Evaluation of Endocan as a Treatment for Acute Inflammatory Respiratory Failure
Bibliographic record
Abstract
Background: Acute respiratory distress syndrome (ARDS) is a life-threatening condition resulting from acute pulmonary inflammation. However, no specific treatment for ARDS has yet been developed. Previous findings suggest that lung injuries related to ARDS could be regulated by endocan (Esm-1). The aim of this study was to evaluate the potential efficiency of endocan in the treatment of ARDS. Methods: We first compared the features of acute pulmonary inflammation and the severity of hypoxemia in a tracheal LPS-induced acute lung injury (ALI) model performed in knockout (Esm1−/−) and wild type (WT) littermate C57Bl/6 mice. Next, we assessed the effects of a continuous infusion of glycosylated murine endocan in our ALI model in Esm1−/− mice. Results: In our ALI model, we report higher alveolar leukocytes (p < 0.001), neutrophils (p < 0.001), and MPO (p < 0.001), and lower blood oxygenation (p < 0.001) in Esm1−/− mice compared to WT mice. Continuous delivery of glycosylated murine endocan after LPS-induced ALI resulted in decreased alveolar leukocytes (p = 0.012) and neutrophils (p = 0.012), higher blood oxygenation levels (p < 0.001), and reduced histological lung injury (p = 0.04), compared to mice treated with PBS. Conclusions: Endocan appears to be an effective treatment in an ARDS-like model in C57Bl/6 mice.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".