High-Pressure Delivery of Oncolytic Viruses via Needle-Free Injection Preserves Therapeutic Activity
Bibliographic record
Abstract
Intratumoural delivery of oncolytic viruses (OVs) to solid tumours is currently performed via multiple percutaneous methods of needle injections (NI). In this study, we investigated the potential use of a novel delivery approach, needle-free injection (NFI), to administer OVs to subcutaneous tumours. The stability and genetic integrity of several RNA and DNA viruses exposed to high-pressure jet injectors were first evaluated in vitro. We demonstrate that replication competence and infectivity of the viruses remained unchanged after NFI, as compared to traditional NI. Using the oncolytic Vesicular Stomatitis Virus expressing luciferase (VSVΔ51-Luc) in the syngeneic CT26 subcutaneous tumour model, we show that NFI administration not only successfully delivers infectious particles but also increases the dissemination of the virus within the tumour tissues when compared to NI. Furthermore, mice treated with VSVΔ51-Luc by NFI delivery showed similar reduction in tumour growth and survival compared to those with needle-administered virus. These results indicate that NFI represents a novel approach to administer and potentially increase the spread of OVs within accessible solid tumours, highlighting its usefulness in virotherapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".