Bibliographic record
Abstract
Heart failure accounts for a significant portion of heart diseases. Molecular mechanisms gradually emerge that participate in pathways leading to left ventricular dysfunction in common systolic heart failure (SHF) and diastolic heart failure (DHF). A human genome-wide association study (GWAS) identified two markers for SHF and no GWAS on DHF has been documented. However, genetic analyses in rat models of SHF and DHF have begun to unravel the genetic components known as quantitative trait loci (QTLs) initiating systolic and diastolic function. A QTL for systolic function was detected and the gene responsible for it is identified to be that encoding the soluble epoxide hydrolase. Diastolic function is determined by multiple QTLs and the Ccl2/monocyte chemotactic protein gene is the strongest candidate. An amelioration on diastolic dysfunction is merely transient from changing such a single QTL accompanied by a blood pressure reduction. A long-term protection can be achieved only via combining alleles of several QTLs. Thus, distinct genes in synergy are involved in physiological mechanisms durably ameliorating or reversing diastolic dysfunction. These data lay the foundation for identifying causal genes responsible for individual diastolic function QTLs and the essential combination of them to attain a permanent protection against diastolic dysfunction, and consequently will facilitate the elucidation of pathophysiological mechanisms underlying hypertensive diastolic dysfunction. Novel pathways triggering systolic and diastolic dysfunction have emerged that will likely provide new diagnostic tools, innovative therapeutic targets and strategies in reducing, curing and even reversing SHF and DHF.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".