAlexaff
Elham Salimi, Samaneh Afshar, Katrin Braasch, Michael Butler, D. J. Thomson, Greg E. Bridges

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsElectroporationDielectrophoresisDielectricCytometryFlow cytometryMaterials scienceCellElectric fieldStarvationCell biologyBiophysicsOptoelectronicsBiologyChemistryNanotechnologyImmunologyPhysicsBiochemistryMicrofluidicsEndocrinology

Abstract

fetched live from OpenAlex

In this paper we present the use of a dielectrophoresis (DEP) cytometry technique to study changes in single cells upon application of a particular stimulus. In one case we measure single CHO cells immediately after exposure to pulsed electric fields. Our results show a significant change in the dielectric response of cells after application of sufficiently strong pulses. In another study we investigate the effect of nutrient deficiency on CHO cells. Many individual cells are measured as they undergo starvation due to lack of nutrients in their medium. Our DEP measurement results, after 48 hours of starvation, show a substantial change in the dielectric response that correlates with the viability of the cells. By the examples we present in the paper, we demonstrate the potential of our DEP cytometry technique in applications such as monitoring the effect of drugs or developing optimal protocols for cell electroporation.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.053
GPT teacher head0.226
Teacher spread0.172 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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