Strategies to Enhance Viral Penetration of Solid Tumors
Bibliographic record
Abstract
The efficient delivery of viral vectors to tumors is an active area of investigation. A number of barriers exist that must be overcome to achieve good penetration of vectors into tumors and distribution of their effects throughout the tumor mass. Replicating oncolytic viruses have the advantage of being able to amplify the initial dose, but progeny virus are prevented from spreading because of a dense mass of tightly packed cells with a dense extracellular matrix, admixed normal stromal cells, and high interstitial pressure. Although intratumoral injection may ensure initial delivery the distribution achieved by intravenous administration may be superior and come with beneficial bystander damage to the tumor vasculature. Strategies to enhance intravenous delivery and subsequent spread of these vectors within tumors are being developed by a number of groups. Achieving the goal of efficient penetration and spread of viruses within solid tumors is a necessary prerequisite to significant improvements in virus-vectored therapy of solid tumors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".