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Record W3110953994 · doi:10.1002/mus.27140

Reduced plasmablast frequency is associated with seronegative myasthenia gravis

2020· article· en· W3110953994 on OpenAlexaff
Jeffrey T. Guptill, Richard Barfield, Cliburn Chan, Melissa A. Russo, Doug Emmett, Shruti M. Raja, Janice M. Massey, Vern C. Juel, Lisa D. Hobson‐Webb, Karissa Gable, Natalia González, Alex Hammett, James F. Howard, Manisha Chopra, Henry J. Kaminski, Zaeem A. Siddiqi, Mattingly Migdal, John S. Yi

Bibliographic record

VenueMuscle & Nerve · 2020
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsUniversity of Alberta
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and Stroke
KeywordsMyasthenia gravisImmunologyCD19ImmunopathologyImmune systemBiomarkerMedicineCD154CD20Odds ratioAntibodyInternal medicineBiologyCD40Genetics

Abstract

fetched live from OpenAlex

BACKGROUND: The immunopathology of autoimmune seronegative myasthenia gravis (SN MG) is poorly understood. Our objective was to determine immune profiles associated with a diagnosis of SN MG. METHODS: We performed high-dimensional flow cytometry on blood samples from SN MG patients (N = 68), healthy controls (N = 46), and acetylcholine receptor antibody (AChR+) MG patients (N = 27). We compared 12 immune cell subsets in SN MG to controls using logistic modeling via a discovery-replication design. An exploratory analysis fit a multinomial model comparing AChR+ MG and controls to SN MG. RESULTS: plasmablast frequencies was associated with lower odds of being a SN MG case in both the discovery and replication analyses (discovery P-value = .0003, replication P-value = .0021). Interleukin (IL) -21 producing helper T cell frequencies were associated with a diagnosis of AChR+ MG (P = .004). CONCLUSIONS: Reduced plasmablast frequencies are strongly associated with a SN MG diagnosis and may be a useful diagnostic biomarker in the future.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.238
Teacher spread0.211 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations6
Published2020
Admission routes1
Has abstractyes

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