Low‐protein medium affects the 293SF central metabolism during growth and infection with adenovirus
Bibliographic record
Abstract
In this study the metabolism of 293SF cells grown in serum-free and low-protein medium was analyzed. This cell line is known for its ability to replicate recombinant adenovirus, mainly used in gene therapy applications. A complete model composed of the main glycolytic, glutaminolytic, and amino acids pathways, as well as the internalization fluxes of certain compounds into the mitochondria, is used for metabolic flux calculations. The pentose-phosphate cycle is also added to the biochemical reactions set and was independently measured with labeled 14C-glucose. Different feeding strategies in two different media were analyzed with the model, and the theoretical ATP production was also calculated. The two media were similar in their glucose and amino acid composition, but one contained BSA at 1g/L whereas the other had a very low protein content. Use of low-protein medium resulted in up to fourfold higher adenoviral vector production. In this medium, glucose utilization was more efficient, as it entered the TCA cycle more efficiently. Also, lower glutamine and amino acids consumption were observed as well as lower lactate and ammonia production. This increased TCA activity led to a twofold higher ATP production in the low-protein medium.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".