Bibliographic record
Abstract
Despite dramatic improvements in immunosuppression, late graft loss after kidney transplantation remains a common and difficult problem. Histologic evaluation may reveal changes related to BK polyomavirus infection, hypertension, or calcineurin inhibitor toxicity, which can help to guide therapy. The designation chronic allograft nephropathy should thus be reserved for biopsies with tubular atrophy and interstitial fibrosis without an apparent cause. Although the cause clearly includes both antigen-dependent and antigen-independent events, the approach remains largely to exclude immune mechanisms. Although this review discusses the potential contribution of antibody to chronic injury, it focuses on the basic elements of kidney injury, the role of parenchymal cells in promoting injury, and the proliferative and inflammatory responses that accompanying injury. Strategies to manage these recipients include close attention to accompanying hypertension, diabetes, and hyperlipidemia, as well as consideration for altering immunosuppression; however, therapies that limit epithelial-to-mesenchymal transition or directly block fibrosis pathways may reduce chronic allograft fibrosis and may prove to be useful. Understanding the basic pathogenesis sufficiently to allow early intervention may finally benefit patients who are at high risk for tubular atrophy and interstitial fibrosis and promote their long-term graft function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".