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Record W2103271174 · doi:10.1152/ajpregu.00125.2002

Glucocorticoid-mediated attenuation of the hsp70 response in trout hepatocytes involves the proteasome

2002· article· en· W2103271174 on OpenAlexaff
Adrienne N. Boone, Mathilakath M. Vijayan

Bibliographic record

VenueAmerican Journal of Physiology-Regulatory, Integrative and Comparative Physiology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHeat shock proteins research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsHsp70Rainbow troutGlucocorticoid receptorTroutInternal medicineEndocrinologyDownregulation and upregulationGlucocorticoidHeat shock proteinProteasome inhibitorHeat shockProteasomeCatabolismBiologyChemistryCell biologyBiochemistryMedicineMetabolism

Abstract

fetched live from OpenAlex

The physiological implication of elevated cortisol levels on cellular heat-shock protein 70 (hsp70) response was examined using primary cultures of rainbow trout (Oncorhynchus mykiss) hepatocytes. Trout hepatocytes treated with cortisol, the predominant glucocorticoid in teleosts, responded to the heat shock (+15 degrees C for 1 h) with a significant drop in hsp70 accumulation over a 24-h recovery period. [(35)S]methionine incorporation and pulse-chase studies confirmed that this cortisol impact was due to decreased hsp70 synthesis and not enhanced protein breakdown. Cortisol also significantly decreased glucocorticoid receptor (GR) expression in trout hepatocytes. This receptor downregulation was inhibited by the proteasomal inhibitors, lactacystin and MG-132, implying a role for the proteasome in GR downregulation by cortisol. Inhibiting the proteasome did not significantly modify heat-induced hsp70 accumulation in the absence of cortisol but significantly elevated hsp70 expression in the presence of cortisol in heat-shocked trout hepatocytes. Taken together, our results suggest proteasome-mediated GR degradation as a mechanism for the attenuation of hsp70 response by cortisol in heat-shocked hepatocytes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.908

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.288
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 teacher head, 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

Citations57
Published2002
Admission routes1
Has abstractyes

Explore more

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