Use of Precision-Cut Lung Slices as an Ex Vivo Tool for Evaluating Viruses and Viral Vectors for Gene and Oncolytic Therapy
Bibliographic record
Abstract
Organotypic slice cultures recapitulate many features of an intact organ, including cellular architecture, microenvironment, and polarity, making them an ideal tool for the ex vivo study of viruses and viral vectors. Here, we describe a procedure for generating precision-cut ovine and murine tissue slices from agarose-perfused normal and murine melanoma tumor-bearing lungs. Furthermore, we demonstrate that these precision-cut lung slices can be maintained up to 1 month and can be used for a range of applications, which include characterizing the tissue tropism of viruses that cannot be propagated in cell monolayers, evaluating the transducing properties of gene therapy vectors, and, finally, investigating the tumor specificity of oncolytic viruses. Our results suggest that ex vivo lung slices are an ideal platform for studying the tissue specificity and cancer cell selectivity of gene therapy vectors and oncolytic viruses prior to in vivo studies, providing justification for pre-clinical work.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".