Emerging Roles for Serotonin in Regulating Metabolism: New Implications for an Ancient Molecule
Bibliographic record
Abstract
Serotonin is a phylogenetically ancient biogenic amine that has played an integral role in maintaining energy homeostasis for billions of years. In mammals, serotonin produced within the central nervous system regulates behavior, suppresses appetite, and promotes energy expenditure by increasing sympathetic drive to brown adipose tissue. In addition to these central circuits, emerging evidence also suggests an important role for peripheral serotonin as a factor that enhances nutrient absorption and storage. Specifically, glucose and fatty acids stimulate the release of serotonin from the duodenum, promoting gut peristalsis and nutrient absorption. Serotonin also enters the bloodstream and interacts with multiple organs, priming the body for energy storage by promoting insulin secretion and de novo lipogenesis in the liver and white adipose tissue, while reducing lipolysis and the metabolic activity of brown and beige adipose tissue. Collectively, peripheral serotonin acts as an endocrine factor to promote the efficient storage of energy by upregulating lipid anabolism. Pharmacological inhibition of serotonin synthesis or signaling in key metabolic tissues are potential drug targets for obesity, type 2 diabetes, and nonalcoholic fatty liver disease (NAFLD).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".