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Record W2065075903 · doi:10.1039/b717759c

Digital microfluidics for cell-based assays

2008· article· en· W2065075903 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLab on a Chip · 2008
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMicrofluidicsMicroscale chemistryJurkat cellsReagentLysisViability assayCellCytotoxicityNanotechnologyChemistryDigital microfluidicsChromatographyMaterials scienceBiologyElectrodeBiochemistryT cellImmunologyMathematicsIn vitro

Abstract

fetched live from OpenAlex

We introduce a new method for implementing cell-based assays. The method is based on digital microfluidics (DMF) which is used to actuate nanolitre droplets of reagents and cells on a planar array of electrodes. We demonstrate that this method is advantageous for cell-based assays because of automated manipulation of multiple reagents in addition to reduced reagent use and analysis time. No adverse effects of actuation by DMF were observed in assays for cell viability, proliferation, and biochemistry. A cytotoxicity assay using Jurkat T-cells was performed using the new method, which had approximately 20 times higher sensitivity than a conventional well plate assay. These results suggest that DMF has great potential as a simple yet versatile analytical tool for implementing cell-based assays on the microscale.

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 score0.051
Threshold uncertainty score0.560

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 head0.011
GPT teacher head0.191
Teacher spread0.180 · 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