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Record W4405655654 · doi:10.1002/cbf.70036

Epigenetic Regulation by Histone Methylation and Demethylation in Freeze‐Tolerant Frog Kidney

2024· article· en· W4405655654 on OpenAlexafffund
Olawale O. Taiwo, Sarah A. Breedon, Kenneth B. Storey

Bibliographic record

VenueCell Biochemistry and Function · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHistone methyltransferaseHistoneEpigeneticsBiologyHistone methylationDemethylationMethylationCell biologyMethyltransferaseCancer epigeneticsHistone H4Histone H3Histone H2AGene expressionBiochemistryDNA methylationGene

Abstract

fetched live from OpenAlex

The wood frog (Rana sylvatica) endures whole-body freezing over the winter, with extensive extracellular ice formation and halted physiological activities. Epigenetic mechanisms, including reversible histone lysine methylation, enable quick alterations in gene expression, helping to maintain viability during freeze-thaw cycles. The present study evaluated eight histone lysine methyltransferases (KMTs), 10 histone lysine demethylases (KDMs), and 11 histone marks in wood frog kidneys. Using immunoblotting, significant changes in relative protein levels of multiple KMTs and KDMs were observed in response to freezing, with variable alterations during thawing. Specifically, the repressive methyl marks H3K27me1 and H4K20me3 significantly decreased during freezing, whereas H3K9me3, H3K27me3, and H3K36me2 decreased during thawing. These results demonstrate that the regulation of histone methylation and demethylation play crucial roles in controlling gene expression over the freeze-thaw cycle and the maintenance of normal renal physiology.

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 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 score0.064
Threshold uncertainty score0.818

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)0.0000.000

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 head0.005
GPT teacher head0.227
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 teacher head, 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

Citations5
Published2024
Admission routes2
Has abstractyes

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