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Record W1995457062 · doi:10.1021/ac025888j

DNA Damage Detection Technique Applying Time-Resolved Fluorescence Measurements

2002· article· en· W1995457062 on OpenAlexafffund
Gonzalo Cosa, Anne L. Vinette, J. R. N. McLean, J. C. Scaiano

Bibliographic record

VenueAnalytical Chemistry · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsUniversity of OttawaHealth Canada
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsDNAChemistryDNA damageFluorescenceBiophysicsMolecular biologyDNA repairBiochemistryOpticsBiologyPhysics

Abstract

fetched live from OpenAlex

A novel DNA damage detection technique based on the characteristic fluorescence lifetimes exhibited by Pico-Green-single-stranded DNA and -double-stranded DNA complexes is employed to establish the damage produced on DNA isolated from sheep white blood cells following gamma radiation. This technique, which incorporates key concepts such as alkaline unwinding buffers and higher unwinding rates of damaged DNA compared to undamaged DNA, allows for the differentiation of DNA damage resulting from doses of gamma radiation in the 0-100-Gy range, with the potential of analyzing samples consisting of as little as 10(4) cells. Experiments were carried out using commercial DNA sources as well as DNA isolated from sheep white blood cells, suggesting its potential for use with isolated DNA from virtually any eukaryotic cell.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.231
Teacher spread0.213 · 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.

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

Citations31
Published2002
Admission routes2
Has abstractyes

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