MétaCan
Menu
Back to cohort
Record W4353041379 · doi:10.1186/s40478-023-01543-8

Localized microglia dysregulation impairs central nervous system myelination in development

2023· article· en· W4353041379 on OpenAlexaff
R. Holloway, Liang Zhang, Irene Molina-González, Kathy Ton, James A. R. Nicoll, James P. Boardman, Yan Liang, Anna Williams, Véronique E. Miron

Bibliographic record

VenueActa Neuropathologica Communications · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsPublic Health OntarioUniversity of TorontoSt. Michael's Hospital
FundersMedical Research Council
KeywordsMicrogliaNeuroscienceCentral nervous systemNeuroinflammationNeurologyMedicineBiologyInflammationImmunology

Abstract

fetched live from OpenAlex

Myelination of neuronal axons is a critical aspect of central nervous system development and function. However, the fundamental cellular and molecular mechanisms influencing human developmental myelination and its failure are not fully understood. Here, we used digital spatial transcriptomics of a rare bank of human developing white matter to uncover that a localized dysregulated innate immune response is associated with impeded myelination. We identified that poorly myelinating areas have a distinct signature of Type II interferon signalling in microglia/macrophages, relative to adjacent myelinating areas. This is associated with a surprising increase in mature oligodendrocytes, which fail to form myelin processes appropriately. We functionally link these findings by showing that conditioned media from interferon-stimulated microglia is sufficient to dysregulate myelin process formation by oligodendrocytes in culture. We identify the Type II interferon inducer, Osteopontin (SPP1), as being upregulated in poorly myelinating brains, indicating a potential biomarker. Our results reveal the importance of microglia-mature oligodendrocyte interaction and interferon signaling in regulating myelination of the developing human brain.

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 score0.267
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.067
GPT teacher head0.285
Teacher spread0.218 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueActa Neuropathologica CommunicationsSame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207