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Record W2046154711 · doi:10.1039/c2an36243k

Wash-less and highly sensitive assay for prostate specific antigen detection

2012· article· en· W2046154711 on OpenAlexaff
Ghadeer A. R. Y. Suaifan, Chiheb Esseghaier, Andy Ng, Mohammed Zourob

Bibliographic record

VenueThe Analyst · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsBiosensorDetection limitProstate-specific antigenChemistrySubstrate (aquarium)AntigenChromatographyProteolysisProstateBiochemistryBiologyImmunologyMedicineInternal medicineCancerEnzyme

Abstract

fetched live from OpenAlex

A novel, simple and facile biosensor for prostate specific antigen (PSA) detection was constructed. In this method, proteolytically active PSA is capable of cleaving PSA substrate-magnetic carrier complexes. Electrochemical analysis of the sensor layer showed a significant decrease in impedance signal after proteolysis has occurred, whereas a positive change in impedance was observed using a negative control substrate, indicating the specificity of our detection mechanism. The biosensor has the ability to monitor PSA concentrations ranging from 1 pg ml(-1) to 1 μg ml(-1) with a detection limit as low as 1 pg ml(-1). The sensor offers the possibility of developing a wash-less and cost-effective point-of-care device due to the simplicity of the probe immobilization process and the elimination of labeling and reporter molecules during the biosensing step.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.012
GPT teacher head0.259
Teacher spread0.247 · 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

Citations24
Published2012
Admission routes1
Has abstractyes

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