Dexamethasone ester treatment alters insulin-like growth factor-I, its binding proteins and thyroid status in finishing calves
Bibliographic record
Abstract
To improve carcass quality in finishing calves, some breeders use preparations containing corticoids alone or in association with other growth promoters. We have investigated the effects of dexamethasone treatment on insulin-like growth factor-I (IGF-I), IGF-binding proteins (IGFBP-2 and 3) and thyroid hormones (T3, T4, free T4). Limousine male calves were allocated to a control group (C) (n = 18) and a group (n = 18) that received dexamethasone esters (DEX). Blood and hepatic tissue samples were collected at slaughtering. Thyroid hormones and IGF-I plasma levels were measured by RIA and IGFBPs were evaluated by immunoblotting. Hepatic type I 5′deiodinase (5′D-I) activity was determined by enzyme assay and hepatic expression of mRNA for GH receptor, IGF-I, IGFBP-2, IGFBP-3 and type I deiodinase (D-I) was evaluated by dot blot analysis. Plasma IGF-I and IGFBP-3 levels were reduced by the DEX treatment (P < 0.001 and P < 0.01, respectively) while IGFBP-2 was unaffected. Significant plasma changes for IGF-I and IGFBP-3 were not corroborated by hepatic mRNA levels, for which only a slight non-significant decrease was noted. Growth hormone receptor mRNA expression was increased after treatment (P < 0.01). T3 plasma level was higher in DEX animals (P < 0.05) than in C calves. Finally, treatment increased 5′D-I activity in the hepatic tissue (P < 0.001) and seemed to also affect D-I mRNA expression (P = 0.1). In conclusion, dexamethasone ester injection in calves altered some of their endocrinological parameters; this could explain the catabolic action of corticoids in the bovine species. Key words: Calves, corticoids, IGF-I, IGFBPs, thyroid axis
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".