Urinary Cysteinyl Leukotrienes as Biomarkers of Endothelial Activation, Inflammation and Oxidative Stress and Their Relationship with Organ Dysfunction in Human Septic Shock
Bibliographic record
Abstract
Cysteinyl leukotrienes (CysLT) are potent vascular leakage-promoting agents but have been scarcely explored in human septic shock (SS). We evaluated CysLT at admission and during hospitalization and their correlation with endothelial dysfunction, inflammation, oxidative stress, the renin-angiotensin-aldosterone system, and cardiac, renal, respiratory, and hepatic parameters in SS patients. Blood and spot-urine samples were collected at days 1-2 (admission), 3-4, and 5-8 in SS patients (n = 13) and at a single time point in controls (n = 22). Urinary CysLT (u-CysLT) and isoprostanes, plasma, and urinary angiotensinogen, serum myeloperoxidase, and IL-10 were quantified by ELISA. Serum intercellular-adhesion molecule-1, vascular cell-adhesion molecule-1, E-selectin, tumor necrosis factor-α, IL-1β, and IL-6 were measured by multiplex immunoassays. Routine markers were evaluated using automated analyzers. At admission, SS patients had increased u-CysLT, endothelial activation, inflammation, oxidative stress, and plasma and urinary angiotensinogen, as well as cardiac, respiratory, hepatic, and renal injury/dysfunction. There were no changes in u-CysLT during hospitalization. Both correlation and multivariate analyses showed positive relationships of u-CysLT with endothelial activation, inflammation, oxidative stress, proteinuria, and hepatic injury/dysfunction markers. These results suggest that u-CysLT may be potential non-invasive biomarkers for monitoring the pathophysiological mechanisms underlying SS, as well as putative therapeutic targets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".