Optimized Pre-Clinical Grade Production of Two Novel Lentiviral Vector Pseudotypes for Lung Gene Delivery
Bibliographic record
Abstract
Lung gene therapy requires efficient transduction of slow-replicating epithelia and stable expression of delivered transgenes in the respiratory tract. Lentiviral (LV) vectors have the ideal coding, expression, and transducing capacity required for gene therapy. A modified envelope glycoprotein from the Jaagsiekte Sheep Retrovirus, termed Jenv, is well suited for LV-mediated lung gene therapy due to its inherent lung tropism. Here, two novel Jenv-pseudotyped LVs that effectively transduce lung tissue and yield titers similar to the gold standard, vesicular stomatitis virus glycoprotein (VSVg)-pseudotyped LVs, were generated. As the concentration efficiency of LVs was found to depend on envelope pseudotype, a large-scale production method tailored for Jenv-pseudotyped LVs was developed and the most appropriate method of concentration was determined. In contrast to VSVg and Ebola virus glycoprotein-pseudotyped LVs, ultracentrifugation through a sucrose cushion drastically reduced the yield of Jenv LVs, whereas polyethylene glycol precipitation and tangential flow filtration (TFF) proved to be more suitable methods for concentrating Jenv LVs. Importantly, pressure during TFF was found to be crucial for increasing LV recovery. Finally, a unique mouse model was developed to test the suitability of these novel Jenv-pseudotyped LVs for use in lung gene therapy applications.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".