A Multi-omic and Multi-Species Analysis of Right Ventricular Failure
Bibliographic record
Abstract
Right ventricular failure (RVF) is a leading cause of morbidity and mortality in multiple cardiovascular diseases, but there are no approved treatments for RVF as therapeutic targets are not clearly defined. Contemporary transcriptomic/proteomic evaluations of RVF are predominately conducted in small animal studies, and data from large animal models are sparse. Moreover, a comparison of the molecular mediators of RVF across species is lacking. Here, we used transcriptomics and proteomics analyses to define the molecular pathways associated with cardiac MRI-derived values of RV hypertrophy, dilation, and dysfunction in pulmonary artery banded (PAB) piglets. Publicly available data from rat monocrotaline-induced RVF and pulmonary arterial hypertension patients with preserved or impaired RV function were used to compare the three species. Transcriptomic and proteomic analyses identified multiple pathways that were associated with RV dysfunction and remodeling in PAB pigs. Surprisingly, disruptions in fatty acid oxidation (FAO) and electron transport chain (ETC) proteins were different across the three species. FAO and ETC proteins and transcripts were mostly downregulated in rats, but were predominately upregulated in PAB pigs, which more closely matched the human data. Thus, the pig PAB metabolic molecular signature was more similar to human RVF than rodents. These data suggest there may be divergent molecular responses of RVF across species, and that pigs more accurately recapitulate the metabolic aspects of human RVF.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".