S100B Mitigates Cytoskeletal and Mitochondrial Alterations in a Glial Cell Model of Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay
Bibliographic record
Abstract
Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS) is an early-onset neurological disorder caused by mutations in the SACS gene, resulting in the loss of sacsin function. Sacsin is a multidomain protein that plays key roles in chaperone regulation, protein quality control, and neurofilament dynamics. Sacsin deficiency leads to disruption of intermediate filament and mitochondrial networks. S100B, a multifunctional brain-enriched protein, exhibits protective neuroprotective functions that include chaperone activity and interactions with filament proteins and mitochondria. In this study, we used an established astroglial C6 cell model of ARSACS to investigate the potential compensatory effects of S100B on sacsin loss with respect to neurofilament integrity and mitochondrial morphological and functional hallmarks. Our results demonstrate that sacsin deletion induces S100B upregulation at both mRNA and protein levels, with the S100B protein colocalizing with perinuclear nestin aggregates and filamentous mitochondria networks. Genetic silencing and pharmacological inhibition of S100B exacerbate filament protein aggregation and mitochondrial defects, while supplementation with exogenous recombinant S100B improves ARSACS hallmarks, including decreased nestin aggregates. These findings provide evidence for functional compensation of sacsin loss by S100B in glial cells, and suggests a potential role for glial cells in ARSACS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".