Increased gut serotonin production in response to bisphenol A structural analogs may contribute to their obesogenic effects
Bibliographic record
Abstract
Obesogens are synthetic, environmental chemicals that can disrupt endocrine control of metabolism and contribute to the risk of obesity and metabolic disease. Bisphenol A (BPA) is one of the most studied obesogens. There is considerable evidence that BPA exposure is associated with weight gain, increased adiposity, poor blood glucose control, and nonalcoholic fatty liver disease in animal models and human populations. Increased usage of structural analogs of BPA has occurred in response to legislation banning their use in some commercial products. However, BPA analogs may also cause some of the same metabolic impairments because of common mechanisms of action. One key effector that is altered by BPA and its analogs is serotonin, however, it is unknown if BPA-induced changes in peripheral serotonin pathways underlie metabolic perturbations seen with BPA exposure. Upon ingestion, BPA and its analogs act as endocrine-disrupting chemicals in the gastrointestinal tract to influence serotonin production by the gut, where over 95% of serotonin is produced. The purpose of this review is to evaluate how BPA and its analogs alter gut serotonin regulation and then discuss how disruption of serotonergic networks influences host metabolism. We also provide evidence that BPA and its analogs enhance serotonin production in gut enterochromaffin cells. Taken together, we propose that BPA and many BPA analogs represent endocrine-disrupting chemicals that can influence host metabolism through the endogenous production of gut-derived factors, such as serotonin.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".