High-Efficiency Retroviral Transduction of Mammalian Cells on Positively Charged Surfaces
Why this work is in the frame
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Bibliographic record
Abstract
The efficiency of retroviruses as transducing agents has been appreciated for many years, particularly for hematopoietic cell targets for which alternative strategies applicable to adherent cells are not effective. Advances in vector design, pseudotyping, and infection conditions have eliminated the need to cocultivate the target cells with virus-producing cells. Nevertheless, improvements are still needed for many applications, including those with a therapeutic or clinical cell-tracking objective. In this study we show that more positively charged surfaces, including those designed for the culture of anchorage-dependent cells, allow measurable levels of adhesion by different pseudotypes of retroviruses, which can result in increased gene transfer efficiencies to a variety of target cells including normal primary human hematopoietic cells as well as human leukemic cell lines and rat and murine fibroblasts. In the experiments with primary human cells, equal aliquots of enriched CD34+ cord blood cells were first stimulated for 2 days with cytokines (Flt3 ligand, Steel factor, IL-3, IL-6, and G-CSF) and then exposed for 4 days to a green fluorescent protein (GFP)- and Neo(r)-encoding retrovirus produced in PG13 cells. Both the final yield (approximately 300% relative to initial numbers), and the proportion (approximately 60%) of transduced CD34+ cells, colony-forming cells, and long-term culture-initiating cells were the same for cells infected either in tissue culture dishes or in fibronectin-coated petri dishes. Similar proportions (approximately 10%) and absolute yields of GFP+ human cells were also found in multilineage engrafted NOD/SCID mice assessed 6 to 8 weeks after being transplanted with these two types of transduced, but unselected, cells. These findings suggest a new and simpler approach for achieving high gene transfer efficiencies to hematopoietic cells.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 it