Whole-blood PUFA and associations with markers of nutritional and health status in acutely malnourished children in Cambodia
Bibliographic record
Abstract
OBJECTIVE: To measure fatty acid composition, particularly whole-blood PUFA content, in acutely malnourished children and identify associations with markers of nutritional and health status. DESIGN: PUFA were assessed in dried blood spots obtained from a cross-sectional study. Nutritional and health status were assessed by anthropometry, haemoglobinopathies, inflammation and blood counts. SETTING: Cambodia. PARTICIPANTS: The study was conducted with 174 children aged 0·5-18 years with acute malnutrition. RESULTS: Among total fatty acids (FA), the relative percentage of total PUFA was 20 % FA, with 14 % of the children having very low PUFA (mead acid (MA):arachidonic acid (AA) >0·02, n-6 docosapentaenoic acid:DHA >0·2 and total n-6:n-3 PUFA >10·5). Wasting was not associated with any PUFA. Stunting and low height were consistently positively associated with total PUFA and positively with n-6 PUFA. Height was positively associated with n-3 long-chain PUFA (LCPUFA). The presence of haemoglobinopathies or inflammation was positively associated with MA:AA, but not total PUFA. Elevated blood platelet counts were positively correlated with linoleic acid and appeared to be influenced by anaemia (P = 0·010) and inflammation (P = 0·002). Monocyte counts were high during inflammation (P = 0·052) and correlated positively with n-6 LCPUFA and n-3 LCPUFA. CONCLUSIONS: Children with acute malnutrition or stunting had low PUFA, while elevated platelets and monocytes were associated with high PUFA. In acutely malnourished children, inflammation could lead to elevated blood cell counts resulting in increased whole-blood PUFA which does not reflect dietary intake or nutritional status.
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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 | 0.001 | 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) | 0.001 | 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".