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Record W4386325811 · doi:10.3389/fncel.2023.1247297

Unraveling the impact of disrupted nucleocytoplasmic transport systems in C9orf72-associated ALS

2023· review· en· W4386325811 on OpenAlexafffund
Philip McGoldrick, Janice Robertson

Bibliographic record

VenueFrontiers in Cellular Neuroscience · 2023
Typereview
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsOccupational Cancer Research CentreUniversity of Toronto
FundersFondation Brain CanadaALS Society of Canada
KeywordsC9orf72Frontotemporal dementiaAmyotrophic lateral sclerosisNuclear transportRanTrinucleotide repeat expansionNeurodegenerationBiologyGeneticsMutationFrontotemporal lobar degenerationNeuroscienceCell biologyGeneDiseaseMedicineDementiaPathologyCell nucleus

Abstract

fetched live from OpenAlex

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are two adult-onset neurodegenerative diseases that are part of a common disease spectrum due to clinical, genetic, and pathological overlap. A prominent genetic factor contributing to both diseases is a hexanucleotide repeat expansion in a non-coding region of the C9orf72 gene. This mutation in C9orf72 leads to nuclear depletion and cytoplasmic aggregation of Tar DNA-RNA binding protein 43 (TDP-43). TDP-43 pathology is characteristic of the majority of ALS cases, irrespective of disease causation, and is present in ~50% of FTD cases. Defects in nucleocytoplasmic transport involving the nuclear pore complex, the Ran-GTPase cycle, and nuclear transport factors have been linked with the mislocalization of TDP-43. Here, we will explore and discuss the implications of these system abnormalities of nucleocytoplasmic transport in C9orf72-ALS/FTD, as well as in other forms of familial and sporadic ALS.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.106
GPT teacher head0.380
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations20
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Cellular NeuroscienceSame topicAmyotrophic Lateral Sclerosis ResearchFrench-language works237,207