Sex-dependent factors encoded in the immune compartment dictate relapsing or progressive phenotype in demyelinating disease
Bibliographic record
Abstract
TCR1640 mice, which have a T cell receptor (TCR) directed against MOG92-106, spontaneously develop experimental autoimmune encephalomyelitis. Female mice mostly develop a relapsing-remitting (RR) course and have a higher incidence of disease, while males most frequently suffer from progressive disease, reflecting the unresolved clinical sex discrepancies seen in multiple sclerosis. Herein, we performed adoptive transfers of male and female TCR1640 immune cells into WT animals to investigate if disease course is dependent on the sex of the donor immune cells or on the sex of the recipient animal. We found that transfer of female TCR1640 immune cells led to a RR disease while transfer of male TCR1640 immune cells led to a progressive course, independent of the sex of the recipient. In addition, regulatory and pathogenic T cell infiltration after transfer was also immune cell sex intrinsic. We performed genetic profiling of the donor immune cells and found significant differences between the transcriptomic profiles of male and female TCR1640 immune cells, interestingly, within genes related to immune regulation of T lymphocytes. These results suggest that differences in gene expression profiles related to regulation of T cell immunity seen in male and female neuroinflammatory disease drive relapsing versus progressive disease course.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".