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Record W2110228021 · doi:10.1530/joe-15-0186

Chronic cortisol and the regulation of food intake and the endocrine growth axis in rainbow trout

2015· article· en· W2110228021 on OpenAlexafffund
Barry N. Madison, Sara Tavakoli, Sarah Krämer, Nicholas J. Bernier

Bibliographic record

VenueJournal of Endocrinology · 2015
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEndocrinologyInternal medicineEndocrine systemBiologyHypophysectomyAppetiteChronic stressMedicineHormone

Abstract

fetched live from OpenAlex

To gain a better understanding of the mechanisms by which cortisol suppresses growth during chronic stress in fish, we characterized the effects of chronic cortisol on food intake, mass gain, the expression of appetite-regulating factors, and the activity of the GH/IGF axis. Fish given osmotic pumps that maintained plasma cortisol levels at ∼70 or 116 ng/ml for 34 days were sampled 14, 28 and 42 days post-implantation. Relative to shams, the cortisol treatments reduced food intake by 40-60% and elicited marked increases in liver leptin (lep-a1) and brain preoptic area (POA) corticotropin-releasing factor (crf) mRNA levels. The cortisol treatments also elicited 40-80% reductions in mass gain associated with increases in pituitary gh, liver gh receptor (ghr), liver igfI and igf binding protein (igfbp)-1 and -2 mRNA levels, reduced plasma GH and no change in plasma IGF1. During recovery, while plasma GH and pituitary gh, liver ghr and igfI gene expression did not differ between treatments, the high cortisol-treated fish had lower plasma IGF1 and elevated liver igfbp1 mRNA levels. Finally, the cortisol-treated fish had higher plasma glucose levels, reduced liver glycogen and lipid reserves, and muscle lipid content. Thus, our findings suggest that the growth-suppressing effects of chronic cortisol in rainbow trout result from reduced food intake mediated at least in part by increases in liver lep-a1 and POA crf mRNA, from sustained increases in hepatic igfbp1 expression that reduce the growth-promoting actions of the GH/IGF axis, and from a mobilization of energy reserves.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score0.403

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.227
Teacher spread0.215 · 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 designTheoretical or conceptual
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

Citations103
Published2015
Admission routes2
Has abstractyes

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