Peritubular Capillary Vessels and Hypoxia/Angiogenesis Genes in Kidney Biopsies With Transplant Glomerulopathy.
Bibliographic record
Abstract
BACKGROUND: Transplant glomerulopathy (TG) is an important cause of late renal allograft loss. TG has been linked to the presence of alloantibodies, chronic rejection, and persistent inflammation, however the mechanisms responsible for TG are incompletely understood. Peritubular capillary (PTC) loss and hypoxia contribute to pathogenesis of chronic rejection in experimental lung transplantation. In these models HIF1A gene upregulation in response to hypoxia contributes to microvascular repair. A role for PTC loss and hypoxia-related gene expression has not been examined in TG. While persistent inflammation is implicated in TG-mediated graft injury it is not known whether this reflects downstream effects of PTC loss. To study the role of PTC loss in the pathogenesis of TG we quantified PTC density, and evaluated expression of hypoxia-associated and inflammatory pathways in kidney biopsies of patients with TG compared to acute antibody-mediated rejection (AMR) and interstitial fibrosis/tubular atrophy not otherwise specified (IFTA NOS). METHODS: We utilized custom Taqman Low Density Arrays (TLDA) designed to measure expression of 48 genes in pathways of interest in archived kidney biopsies for cause. Formalin-fixed paraffin embedded sections were stained with antibody to CD31, an endothelial cell marker for detection of microvessel density. PTC leukocytes were immunophenotyped in TG cases. RESULTS: Among 19 cases of TG, 16 of IFTA NOS, and 10 of AMR, we found significant differences in the expression of VCAM1, CCL5, CCL2 and IFNg in TG compared to AMR and IFTA NOS. CD68 (monocyte marker) was most elevated in AMR, and the lowest in IFTA NOS. Hypoxia/angiogenesis genes (HIF1A, VEGFA and EDN1) were increased in AMR with no significant difference between TG and IFTA NOS. Peritubular capillary density was comparable in TG and other groups. The majority of PTC leukocytes in TG were macrophages and T cells. CONCLUSIONS: Inflammation is a prominent finding in TG biopsies, and macrophages and T cells appear to be important mediators. We found no evidence of prominent PTC drop out or hypoxia responses in TG. Neither PTC drop out nor hypoxia appear important in established TG.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".