LncRNA H19 promotes inflammatory response induced by cerebral ischemia–reperfusion injury through regulating the miR-138-5p–p65 axis
Bibliographic record
Abstract
Recent studies have shown that long non-coding RNA(LncRNA) H19 is up-regulated in the brain of rats suffering from cerebral ischemia-reperfusion (I/R) injury, inducing severe disability and mortality. Little was known about the molecular mechanisms underlying the involvement of H19 in cerebral I/R injury. In this study, a rat model of I/R was induced by transient middle cerebral artery occlusion (tMCAO). PC-12 cells exposed to oxygen and glucose deprivation/reoxygenation (OGD/R) were used as an in vitro model. Our results show that H19 is up-regulated in both in vivo and in our in vitro model. Further study indicated that knockdown of H19 promotes cell proliferation, decreases the rate of cell apoptosis, and ameliorates inflammation after OGD/R simulation. Our in vivo study shows that H19 knockdown ameliorates inflammation and improves neurological function in our rat model of tMCAO. Remarkably, the results from our luciferase reporter assays suggest that H19 negatively regulates the expression of miR-138-5p, and p65 was identified as a target of miR-138-5p. To sum up, this study demonstrated that H19 promotes an inflammatory response and improves neurological function in a rat model of tMCAO by regulating the expression of miR-138-5p and p65. This study reveals the important role and underlying mechanism of H19 in the progress of cerebral I/R injury, which could serve as a potential target for further treatment.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".