Peripheral Serotonin Controls Dietary Fat Absorption and Chylomicron Secretion via 5-HT4 Receptor in Males
Bibliographic record
Abstract
Postprandial dyslipidemia is commonly present in people with type 2 diabetes and obesity and is characterized by overproduction of apolipoprotein B48-containing chylomicron particles from the intestine. Peripheral serotonin is emerging as a regulator of energy homeostasis with profound implications for obesity; however, its role in dietary fat absorption and chylomicron production is unknown. Chylomicron production was assessed in Syrian golden hamsters by administering an olive oil gavage and IP poloxamer to inhibit lipoprotein clearance. Administration of serotonin or selective serotonin reuptake inhibitor, fluoxetine, increased postprandial plasma triglyceride (TG) and TG-rich lipoproteins. Conversely, inhibiting serotonin synthesis pharmacologically by p-chlorophenylalanine (PCPA) led to a reduction in both the size and number of TG-rich lipoprotein particles, resulting in lower plasma TG and apolipoprotein B48 levels. The effects of PCPA occurred independently of gastric emptying and vagal afferent signaling. Inhibiting serotonin synthesis by PCPA led to increased TG within the intestinal lumen and elevated levels of TG and cholesterol in the stool when exposed to a high-fat/high-cholesterol diet. These findings imply compromised fat absorption, as evidenced by reduced lipase activity in the duodenum and lower levels of serum bile acids, which are indicative of intestinal bile acids. During the postprandial state, mRNA levels for serotonin receptors (5-HTRs) were upregulated in the proximal intestine. Administration of cisapride, a 5-HT4 receptor agonist, alleviated reductions in postprandial lipemia caused by serotonin synthesis inhibition, indicating that serotonin controls dietary fat absorption and chylomicron secretion via 5-HT4 receptor.
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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) | 0.002 | 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".