Passion fruit peel extract attenuates bleomycin-induced pulmonary fibrosis in mice
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis is a progressive fatal lung disease characterized by excessive collagen deposition, with no effective treatments. We investigated the efficacy of natural products with high anti-inflammatory activity, such as passion fruit peel extract (PFPE), in a mouse model of bleomycin-induced pulmonary fibrosis (PF). C57BL/6J mice were subjected to a single intratracheal instillation of bleomycin to induce PF. Daily PFPE treatment significantly reduced loss of body mass and mortality rate in mice compared with those treated with bleomycin. While bleomycin-induced PF resulted in elevated total numbers of inflammatory cells, macrophages, lymphocytes, and neutrophils in bronchoalveolar lavage fluid on both days 7 and 21, PFPE administration significantly attenuated these phenomena compared with bleomycin group. On day 7, the decreased superoxide dismutase and myeloperoxidase activities observed in the bleomycin group were significantly restored with PFPE treatment. On day 21, enhanced hydroxyproline deposition in the bleomycin group was also suppressed by PFPE administration. PFPE treatment significantly attenuated extensive inflammatory cell infiltration and accumulation of collagen in lung tissue sections of bleomycin-induced mice on days 7 and 21, respectively. Our results indicate that administration of PFPE decreased bleomycin-induced PF because of anti-inflammatory and antioxidant activities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".