<i>In vitro</i> insulin treatment reverses changes elicited by nutrients in cellular metabolic processes that regulate food intake in fish
Bibliographic record
Abstract
This research assessed the direct effects of insulin on nutrient sensing mechanisms in the brain of rainbow trout (Oncorhynchus mykiss) using an in vitro approach. Cultured hypothalamus and hindbrain were exposed to 1 µM insulin for 3 h, and signals involved in appetite regulation and nutrient sensing mechanisms were measured. Additionally, the involvement of the phosphatidylinositide 3-kinase (PI3K)/protein kinase B (Akt) signaling pathway in the actions of insulin was studied by using the inhibitor wortmannin. Treatment with insulin alone did not elicit many changes on the appetite regulators and nutrient sensing-related genes and enzymes tested in the hypothalamus and hindbrain. However, we found that, when insulin and nutrients were added together, insulin reverses most of the effects exerted by nutrients alone, suggesting that insulin changes responsiveness to nutrients at the central level. Effects reversed by insulin include expression levels of genes related to the sensing of both glucose (slc2a2, slc5a1, gck, pck1, pklr, g6pcb, gys1, tas1r3 and nr1h3 in the hindbrain, and slc2a2, pklr and pck1 in the hypothalamus) and fatty acid (cd36 in the hindbrain, and cd36 and acly in the hypothalamus). Nutrient-induced changes in the activity of Acly and Cpt-1 in the hindbrain and of Pepck, Acly, Fas and Hoad in the hypothalamus were also reversed by insulin. Most of the insulin effects disappeared in the presence of wortmannin, suggesting the PI3K-Akt pathway is a mediator of the effects of insulin reported here. This study adds new information on our knowledge of the mechanisms regulating nutrient sensing in fish.
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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".