Expression of S100A6 in Cardiac Myocytes Limits Apoptosis Induced by Tumor Necrosis Factor-α
Bibliographic record
Abstract
S100A6 is induced in myocardium post-infarction in vivo and in response to growth factors and inflammatory cytokines in vitro. Forced expression of S100A6 in cardiomyocytes inhibits regulation of cardiac specific gene expression in response to trophic stimulation. To define regulation and function of S100A6, we characterized the human S100A6 promoter and mapped upstream regulatory elements in rat neonatal cardiac myocytes, fibroblasts, and vascular smooth muscle cells and defined a functional role for S100A6 in tumor necrosis factor-alpha-induced myocyte apoptosis. The functional S100A6 promoter was localized to region -167/+134 containing 167 upstream base pairs. The S100A6 promoter is regulated by positive (-361/-167 and -588/-361) and negative (-1371/-1194) elements. Tumor necrosis factor-alpha induced the maximal S100A6 promoter and transcription factor NF-kappaB (p65 subunit). Electrophoretic mobility shift showed that tumor necrosis factor-alpha induced p65 binding to a potential NF-kappaB-binding site at -460/-451. Chromatin immunoprecipitation analysis revealed p65 is recruited to the S100A6 promoter upon tumor necrosis factor-alpha stimulation. The NF-kappaB inhibitor caffeic acid phenethyl ester and mutation of the NF-kappaB-binding site inhibited S100A6 promoter activation by tumor necrosis factor-alpha. Tumor necrosis factor-alpha induced cardiac myocyte apoptosis. Specific inhibition of S100A6 using a small interfering RNA directed against S100A6 potentiated tumor necrosis factor-alpha-induced myocyte apoptosis, whereas overexpression of S100A6 by gene transfer prevented tumor necrosis factor-alpha-induced myocyte apoptosis by interfering with p53 phosphorylation. These results demonstrate that S100A6 is induced by tumor necrosis factor-alpha via an NF-kappaB-dependent mechanism, serving a role in homeostasis to limit tumor necrosis factor-alpha-induced apoptosis by regulating p53 phosphorylation.
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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 | 0.000 |
| 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".