The CD8+ T cell content of transbronchial biopsies from patients with a first episode of clinically stable grade A1 cellular rejection is associated with future chronic lung allograft dysfunction
Bibliographic record
Abstract
Background T cells drive acute cellular rejection (ACR) and its progression to chronic lung allograft dysfunction (CLAD) following lung transplantation. International Society for Heart and Lung Transplantation grade A1 ACR without associated allograft dysfunction is often untreated, yet some patients develop progressive graft dysfunction. T-cell composition of A1 ACR lesions may have prognostic value; therefore, protein-level and epigenetic techniques were applied to transbronchial biopsy tissue to determine whether differential T-cell infiltration in recipients experiencing a first episode of stable grade A1 ACR (StA1R) is associated with early CLAD. Methods Sixty-two patients experiencing a first episode of StA1R were divided into those experiencing CLAD within 2 years ( n = 13) and those remaining CLAD-free for 5 or more years ( n = 49). Imaging mass cytometry (IMC) was used to profile the spectrum and distribution of intragraft T cell phenotypes on a subcohort ( n = 16; 8 early-CLAD and 8 no early-CLAD). Immunofluorescence was used to quantify CD4 + , CD8 + , and FOXP3 + cells. Separately, CD3 + cells were fluorescently labeled, micro-dissected, and the degree of Treg-specific demethylated region methylation was determined. Results PhenoGraph unsupervised clustering on IMC revealed 50 unique immune cell subpopulations. Methylation and immunofluorescence analyses demonstrated no significant differences in Tregs between early-CLAD and no early-CLAD groups. Immunofluorescence revealed that patients who developed CLAD within 2 years of lung transplantation showed greater CD8 + T cell infiltration compared to those who remained CLAD-free for 5 or more years. Conclusions In asymptomatic patients with a first episode of A1 rejection, greater CD8 + T cell content may be indicative of worse long-term outlook.
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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".