scyllo-Inositol Promotes Robust Mutant Huntingtin Protein Degradation
Bibliographic record
Abstract
Huntington disease is characterized by neuronal aggregates and inclusions containing polyglutamine-expanded huntingtin protein and peptide fragments (polyQ-Htt). We have used an established cell-based assay employing a PC12 cell line overexpressing truncated exon 1 of Htt with a 103-residue polyQ expansion that yields polyQ-Htt aggregates to investigate the fate of polyQ-Htt-drug complexes. scyllo-Inositol is an endogenous inositol stereoisomer known to inhibit accumulation and toxicity of the amyloid-β peptide and α-synuclein. In light of these properties, we investigated the effect of scyllo-inositol on polyQ-Htt accumulation. We show that scyllo-inositol lowered the number of visible polyQ-Htt aggregates and robustly decreased polyQ-Htt protein abundance without concomitant cellular toxicity. We found that scyllo-inositol-induced polyQ-Htt reduction was by rescue of degradation pathways mediated by the lysosome and by the proteasome but not autophagosomes. The rescue of degradation pathways was not a direct result of scyllo-inositol on the lysosome or proteasome but due to scyllo-inositol-induced reduction in mutant polyQ-Htt protein levels.
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.
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".