S100B Interaction With the Receptor for Advanced Glycation End Products (RAGE)
Bibliographic record
Abstract
RATIONALE: Post-myocardial infarction ventricular remodeling is associated with the expression of a variety of factors including S100B that can potentially modulate myocyte apoptosis. OBJECTIVE: This study was undertaken to investigate the expression and function of S100B and its receptor, the receptor for advanced glycation end products (RAGE) in both postinfarction myocardium and in a rat neonatal myocyte culture model. METHODS AND RESULTS: In a rat model of myocardial infarction following coronary artery ligation, we demonstrate in periinfarct myocytes, upregulation of RAGE, induction of S100B, and release into plasma with consequent myocyte apoptosis. Using a coimmunoprecipitation strategy, we demonstrate a direct interaction between S100B and RAGE. In rat neonatal cardiac myocyte cultures, S100B at concentrations > or = 50 nmol/L induced myocyte apoptosis, as evidenced by increased terminal DNA fragmentation, TUNEL, cytochrome c release from mitochondria to cytoplasm, phosphorylation of extracellular signal-regulated kinase (ERK)1/2 and p53, increased expression and activity of proapoptotic caspase-3, and decreased expression of antiapoptotic Bcl-2. Transfection of a full-length cDNA of RAGE or a dominant-negative mutant of RAGE resulted in increased or attenuated S100B-induced myocyte apoptosis, respectively. Inhibition of ERK1/2 by U0126/PD-98059 or overexpression of a dominant negative p53 comparably inhibited S100B-induced myocyte apoptosis. CONCLUSIONS: These results suggest that interaction of RAGE and its ligand S100B after myocardial infarction may play a role in myocyte apoptosis by activating ERK1/2 and p53 signaling. This receptor-mediated mechanism is uniquely amenable to therapeutic intervention.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".