Hexarelin modulates lung mechanics, inflammation, and fibrosis in acute lung injury
Bibliographic record
Abstract
Introduction: Acute respiratory distress syndrome (ARDS) is an acute form of diffuse lung injury characterized by (i) an intense inflammatory response, (ii) increased pulmonary vascular permeability, and (iii) the loss of respiratory pulmonary tissue. In this article we explore the therapeutic potential of hexarelin, a synthetic hexapeptide growth hormone secretagogue (GHS), in an experimental model of ARDS. Hexarelin has anti-inflammatory properties and demonstrates cardiovascular-protective activities including the inhibition of cardiomyocyte apoptosis and cardiac fibrosis, both of which may involve the angiotensin-converting enzyme (ACE) system. Methods: In our experimental model, ARDS was induced by the instillation of 100 mM HCl into the right bronchus; these mice were treated with hexarelin (320 μg/kg, ip) before (Pre) or after (Post) HCl challenge, or with vehicle. Respiratory system compliance, blood gas analysis, and differential cell counts in a selective bronchoalveolar lavage (BAL) were determined 6 or 24 hours after HCl instillation. In an extended study, mice were observed for a subsequent 14 days in order to assess lung fibrosis. Results: Hexarelin induced a significant improvement in lung compliance and a reduction of the number of total immune cells in BAL 24 hours after HCl instillation, accompanied with a lower recruitment of neutrophils compared with the vehicle group. At day 14, hexarelin-treated mice presented with less pulmonary collagen deposition compared with vehicle-treated controls. Conclusions: Our data suggest that hexarelin can inhibit the early phase of the inflammatory response in a murine model of HCl-induced ARDS, thereby blunting lung remodeling processes and fibrotic development.
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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".