Bibliographic record
Abstract
Two significant barriers limit the use of amphotropic retrovirus for human gene transfer protocols: 1) low transduction efficiency in cells with low receptor expression and 2) safety concerns originating from the risk of formation and propagation of replication competent virus in vivo. In principle, if ecotropic retrovirus, which is incapable of infecting human cells, could be transiently modified to effectively transduce human cells, this safety risk could be alleviated. Here we demonstrate that formation of amphotropic retrovirus polylysine molecular conjugates (aMMLV-PL) enhanced gene transfer up to 10-fold in a variety of human cell lines over the equivalent of unconjugated vector (aMMLV). The polylysine modification and formation of ecotropic retrovirus molecular conjugates (eMMLV-PL) permitted effective and stable transduction of different human cell lines as well as primary human bone marrow stroma cells at frequencies of greater than 80%. It is conceivable that this novel ecotropic-based conjugate retrovirus vector could also potentially provide enhanced safety characteristics not only over amphotropic retrovirus vectors but also over genetically tropism-modified recombinant ecotropic vectors. In contrast to genetic modifications, physical or chemical modifications are not propagated. Thus, formation of replication competent eMMLV from conjugates would be self-limited and would not result in virus propagation in humans.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.007 |
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".