Improving AAV vector yield in insect cells by modulating the temperature after infection
Bibliographic record
Abstract
Vectors based on adeno-associated viruses (AAV) are sought for therapeutic gene delivery because of their ability to transduce a variety of tissues with no significant immunological response. Production using the baculovirus expression vector (BEV)/insect cell system has the potential to meet the needs for pre-clinical and clinical trials. In this co-infection system, three baculoviruses are used to produce the AAV vector. A strategy aimed at increasing encapsidation/maturation of the viral vector involved varying the temperature over the course of the process. Cultures were subjected to temperature changes at various times pre- and post-infection (up to 24 h post-infection). It was found that raising the culture temperature to 30 degrees C at the time of infection nearly tripled the infectious titer. In fact, increasing the temperature to 30 degrees C at any time in the process investigated resulted in an increase in titer. Also, raising the culture to 33 degrees C or lowering the temperature to 24 degrees or 21 degrees C resulted in lower titers. The rise in infectious titer was also confirmed by an increase in DNase resistant particles (DRPs). Varying the temperature, however, did not affect the total amount of capsids significantly. Therefore increasing the culture temperature resulted in better encapsidation as determined by the ratio of capsids to DRPs to infectious particles. It is believed that an increase in early proteins and possibly a quicker cascade of baculovirus infection events resulted in this increased packaging efficiency.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 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".