Fecal Short-Chain Fatty Acid Variations by Breastfeeding Status in Infants at 4 Months: Differences in Relative versus Absolute Concentrations
Bibliographic record
Abstract
Our gut microbiota provide a number of important functions, one of which is the metabolism of dietary fiber and other macronutrients that are undigested by the host. The main products of this fermentation process are short-chain fatty acids (SCFAs) and other intermediate metabolites including lactate and succinate. Production of these metabolites is dependent on diet and gut microbiota composition. There is increasing evidence for the role of SCFAs in host physiology and metabolic processes as well as chronic inflammatory conditions such as allergic disease and obesity. We aimed to investigate differences in fecal SCFAs and intermediate metabolites in 163 infants at 3-5 months of age according to breastfeeding status. Compared to no exposure to human milk at time of fecal sample collection, exclusive breastfeeding was associated with lower absolute concentrations of total SCFAs, acetate, butyrate, propionate, valerate, isobutyrate, and isovalerate, yet higher concentrations of lactate. Further, the relative proportion of acetate was higher with exclusive breastfeeding. Compared to non-breastfed infants, those exclusively breastfed were four times more likely (aOR 4.50, 95% CI 1.58-12.82) to have a higher proportion of acetate relative to other SCFAs in their gut. This association was independent of birth mode, intrapartum antibiotics, infant sex, age, recruitment site, and maternal BMI or socioeconomic status. Our study confirms that breastfeeding strongly influences the composition of fecal microbial metabolites in infancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".