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Record W1993487480 · doi:10.1073/pnas.0810067106

Integrative analysis of HIF binding and transactivation reveals its role in maintaining histone methylation homeostasis

2009· article· en· W1993487480 on OpenAlexaff
Xiaobo Xia, Madeleine E. Lemieux, Wěi Li, Jason S. Carroll, Myles Brown, X. Shirley Liu, Andrew L. Kung

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsPediatric Oncology Group
FundersNational Human Genome Research InstituteNational Institutes of HealthSidney Kimmel FoundationDana-Farber Cancer Institute
KeywordsTransactivationEpigeneticsHistoneBiologyHypoxia-inducible factorsCellular adaptationRegulation of gene expressionCell biologyHypoxia (environmental)MethylationGene expressionTranscription factorGeneticsGeneChemistryOxygen

Abstract

fetched live from OpenAlex

Adaptation to hypoxia is mediated through a coordinated transcriptional response driven largely by hypoxia-inducible factor 1 (HIF-1). We used ChIP-chip and gene expression profiling to identify direct targets of HIF-1 transactivation on a genome-wide scale. Several hundred direct HIF-1 targets were identified and, as expected, were highly enriched for proteins that facilitate metabolic adaptation to hypoxia. Surprisingly, there was also striking enrichment for the family of 2-oxoglutarate dioxygenases, including the jumonji-domain histone demethylases. We demonstrate that these histone demethylases are direct HIF targets, and their up-regulation helps maintain epigenetic homeostasis under hypoxic conditions. These results suggest that the coordinated increase in expression of several oxygen-dependent enzymes by HIF may help compensate for decreased levels of oxygen under conditions of cellular 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 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 head0.022
GPT teacher head0.315
Teacher spread0.293 · 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

Citations408
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicCancer, Hypoxia, and MetabolismFrench-language works237,207