Role of circRNA circ_0000080 in myocardial hypoxia injury
Bibliographic record
Abstract
This study aimed to investigate the potential role of circRNA circ_0000080 in myocardial hypoxia injury and the underlying mechanisms. Patients with myocardial hypoxia injury who were admitted to Xi’an No. 1 Hospital, China, were included in this study. The expression levels of circ_0000080, miR-367-5p, and <i>COX2</i> were analyzed by real-time quantitative PCR (RT-qPCR); cell viability was measured by cell counting kit-8 (CCK-8) assay; and apoptosis was detected by flow cytometry. In addition, the release of cytokines was determined by Enzyme-linked immunosorbent assay (ELISA), and the binding sites between miR-367-5p and circ_0000080/<i>COX2</i> were predicted by bioinformatics analysis and confirmed by dual-luciferase reporter and RNA pull-down assays. circ_0000080 was upregulated in patients with MI and in H9c2 cells treated with H<sub>2</sub>O<sub>2</sub> and hypoxia/reoxygenation (H/R). Silencing circ_0000080 reduced the H/R-mediated apoptosis of cardiomyocytes and secretion of pro-inflammatory cytokines. Moreover, circ_0000080 functioned as an miR-367-5p sponge to regulate the expression of <i>COX2</i>. Downregulated miR-367-5p or overexpressed <i>COX2</i> degraded cellular functions of cardiomyocytes. circ_0000080 knockdown alleviated myocardial hypoxia injury through the miR-367-5p/<i>COX2</i> axis.
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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) | 0.000 | 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) | 0.001 | 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".