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Record W1999202494 · doi:10.1002/mc.20454

The transcription factor Egr1 regulates the HIF‐1α gene during hypoxia

2008· article· en· W1999202494 on OpenAlexafffund
Sabina Sperandio, Jessyka Fortin, Roman Šášik, Lynda Robitaille, Jacques Corbeil, Ian de Belle

Bibliographic record

VenueMolecular Carcinogenesis · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsCentre hospitalier de l'Université Laval
FundersCanadian Institutes of Health ResearchUniversity of California, San DiegoTobacco-Related Disease Research Program
KeywordsEGR1BiologyDU145Transcription factorChromatin immunoprecipitationHypoxia-inducible factorsMolecular biologyDownregulation and upregulationCancer researchPromoterGene expressionTranscription (linguistics)Activating transcription factorGeneProstate cancerGeneticsCancer

Abstract

fetched live from OpenAlex

Using oligonucleotide expression microarrays we have examined the modulation of gene expression in the DU145 prostate cancer cell line. Our findings confirm that the Egr1 transcription factor is rapidly and transiently upregulated by hypoxia. Furthermore, we have demonstrated that HIF-1alpha mRNA is also transiently upregulated, as is its target gene VEGF. To elucidate the mechanism of the transcriptional upregulation of the HIF-1alpha gene, we have shown that Egr1 is able to directly bind to the HIF-1alpha promoter using chromatin immunoprecipitation. We also provide evidence that the binding of Egr1 is necessary for the trans-activation of the HIF-1alpha promoter. These studies highlight the importance for the Egr1 transcription factor in the hypoxic response in cultured prostate cancer cell lines, and indicate that the response of Egr1 is upstream of HIF-1 in these cells. These studies are the first demonstration that the HIF-1alpha transcription factor is targeted directly by Egr1 in 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 score0.003

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 head0.207
Teacher spread0.195 · 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

Citations84
Published2008
Admission routes2
Has abstractyes

Explore more

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