Human GSTA1-1 reduces c-Jun N-terminal kinase signalling and apoptosis in Caco-2 cells
Bibliographic record
Abstract
The effect of GSTA1-1 (glutathione S-transferase Alpha 1-1) on JNK (c-Jun N-terminal kinase) activation was investigated in Caco-2 cells in which GSTA1 expression increases with degree of confluency, and in MEF3T3 cells with Tet-Off-inducible GSTA1 expression. Comparison of GSTA1 expression in pre-confluent, confluent and 8-day post-confluent Caco-2 cells revealed progressively increasing mRNA and protein levels at later stages of confluency. Exposure of pre-confluent cells to stress conditions including IL-1beta (interleukin-1beta), H2O2 or UV irradiation resulted in marked increases in JNK activity as indicated by c-Jun phosphorylation. However, JNK activation was significantly reduced in post-confluent cells exposed to the same stresses. Western-blot analysis of GSTA1-1 protein bound to JNK protein pulled down from cellular extracts showed approx. 4-fold higher GSTA1-1-JNK complex formation in post-confluent cells compared with pre-confluent cells. However, stress conditions did not alter the amount of GSTA1-1 bound to JNK. The role of GSTA1-1 in JNK suppression was more specifically revealed in Tet-Off-inducible MEF3T3-GSTA1-1 cells in which GSTA1 overexpression significantly reduced phosphorylation of c-Jun following exposure to IL-1beta, H2O2 and UV irradiation. Finally, the incidence of tumour necrosis factor alpha/butyrate-induced apoptosis was significantly higher in pre-confluent Caco-2 cells expressing low levels of GSTA1 compared with post-confluent cells. These results indicate that GSTA1 suppresses activation of JNK signalling by a pro-inflammatory cytokine and oxidative stress and suggests a protective role for GSTA1-1 in JNK-associated apoptosis.
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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) | 0.002 | 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".