Limitations and Flaws of Preclinical Pulmonary Hypertension Studies
Bibliographic record
Abstract
Despite advances in our understanding of the disease, significant therapeutic gaps remain for pulmonary arterial hypertension (PAH). Indeed, no cure exists yet for this devastating disease, and very few innovative therapies beyond the traditional pathways of endothelial dysfunction have reached late clinical trial phases in PAH. While there are inherent limitations to the currently available animal models of PAH, the delayed translation of innovative therapies to the clinic may also relate to flawed preclinical research methodologies. The present article discusses the limitations and flaws in the design of preclinical PH trials and discusses opportunities to create preclinical studies with improved predictive value in identifying key mechanisms involved in PAH development and progression and guiding early phase drug development in PAH patients. The implementation of rigorous study design will need support not only from researchers, peer reviewers, and editors, but also from academic institutions, funding agencies, and animal ethics authorities.
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.
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 | 0.578 | 0.640 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".