Complex Relation Between Diet and Phospholipid Fatty Acids in Children With Cystic Fibrosis
Bibliographic record
Abstract
OBJECTIVES: Altered total plasma n-6 and n-3 fatty acids are common in cystic fibrosis (CF). Whether alterations extend to plasma phosphatidylcholine (PC) and phosphatidylethanolamine (PE) and are explained by diet is unclear. The present study was to describe the dietary intake of a large group of children with CF and to determine whether dietary fat composition explains differences in plasma PC and PE fatty acids between children with and without CF. METHODS: Dietary intake was assessed using a food frequency questionnaire. Venous blood was collected. Plasma PC and PE were separately analyzed for fatty acids. RESULTS: Children with CF, n = 74, consumed more calories and fat (g/day and % energy), with significantly more saturates mainly from dairy foods and less polyunsaturates including linoleic acid (LA), arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) (% fat) than reference children, n = 71. A subset of children with CF, not differing in dietary intake from the larger group, had significantly lower LA and DHA, but higher EPA in plasma PC and had higher LA and lower ARA and DHA in plasma PE, compared to a subset of reference children. In both groups, LA intake and LA in plasma PC and PE were not associated. EPA and DHA intakes were positively associated with EPA and DHA, respectively, in plasma PC, but not PE, in reference children only. CONCLUSIONS: The fatty acid composition of plasma PC and PE is altered in CF. Fatty acid differences between children with and without CF are inconsistent between PC and PE and are not explained by dietary fat.
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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 | 0.002 |
| 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) | 0.002 | 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".