Prebiotic Oligofructose Prevents Antibiotic‐Induced Obesity Risk and Improves Metabolic and Gut Microbiota Profiles in Rat Dams and Offspring
Bibliographic record
Abstract
SCOPE: Antibiotics in early life disrupt microbiota and increase obesity risk. Dietary agents such as prebiotics may reduce obesity risk. The authors examine how antibiotics administered with/without prebiotic oligofructose, alter metabolic and microbial outcomes in pregnant rats and their offspring. METHODS AND RESULTS: Pregnant rats are randomized to: 1) Control, 2) Antibiotic (ABT), 3) Prebiotic (PRE), 4) Antibiotic+Prebiotic (ABT+PRE) during the 3rd week of pregnancy and lactation. Offspring were fed a high fat/high sucrose (HFS) diet from 9-17 weeks of age to unmask obesity risk. ABT dams had higher body weight, body fat and leptin during lactation than all other groups. Prebiotics attenuate these outcomes and increase cecal Bifidobacterium. ABT offspring have higher body weight, fat mass, and liver triglycerides after HFS diet, with a stronger phenotype in males; prebiotics attenuate these. At weaning, male ABT offspring have lower Lactobacillus while PRE and ABT+PRE offspring had higher Bifidobacterium and Collinsella. Fecal microbiota transfer of adult offspring cecal matter could not reliably transfer the obese ABT phenotype. CONCLUSIONS: Antibiotic use during pregnancy/lactation increases adiposity and impairs post-partum weight loss in dams. Co-administering prebiotics with antibiotics in rat dams prevented obesity risk in offspring and is associated with altered gut microbiota.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".