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Record W2574076923 · doi:10.1002/eji.201646716

TGF‐β regulation of encephalitogenic and regulatory T cells in multiple sclerosis

2017· review· en· W2574076923 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Journal of Immunology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsInstitute of Infection and Immunity
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and StrokeNational Institutes of HealthNational Multiple Sclerosis Society
KeywordsExperimental autoimmune encephalomyelitisMultiple sclerosisAutoimmunityBiologyTransforming growth factorImmunologyRegulatory T cellImmune systemTransforming growth factor betaCytokineT cellEffectorCell biologyMediatorAutoimmune diseaseIL-2 receptorAntibody

Abstract

fetched live from OpenAlex

Transforming growth factor beta (TGF‐β) is a pleiotropic cytokine that has been shown to influence the differentiation and function of T cells. The role that TGF‐β plays in immune‐mediated disease, such as multiple sclerosis (MS), has become a major area of investigation since CD4 + T cells appear to be a major mediator of autoimmunity. This review provides an analysis of the literature on the role that TGF‐β plays in the generation and regulation of encephalitogenic and regulatory T cells (Treg) in experimental autoimmune encephalomyelitis (EAE), an animal model of MS, as well as in T cells of MS patients. Since TGF‐β plays a major role in the development and function of both CD4 + effector and Treg, which are defective in MS patients, recent studies have found potential mechanisms to explain the basis for these T‐cell defects to establish a foundation for potentially modulating TGF‐β signaling to restore normal T‐cell function in MS patients.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.952
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.093
GPT teacher head0.280
Teacher spread0.186 · 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