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Record W2982464794 · doi:10.1093/jnen/nlz098

Astrocytes in the Pathogenesis of Multiple Sclerosis: An In Situ MicroRNA Study

2019· article· en· W2982464794 on OpenAlexaff
Vijayaraghava T.S. Rao, Shih-Chieh Fuh, Jason Karamchandani, John Woulfe, David G. Muñoz, Benjamin Ellezam, Manon Blain, Ming‐Kai Ho, Barry J. Bedell, Jack P. Antel, Samuel K. Ludwin

Bibliographic record

VenueJournal of Neuropathology & Experimental Neurology · 2019
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsQueen's UniversityUniversité de MontréalOttawa HospitalMcGill UniversityUniversity of OttawaMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMultiple sclerosisWhite matterGrey mattermicroRNAPathogenesisBiologyNeuroprotectionLesionAstrocyteIn situ hybridizationPathologyDownregulation and upregulationGlutamate receptorNeurogliaNeuroscienceCentral nervous systemGene expressionImmunologyMedicineGeneticsGeneMagnetic resonance imaging

Abstract

fetched live from OpenAlex

Astrocytes are increasingly recognized as active contributors to the disease process in multiple sclerosis (MS), rather than being merely reactive. We investigated the expression of a selected microRNA (miRNA) panel that could contribute both to the injury and to the recovery phases of the disease. Individual astrocytes were laser microdissected from brain sections. We then compared the miRNAs' expressions in MS and control brain samples at different lesional stages in white versus grey matter regions. In active MS lesions, we found upregulation of ischemia-related miRNAs in white but not grey matter, often with reversion to the normal state in inactive lesions. In contrast to our previous findings on MS macrophages, expression of 2 classical inflammatory-related miRNAs, miRNA-155 and miRNA-146a, was reduced in astrocytes from active and chronic active MS lesions in white and grey matter, suggesting a lesser direct pathogenetic role for these miRNAs in astrocytes. miRNAs within the categories regulating aquaporin4 (-100, -145, -320) and glutamate transport/apoptosis/neuroprotection (-124a, -181a, and -29a) showed some contrasting responses. The regional and lesion-stage differences of expression of these miRNAs indicate the remarkable ability of astrocytes to show a wide range of selective responses in the face of differing insults and phases of resolution.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.058
GPT teacher head0.323
Teacher spread0.265 · 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 designObservational
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

Citations27
Published2019
Admission routes1
Has abstractyes

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