MétaCan
Menu
Back to cohort
Record W3120404256 · doi:10.3389/fncel.2020.600656

An “Outside-In” and “Inside-Out” Consideration of Complement in the Multiple Sclerosis Brain: Lessons From Development and Neurodegenerative Diseases

2021· review· en· W3120404256 on OpenAlexafffund
B. Paul Morgan, Jennifer L. Gommerman, Valeria Ramaglia

Bibliographic record

VenueFrontiers in Cellular Neuroscience · 2021
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Toronto
FundersUK Dementia Research InstituteMultiple Sclerosis Society of CanadaMultiple Sclerosis SocietyMultiple Sclerosis Scientific Research Foundation
KeywordsSynaptic pruningNeuroscienceComplement systemComplement (music)Multiple sclerosisComplement receptorCentral nervous systemImmune systemMicrogliaInflammationBiologySynapseImmunologyPhenotype

Abstract

fetched live from OpenAlex

The last 15 years have seen an explosion of new findings on the role of complement, a major arm of the immune system, in the central nervous system (CNS) compartment including contributions to cell migration, elimination of synapse during development, aberrant synapse pruning in neurologic disorders, damage to nerve cells in autoimmune diseases, and traumatic injury. Activation of the complement system in multiple sclerosis (MS) is typically thought to occur as part of a primary (auto)immune response from the periphery (the outside) against CNS antigens (the inside). However, evidence of local complement production from CNS-resident cells, intracellular complement functions, and the more recently discovered role of early complement components in shaping synaptic circuits in the absence of inflammation opens up the possibility that complement-related sequelae may start and finish within the brain itself. In this review, the complement system will be introduced, followed by evidence that implicates complement in shaping the developing, adult, and normal aging CNS as well as its contribution to pathology in neurodegenerative conditions. Discussion of data supporting "outside-in" vs. "inside-out" roles of complement in MS will be presented, concluded by thoughts on potential approaches to therapies targeting specific elements of the complement system.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.233
GPT teacher head0.381
Teacher spread0.149 · 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 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

Citations46
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Cellular NeuroscienceSame topicMultiple Sclerosis Research StudiesFrench-language works237,207