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Microfluidic Two-Dimensional Separation of Proteins Combining Temperature Gradient Focusing and Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis

2015· article· en· W94937517 on OpenAlexafffund
Seyed Mostafa Shameli, Carolyn L. Ren

Bibliographic record

VenueAnalytical Chemistry · 2015
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsChemistrySodium dodecyl sulfateMicrofluidicsChromatographyPolyacrylamideGel electrophoresisPolyacrylamide gel electrophoresisSeparation methodSodiumElectrophoresisNanotechnologyBiochemistryPolymer chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

A two-dimensional separation system is presented combining scanning temperature gradient focusing (TGF) and sodium dodecyl sulfate (SDS)-polyacrylamide gel electrophoresis (PAGE) in a PDMS/glass microfluidic chip. Denatured proteins are first focused and separated in a 15 mm long channel via TGF with a temperature range of 16-47 °C and a pressure scanning rate of -0.5 Pa/s and then further separated via SDS-PAGE in a 25 mm long channel. A side channel is designed at the intersection between the two dimensions to continuously inject SDS into the gel, allowing SDS molecules to be compiled within the focused bands. Separation experiments are performed using several fluorescently labeled proteins with single point detection. Experimental results show a dramatic improvement in peak capacity over one-dimensional separation techniques.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.230
Teacher spread0.221 · 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

Citations18
Published2015
Admission routes2
Has abstractyes

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