Targeting and Killing of Metastatic Cells in the Transgenic Adenocarcinoma of Mouse Prostate Model With Vesicular Stomatitis Virus
Bibliographic record
Abstract
Vesicular stomatitis virus (VSV) is an oncolytic virus which selectively infects and kills cancer cells. The goal of the present study was to determine whether VSV is capable of targeting metastatic lesions that arise in situ in the transgenic adenocarcinoma of the mouse prostate (TRAMP) model. The interferon (IFN)-responsive luciferase containing VSV(AV3) strain was injected intraprostatically into both control and TRAMP mice. Distribution, infectivity, apoptosis, and status of the IFN response were evaluated at the site of viral injection (prostate), as well as in metastatic lesions (lymph nodes), through plaque, polymerase chain reaction (PCR), and immunohistochemical analysis. Bioluminescence analyses demonstrated that VSV(AV3) persisted at high levels in the prostate region of TRAMP mice for up to 96 hours, but at relatively low levels and for only 48 hours in control mice. Live virus was discovered in the lymph nodes of TRAMP mice, but not in control mice. TUNEL staining revealed increased cell death in VSV(AV3) infected metastatic cells present in the lymph nodes of TRAMP mice. There was an evidence of IFN activation in lymph nodes containing metastatic cells. Our results indicate that intraprostatic injections of VSV(AV3) can be used as a means to infect and kill metastatic lesions associated with advanced prostate 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) | 0.001 | 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".