Glucose, amino acids and fatty acids directly regulate ghrelin and NUCB2/nesfatin-1 in the intestine and hepatopancreas of goldfish (Carassius auratus) in vitro
Bibliographic record
Abstract
Ghrelin and nesfatin-1 are two peptidyl hormones primarily involved in food intake regulation. We previously reported that the amount of dietary carbohydrates, protein and lipids modulates the expression of these peptides in goldfish in vivo. In the present work, we aimed to characterize the effects of single nutrients on ghrelin and nesfatin-1 in the intestine and hepatopancreas. First, immunolocalization of ghrelin and NUCB2/nesfatin-1 in goldfish hepatopancreas cells was studied by immunohistochemistry. Second, the effects of 2 and 4hour-long exposures of cultured intestine and hepatopancreas sections to glucose, l-tryptophan, oleic acid, linolenic acid (LNA), eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) on ghrelin and nesfatin-1 gene and protein expression were studied. Co-localization of ghrelin and NUCB2/nesfatin-1 in the cytoplasm of goldfish hepatocytes was found. Exposure to glucose led to an upregulation of preproghrelin and a downregulation of nucb2/nesfatin-1 in the intestine. l-Tryptophan mainly decreased the expression of both peptides in the intestine and hepatopancreas. Fatty acids, in general, downregulated NUCB2/nesfatin-1 in the intestine, but only the longer and highly unsaturated fatty acids inhibited preproghrelin. EPA exposure led to a decrease in preproghrelin, and an increase in nucb2/nesfatin-1 expression in hepatopancreas after 2h. These results show that macronutrients exert a dose- and time-dependent, direct regulation of ghrelin and nesfatin-1 in the intestine and hepatopancreas, and suggest a role for these hormones in the digestive process and nutrient metabolism.
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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 | 0.001 |
| 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".