Characterization of an alternative packaging system derived from the cat RD114 retrovirus for gene delivery
Bibliographic record
Abstract
BACKGROUND: Retroviral vectors derived from the Moloney murine leukemia virus (MLV) are widely used in gene therapy. Pseudotyping of these vectors with the cat RD114 retrovirus envelope increases their potential for delivering genes into human hematopoietic cells. In the present study, we have further investigated the potential of the RD114 retrovirus in gene therapy. We describe and characterize an alternative retroviral packaging system derived from the RD114 retrovirus. METHODS: RD114-derived recombinant retroviruses were produced transiently by transfection of 293T cells, and viral titers were assessed on TE671 cells by measuring the percentage of infected green fluorescent protein (GFP) positive cells by fluorescence-activated cell sorter (FACS) analysis. Purified human hematopoietic cells (lymphocytes and CD34(+) cells) were activated and transduced on retronectin-coated plates. Two days later, the percentage of GFP positive cells was evaluated by FACS analysis. RESULTS: We demonstrate that RD114 viral particles could package MLV transfer vectors, and that, in addition to its natural envelope, RD114 cores could be efficiently pseudotyped by the Gibbon ape leukemia, the MLV-amphotropic and the vesicular stomatitis virus G protein envelopes. Furthermore, we found that RD114 viral particles were highly efficient to transduce human lymphocytes and CD34(+) cells. CONCLUSIONS: This is the first demonstration that replication-defective RD114 viral particles can be generated and used for efficient gene delivery into human hematopoietic cells. We conclude that RD114-derived vectors could be useful in the field of gene therapy.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".