Anti-Metastatic Function of Extracellular Vesicles Derived from Nanog-Overexpressing Melanoma
Bibliographic record
Abstract
A metastatic melanoma cell line B16-F10 (F10) was modified to a more undifferentiated state by Nanog overexpression. The produced cell line Nanog+F10 showed a higher metastatic potential than F10. Instead of whole cells, the extracellular vesicles (EVs) therefrom were investigated about their possible role as an autovaccine against metastasis. EVs from Nanog+F10 cells (Nanog+F10-EVs) could suppress the metastasis, contrasting the EVs from less metastatic F10 cells (F10-EVs) enhanced metastasis. The involvement of TGF-β1 in the role of Nanog+F10-EVs was analyzed, as TGF-β1 was a secretory cytokine being affected most intensively by Nanog overexpression. It was suggested to be crucial that the TGF-β1 concentration in Nanog+F10-EVs should be as low as 1.6 pg/μg for its metastasis-suppressive role. In response to Nanog+F10-EVs, immunoreaction was observed in liver, indicating the specific decrease in the number of tumor-promotive CD163-positive macrophages. These indicate a possibility of Nanog+F10-EVs as a novel autovaccine candidate against melanoma metastasis.
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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) | 0.000 | 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 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".