Bibliographic record
Abstract
The incidence of cardiac complications such as myocardial infarction and congestive heart failure is increasing. Once congestive heart failure emerges, little can be done to improve long-term cardiac function. The cellular basis of this downward spiral may be the dramatic loss of viable cardiomyocytes following acute ischemia and/or chronic apoptosis/necrosis which are not adequately replaced. Contrary to the old postulates of developmental biology, tissue self-renewal is not limited to blood, intestines and skin, but other organs including the heart have some capabilities of self-renewal. However, the intrinsic ability of self-renewal of adult myocardium or cardiomyogenesis is limited and thus novel paradigms capable of potentiating this process of regenerative organogenesis should be sought. Several strategies and paradigms are being currently explored, and among these is the heme-oxygenase system. Emerging evidence indicate that the heme-oxygenase system could be explored in regenerative medicine given its unique ability to concomitantly suppress apoptosis and necrosis, while facilitating tissue regeneration/repair and the formation of new blood vessels. This review highlights the recent development of heme-oxygenase in myocardial repair and regeneration.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".