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Record W3120893959 · doi:10.3389/fnagi.2020.613628

The Neuroimmunology of Guillain-Barré Syndrome and the Potential Role of an Aging Immune System

2021· review· en· W3120893959 on OpenAlexafffund
Kathleen M. Hagen, Shalina S. Ousman

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2021
Typereview
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchCumming School of Medicine, University of CalgaryUniversity of Calgary
KeywordsGuillain-Barre syndromeNeuroimmunologyImmune systemImmunologyNeurosciencePeripheral nervous systemMedicineSchwann cellPeripheralCentral nervous systemBiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Guillain-Barré syndrome (GBS) is a paralyzing autoimmune condition affecting the peripheral nervous system (PNS). Within GBS there are several variants affecting different aspects of the peripheral nerve. In general, there appears to be a role for T cells, macrophages, B cells, and complement in initiating and perpetuating attacks on gangliosides of Schwann cells and axons. Of note, GBS has an increased prevalence and severity with increasing age. In addition, there are alterations in immune cell functioning that may play a role in differences in GBS with age alongside general age-related declines in reparative processes (e.g., delayed de-differentiation of Schwann cells and decline in phagocytic ability of macrophages). The present review will explore the immune response in GBS as well as in animal models of several variants of the disorder. In addition, the potential involvement of an aging immune system in contributing to the increased prevalence and severity of GBS with age will be theorized.

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)0.001
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.011
GPT teacher head0.259
Teacher spread0.249 · 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

Citations64
Published2021
Admission routes2
Has abstractyes

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