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Record W4309565048 · doi:10.1038/s42003-022-04248-1

Chronic oligodendrocyte injury in central nervous system pathologies

2022· review· en· W4309565048 on OpenAlexaff
Irene Molina-González, Véronique E. Miron, Jack P. Antel

Bibliographic record

VenueCommunications Biology · 2022
Typereview
Languageen
FieldNeuroscience
TopicNeurogenesis and neuroplasticity mechanisms
Canadian institutionsMcGill UniversityMontreal Neurological Institute and HospitalOccupational Cancer Research CentreUniversity of Toronto
FundersMedical Research CouncilUniversity of EdinburghMultiple Sclerosis International FederationInternational Progressive MS AllianceAstex Pharmaceuticals
KeywordsMyelinCentral nervous systemOligodendrocyteMultiple sclerosisNeuroscienceNervous systemDiseaseMedicineRemyelinationBiologyImmunologyPathology

Abstract

fetched live from OpenAlex

Myelin, the membrane surrounding neuronal axons, is critical for central nervous system (CNS) function. Injury to myelin-forming oligodendrocytes (OL) in chronic neurological diseases (e.g. multiple sclerosis) ranges from sublethal to lethal, leading to OL dysfunction and myelin pathology, and consequent deleterious impacts on axonal health that drive clinical impairments. This is regulated by intrinsic factors such as heterogeneity and age, and extrinsic cellular and molecular interactions. Here, we discuss the responses of OLs to injury, and perspectives for therapeutic targeting. We put forward that targeting mature OL health in neurological disease is a promising therapeutic strategy to support CNS function.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0040.003
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 head0.175
GPT teacher head0.374
Teacher spread0.198 · 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 teacher head, not a consensus.

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

Citations37
Published2022
Admission routes1
Has abstractyes

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