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C-terminus of Hsp70 Interacting Protein (CHIP) and Neurodegeneration: Lessons from the Bench and Bedside

2020· review· en· W3098653109 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Neuropharmacology · 2020
Typereview
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsToronto Western HospitalUniversity Health NetworkUniversity of Toronto
Fundersnot available
KeywordsNeurodegenerationAmyotrophic lateral sclerosisNeuroscienceSpinocerebellar ataxiaFrontotemporal lobar degenerationMedicineDiseaseAtaxiaBiologyFrontotemporal dementiaDementiaPathology

Abstract

fetched live from OpenAlex

Neurodegenerative diseases are characterized by the increasing dysfunction and death of neurons, resulting in progressive impairment of a person's mobility and/or cognition. Protein misfolding and aggregation are commonly hypothesized to cause neurotoxicity and, eventually, neuronal degeneration that are associated with these diseases. Emerging experimental evidence, as well as recent findings from human studies, reveal that the C-terminus of Hsp70 Interacting Protein (CHIP), or STIP1 Homology and U-box containing Protein 1 (STUB1), is a quality control protein involved in neurodegeneration. Here, we review evidence that CHIP interacts with and plays a role in regulating proteins implicated in the pathogenesis of Parkinson's disease, Alzheimer's disease, amyotrophic lateral sclerosis, and polyglutamine diseases, including Huntington's disease and spinocerebellar ataxias. We also review clinical findings identifying mutations in STUB1 as a cause of both autosomal recessive and autosomal dominant forms of cerebellar ataxia. We propose that CHIP modulation may have therapeutic potential for the treatment of multiple neurodegenerative diseases.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.933
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.152
GPT teacher head0.413
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it