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Record W2966265919

Unravelling the physiopathological role of sacsin, the protein mutated in the autosomal recessive spastic ataxia of Charlevoix-Saguenay (ARSACS).

2019· dissertation· en· W2966265919 on OpenAlexaboutno aff
Fabiana Longo

Bibliographic record

VenueIrInSubria (University of Insubria) · 2019
Typedissertation
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsAtaxiaGeneticsNeuroscienceBiologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

Sacsin is a large, multimodular protein encoded by the SACS gene and found only in vertebrates. It is expressed in the central nervous system, especially in Purkinje cells and corticospinal neurons. Bioinformatics’ predictions suggest that sacsin plays a role in protein quality control. However, to date sacsin physiological functions and subcellular localization are still open questions.\nLoss of function mutations in SACS gene cause Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS), an early-onset neurodegenerative disorder. Being sacsin function still unknown, the molecular pathogenesis leading to ARSACS has very poorly been investigated. My thesis is focused on exploring sacsin physiopathological role at the cellular level and on dissecting the pathogenesis of ARSACS.\nFirst, we examined how sacsin mutations alter the residual amount of the protein in ARSACS patient cells, since until now it has never been evaluated, leaving a hole in the genotypephenotype correlation in ARSACS.\nAt the same time, we investigated the effects of the lack of sacsin in different models depleted of its expression (ARSACS patient fibroblasts, SACS KO HeLa cells, Sacs KO mouse embryonic fibroblasts, and primary Purkinje neurons from the Sacs KO mouse model). We found alterations in mitochondrial dynamics, namely mitochondrial hyperfusion and, by dissecting the molecular mechanism, we demonstrated that the mitochondrial fission process was indeed impaired. In line with these results, we showed that mitochondrial hyperfusion has a strong impact on mitochondrial trafficking in primary Purkinje cells that lack sacsin expression. This highlights the importance of this phenotype in the pathogenesis of ARSACS, as Purkinje neurons are the first cells to be affected.\nIn sacsin-depleted cells, we detected a dramatic remodelling of the cytoskeletal network, particularly of intermediate filaments. Our data supports the hypothesis that sacsin may be involved in intermediate filament remodelling in an indirect manner, such as by regulating their folding. This is also suggested by the predicted chaperone-like activities of certain sacsin domains. An intermediate filament reorganization and/or accumulation could sterically hinder both transport and distribution of mitochondria in Purkinje neurons of Sacs KO mouse. On the other hand, cytoskeletal derangement could be responsible for impairing DRP1 recruitment.\nThe cellular phenotypes that we have identified in the absence of sacsin are steps forward in understanding the pathogenetic cascade of ARSACS and shed light on potential sacsin functions.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.234
Teacher spread0.211 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2019
Admission routes1
Has abstractyes

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