Akt Depletion Is an Important Determinant of L929 Cell Death following Heat Stress
Bibliographic record
Abstract
Exposure of mammalian cells to heat stress causes impairment of numerous physiological functions and activates a number of signaling pathways. Some of these pathways, such as induction of heat-shock proteins and activation of Akt, enhance the ability of cells to survive heat stress. On the other hand, heat stress can trigger cell-death signaling via activation of the stress-activated protein kinase/c-Jun NH2-terminal kinase (SAPK/Jnk). Recently, it has been shown that kinases activated by heat stress can regulate synthesis and functioning of the molecular chaperones, and these chaperones modulate the activity of the cell death and survival pathways. We have found that Akt plays a central role in determining the fate of L929 fibroblast cells exposed to heat stress. In our experiments heat stress causes Akt depletion and L929 cells to undergo cell death. Heat-shock protein 70 (Hsp70) is known to prevent stress-induced cell death by interfering with the SAPK/Jnk signaling pathway. In our study, there is a very high level of induction of Hsp70, yet this is not sufficient to rescue Akt depletion and L929 from cell death. The Akt depletion is specific, since actin protein level does not change during the heat stress. Moreover, our studies show that L929 cells can recover from a short-term heat shock, whereby, Akt level is returned to normal following recovery from heat shock. Therefore, it appears that the fate of the prolonged heat-stressed fibroblast cells is determined by Akt level, and that return of Akt protein level to normal prevents cell death.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".