A novel approach to tumor suppression using microencapsulated engineered J558/TNF-alpha cells.
Bibliographic record
Abstract
AIM: Immunoisolation technology using microencapsulated nonautologous cells is a novel alternative approach to the treatment of cancer. The work was aimed on investigation of the effect of implantation of microencapsulates on tumor growth in vivo. METHODS: In this study, we constructed an engineered tumor cell line J558/TNF-alpha that secreted functional tumor necrosis factor-alpha (TNF-alpha) (2 ng/ml), and went on to encapsulate the engineered cells into microencapsules. RESULTS: Our data showed that the microencapsulates thus produced could release functional TNF-alpha (1.2 ng/ml), which then diffused through the microencapsule membrane into the supernatant, and produced a cytotoxic effect on L929 cells in vitro. Microencapsulated cells were intratumorally (i.t.) implanted into athymic nude mice bearing the human breast cancer MCF-7. The results showed that the i.t. implantation induced extensive tumor cell apoptosis and necrosis leading to significant tumor regression and slower tumor growth than in the control groups that were i.t. injected with microencapsulated J558 or PBS respectively (p < 0.05). CONCLUSION: This study provides further evidence that the microencapsulation of recombinant tumor cells secreting cytokines may be an alternative approach in treatment of cancer.
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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) | 0.000 | 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".