Pushing the limits of glucose kinetics: how rainbow trout cope with a carbohydrate overload
Bibliographic record
Abstract
Rainbow trout are generally considered to be poor glucoregulators. To evaluate this, exogenous glucose was administered to chronically hyperglycemic fish at twice the endogenous rate of hepatic production, and their ability to modulate glucose fluxes was tested. Our goals were to determine: (1) whether hyperglycemic fish maintain higher glucose fluxes than normal; (2) whether they can lower hepatic production (Ra glucose) or stimulate disposal (Rd glucose) to cope with a carbohydrate overload; and (3) an estimate of the relative importance of glucose as an oxidative fuel. Results show that hyperglycemic trout sustain elevated baseline Ra and Rd glucose of 10.6 ± 0.1 µmol kg(-1) min(-1) (or 30% above normal). If 50% of Rd glucose was oxidized as in mammals, glucose could account for 36 to 100% of metabolic rate when exogenous glucose is supplied. In response to exogenous glucose, rainbow trout can completely suppress hepatic glucose production and increase disposal 2.6-fold, even with chronically elevated baseline fluxes. Such large changes in fluxes limit the increase in blood glucose to 2.5-fold and are probably mediated by the effects of insulin on glucose transporters 2 and 4 and on key enzymes of carbohydrate metabolism. Without this strong and rapid modulation of glucose kinetics, glycemia would rise four times faster to reach dangerous levels, exceeding 100 mmol l(-1). Such responses are typical of mammals, but rather unexpected for an ectotherm. The impressive plasticity of glucose kinetics demonstrated here suggests that trout have a much better glucoregulatory capacity than is usually portrayed in the literature.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".