Changes in Neutrophil Fatty Acid Composition and Its Relationship to Function Following Burn Injury in Humans
Bibliographic record
Abstract
Membrane lipid composition influences a number of immune functions including those of neutrophils, an important defense against infection after burn injury that has also been implicated in causing damage to host tissues. This study investigates compositional changes in phospholipid (PL) fatty acids and functional alterations of neutrophils immediately following and during recovery from burn injury. Ten patients with>10% total body surface area burn had blood drawn at specific times (0 days to>50 days) following burn injury. Neutrophil lipids were extracted, major PL classes separated by thin layer chromatography, and fatty acid composition determined using gas liquid chromatography. Neutrophil granularity and oxidative burst were measured in whole blood before and after stimulation with phorbol myristate acetate using flow cytometry. Neutrophils were less granular and had a greater oxidative burst early (<20 days) vs. later (>50 days) after burn injury. The arachidonic acid (20: 4n-6) content in all PL fractions was significantly reduced following burn injury and increased with recovery (p<0.05). The total n-6 fatty acid content of PS and PI increased with recovery (p<0.05). In conclusion, reduced 20: 4n-6 in neutrophil PL is suggestive of increased release or reduced synthesis of 20: 4n-6 early after burn. Lower granularity and higher oxidative burst immediately post-injury normalized with increases in 20: 4n-6. Compositional changes in neutrophil membranes early after burn may impact effector functions of neutrophils. Further work is needed to develop nutritional intervention strategies designed to modulate fatty acid composition of neutrophils to reduce the harmful effects of the oxidative burst while maintaining important infection defense mechanisms following burn injury.
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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 | 0.000 |
| 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".