Bibliographic record
Abstract
OBJECTIVE: Recently, effector T-cell subpopulations have been identified that can be distinguished by expression of members of the TNF-R family: CD4+OX-40+ cells are CD4 helper-effector cells CD8+CD45RA+CD27 cells are CD8-killer-effector cells. We investigated whether these lymphocyte subsets were increased in the active phase of multiple sclerosis (MS). MATERIAL AND METHODS: Multiple colour immunofluorescence staining was performed on peripheral blood lymphocytes of 28 patients with active MS and of 29 healthy controls, followed by FACS analysis. RESULTS: Frequencies of CD8-killer-effector cells showed a wide interindividual range in both groups and percentages of CD4 helper-effector cells were low. No significant difference between the groups was observed for these subsets, but CD8+CD45RA-CD27 were increased in MS. In healthy individuals, CD4 helper-effector cells correlated with the total percentages of memory cells. Moreover, CD4+ and CD8 memory cells were strongly correlated. CONCLUSION: The here described recently identified effector CD4 and CD8 lymphocyte subpopulations were not increased in clinically active MS. It is however still possible that in MS, myelin-specific encephalitogenic cells reside within these subsets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.050 | 0.002 |
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; both teacher heads agree on what is shown here.
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".