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Record W2322760093 · doi:10.1038/protex.2015.033

Graphene-based C-reactive protein immunoassay with smartphone readout

2015· article· en· W2322760093 on OpenAlexfundno aff
Sandeep Kumar Vashist, A. G. Venkatesh, E. Marion Schneider, Roland Zengerle, Felix von Stetten, John H. T. Luong

Bibliographic record

VenueProtocol Exchange · 2015
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsImmunoassayGrapheneChemistryChromatographyNanotechnologyMaterials scienceMedicineImmunologyAntibody

Abstract

fetched live from OpenAlex

A highly-sensitive immunoassay \(IA) procedure with minimal process steps has been developed for the detection of human C-reactive protein \(CRP) in less than 30 min.Graphene nanoplatelets \(GNP) was admixed with 3-aminopropyltriethoxysilane \(APTES) and EDC-activated anti-human CRP antibody \(Ab) to form a stable complex that was then covalently attached to a KOH-pretreated polystyrene microtiter plate \(MTP).The developed one-step kinetics-based IA involves the formation of a sandwich immune complex followed by two washings and an enzyme-based colorimetric reaction that was read by a smartphone-based colorimetric reader \(SBCR).The detection range of CRP was 0.03-81 ng mL -1 with a limit of detection \(LOD) and a limit of quanti cation \(LOQ) of 0.07 ng mL -1 and 0.9 ng mL -1 , respectively.Moreover, the developed IA enabled the detection of CRP spiked in diluted human whole blood and plasma as well as CRP present in clinical plasma samples with high analytical precision, thereby demonstrating its immense utility for biomedical diagnostics.

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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.106
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.071
GPT teacher head0.326
Teacher spread0.255 · 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
GenreProtocol

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

Citations0
Published2015
Admission routes1
Has abstractyes

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