Characterization of bronchoalveolar lavage T cell subsets in sarcoidosis on the basis of CD57, CD4 and CD8
Bibliographic record
Abstract
T cells expressing CD57 (a natural killer cell marker) with interferon-gamma (IFN-gamma) producing capacity increase under various conditions. CD57+ T cells are also present in the bronchoalveolar lavage fluid (BALF) of sarcoidosis, and several phenotypical and functional analyses of these cells have been reported. In the present study, BALF T cells obtained from 52 patients with sarcoidosis were classified further into CD4+CD57+ T cells, CD4+CD57- T cells, CD8+CD57+ T cells and CD8+CD57- T cells and their phenotypes and functional characteristics were assessed. Substantial proportions of these T cell subsets expressed natural killer cell markers CD161 and CD122. The biased expansion of Vbeta2 T cells was observed in both CD4+CD57+ T cells and CD4+CD57- T cells in BALF from most patients, while the expansion of other Vbeta T cells was also observed in some patients. Unexpectedly, the biased expansion of certain Vbeta T cells was also seen in either CD8+CD57+ T cells or CD8+CD57- T cells, while the expanded Vbeta T cells in CD8+ T cells differed substantially among individuals. BALF T cells showed a remarkably lower T cell receptor (TCR) intensity than that of peripheral blood T cells. Both CD8+ T cell subsets in BALF of sarcoidosis expressed the intracellular perforin/granzyme B, while all four subsets expressed intracellular IFN-gamma after in vitro activation, and CD4+ T cells, especially CD4+CD57+ T cells, expressed tumour necrosis factor-alpha. These findings indicate that CD57+ T cells as well as CD57- T cells in the BALF are phenotypically and functionally different from peripheral blood T cells and may play an important role in the Th1 dominant state and inflammation in pulmonary sarcoidosis.
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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 | 0.001 | 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".