LncRNA-modulated autophagy in plaque cells: a new paradigm of gene regulation in atherosclerosis?
Bibliographic record
Abstract
The development of atherosclerosis is accompanied by the functional deterioration of plaque cells, which leads to the escalation of endothelial inflammation, abnormal vascular smooth muscle cell phenotype switching and the accumulation of lipid-laden macrophages within vascular walls. Autophagy, a highly conserved homeostatic mechanism, is critical for the delivery of cytoplasmic substrates to lysosomes for degradation. Moderate levels of autophagy prevent atherosclerosis by safeguarding plaque cells against apoptosis, preventing inflammation, and limiting the lipid burden, whereas excessive autophagy exacerbates cell damage and inflammation and thereby accelerates the formation of atherosclerotic plaques. Increasing lines of evidence suggest that long noncoding RNAs can be either beneficial or detrimental to atherosclerosis development by regulating the autophagy level. This review summarizes the research progress related to 1) the significant role of autophagy in atherosclerosis and 2) the effects of the lncRNA-mediated modulation of autophagy on the plaque cell fate, inflammation levels, proliferative capacity, and cholesterol metabolism and subsequently on atherogenesis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".