Alcohol consumption during pregnancy differentially affects the fecal microbiota of dams and offspring
Bibliographic record
Abstract
Microbiota imbalances are linked to inflammation and disease, as well as neurodevelopmental conditions where they may contribute to behavioral, physiological, and central nervous system dysfunction. By contrast, the role of the microbiota in Fetal Alcohol Spectrum Disorder (FASD), the group of neurodevelopmental conditions that can occur following prenatal alcohol exposure (PAE), has not received similar attention. Here we utilized a rodent model of alcohol consumption during pregnancy to characterize the impact of alcohol on the microbiota of dam-offspring dyads. Overall, bacterial diversity decreased in alcohol-consuming dams and community composition differed from that of controls in alcohol-consuming dams and their offspring. Bacterial taxa and predicted biochemical pathway composition were also altered with alcohol consumption/exposure; however, there was minimal overlap between the changes in dams and offspring. These findings illuminate the potential importance of the microbiota in the pathophysiology of FASD and support investigation into novel microbiota-based interventions.
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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 | 0.001 |
| 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 | 0.001 |
| 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".