Circular RNA Foxo3 in cardiac ischemia-reperfusion injury in heart transplantation: A new regulator and target
Bibliographic record
Abstract
Ischemia-reperfusion (I/R) injury occurring in heart transplantation (HT) remains as a leading cause of transplant heart graft failure. Circular RNAs (circRNAs) play important roles in gene regulation and diseases. However, the impact of circRNAs on I/R injury during HT remains unknown. This study aims to investigate the role of circular RNA Foxo3 (circFoxo3) in I/R injury in HT. Using an in vivo mouse HT model and an in vitro cardiomyocyte culture model, we demonstrated that circFoxo3 is significantly upregulated in I/R-injured hearts and hypoxia/reoxygenation (H/R)-damaged cardiomyocytes. Knockdown of circFoxo3 using siRNA not only reduces cell apoptosis and death, mitochondrial damage, and expression of apoptosis/death-related genes in vitro, but also protects heart grafts from prolonged cold I/R injury in HT. We also show that circFoxo3 interacts with Foxo3 proteins and inhibits the phosphorylation of Foxo3 and that it indirectly affects the expression of miR-433 and miR-136. In conclusion, circRNA is involved in I/R injury in HT and knockdown of circFoxo3 with siRNA can reduce I/R injury and improve heart graft function through interaction with Foxo3. This study highlights that circRNA is a new type of molecular regulator and a potential target for preventing I/R injury in HT.
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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".