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Record W2396480108 · doi:10.1007/978-1-61779-037-9_10

Detection of Viral microRNA with S1 Nuclease Protection Assay

2011· article· en· W2396480108 on OpenAlexfundno aff
Matthias John, Sébastien Pfeffer

Bibliographic record

VenueMethods in molecular biology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsnot available
FundersInstitute of Cancer ResearchInstitut National Du CancerCentre National de la Recherche ScientifiqueInternational Business Machines Corporation
KeywordsNucleaseRNAOligonucleotideDNABiologyNuclease protection assayMolecular biologyRNA extractionNucleic acidNon-coding RNABiochemistryGene

Abstract

fetched live from OpenAlex

Mammalian host cells and their viral pathogens express and make use of short noncoding RNA molecules to control the infectious cycle. In order to understand their physiological role, it is necessary to develop tools for detection and quantification of these molecules. Here, we present a simple, specific, and very sensitive protocol using short radioactive DNA oligonucleotides for hybridization to homologous RNA target in a nuclease protection assay. The S1 nuclease from Aspergillus oryzae degrades single-stranded oligonucleotides composed of either deoxynucleotides or ribonucleotides. In contrast, double-stranded DNA, double-stranded RNA, or DNA-RNA hybrids are resistant to digestion. Subsequent analysis of the protected DNA oligonucleotide with denaturing gel electrophoresis results in radioactive signals strictly proportional to the abundance of short RNA in a given sample. The protocol works equally well for in vitro cell culture assays and for tissue samples obtained from in vivo experiments.

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)0.002
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.024
GPT teacher head0.316
Teacher spread0.292 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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