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Record W2319870038 · doi:10.1089/ham.2014.1016

Hypoxia and Environmental Epigenetics

2014· review· en· W2319870038 on OpenAlexafffund
Carolyn J. Brown, James L. Rupert

Bibliographic record

VenueHigh Altitude Medicine & Biology · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHypoxia (environmental)EpigeneticsMedicineBiologyPsychologyChemistryGeneticsOxygen

Abstract

fetched live from OpenAlex

Epigenetics refers to long-term modifications of gene activity that can be inherited, either somatically or transgenerationally, but that are independent of alterations in the primary base sequence of the organism's DNA. These changes can include chemical modifications of both the DNA bases and the proteins that associate with the DNA helices to form chromatin, the nucleic acid:protein complex of which the chromosomes are comprised. Epigenetic modifications can affect the accessibility of the DNA for transcription factors (the DNA-binding proteins that specify which genes are to be active or silent by modulating the recruitment of the transcriptional machinery that reads the information encoded in the sequence) and thereby regulate the expression of genes and alter the phenotype of the organism. Epigenetic marks can also be re-established following mitosis, allowing patterns of differential gene expression to be transmitted from one cell generation to the next, and can even be maintained through meiosis, allowing transgenerational transfer of regulatory cues. Unlike the information encoded in the DNA sequence, which is invariant between most cell types and over time, epigenetic information is tissue specific and can change in response to exogenous and endogenous perturbations. This responsive capacity enables a sensitive and reactive system that can optimize gene expression in relevant tissue in response to environmental change. The realization that organisms are capable of genetically 'reprograming' themselves as well as 'preprograming' future cells, and even future offspring to optimize gene expression for a given environment may have tremendous ramifications on our understanding of both acclimatization and adaptation to hypoxia.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.020
GPT teacher head0.314
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations23
Published2014
Admission routes2
Has abstractyes

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