Stability of Serum-Free and Purified Baculovirus Stocks under Various Storage Conditions
Bibliographic record
Abstract
In a context of large-scale production of baculoviruses in serum-free media for use as gene delivery vectors, the stability of these viruses has become an important factor. The development of robust processes heavily relies on baculovirus stock stability. In the present work, we studied over a period of 300 days the stability of baculovirus vectors produced in serum-free media stored at 4, -20, or -80 degrees C or in liquid nitrogen. The viral stocks investigated were either crude baculovirus supernatant, baculovirus supernatant concentrated 10 times and diafiltered against fresh serum-free media by tangential flow filtration, or baculovirus purified by size exclusion chromatography. The results showed that baculovirus supernatant and diafiltered concentrate stored at 4 degrees C underwent a progressive loss of infectivity after a period of 100 and 50 days of storage, respectively. Aggregation has been recognized as the probable mechanism for the loss of infectivity. Baculovirus stocks were unstable at -20 degrees C, whereas in liquid nitrogen they retained infectivity after successive freeze thaw cycles. Concentration and diafiltration of baculovirus supernatant prior to storing at -80 degrees C contributed to improving viral stock stability over time. Glycerol as well as DMSO and sucrose have proven to be equally effective as additives to maintain the purified baculovirus stability after storage at -80 degrees C or in liquid nitrogen.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".