The Antifibrotic Effects of Inhaled Treprostinil: An Emerging Option for ILD
Bibliographic record
Abstract
Interstitial lung diseases (ILD) encompasses a heterogeneous group of parenchymal lung diseases characterized by variable amounts of inflammation and fibrosis. The targeting of fibroblasts and myofibroblasts with antifibrotic treatments is a potential therapeutic target for these potentially fatal diseases. Treprostinil is unique among the prostacyclin mimetics in that it has distinct actions at additional prostaglandin receptors. Preclinical and clinical evidence suggests that treprostinil has antifibrotic effects through the activation of the prostaglandin E receptor 2 (EP 2 ), the prostaglandin D receptor 1 (DP 1 ), and peroxisome proliferator-activated receptors (PPAR). In vivo studies of EP 2 and the DP 1 have found that administration of treprostinil resulted in a reduction in cell proliferation, reduced collagen secretion and synthesis, and reduced lung inflammation and fibrosis. In vitro and in vivo studies of PPARβ and PPARγ demonstrated that treprostinil inhibited fibroblast proliferation in a dose-dependent manner. Clinical data from a post hoc analysis of the INCREASE trial found that inhaled treprostinil improved forced vital capacity in the overall population as well as in idiopathic interstitial pneumonia and idiopathic pulmonary fibrosis subgroups. These preclinical and clinical findings suggest a dual benefit of treprostinil through the amelioration of both lung fibrosis and pulmonary hypertension.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| 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".