Reduced plasmablast frequency is associated with seronegative myasthenia gravis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".