Phenotypic and molecular characterization of CD103<sup>+</sup> CD4<sup>+</sup> T cells in bronchoalveolar lavage from patients with interstitial lung diseases
Bibliographic record
Abstract
BACKGROUND: The integrin CD103 is preferentially expressed on intraepithelial T lymphocytes, and cells expressing this integrin may play a regulatory role in the microenvironment of the epithelial cell layer. METHODS: The relative number of CD103(+)/CD4(+) T cells in the bronchoalveolar lavage was significantly elevated in all patients diagnosed with interstitial lung diseases compared with patients with other non-fibrotic disorders of the lung. RESULTS: Analysis by flow cytometry showed that the CD103(+) and the CD103(-) subpopulations were memory T cells based on the high expression of CD45RO(+). However, the CD103(+)/CD4(+) T cells were CD25(low), CD27(-), CD28(low), and CD62L(-), whereas the CD103(-)/CD4(+) T cells expressed CD25 and CD62L and were CD27(high) and CD28(high). In addition, the CD103(+)/CD4(+) T cells expressed significantly higher quantities of VLA-1 and CD101 than did CD103(-)/CD4(+) T cells. Reverse transcriptase polymerase chain reaction analysis of purified CD103(+) and CD103(-) CD4(+) T cells showed production of tumor necrosis factor (TNF) alpha-R-1 (p55), TNF-alpha-R-2 (p75), interferon gamma, interleukin-10, and TNF-alpha mRNA in both subpopulations. No interleukin-4 mRNA was detected in either subpopulation. CONCLUSIONS: CD103(+)/CD4(+) T cells represent a T-helper 1-like subpopulation in human lungs with a distinct effector phenotype. Despite the lack of CD27 and the low CD25 and CD28 expression, these cells show a high degree of activation. These results suggest that CD103 expressing CD4 T cells in the lung are continuously activated, long-living cells.
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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 | 0.001 |
| 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) | 0.002 | 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".