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Record W4385516272 · doi:10.3389/fimmu.2023.1188750

Under the influence: environmental factors as modulators of neuroinflammation through the IL-10/IL-10R axis

2023· review· en· W4385516272 on OpenAlexafffund
Eryn Bugbee, A. Wang, Jennifer L. Gommerman

Bibliographic record

VenueFrontiers in Immunology · 2023
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of Toronto
FundersMultiple Sclerosis SocietyMultiple Sclerosis Society of CanadaEuropean Genomic Institute for Diabetes
KeywordsNeuroinflammationMultiple sclerosisNeuroscienceInterleukin 17DiseaseCentral nervous systemReceptorInterleukin 23Identification (biology)MedicineImmunologyBiologyImmune systemInternal medicineEcology

Abstract

fetched live from OpenAlex

The IL-10/IL-10 receptor (IL-10R) axis plays an important role in attenuating neuroinflammation in animal models of Multiple Sclerosis (MS) and increased IL-10 has been associated with a positive response to MS disease modifying therapy. Because environmental factors play an important role in MS susceptibility and disease course, identification of environmental factors that impact the IL-10/IL-10R axis has therapeutic potential. In this review, we provide historical and updated perspectives of how IL-10R signaling impacts neuroinflammation, discuss environmental factors and intestinal microbes with known impacts on the IL-10/IL-10R axis, and provide a hypothetical model for how B cells, via their production of IL-10, may be important in conveying environmental "information" to the inflamed central nervous 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)0.000
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.056
GPT teacher head0.335
Teacher spread0.278 · 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

Citations21
Published2023
Admission routes2
Has abstractyes

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