Recent advancements in pulmonary arterial hypertension and right heart failure research: overview of selected abstracts from ATS2020 and emerging COVID‐19 research
Bibliographic record
Abstract
Each year the American Thoracic Society (ATS) Conference brings together scientists who conduct basic, translational and clinical research to present on the recent advances in the field of respirology. Due to the Coronavirus Disease of 2019 (COVID-19) pandemic, the ATS2020 Conference was held online in a series of virtual meetings. In this review, we focus on the breakthroughs in pulmonary hypertension research. We have selected 11 of the best basic science abstracts which were presented at the ATS2020 Assembly on Pulmonary Circulation mini-symposium "What's New in Pulmonary Arterial Hypertension (PAH) and Right Ventricular (RV) Signaling: Lessons from the Best Abstracts," reflecting the current state of the art and associated challenges in PH. Particular emphasis is placed on understanding the mechanisms underlying RV failure, the regulation of inflammation, and the novel therapeutic targets that emerged from preclinical research. The pathologic interactions between pulmonary hypertension, right ventricular function and COVID-19 are also discussed.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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; 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".