Bcl‐xL expression interferes with the effects of <scp>L</scp>‐glutamine supplementation on hybridoma cultures
Bibliographic record
Abstract
While feeding protocols and ectopic expression of anti-apoptotic genes have been used to improve the viability of hybridoma cell lines, the effect of the expression levels of survival genes on the behavior of hybridomas following nutrient supplementation is unknown. In this study, we compared the behavior of the Sp2/0-Ag14 hybridoma (Bcl-xL(low)) and the P3x63-Ag8.653 myeloma (Bcl-xL(high)) following culture supplementation with the amino acid L-glutamine (L-Gln). Our data revealed that L-Gln addition substantially increased Sp2/0-Ag14 cell viability and total cell density, concomitant with a decrease in the rate of cell death. This effect was not seen when other amino acids or D-glucose (D-Glc) replaced L-Gln. The improvement in the culture behavior of Sp2/0-Ag14 cells was attributed to a reduction in the rate of accumulation of apoptotic cells. On the other hand, L-Gln supplementation had only a limited effect on the growth of the P3x63-Ag8.653 cells. Interestingly, Sp2/0-Ag14 cells over-expressing Bcl-xL showed a culture behavior upon L-Gln complementation that was similar to the P3x63-Ag8.653 myeloma. These results suggest that the anti-apoptotic gene expression profile of hybridoma cells can markedly impact on the beneficial effects afforded by nutrient supplementation.
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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) | 0.001 | 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 | 0.001 |
| 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".