Cancer cell-oriented migration of mesenchymal stem cells engineered with an anticancer gene (PTEN): an imaging demonstration
Bibliographic record
Abstract
BACKGROUND: Mesenchymal stem cells (MSCs) have been considered to hold great potential as ideal carriers for the delivery of anticancer agents since the discovery of their tumor tropism. This study was performed to demonstrate the effects of phosphatase and tensin homolog (PTEN) engineering on MSCs' capacity for cancer cell-oriented migration. METHODS: MSCs were engineered with a PTEN-bearing plasmid and the expression was confirmed with Western blotting. A human glioma cell line (DBTRG) was used as the target cell; DBTRG cell-oriented migration of MSCs was monitored with a micro speed photographic system. RESULTS: The expression of transfected PTEN in MSCs was identified by immunoblotting analysis and confirmed with cell viability assessment of target cells. The DBTRG cell-oriented migration of PTEN-engineered MSCs was demonstrated by a real-time dynamic monitoring system, and a phagocytosis-like action of MSCs was also observed. CONCLUSION: MSCs maintained their capacity for cancer cell-directed migration after they were engineered with anticancer genes. This study provides the first direct evidence of MSCs' tropism post-anticancer gene engineering.
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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".