Effect of microRNA‐26a on vascular endothelial cell injury caused by lower extremity ischemia–reperfusion injury through the AMPK pathway by targeting PFKFB3
Bibliographic record
Abstract
Vascular endothelial cell (VEC) dysfunction plays an important role in the ischemia-reperfusion injury (IRI)-related diseases, and microRNAs (miRNAs) are key factors during this process. We conducted this study to investigate whether miRNA-26a (miR-26a) has effect on the IRI-induced VEC injury via the AMPK pathway by targeting 6-phosphofructo-2-kinase-fructose-2,6-biphosphatase 3 (PFKFB3). IRI rat models were successfully constructed by an abdominal incision. Additionally, the cultured VECs were further treated with miR-26a mimic or inhibitor, and si-PFKFB3. Both the reverse-transcription quantitative polymerase chain reaction and the western blot assay method were carried out to examine the expressions of PFKFB3, endothelial nitric oxide synthase (eNOS), and 5'-adenosine monophosphate-activated protein kinase (AMPK) α1, as well as the extent of the AMPK α1 phosphorylation levels in vascular tissues. Circulating endothelial cell (CEC), von Willebrand factor (VWF), thrombomodulin (TM), superoxide dismutase (SOD), malondialdehyde (MDA), nitric oxide (NO), and endothelin (ET) were all measured. In the rat model of an IRI, a poorly expressed miR-26a and contrarily highly expressed PFKFB3 were identified in vascular tissues. In response to an overexpression of miR-26a or to the PFKFB3 gene silencing, decreased CEC number, TM, VWF, MDA, and ET contents, increased AMPK α1, and eNOS levels, as well as the extent of AMPK α1 phosphorylation coordinate with both increased SOD and NO contents based on the restoration of the AMPK pathway. Overexpression of the miR-26a or si-PFKFB3 provides an elevation in cell proliferation. Our study suggests that the miR-26a RNA alleviates lower extremity IRI-induced VEC injury in rats through the activation of the AMPK pathway by inhibiting PFKFB3.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".