MétaCan
Menu
Back to cohort

An electrokinetic microdevice for isolation and quantification of circulating cell-free DNA from physiological samples

2015· article· en· W1504746393 on OpenAlexfundno aff
Ariana Lamanda, Yi Lu, Navrose Gill, Pak Kin Wong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsnot available
FundersNational Institutes of HealthCanadian Association for the Study of the Liver
KeywordsElectrokinetic phenomenaDielectrophoresisMicrofluidicsCell-free fetal DNAChromatographyBiological fluidsChemistryMaterials scienceNanotechnologyBiology

Abstract

fetched live from OpenAlex

This study reports a hybrid electrokinetic microdevice for rapid concentration and detection of circulating cell-free (cf)DNA. Rapid molecular analysis of cfDNA has the potential to change the current practice of medicine, such as in cancer diagnostics and in monitoring the efficacy of cancer treatments. With a combination of AC electrothermal flow and dielectrophoresis, the hybrid electrokinetic microdevice efficiently concentrates cfDNA from blood plasma and other physiological fluids. In this design, the long-range AC electrothermal flow, which is effective in conductive fluids, drives the cfDNA towards the center of the electrode where dielectrophoretic trapping of the cfDNA occurs. Once the cfDNA is collected at the electrode, the concentration in the blood sample can be quantified by fluorescence analysis with an intercalating dye that binds specifically to double-stranded DNA. The effects of the electrokinetic parameters were elucidated to optimize the design of the device. The device was demonstrated to separate high molecular weight DNA from low molecular weight DNA. Quantitative detection of clinically relevant concentrations of cfDNA was achieved in 10 minutes.

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 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 score0.170
Threshold uncertainty score0.269

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 head0.048
GPT teacher head0.240
Teacher spread0.192 · 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 teacher head, 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

Citations2
Published2015
Admission routes1
Has abstractyes

Explore more

Same topicMicrofluidic and Bio-sensing TechnologiesFrench-language works237,207