Oxidative Preconditioning and Apoptosis in L-cells
Bibliographic record
Abstract
Oxidative stress can cause significant cell death by apoptosis. We performed studies in L-cells to explore whether prior exposure to oxidative stress ("oxidative preconditioning") can protect the cell against the apoptotic consequences of subsequent oxidative insults and to establish the mediators in the preconditioning signaling cascade. Cells were preconditioned with three 5-min exposures to H(2)O(2), followed by 10-h recovery and subsequent exposure to 600 microm H(2)O(2) for 10 h. A single 10-h exposure to H(2)O(2) induced substantial apoptotic cell death (approximately 90%), as determined by enzyme-linked immunosorbent assay, TUNEL (terminal deoxyribonucleotide transferase-mediated dUTP nick end labeling), and Annexin V methods, but apoptosis was largely prevented in preconditioned cells. The degree of cytoprotection depended on the strength of preconditioning or H(2)O(2) concentration (20 approximately 600 microm). Transient increases in mitogen-activated protein kinase (MAPK), p38, and JNK/SAPK activities and sustained protein kinase B (Akt) activation, accompanied by drastically reduced caspase 3 activity, were seen after preconditioning. The expression levels of these kinases were unaltered. Inhibitors of p38 (SB203580) and phosphoinositide 3-kinase (PI3K, LY294002) pathways abolished the protection provided by preconditioning. We conclude that oxidative preconditioning protects cells against apoptosis and that this effect involves MAPK and PI3K/Akt pathways. This system may be important in regulating apoptotic cell death in development and disease states.
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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) | 0.001 | 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".