MétaCan
Menu
Back to cohort
Record W6998570759

ALTERATIONS OF SACSIN RNA-BINDING PROPERTIES ARE CONNECTED TO THE DEVELOPMENT OF ARSACS

2025· book-chapter· en· W6998570759 on OpenAlexaboutno aff

Bibliographic record

VenueNova Science Publishers (Nova Science Publishers, Inc.) · 2025
Typebook-chapter
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsDiseaseMutationProtein aggregationGenePoint mutationPhenotypeSpinocerebellar ataxiaAtaxiaProtein stabilityUnfolded protein response
DOInot available

Abstract

fetched live from OpenAlex

Autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) is a neurodegenerative disease mainly characterized by cerebellar ataxia, progressive spasticity and peripheral neuropathy. It is a childhood onset disease caused by point mutations in the SACS gene (13q11) that codifies the protein SACSIN. The loss of SACSIN expression has been reported to affect the proper structure and functions of the neuronal cytoskeleton and mitochondria. However, it is still under debate whether this is a cause or a consequence. SACSIN is a multidomain protein that was suggested to bind to RNAs. However, the RNA-binding properties of SACSIN have never been investigated. Thus, we decided to investigate whether the putative alteration of SACSIN RNA-binding ability can be at the basis of the molecular mechanisms that lead to ARSACS etiology. To this extent, we are currently characterizing the structural and stability properties of SACSIN domains, as well as its RNA-binding ability through in silico, in vitro and in cells strategies. We aim at unveiling key molecular aspects that can eventually be exploited to restore SACSIN altered RNA-binding properties as innovative strategies to treat ARSACS patients

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 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)0.005
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.510
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.010
Science and technology studies0.0020.012
Scholarly communication0.0080.012
Open science0.0110.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.096
GPT teacher head0.292
Teacher spread0.196 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueNova Science Publishers (Nova Science Publishers, Inc.)Same topicGenetic Neurodegenerative DiseasesFrench-language works237,207