<i>In vitro</i>Canine Distemper Virus Infection of Canine Lymphoid Cells: A Prelude to Oncolytic Therapy for Lymphoma
Bibliographic record
Abstract
PURPOSE: Measles virus (MV) causes the regression of human lymphoma xenografts. The purpose of this study was to determine if canine lymphoid cells could be infected in vitro with MV or canine distemper virus (CDV, the canine Morbillivirus equivalent of MV) and determine if in vitro viral infection leads to apoptotic cell death. EXPERIMENTAL DESIGN: Reverse transcriptase-PCR was used to examine the expression of both signal lymphocyte activation molecule (CD150) and membrane cofactor molecule (CD46) mRNA. An attenuated CDV expressing enhanced green fluorescent protein was used to infect canine cells in vitro. Both flow cytometry and reverse transcriptase-PCR was used to document CDV infection. Cell death was examined using a propidium iodide staining assay and Annexin V binding. RESULTS: Canine lymphoid cell lines and neoplastic B and T lymphocytes collected from dogs with spontaneous lymphoma expressed the Morbillivirus receptor CD150 mRNA. In contrast, only neoplastic lymphocytes expressed detectable levels of CD46 mRNA. Although MV did not infect canine cells, CDV efficiently infected between 40% and 70% of all three canine lymphoid lines tested. More importantly, CDV infected 50% to 90% of neoplastic lymphocytes isolated from dogs with both B and T cell lymphoma. Apoptosis of CDV-infected cell lines was documented. CONCLUSIONS: Attenuated CDV may be a useful treatment for canine lymphoma. As such, dogs with lymphoma may represent a biologically relevant large animal model to investigate the feasibility, safety, and efficacy of Morbillivirus therapy in a clinical setting with findings that may have direct applicability in the treatment of human non-Hodgkin's lymphoma.
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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".