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Record W2056110843 · doi:10.1139/cjpp-2013-0238

Loss of hepatic aryl hydrocarbon receptor protein in adrenalectomized rats does not involve altered levels of the receptor’s cytoplasmic chaperones

2013· article· en· W2056110843 on OpenAlexafffundvenue
Chunja Lee, Anne K. Mullen Grey, David S. Riddick

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2013
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchCancer Research Institute
KeywordsAryl hydrocarbon receptorInternal medicineEndocrinologyHsp90Heat shock proteinReceptorMessenger RNAChaperone (clinical)Glucocorticoid receptorBiologyHepatocyteCytoplasmAdrenalectomyGlucocorticoidChemistryCell biologyBiochemistryTranscription factorIn vitroMedicineGene

Abstract

fetched live from OpenAlex

The aryl hydrocarbon receptor (AHR) plays physiological roles and mediates adaptive and toxic responses to environmental pollutants. Adrenalectomized rats display decreased hepatic AHR protein levels, with no change in mRNA, and selectively impaired induction of cytochrome P450 1B1. This is similar to reported phenotypes for mice with hepatocyte-specific conditional deletion of AHR-interacting protein (AIP), a chaperone protein of the cytoplasmic AHR complex. In this study, we demonstrated that adrenalectomy (ADX) and acute dexamethasone (DEX) treatment do not alter hepatic AIP mRNA or protein levels. Also, hepatic protein levels of the 90 kDa heat shock protein and p23 were not altered by ADX or acute DEX treatment. These results suggest that the loss of rat hepatic AHR protein following ADX cannot be explained by changes in the levels of the receptor's cytoplasmic chaperone proteins.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.258
Teacher spread0.241 · 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

Citations1
Published2013
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Physiology and Pharmacology→Same topicAdipose Tissue and Metabolism→French-language works237,207→