LncRNAs: Proverbial Genomic “Junk” or Key Epigenetic Regulators During Cardiac Fibrosis in Diabetes?
Bibliographic record
Abstract
Long non-coding RNAs (lncRNAs) are critical regulators in a multitude of biological processes. Recent evidences demonstrate potential pathogenetic implications of lncRNAs in diabetic cardiomyopathy (DCM); however, the majority of lncRNAs have not been comprehensively characterized. While the precise molecular mechanisms underlying the functions of lncRNAs remain to be deciphered in DCM, emerging data in other pathophysiological conditions suggests that lncRNAs can have versatile features such as genomic imprinting, acting as guides for certain histone-modifying complexes, serving as scaffolds for specific molecules, or acting as molecular sponges. In an effort to better understand these features of lncRNAs in the context of DCM, our review will first summarize some of the key molecular alterations that occur during fibrosis in the diabetic heart (extracellular proteins and endothelial-to-mesenchymal transitioning), followed by a review of the current knowledge on the crosstalk between lncRNAs and major epigenetic mechanisms (histone methylation, histone acetylation, DNA methylation, and microRNAs) within this fibrotic process.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".