MétaCan
Menu
Back to cohort
Record W3216185544 · doi:10.1101/2021.11.29.21267025

Inexpensive and colorimetric RNA detection by <i>E. coli</i> cell-free protein synthesis platform at room temperature

2021· preprint· en· W3216185544 on OpenAlexaff
Michela Notarangelo, Alessandro Quattrone, Massimo Pizzato, Sheref S. Mansy, Ö. Duhan Toparlak

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRNAlac operonComplementationTranscription (linguistics)In vitroTranslation (biology)ChemistryCellMessenger RNAMolecular biologyEscherichia coliGene expressionGeneBiologyBiochemistry

Abstract

fetched live from OpenAlex

ABSTRACT We report colorimetric detection of SARS-CoV-2 viral RNA by an in vitro transcription/translation assay with crude E. coli extracts at room temperature, with the aid of body heat. Clinically-relevant concentrations of viral RNA (ca. 600 copies/test) were detected from synthetic RNA samples. The activation of cell-free gene expression was achieved by toehold-switch-mediated riboregulatory elements that are specific to viral RNA sequences. The colorimetric output was generated by the α-complementation of β-galactosidase ω-fragment (LacZω) with cell-free expressed LacZα, using an X-gal analogue as a substrate. The estimated cost of single reaction is <€1/test, which may facilitate diagnostic kit accessibility in developing countries.

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)0.001
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.008

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 head0.020
GPT teacher head0.242
Teacher spread0.222 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuemedRxivSame topicSARS-CoV-2 detection and testingFrench-language works237,207