Glucose intolerance induced by glucocorticoid excess is further impaired by co-administration with β-hydroxy-β-methylbutyrate in rats
Bibliographic record
Abstract
Glucocorticoid (GC) excess alters glucose homeostasis and promotes modifications in murinometric and anthropometric parameters in rodents and humans, respectively. β-hydroxy-β-methylbutyrate (HMB), a leucine metabolite, has been proposed as a nutritional strategy for preventing muscle wasting, but few data regarding its effects on glucose homeostasis are available. Here, we analyzed whether the effects of GC excess on glucose homeostasis may be attenuated or exacerbated by the concomitant ingestion of HMB. Adult Wistar rats (90-days-old) were assigned to four groups: (1) vehicle treated (Ctl), (2) dexamethasone (DEX) treated (Dex), (3) HMB treated (Hmb), and (4) DEX plus HMB treated (DexHmb). Dex groups received DEX (1 mg·kg body weight (BW)(-1), intraperitoneal) for 5 consecutive days. HMB groups ingested HMB (320 mg·kg BW(-1), oral gavage) for the same 5 days. HMB ingestion did not attenuate the effects of DEX on food intake and body weight loss, changes in masses of several organs, insulin resistance, and glucose intolerance (p > 0.05). In fact, in DexHmb rats, there was increased fasting glycemia and exacerbated glucose intolerance with the main effect attributed to DEX treatment (p < 0.05). HMB exerted no attenuating effect on plasma triacylglycerol levels from DexHmb rats, but it seems to attenuate the lipolysis induced by β-adrenergic stimulation (20 μmol·L(-1) isoproterenol) in fragments of retroperitoneal adipose tissue from DexHmb rats. Therefore, HMB does not attenuate the diabetogenic characteristics of GC excess. In fact, the data suggest that HMB may exacerbate GC-induced glucose intolerance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".