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Record W4387108150 · doi:10.1016/j.msard.2023.105029

The role of autophagy protein Atg5 in multiple sclerosis

2023· review· en· W4387108150 on OpenAlexaff
Maria-Elizabeth Baeva, Carlos R. Cámara-Lemarroy

Bibliographic record

VenueMultiple Sclerosis and Related Disorders · 2023
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsHotchkiss Brain InstituteOntario Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsAutophagyATG5Multiple sclerosisBiologyCell biologyImmunologyGeneticsApoptosis

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is a neurological disease which has a strong autoimmune component to its pathology. Although there are currently many approved immunomodulatory treatments that reduce the rate of relapse and slow down the progression of the disease, the cure is still elusive. This may be due to the underlying etiology still being unknown. Autophagy is the potential link between neurodegeneration and autoimmunity. Specifically, this review will focus on the autophagy protein Atg5 and examine the in vitro cell culture, animal and human studies that have examined its expression and effects in the context of MS. The findings of these investigations are summarized, and a model is proposed in which elevated Atg5 levels leads to dysfunctional autophagy, neurodegeneration, inflammation, and eventually clinical disability. While there are currently no drugs that specifically target Atg5, our review recommends that further investigations into the role that Atg5 plays in MS pathophysiology may eventually lead to the development of autophagy-specific treatments of MS.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.054
GPT teacher head0.275
Teacher spread0.221 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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