A 2-fold Approach to Polyoma Virus (BK) Nephropathy in Kidney Transplants: Distinguishing Direct Virus Effects From Cognate T Cell–mediated Inflammation
Bibliographic record
Abstract
BACKGROUND: BK nephropathy (BKN) in kidney transplants diagnosed by histology is challenging because it involves damage from both virus activity and cognate T cell-mediated inflammation, directed against alloantigens (rejection) or viral antigens. The present study of indication biopsies from the Integrated Diagnostic System in the International Collaborative Microarray Study Extension study measured major capsid viral protein 2 (VP2) mRNA to assess virus activity and a T cell-mediated rejection (TCMR) classifier to assess cognate T cell-mediated inflammation. METHODS: Biopsies were assessed by local standard-of-care histology and by genome-wide microarrays and Molecular Microscope Diagnostic System (MMDx) algorithms to detect rejection and injury. In a subset of 102 biopsies (50 BKN and 52 BKN-negative biopsies with various abnormalities), we measured VP2 transcripts by real-time polymerase chain reaction. RESULTS: BKN was diagnosed in 55 of 1679 biopsies; 30 had cognate T cell-mediated activity assessed by by MMDx and TCMR lesions, but only 3 of 30 were histologically diagnosed as TCMR. We developed a BKN probability classifier that predicted histologic BKN (area under the curve = 0.82). Virus activity (VP2 expression) was highly selective for BKN (area under the curve = 0.94) and correlated with acute injury, atrophy-fibrosis, macrophage activation, and the BKN classifier, but not with the TCMR classifier. BKN with molecular TCMR had more tubulitis and inflammation than BKN without molecular TCMR. In 5 BKN cases with second biopsies, VP2 mRNA decreased in second biopsies, whereas in 4 of 5 TCMR classifiers, scores increased. Genes and pathways associated with BKN and VP2 mRNA were similar, reflecting injury, inflammation, and macrophage activation but none was selective for BKN. CONCLUSIONS: Risk-benefit decisions in BKN may be assisted by quantitative assessment of the 2 major pathologic processes, virus activity and cognate T cell-mediated inflammation.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".