Sex-dependent associations between human milk oligosaccharides and malaria outcomes in breastfeeding Ugandan children
Bibliographic record
Abstract
Abstract Human milk oligosaccharides (HMOs), whose compositions vary between secretor and non-secretor mothers, protect breastfeeding children against various diseases. We investigated the relationship between HMOs in Ugandan secretor mothers and malaria outcomes in their children. Malaria outcomes in breastfeeding children followed up over seven months were classified as malaria-free and asymptomatic, mild, or severe malaria. A single human milk sample collected from each mother was analyzed for HMOs. Significantly higher 2’fucosyllactose (2’FL) and lacto-N-fucopentaose I (LNFP I) concentrations were observed in mothers of malaria-free children, and significantly higher lacto-N-tetraose (LNT) concentrations were observed in mothers of children with asymptomatic malaria. Concentrations of five HMOs, 3-fucosyllactose (3 FL), 3’sialyllactose (3’SL), difucosyllactose (DFLac), lacto-N-fucopentaose II (LNFP II), and sialyllacto- N -tetraose b (LSTb); and two HMOs, difucosyllacto-N-tetrose (DFLNT) and fucosyllacto-N-hexaose (FLNH) were significantly higher in mothers of malaria-infected children and children with severe malaria, respectively. Sex-dependent associations were observed for some HMOs.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".