Feeding and food availability modulate brain-derived neurotrophic factor, an orexigen with metabolic roles in zebrafish
Bibliographic record
Abstract
Emerging findings point to a role for brain-derived neurotrophic factor (BDNF) on feeding in mammals. However, its role on energy balance is unclear. Moreover, whether BDNF regulates energy homeostasis in non-mammals remain unknown. This research aimed to determine whether BDNF is a metabolic peptide in zebrafish. Our results demonstrate that BDNF mRNAs and protein, as well as mRNAs encoding its receptors trkb2, p75ntra and p75ntrb, are detectable in the zebrafish brain, foregut and liver. Intraperitoneal injection of BDNF increased food intake at 1, 2 and 6 h post-administration, and caused an upregulation of brain npy, agrp and orexin, foregut ghrelin, and hepatic leptin mRNAs, and a reduction in brain nucb2. Fasting for 7 days increased bdnf and p75ntrb mRNAs in the foregut, while decreased bdnf, trkb2, p75ntra and p75ntrb mRNAs in the brain and liver. Additionally, the expression of bdnf and its receptors increased preprandially, and decreased after a meal in the foregut and liver. Finally, we observed BDNF-induced changes in the expression and/or activity of enzymes involved in glucose and lipid metabolism in the liver. Overall, present results indicate that BDNF is a novel regulator of appetite and metabolism in fish, which is modulated by energy intake and food availability.
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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 | 0.000 |
| 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".