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Record W4386695348 · doi:10.1186/s12974-023-02893-9

N-acetylglucosamine inhibits inflammation and neurodegeneration markers in multiple sclerosis: a mechanistic trial

2023· article· en· W4386695348 on OpenAlexaff
Michael Sy, Barbara L. Newton, Judy Pawling, Ken Hayama, Andres Cordon, Zhaoxia Yu, Jens Kühle, James W. Dennis, Alexander U. Brandt, Michael A. Demetriou

Bibliographic record

VenueJournal of Neuroinflammation · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlycosylation and Glycoproteins Research
Canadian institutionsUniversity of TorontoLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersNational Center for Complementary and Integrative HealthNational Center for Advancing Translational SciencesNational Institute of Allergy and Infectious Diseases
KeywordsNeurodegenerationMultiple sclerosisRemyelinationInflammationMedicineImmunologyMyelin oligodendrocyte glycoproteinMyelinExperimental autoimmune encephalomyelitisInternal medicineDiseaseCentral nervous system

Abstract

fetched live from OpenAlex

BACKGROUND: In the demyelinating disease multiple sclerosis (MS), chronic-active brain inflammation, remyelination failure and neurodegeneration remain major issues despite immunotherapy. While B cell depletion and blockade/sequestration of T and B cells potently reduces episodic relapses, they act peripherally to allow persistence of chronic-active brain inflammation and progressive neurological dysfunction. N-acetyglucosamine (GlcNAc) is a triple modulator of inflammation, myelination and neurodegeneration. GlcNAc promotes biosynthesis of Asn (N)-linked-glycans, which interact with galectins to co-regulate the clustering/signaling/endocytosis of multiple glycoproteins simultaneously. In mice, GlcNAc crosses the blood brain barrier to raise N-glycan branching, suppress inflammatory demyelination by T and B cells and trigger stem/progenitor cell mediated myelin repair. MS clinical severity, demyelination lesion size and neurodegeneration inversely associate with a marker of endogenous GlcNAc, while in healthy humans, age-associated increases in endogenous GlcNAc promote T cell senescence. OBJECTIVES AND METHODS: An open label dose-escalation mechanistic trial of oral GlcNAc at 6 g (n = 18) and 12 g (n = 16) for 4 weeks was performed in MS patients on glatiramer acetate and not in relapse from March 2016 to December 2019 to assess changes in serum GlcNAc, lymphocyte N-glycosylation and inflammatory markers. Post-hoc analysis examined changes in serum neurofilament light chain (sNfL) as well as neurological disability via the Expanded Disability Status Scale (EDSS). RESULTS: 17 and B cell activity as well as sNfL, yet the addition of oral GlcNAc dose-dependently lowered serum IFNγ, IL-17, IL-6 and NfL. Oral GlcANc also dose-dependently reduced serum levels of the anti-inflammatory cytokine IL-10, which is increased in the brain of MS patients. 30% of treated patients displayed confirmed improvement in neurological disability, with an average EDSS score decrease of 0.52 points. CONCLUSIONS: Oral GlcNAc inhibits inflammation and neurodegeneration markers in MS patients despite concurrent immunomodulation by glatiramer acetate. Blinded studies are required to investigate GlcNAc's potential to control residual brain inflammation, myelin repair and neurodegeneration in 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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.068
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.042
GPT teacher head0.263
Teacher spread0.220 · 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.

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

Citations32
Published2023
Admission routes1
Has abstractyes

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