Unexpected effect of insulin on glucose disposal explains glucose intolerance of rainbow trout
Bibliographic record
Abstract
The physiological reasons why salmonids show glucose intolerance are unclear. In mammals, rapid clearance of a glucose load is mainly achieved through insulin-mediated inhibition of hepatic glucose production ( Ra) and stimulation of glucose disposal ( Rd), but the effects of insulin on Raand Rdglucose have never been measured in fish. The goal of this study was to characterize the impact of insulin on the glucose kinetics of rainbow trout in vivo. Glucose fluxes were measured by continuous infusion of [6-3H]glucose before and during 4 h of insulin administration. The phosphorylated form of the key signaling proteins Akt and S6 in the insulin cascade were also examined, confirming activation of this pathway in muscle but not liver. Results show that insulin inhibits trout Rdglucose from 8.6 ± 0.6 to 5.4 ± 0.5 µmol kg−1min−1: the opposite effect than classically seen in mammals. Such a different response may be explained by the contrasting effects of insulin on gluco/hexokinases of trout versus mammals. Insulin also reduced trout Rafrom 8.5 ± 0.7 to 4.8 ± 0.6 µmol·kg−1·min−1, whereas it can almost completely suppresses Rain mammals. The partial inhibition of Raglucose may be because insulin only affects gluconeogenesis but not glycogen breakdown in trout. The small mismatch between the responses to insulin for Rd(−37%) and Raglucose (−43%) gives trout a very limited capacity to decrease glycemia. We conclude that the glucose intolerance of rainbow trout can be explained by the inhibiting effect of insulin on glucose disposal.
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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 | 0.001 |
| 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".