Differential Expression of Peripheral Circulating MicroRNA-146a Between Patients with Atherosclerotic Vulnerable Plaque and Stable Plaque
Bibliographic record
Abstract
Atherosclerotic plaque rupture and subsequent cardiovascular complications threaten the population's health worldwide. The polymorphism of miR-146a rs2910164 was significantly associated with the risk of vulnerable plaques. However, it remains unclear whether the circulating miR-146a is differentially expressed in stable and vulnerable plaques and thus, serves as a potential biomarker.This study aims to analyze the differential expression of circulating miR-146a between patients with stable and vulnerable plaques to explore the potential molecular mechanisms.Public databases were searched from their inception up to November 2022. A study reporting the specific circulating miR-146a levels between patients with stable and vulnerable plaques was included. The study quality was assessed using the modified genetic 8-stars Newcastle-Ottawa scale. The differential expression levels of miR-146a were evaluated using the standardized mean difference (SMD).Eight studies with 978 patients were included and analyzed. The results showed that miR-146a expression levels were significantly higher in the vulnerable plaque population than in the stable plaque population (SMD: 1.91; 95% confidence interval: 1.35, 2.47; P < 0.01). A similar statistical significance was found in subgroup analyses regarding sample source, disease type, and vulnerable plaque characteristics. Sensitivity analysis suggested the robustness of the results. Analysis of downstream genes suggested that miR-146a-targeted regulation of ACTN4, SARM1, and ULK2 may affect intraplaque hemorrhage.Patients with vulnerable plaque have higher circulating miR-146a levels than those with stable plaque. However, based on the limitations of this study, high-quality studies are still needed to confirm the results.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".