Gene expression using microarrays in transplant recipients at risk of EBV lymphoproliferation after organ transplantation: Preliminary proof‐of‐concept
Bibliographic record
Abstract
We hypothesized that aspects of the virus-host interaction could be measured to help predict progression to EBV-PTLD. We examined the spectrum of host genes differentially expressed and any relevant clustering in children at risk of EBV lymphoproliferation after organ transplantation. We compared the genes expressed among patients with different levels of viral loads. Gene expression was measured by microarray analysis of RNA from CD19+ B lymphocytes using the Human Genome U133 Plus 2.0 GeneChip. Among 27 samples from 26 transplant recipients, the viral load categories were: low or undetectable loads (LU), n = 14; high or intermediate loads (HI), n = 13. There were seven healthy EBV-seropositive (P) and -seronegative controls (N). Median time of post-transplantation was 0.5 yr (range 0.1-3.8). We identified 24-54 differentially expressed genes in each of four comparisons of HI vs. P, LU vs. P, HI vs. LU, and P vs. N. We identified patterns of 563 gene expressions, creating five clusters aligned with levels of viral load. PTLD occurred in four of five clusters. In summary, we demonstrated varying degrees of alignment between levels of VL and gene clusters. Analyses for differential expression of genes showed genes that could be implicated in the pathogenesis of EBV-PTLD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".