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.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.348 | 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".