The Plasma Oxylipidome Links Smoking Status to Peripheral Artery Disease
Bibliographic record
Abstract
Peripheral artery disease (PAD) is prevalent among individuals with a history of tobacco smoking. Although oxidation of lipids may contribute to atherogenesis in vascular disease, enzymatically and nonenzymatically produced oxidized lipids can have varying and contrasting physiological effects. The underlying mechanisms of atherogenic vulnerability can be better elucidated with the recent advances in oxylipidome quantification using HPLC-MS/MS technology. In a randomized, controlled clinical trial, the plasma oxylipidome was analyzed in participants living with PAD by smoking status (n = 98) and in nonsmoking comparators without chronic disease (n = 20). Individuals with PAD had approximately a four-fold higher level of total plasma oxylipins versus the comparator. Cessation of smoking in individuals with PAD was associated with significantly lower levels of linoleic acid-derived TriHOMEs, greater levels of omega-3 fatty acid-derived oxylipins, and greater levels of nonfragmented oxidized phosphatidylcholines (OxPCs). Individuals living with PAD but without a history of smoking, exhibited higher levels of the putative atherogenic fragmented OxPCs versus individuals who currently or previously smoked. These data implicate the plasma oxylipidome in PAD and that smoking cessation is associated with a less inflammatory profile. Furthermore, fragmented OxPCs may play a more significant role in the pathophysiology of PAD in individuals without a history of smoking.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".