Up-regulated Expression of Fas Antigen in Peripheral T cell Subsets in Patients with Myasthenia Gravis
Bibliographic record
Abstract
PURPOSE: Recent reports have linked various autoimmune diseases to defective Fas-mediated apoptosis or Fas expression. Here we aimed to determine whether Fas-mediated apoptosis is involved in the pathogenesis of myasthenia gravis (MG). METHODS: The expression of Fas antigen in peripheral T cell subsets from 17 Chinese patients with MG and 13 healthy individuals was determined by flow cytometry, and its associations with clinical classification, thymus pathology, the concomitance with hyperthyroidism (HT) and corticosteroid treatment were investigated. RESULTS: Compared with normal controls, a significantly up-regulated expression of Fas antigen was observed in the peripheral CD4+, CD4+CD8- and CD4-CD8- T cell subsets from patients with MG. Fas expression in CD4-CD8+ T cells of MG patients with normal thymus was significantly higher than that of patients with thymoma. Fas expressions in CD4+CD8+ T cells in MG patients with HT was significantly higher than controls and the ones without HT. Enhanced Fas expressions was found in CD4-CD8+ and CD4-CD8- T cells of MG patients with corticosteroid treatment, but no significant difference of Fas expression in peripheral T cells between patients with ocular MG (OMG) and general MG (GMG) was observed. CONCLUSION: Fas antigen may play a role in the pathogenesis of MG. It may be involved in the mechanisms of corticosteroid treatment, and with the occurrence of HT. OMG may represent a systemic disease, similar to that of GMG.
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 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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".