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Record W3166748034 · doi:10.22215/etd/2019-13666

Regulation of DNA damage repair in response to freezing and anoxia in the wood frog, Rana sylvatica

2019· dissertation· en· W3166748034 on OpenAlexaff
Zephanie D. Lung

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsCarleton University
Fundersnot available
KeywordsDNA damageOxidative stressDNAAntioxidantDNA repairBiologyCell biologyReactive oxygen speciesBiochemistryChemistry

Abstract

fetched live from OpenAlex

The wood frog, Rana sylvatica, can survive freezing up to 65% of its body water in subzero temperatures and endures anoxia due to the cessation of vital functions while frozen.Fluctuating oxygen levels, particularly upon reperfusion and reoxygenation, increase vulnerability to reactive oxygen species and oxidative damage to macromolecules, including DNA.This thesis assesses DNA damage and responses by antioxidant capacity and DNA damage repair pathways to freezing or anoxia in wood frog liver and skeletal muscle.DNA oxidation remained largely constant, with observed increased antioxidant capacity in anoxia but not freezing.Although many observed DNA repair proteins displayed constant expression through stress and recovery, the MRN complex, Ku heterodimer, and ligation complexes, displayed changes in expression that vary based on tissue and stress.Overall, the data indicate that DNA damage is minimized through tissue and stress specific regulation of antioxidant capacity and DNA damage repair to preserve genomic integrity.

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)0.000
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.012
GPT teacher head0.236
Teacher spread0.224 · 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
Published2019
Admission routes1
Has abstractyes

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