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Record W2037604947 · doi:10.1186/1756-0500-6-264

Control and target gene selection for studies on UV-induced genotoxicity in whales

2013· article· en· W2037604947 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Research Notes · 2013
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsTrent University
FundersNatural Environment Research CouncilConsejo Nacional de Ciencia y TecnologíaQueen Mary University of London
KeywordsGenotoxicitySelection (genetic algorithm)BiologyGeneticsGeneComputational biologyMedicineBioinformaticsComputer scienceInternal medicineArtificial intelligenceToxicity

Abstract

fetched live from OpenAlex

BACKGROUND: Despite international success in reducing ozone-depleting emissions, ultraviolet radiation (UV) is not expected to decrease for several decades. Thus, it is pressing to implement tools that allow investigating the capacity of wildlife to respond to excessive UV, particularly species like cetaceans that lack anatomical or physiological protection. One approach is to examine epidermal expression of key genes involved in genotoxic stress response pathways. However, quantitation of mRNA transcripts requires previous standardization, with accurate selection of control and target genes. The latter is particularly important when working with environmental stressors such as UV that can activate numerous genes. RESULTS: Using 20 epidermal biopsies from blue, fin and sperm whale, we found that the genes encoding the ribosomal proteins L4 and S18 (RPL4 and RPS18) were the most suitable to use as controls, followed by the genes encoding phosphoglycerate kinase 1 (PGK1) and succinate dehydrogenase complex subunit A (SDHA). A careful analysis of the transcription pathways known to be activated by UV-exposure in humans and mice led us to select as target genes those encoding for i) heat shock protein 70 (HSP70) an indicator of general cell stress, ii) tumour suppressor protein P53 (P53), a transcription factor activated by UV and other cell stressors, and iii) KIN17 (KIN), a cell cycle protein known to be up-regulated following UV exposure. These genes were successfully amplified in the three species and quantitation of their mRNA transcripts was standardised using RPL4 and RPS18. Using a larger sample set of 60 whale skin biopsies, we found that the target gene with highest expression was HSP70 and that its levels of transcription were correlated with those of KIN and P53. Expression of HSP70 and P53 were both related to microscopic sunburn lesions recorded in the whales' skin. CONCLUSION: This article presents groundwork data essential for future qPCR-based studies on the capacity of wildlife to resolve or limit UV-induced damage. The proposed target genes are HSP70, P53 and KIN, known to be involved in genotoxic stress pathways, and whose expression patterns can be accurately assessed by using two stable control genes, RPL4 and RPS18.

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.

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)0.001
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0000.000

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 head0.269
GPT teacher head0.456
Teacher spread0.187 · 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