Endostatin-expressing endometrial mesenchymal stem cells inhibit angiogenesis in endometriosis through the miRNA-21-5p/TIMP3/PI3K/Akt/mTOR pathway
Bibliographic record
Abstract
Endometriosis is a chronic inflammatory and neoangiogenic disease. Endostatin is one of the most effective inhibitors of angiogenesis. Mesenchymal stem cells (MSCs) have been investigated as compelling options for cell therapy. However, the effect and mechanism of action of endostatin-expressing endometrial MSCs (EMSCs) in endometriosis are unclear. Here, EMSCs were genetically modified to overexpress endostatin (EMSCs-Endo). A reduction in the angiogenic capacity of HUVECs was observed in vitro after treatment with EMSCs-Endo. EMSCs-Endo significantly suppressed endometriotic lesion growth in vivo. The limited efficacy was associated with suppressed angiogenesis. The miRNA-21-5p level and the levels of p-PI3K, p-mTOR, and p-Akt in HUVECs and mouse endometriotic lesions significantly decreased after treatment with EMSCs-Endo, whereas TIMP3 expression significantly increased. In summary, targeted gene therapy with EMSCs-Endo is feasible, and its efficacy in regulating endometriosis can be attributed to the inhibition of angiogenesis, suggesting that EMSCs could be used as promising vehicles for targeted gene therapy.
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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 | 0.001 |
| 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".