miRNA-221 of exosomes originating from bone marrow mesenchymal stem cells promotes oncogenic activity in gastric cancer
Bibliographic record
Abstract
Worldwide, gastric cancer (GC) is one of the deadliest malignant tumors of the digestive system. Moreover, microRNAs (miRNAs) of exosomes harbored within cancer cells have been determined to induce inflammatory conditions that accelerate tumor growth and metastasis. Interestingly, the oncogenic role of bone marrow mesenchymal stem cells (BM-MSCs) in the modulation of immunosuppression, tumor invasion, and metastasis was discovered to be partly mediated through the secretion of exosomes. In this article, high expression of miRNA-221 (miR-221) in exosomes of the peripheral blood was determined to be positively correlated with the poor clinical prognosis of GC, especially with respect to tumor, node, and metastases stage. Therefore, the expression of miR-221 in exosomes of the peripheral blood may be an important detection index for GC. Proliferation, migration, invasion, and adhesion to the matrix of GC BGC-823 and SGC-7901 cells were significantly enhanced by exosomes that originated from BM-MSCs that were transfected with miR-221 mimics. In conclusion, extracted exosomes from BM-MSCs transfected with miR-221 oligonucleotides can act as high-efficiency nanocarriers, which can provide sufficient miR-221 oligonucleotides to influence the tumor microenvironment and tumor aggressiveness effectively. Notably, the use of a miR-221 inhibitor with an excellent restraining effect in exosomes provides therapeutic potential for GC in future clinical medicine.
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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 | 0.000 |
| 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".