Heat shock protein 70 alters the endosome-lysosomal localization of huntingtin
Bibliographic record
Abstract
Huntington's disease is caused by CAG trinucleotide expansions in the gene encoding huntingtin. N- terminal fragments of huntingtin with polyglutamine produce aggregates in the endosome-lysosomal system, where proteolytic fragments of huntingtin is generated. Heat shock protein 70 (HSP70) prevents the formation of protein aggregates, but the effect of HSP70 on the huntingtin in the endosome-lysosomal system is unknown. This study was to determine whether HSP70 alters the distribution of huntingtin in endosome-lysosomal system. HSP70 expressing stable cells (NIH/3T3 or cerebral hybrid cell line A1) were generated, and mutant [(CAG)(100)] huntingtin was transiently overexpressed. Analysis of subcellular distribution by immunocytochemistry or proteolysis cleavage by Western blotting was performed. 18 CAG repeat wild type [WT; (CAG)(18)] huntingtin was used as a control. Cells with huntingtin showed patterns of endosome-lysosomal accumulation, from a "dispersed vacuole (DV)" type into a coalescent "perinuclear vacuole (PV)" type over time. In WT huntingtin, HSP70 increased the cells with the PV types that enhanced the proteolytic cleavage of huntingtin. However, HSP70 reduced cells of the DV and PV types expressing mutant huntingtin, that result in less proteolysis than that of control. In addition, intranuclear inclusions were formed only in mutant cells, which was not affected by HSP70. These results suggest that HSP70 alters the distribution of huntingtin in the endosome- lysosomal system, and that this contributes to huntingtin proteolysis.
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".