Bibliographic record
Abstract
Heart failure explains a large portion of heart diseases. Molecular mechanisms determining cardiac function, by inference dysfunction in heart failure, are incompletely understood, especially in the common (or congestive) systolic (SHF) and diastolic heart failure (DHF). Limited genome-wide association studies (GWASs) in humans are reported on SHF and no GWAS has been performed on DHF. Genetic analyses in a rodent model of true DHF, Dahl salt-sensitive (DSS) rats, have begun to unravel the genetic components determining diastolic function. Diastolic dysfunction of DSS rats can be ameliorated or even normalized by distinct quantitative trait loci (QTLs), designated as diastolic function/blood pressure QTLs (DF/BP QTLs), which also affect blood pressure (BP). However, an improvement in diastolic dysfunction is merely transitory from a single DF/BP QTL, despite a permanent lowering of BP. A long-term protection against diastolic dysfunction can be realized only through combining specific DF/BP QTLs. Moreover, the worsening diastolic dysfunction with age can also be reversed in a different combination of DF/BP QTLs. Thus, distinct genes in combinations must be involved in the physiological mechanisms ameliorating or reversing diastolic dysfunction. As not all the QTLs that influence BP can affect diastolic function, it is not BP reduction itself that restores diastolic function, but rather specific genes that are uniquely integrated into the pathways of blood pressure homeostasis as well as diastolic function. Thus, the elucidation of pathophysiological mechanisms causal to hypertensive diastolic dysfunction will not only provide new diagnostic tools, but also novel therapeutic targets and strategies in reducing, curing, and even reversing 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".