Obese-associated gut microbes and derived phenolic metabolite as mediators of excessive motivation for food reward
Bibliographic record
Abstract
Abstract Background Excessive hedonic consumption is one of the main drivers for weight gain. Identifying contributors of this dysregulation would help to tackle obesity. The gut microbiome is altered during obesity and regulates host metabolism including food intake. Results By using fecal material transplantation (FMT) from lean or obese mice into recipient mice, we demonstrated that gut microbes play a role in the regulation of food reward (i.e., wanting and learning processes associated with hedonic food intake) and could be responsible for excessive motivation to obtain sucrose pellets and alterations in dopaminergic and opioid markers in reward-related brain areas. Through untargeted metabolomic approach, we identified the 3-(3’-hydroxyphenyl)propanoic acid (33HPP) as highly positively correlated with the motivation. By administrating 33HPP in mice, we revealed its effects on food reward. Conclusions Our data suggest that targeting the gut microbiota and its metabolites would be an interesting therapeutic strategy for compulsive eating, preventing inappropriate hedonic food intake. Video Abstract
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.194 | 0.028 |
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".