The 5-lipoxygenase/leukotriene pathway in preclinical models of cardiovascular disease
Bibliographic record
Abstract
Leukotrienes (LTs) derived from 5-lipoxygenase (5-LO) activity are most widely known for their actions during acute inflammation and asthma. 5-LO/LT pathway involvement in cardiovascular disease (CVD) pathogenesis has come to the forefront based on provocative human genetic/population and animal studies leading to the hypothesis that this pathway promotes atherosclerosis, abdominal aortic aneurysm, and myocardial infarction/reperfusion injury via increased leucocyte chemotaxis, vascular inflammation and enhanced permeability, and subsequent tissue/matrix degeneration. A series of pre-clinical studies have tested this hypothesis by means of genetic or pharmacological inhibition of either the LT biosynthesis axis (5-LO, 5-LO-activating protein, LTA(4) hydrolase, LTC(4) synthase) or the cognate LT receptors. Here, we summarize, compare, and analyse these animal studies and relate their findings to human disease pathogenesis. We draw a complex picture of 5-LO/LT participation in cardiovascular disorders, which is further complicated by marked differences between species. Moreover, we discuss how the cytokine footprint of the respective pathological conditions determines the expression level and hence, the contribution of components of the pathway to the overall disease state. Current knowledge implies a role for 5-LO and LTs during the early/acute phase of CVD, but our understanding of a putative 5-LO/LT involvement in more advanced stages of CVD is limited, thereby preventing simple extrapolation of findings from animal studies to humans.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".