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Record W2965344954 · doi:10.1787/063e1bf4-en

Adverse Outcome Pathway on Aryl hydrogen receptor activation leading to early life stage mortality, via reduced VEGF

2019· paratext· en· W2965344954 on OpenAlexaff
Amani Farhat, Sean W. Kennedy

Bibliographic record

VenueOECD series on adverse outcome pathways · 2019
Typeparatext
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsAryl hydrocarbon receptor nuclear translocatorAryl hydrocarbon receptorVascular endothelial growth factorAngiogenesisInternal medicineHeart failureBiologyEndocrinologyCell biologyCancer researchChemistryTranscription factorMedicineVEGF receptorsBiochemistry

Abstract

fetched live from OpenAlex

Interference with endogenous developmental processes that are regulated by the aryl hydrocarbon receptor (AHR), through sustained exogenous activation, causes molecular, structural, and functional cardiac abnormalities in avian, mammalian and piscine embryos; this cardiotoxicity ultimately leads to severe oedema and embryo death in birds and fish and some strains of rat. There have been numerous proposed mechanisms of action for this toxicity profile, many of which include the dysregulation of vascular endothelial growth factor (VEGF). This AOP describes the indirect suppression of VEGF expression through the sequestration of the aryl hydrocarbon receptor nuclear translocator (ARNT) by AHR. ARNT is common dimerization partner for both AHR and hypoxia inducible factor alpha (HIF-1α), which stimulates angiogenesis through the transcriptional regulation of VEGF. The suppression of VEGF thereby reduces cardiomyocyte and endothelial cell proliferation, altering cardiovascular morphology and reducing cardiac output, which ultimately leads to congestive heart failure and death.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.115

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)0.0340.006

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 head0.052
GPT teacher head0.314
Teacher spread0.262 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

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