Transfer RNA-derived small RNAs as novel players and biomarkers in cardiovascular disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An emerging field in cardiovascular research is the translational investigation of transfer RNA-derived small RNAs (tsRNAs). TsRNAs, a class of small non-coding RNA molecules, have been shown to modulate cellular functions by regulating gene expression post-transcriptionally. They are implicated in diverse pathological conditions, including cancer, cardiovascular disease (CVD), infectious disease, diabetes, neurological disease, and metabolic disorder. Accumulating evidence suggests tsRNAs as important players and biomarkers in CVD. Dysregulated tsRNAs are identified in atherosclerosis, heart failure, hypertension and other types of CVD. Bioinformatics and in vitro experimental analyses reveal that tsRNAs may participate in the regulation of endothelial and inflammatory cell interactions, endothelial cell and vascular smooth muscle cell proliferation and migration, and cardiac metabolism, mitophagy and remodeling, contributing to the pathogenesis of CVD. In addition, altered tsRNAs possess great diagnostic and prognostic potential in CVD. Nevertheless, there are currently no in vivo mechanistic studies using animal models, and the small sizes of reported clinical studies that examined tsRNAs limit their diagnostic and prognostic value. Although of promise, further research is needed to address the utility of tsRNAs in cardiovascular care.
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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 | 0.000 | 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) | 0.000 | 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 it