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Record W2108374162 · doi:10.1088/0960-1317/20/6/065007

Mechanical properties of mammalian cells in suspension measured by electro-deformation

2010· article· en· W2108374162 on OpenAlexafffund
Luke A. MacQueen, Michael D. Buschmann, M. R. Wertheimer

Bibliographic record

VenueJournal of Micromechanics and Microengineering · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMicroelectrodeMaterials scienceDeformation (meteorology)Elasticity (physics)ElectrodeChinese hamster ovary cellComposite materialPlanarPolydimethylsiloxaneSuspension (topology)Chemistry

Abstract

fetched live from OpenAlex

We describe a planar, micro-fabricated device for generating fringing non-uniform electric fields. We used it to measure the mechanical properties of individual mammalian cells in suspension by deforming them in time-varying, non-uniform electric fields. Electrical stresses generated by the planar microelectrodes were used to trap and stretch cells, while cell deformation was observed using optical microscopy. Two distinct cell types were compared after fitting strain data with a three-parameter 'standard linear solid' model of visco-elasticity, and with a two-parameter power-law method. Chinese hamster ovary (CHO) cells were approximately twice as stiff as U937 human promonocytes, and CHO cells displayed an elastic behaviour with recovery of initial shape, while U937 strain data bore witness to plastic deformation. Our results demonstrate that electrical stresses generated by micro-fabricated electrodes permit mechanical characterization of distinct mammalian cell types.

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 score0.001
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)0.0010.000

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 head0.163
Teacher spread0.157 · 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

Citations78
Published2010
Admission routes2
Has abstractyes

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