A Method to Generate and Rescue Recombinant Adenovirus Devoid of Replication-Competent Particles in Animal-Origin-Free Culture Medium
Bibliographic record
Abstract
Adenoviruses are promising vectors for vaccine production and gene therapy. Despite all the efforts in removing animal-derived components such as fetal bovine serum (FBS) during the production of adenovirus vector (AdV), FBS is still frequently employed in the early stages of production. Conventionally, first-generation AdVs (E1 deleted) are generated in different variants of adherent HEK293 cells, and plaque purification (if needed) is performed in adherent cell lines in the presence of FBS. In this study, we generated an AdV stock in SF-BMAdR (A549 cells adapted to suspension culture in serum-free medium). We also developed a limiting dilution method using the same cell line to replace the plaque purification assay. By combining these two technologies, we were able to completely remove the need for FBS from the process of generating and producing AdVs. In addition, we demonstrated that the purified AdV stock is free of any replication-competent adenovirus (RCA). Furthermore, we demonstrated that our limiting dilution method could effectively rescue an AdV from a stock that is highly contaminated with RCA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".