Effects of oral florfenicol and azithromycin on gut microbiota and adipogenesis in mice
Bibliographic record
Abstract
Certain antibiotics detected in urine are associated with childhood obesity. In the current experimental study, we investigated two representative antibiotics detected in urine, florfenicol and azithromycin, for their early effects on adipogenesis, gut microbiota, short-chain fatty acids (SCFAs), and bile acids in mice. Thirty C57BL/6 mice aged four weeks were randomly divided into three groups (florfenicol, azithromycin and control). The two experimental groups were administered florfenicol or azithromycin at 5 mg/kg/day for four weeks. Body weight was measured weekly. The composition of the gut microbiota, body fat, SCFAs, and bile acids in colon contents were measured at the end of the experiment. The composition of the gut microbiota was determined by sequencing the bacterial 16S rRNA gene. The concentration of SCFAs and bile acids was determined using gas chromatography and liquid chromatography coupled to tandem mass spectrometry, respectively. The composition of the gut microbiota indicated that the two antibiotics altered the gut microbiota composition and decreased its richness and diversity. At the phylum level, the ratio of Firmicutes/Bacteroidetes increased significantly in the antibiotic groups. At the genus level, there were declines in Christensenella, Gordonibacter and Anaerotruncus in the florfenicol group, in Lactobacillus in the azithromycin group, and in Alistipes, Desulfovibrio, Parasutterella and Rikenella in both the antibiotic groups. The decrease in Rikenella in the azithromycin group was particularly noticeable. The concentration of SCFAs and secondary bile acids decreased in the colon, but the concentration of primary bile acids increased. These findings indicated that florfenicol and azithromycin increased adipogenesis and altered gut microbiota composition, SCFA production, and bile acid metabolism, suggesting that exposure to antibiotics might be one risk factor for childhood obesity. More studies are needed to investigate the specific mechanisms.
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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 | 0.000 |
| 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) | 0.001 | 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".