PERITUBULAR CAPILLARY BASEMENT MEMBRANE REDUPLICATION IN ALLOGRAFTS AND NATIVE KIDNEY DISEASE
Bibliographic record
Abstract
BACKGROUND: An association has been found between transplant glomerulopathy (TG) and reduplication of peritubular capillary basement membranes (PTCR). Although such an association is of practical and theoretical importance, only one prospective study has tried to confirm it. METHODS: We examined 278 consecutive renal specimens (from 135 transplants and 143 native kidneys) for ultrastructural evidence of PTCR. In addition to renal allografts with TG, we also examined grafts with acute rejection, recurrent glomerulonephritis, chronic allograft nephropathy and stable grafts ("protocol biopsies"). Native kidney specimens included a wide range of glomerulopathies as well as cases of thrombotic microangiopathy, malignant hypertension, acute interstitial nephritis, and acute tubular necrosis. RESULTS: We found PTCR in 14 of 15 cases of TG, in 7 transplant biopsy specimens without TG, and in 13 of 143 native kidney biopsy specimens. These 13 included cases of malignant hypertension, thrombotic microangiopathy, lupus nephritis, Henoch-Schonlein nephritis, crescentic glomerulonephritis, and cocaine-related acute renal failure. Mild PTCR in allografts without TG did not predict renal failure or significant proteinuria after follow-up periods of between 3 months and 1 year. CONCLUSIONS: We conclude that in transplants, there is a strong association between well-developed PTCR and TG, while the significance of mild PTCR and its predictive value in the absence of TG is unclear. PTCR also occurs in certain native kidney diseases, though the association is not as strong as that for TG. We suggest that repeated endothelial injury, including immunologic injury, may be the cause of this lesion both in allografts and native kidneys.
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 | 0.002 |
| 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 | 0.001 |
| 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".