Modulation of late apoptotic events by ammonia in glutaminedeprived mouse hybridoma cells
Bibliographic record
Abstract
Highly proliferating cells reprogram their metabolism in order to fulfill their requirements in biosynthetic precursors. One consequence of this metabolic adaptation is glutamine (Gln) addiction, a phenomenon whereby cells become dependent on Gln for their survival. Using Sp2/0‐Ag14 (Sp2/0) hybridoma cells, we examined the effect of ammonium ions, a product of glutaminolysis, on the viability of Gln‐deprived cells. Supplementing Gln‐deprived Sp2/0 cells with 5 mM ammonium acetate (NH 4 + acetate) or 5 mM ammonium chloride (NH 4 + chloride) resulted in a significant increase in cell viability. Both ammonium salts also protected Sp2/0 cells treated with the toxic Gln analog azaserine. Supplementing Gln‐starved Sp2/0 cells with either ammonium salt did not alter cytosolic cytochrome c release or caspase‐3 activation, indicating that the mechanisms triggering the apoptotic machinery remained intact. Interestingly, a significant reduction in the number of cells with apoptotic nuclear condensation and fragmentation was observed. However, neither NH 4 + acetate nor NH 4 + chloride interfered with DNA fragmentation and nuclear lamin A/C cleavage, two key events observed in apoptotic nuclear condensation and fragmentation. All together, these data suggest that the pro‐survival effect of ammonium salts are linked with an inhibition of late apoptotic events. Funded by NSERC‐CANADA (to ERG).
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".