Human GSTA1-1 reduces c-Jun N-terminal kinase signalling and apoptosis in Caco-2 cells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it