Human Milk Microbiota in an Indigenous Population Is Associated with Maternal Factors, Stage of Lactation, and Breastfeeding Practices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Human milk contains a diverse community of bacteria that are modified by maternal factors, but whether these or other factors are similar in developing countries has not been explored. Our objective was to determine whether the milk microbiota was modified by maternal age, BMI, parity, lactation stage, subclinical mastitis (SCM), and breastfeeding practices in the first 6 mo of lactation in an indigenous population from Guatemala. METHODS: = 86) and processed for 16S rRNA sequencing at the genus level. Microbial diversity and relative abundance were compared with maternal factors [age, BMI, parity, stage of lactation, SCM, and 3 breastfeeding practices (exclusive, predominant, mixed)] obtained through questionnaires. RESULTS: was found in mothers with a healthy BMI. Finally, distinct microbial communities differed by stage of lactation and by exclusive, predominant, or mixed breastfeeding practices. CONCLUSION: Milk bacterial communities in an indigenous community were associated with maternal factors. Higher microbial diversity was supported by having a healthy BMI, the absence of SCM, and by breastfeeding. Interestingly, breastfeeding practices when assessed by lactation stage were associated with distinct microbiota profiles.
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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 | 0.000 | 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 | 0.001 |
| 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 it