Expression of B Cell and Immunoglobulin Transcripts Is a Feature of Inflammation in Late Allografts
Bibliographic record
Abstract
To assess the significance of B-cell and plasma cell infiltrates in renal allografts, we compared expression of B-cell-associated transcripts (BATs) and immunoglobulin transcripts (IGTs) to histopathology and function in 177 renal allograft biopsies for clinical indications. BAT and IGT expression correlated with immunostaining for B cells and plasma cells and with expression of B-cell and plasma cell transcription factors. BATs and IGTs were increased in both T-cell-mediated and antibody-mediated rejection. BAT and IGT scores were strongly related to time posttransplant: biopsies <5 months expressed less BATs and did not express increased IGTs. In contrast, T-cell-associated transcripts were independent of time posttransplant. In biopsies > or =5 months, BAT and IGT scores correlated with interstitial inflammation, tubular atrophy and interstitial fibrosis. By regression tree analysis, the only variables independently correlated with BATs and IGTs were time and inflammation. Expression of BATs and IGTs correlated with renal function, but this relationship was due to differences in early versus late biopsies: BATs and IGTs were not related to function or future function after correcting for time.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".