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Record W2859099014 · doi:10.1038/s41598-018-29065-7

A Multiwell-Based Detection Platform with Integrated PDMS Concentrators for Rapid Multiplexed Enzymatic Assays

2018· article· en· W2859099014 on OpenAlexfundno aff
Xi Wei, Vu Quang, Van-Sang Pham, Diogo Martins, Yong‐Ak Song

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsnot available
FundersDepartment of Education and KnowledgeYork UniversityNew York University Abu Dhabi
KeywordsPolydimethylsiloxaneMicrofluidicsConcentratorMultiplexingMaterials scienceFabricationChipNanotechnologyChemistryComputer science

Abstract

fetched live from OpenAlex

We report an integrated system for accelerating assays with concentrators in a standard 12-well plate (ISAAC-12) and demonstrate its versatility for rapid detection of matrix metalloproteinase (MMP)-9 expression in the cell culture supernatant of breast cancer cell line MDA-MB-231 by accelerating the enzymatic reaction and end-point signal intensity via electrokinetic preconcentration. Using direct printing of a conductive ion-permselective polymer on a polydimethylsiloxane (PDMS) channel, the new microfluidic concentrator chip can be built without modifying the underlying substrate. Through this decoupling fabrication strategy, our microfluidic concentrator chip can easily be integrated with a standard multiwell plate, the de facto laboratory standard platform for high-throughput assays, simply by reversible bonding on the bottom of each well. It increases the reaction rate of enzymatic assays by concentrating the enzyme and the reaction product inside each well simultaneously for rapid multiplexed detection.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.203
Teacher spread0.194 · 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
GenreMethods

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

Citations11
Published2018
Admission routes1
Has abstractyes

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