CMV-specific T cell dynamics revealed by immune profiling in kidney transplant recipients
Bibliographic record
Abstract
Objectives: Cytomegalovirus (CMV) remains a major cause of morbidity following kidney transplantation (KT). We applied flow-cytometric phenotyping and activation-induced marker (AIM) assays to characterize immune reconstitution and CMV-specific T cell signatures after KT and assess whether early AIM responses predict clinically significant CMV infection (CS-CMVi). Methods: Twenty-nine adult KT recipients were followed prospectively for 12 months: 13 donor CMV-positive/recipient CMV-negative (D + /R - ) and 16 CMV-seropositive recipients (R + ). CMV-specific CD4 + and CD8 + T cells were quantified by AIM assay at 2 weeks and at 3, 9, and 12 months. CS-CMVi was defined as CMV infection requiring antiviral therapy. Results: Immune reconstitution featured expansion of CD4 + TEMRA and Th1-like cells with contraction of Th2/Th17 subsets. Seven recipients (24%) developed CS-CMVi, including five D + /R - . Early CD4 + -predominant CMV-specific responses shifted toward CD8 + expansion with viral replication. At 2 weeks, the CMV-specific CD4 + :CD8 + ratio predicted CS-CMVi (AUC 0.83, p=0.012); a cut-off ≥1.37 yielded 86% sensitivity and 71% specificity. After 6 months, CMV serostatus shaped Th-cell activation, with R + recipients showing greater Th1/Treg and reduced Th2/Th17 responsiveness. Conclusion: Early CMV-specific CD4 + /CD8 + imbalances measured by AIM are associated with CS-CMVi. These findings support the prospective evaluation of CMV-AIM assays as a precision immune-monitoring tool in larger prospective studies.
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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 | 0.000 | 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) | 0.001 | 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".