Extracellular Vesicles in Pulmonary Hypertension: A Dangerous Liaison?
Bibliographic record
Abstract
The term pulmonary hypertension (PH) refers to different conditions, all characterized by increased pressure and resistance in the pulmonary arterial bed. PH has a wide range of causes (essentially, cardiovascular, pulmonary, or connective tissue disorders); however, idiopathic (i.e., without a clear cause) PH exists. This chronic, progressive, and sometimes devastating disease can finally lead to right heart failure and eventually death, through pulmonary vascular remodeling and dysfunction. The exact nature of PH pathophysiology is sometimes still unclear. Extracellular vesicles (EVs), previously known as apoptotic bodies, microvesicles, and exosomes, are small membrane-bound vesicles that are generated by almost all cell types and can be detected in a variety of physiological fluids. EVs are involved in intercellular communication, thus influencing immunological response, inflammation, embryogenesis, aging, and regenerative processes. Indeed, they transport chemokines, cytokines, lipids, RNA and miRNA, and other biologically active molecules. Although the precise functions of EVs are still not fully known, there is mounting evidence that they can play a significant role in the pathophysiology of PH. In this review, after briefly recapping the key stages of PH pathogenesis, we discuss the current evidence on the functions of EVs both as PH biomarkers and potential participants in the distinct pathways of disease progression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".