MicroRNA networks in pulmonary arterial hypertension
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE OF REVIEW: Pulmonary arterial hypertension (PAH) is a rare disease with poor prognosis and no therapeutics. PAH is characterized by severe remodeling of precapillary pulmonary arteries, leading to increased vascular resistance, pulmonary hypertension compensatory right ventricular hypertrophy, then heart failure and death. PAH pathogenesis shares similarities with carcinogenesis such as excessive cell proliferation, apoptosis resistance, metabolic shifts, or phenotypic transition. Although PAH is not a cancer, comparison of analogous mechanisms between PAH and cancer led to the concept of a cancer-like disease to emerge. MicroRNAs (miRNAs) are small noncoding RNAs involved in the regulation of posttranscriptional gene expression. miRNA dysregulations have been reported as promoter of the development of various diseases including cancers. RECENT FINDINGS: Recent studies revealed that miRNA dysregulations also occur in PAH pathogenesis. In PAH, different miRNAs have been implicated to be the main features of PAH pathophysiology (in pulmonary inflammation, vascular remodeling, angiogenesis, and right heart hypertrophy). SUMMARY: The review summarizes the implication of miRNA dysregulation in PAH development and discusses the similarities and differences with those observed in cancers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 it