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Record W2966222235 · doi:10.1787/fde13d2c-en

Adverse Outcome Pathway on Aryl hydrogen receptor activation leading to uroporphyria

2019· paratext· en· W2966222235 on OpenAlexaff
Amani Farhat, Gillian E. Manning, Jason M. O’Brien, Sean W. Kennedy

Bibliographic record

VenueOECD series on adverse outcome pathways · 2019
Typeparatext
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPorphyrin Metabolism and Disorders
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsUroporphyrinogen III decarboxylaseAryl hydrocarbon receptorHemeChemistryCytochrome P450EnzymePorphyriaArylLigand (biochemistry)StereochemistryBiochemistryReceptorTranscription factorBiologyEndocrinologyGene

Abstract

fetched live from OpenAlex

Hepatic uroporphyria is a disorder where the disturbance of heme biosynthesis results in accumulation and excretion of uroporphyrin, heptacarboxyl- and hexacarboxyl porphyrin: collectively referred to as highly carboxylated porphyrins (HCPs). The disorder is due to a homozygous mutation in uroporphyrinogen decarboxylase (UROD), an enzyme involved in the heme biosynthesis pathway, or may be chemically induced, which involves the inhibition of UROD. This AOP describes the linkages leading to chemically induced porphyria through the activation of the aryl hydrocarbon receptor (AHR), a ligand-activated transcription factor. AHR activation leads to the induction of cytochrome P450 1A2, a phase I metabolising enzyme, which in turn results in excessive oxidation of uroporphyrinogen. This oxidation produces a UROD inhibitor, preventing the conversion of uroporphyrinogen to coprouroporphyrinogen and increasing the synthesis of the UROD inhibitor in a positive feedback loop. The accumulation of uroporphyrinogen leads to its preferential oxidation and accumulation of HCP in various organs (Uroporphyria).

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), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.072

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 head0.025
GPT teacher head0.273
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations1
Published2019
Admission routes1
Has abstractyes

Explore more

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