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Record W3002308644 · doi:10.1177/1352458519899040

A critical analysis of helminth immunotherapy in multiple sclerosis

2020· article· en· W3002308644 on OpenAlexaff
Marc Charabati, Sarah J. Donkers, Megan C. Kirkland, Lisa C. Osborne

Bibliographic record

VenueMultiple Sclerosis Journal · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsUniversity of SaskatchewanUniversity of British ColumbiaMemorial University of NewfoundlandCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMultiple sclerosisImmunologyImmunotherapyHelminthsPopulationHelminth infectionsHelminthiasisImmune systemMedicineBiologyEnvironmental health

Abstract

fetched live from OpenAlex

Helminthic worms are ancestral members of the intestinal ecosystem that have been largely eradicated from the general population in industrialized countries. Immunomodulatory mechanisms induced by some helminths mediate a "truce" between the mammalian host and the colonizing worm, thus allowing for long-term persistence in the absence of immune-mediated collateral tissue damage. This concept and the geographic discrepancy between global burdens of chronic inflammatory diseases and helminth infection have sparked interest in the potential of using helminthic worms as a therapeutic intervention to limit the progression of autoimmune diseases such as multiple sclerosis (MS). Here, we present and evaluate the evidence for this hypothesis in the pre-clinical animal model of MS, experimental autoimmune encephalitis, in helminth-infected MS patients and in clinical trials of administered helminth immunotherapy (HIT).

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)0.002
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.109
GPT teacher head0.304
Teacher spread0.195 · 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

Citations29
Published2020
Admission routes1
Has abstractyes

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