S100B protein activates a RAGE‐dependent autocrine loop in astrocytes: implications for its role in the propagation of reactive gliosis
Bibliographic record
Abstract
Extracellular S100B dramatically increases after brain injury. While low S100B levels are neuroprotective, micromolar S100B levels have shown in vitro to activate microglia and facilitate neuronal death. In astrocytes, S100B exposure activates nuclear factor kappa B (NF-κB) and induces pro-inflammatory mediators. On microglia and neurons S100B effects are essentially mediated by receptor for advanced glycation end products (RAGE)/NF-κB, but it is not clear if these intracellular cascades are activated by different S100B levels in astrocytes and whether increased extracellular S100B is sufficient to induce reactive gliosis. A better understanding of these pathways is essential for developing successful strategies to preserve the beneficial S100B effects after brain injury. Here, we show that microglia-depleted cultured astrocytes exposed to S100B mimicked several features of reactive gliosis by activating RAGE/Rac-1-Cdc42, RAGE/Erk-Akt or RAGE/NF-κB-dependent pathways. S100B effects include RAGE/Rac1-Cdc42-dependent astroglial hypertrophy and facilitation of migration as well as increased mitosis. S100B exposure improved the astrocytic survival to oxidative stress, an effect that requires Erk/Akt. S100B also activates NF-κB in a dose-dependent manner; increases RAGE proximal promoter transcriptional activity and augmented endogenous RAGE expression. S100B-exposed astrocytes showed a pro-inflammatory phenotype with expression of Toll-like receptor 2 (TLR 2), inducible nitric oxide synthase (iNOS) and interleukin 1-beta (IL-1β), and facilitated neuronal death induced by oxygen-glucose deprivation. In vivo, intracerebral infusion of S100B was enough to induce an astroglial reactive phenotype. Together, these findings demonstrate that extracellular S100B in the micromolar level activates different RAGE-dependent pathways that turn astrocytes into a pro-inflammatory and neurodegenerative phenotype. We propose that S100B turns astrocytes into a reactive phenotype in a RAGE-dependent manner but engaging different intracellular pathways. While both nanomolar and micromolar S100B turn astrocytes into a reactive phenotype, micromolar S100B induces a conversion into a pro-inflammatory-neurodegenerative profile that facilitates neuronal death of OGD-exposed neurons. We think that S100B/RAGE interaction is essential to expand reactive gliosis in the injured brain being a tempting target for limiting reactive gliosis to prevent the glial conversion into the neurodegenerative profile.
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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 | 0.001 |
| 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".