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Record W4405626339 · doi:10.1101/2024.12.17.628958

Pro-Inflammatory Molecules Implicated in Multiple Sclerosis Divert the Development of Human Oligodendrocyte Lineage Cells

2024· preprint· en· W4405626339 on OpenAlexaff
Gabriela J. Blaszczyk, Abdulshakour Mohammadnia, Valerio E. C. Piscopo, Julien Sirois, Qiao‐Ling Cui, Moein Yaqubi, Thomas M. Durcan, Raphaël Schneider, Jack P. Antel

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsToronto Public HealthMcGill UniversityUniversity of TorontoMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMultiple sclerosisLineage markersOligodendrocyteBiologyMyelinTumor necrosis factor alphaTranscriptomeCell biologyContext (archaeology)Induced pluripotent stem cellImmunologyTranscription factorAstrocyteStem cellGene expressionNeuroscienceGeneGeneticsProgenitor cellCentral nervous system

Abstract

fetched live from OpenAlex

Abstract Background and Objectives Oligodendrocytes (OL) and their myelin-forming processes are targeted and lost during the disease course of Multiple Sclerosis (MS), targeted by infiltrating leukocytes and their effector cytokines. Myelin repair is considered to be dependent on recruitment and differentiation of oligodendrocyte precursor cells (OPCs). The basis of failure of re-myelination during the disease course of MS remains to be defined. The aim of this study is to determine the impact of pro-inflammatory molecules tumor necrosis factor ⍰ (TNF⍰) and interferon gamma (IFN γ ) on the differentiation of human OPCs. Methods We generated human OPCs from induced pluripotent stem cells with a reporter gene under the OL-specific transcription factor SOX10. We treated the cells in vitro with TNF⍰ or IFN γ and evaluated effects in terms of cell viability, expression of OL-lineage markers, and co- expression of astrocyte markers. To relate our findings to the molecular properties of OPCs as found in the MS brain we re-analyzed publicly available single nuclear RNAseq datasets. Results Our analysis indicated that both TNF⍰ and IFN γ decreased the proportion of cells differentiating into the OL-lineage; consistent with previous reports. We now observe the TNF⍰ effect is linked to aberrant OPC differentiation. A subset of O4+, reporter-positive cells co- expressed the astrocytic marker Aquaporin-4 (AQP4). On the transcriptomic level, the cells acquire an astrocyte-like signature alongside a conserved reactive phenotype. Analysis of single- nuclear RNAseq datasets from human MS brain revealed a subset of OPCs expressing an astrocytic signature. Discussion In the context of MS, these results imply that OPCs are present but inhibited from differentiating along the OL-lineage, with a subset acquiring a reactive and stem-cell like phenotype, reducing their capacity to contribute towards repair. These findings help define a potential basis for the impaired myelin repair in MS and provide a prospective route for regenerative treatment.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.021
GPT teacher head0.226
Teacher spread0.205 · 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
Published2024
Admission routes1
Has abstractyes

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