MPA Cpredose and MPA AUC are significantly related to the incidence of biopsy-proven rejection after kidney transplantation, whereas MMF dose is significantly related to the occurrence of adverse events.
BackgroundThe development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized kidney tissue sections stained with periodic acid–Schiff (PAS).MethodsWe trained the network using multiclass annotations from 40 whole-slide images of stained kidney transplant biopsies and applied it to four independent data sets. We assessed multiclass segmentation performance by calculating Dice coefficients for ten tissue classes on ten transplant biopsies from the Radboud University Medical Center in Nijmegen, The Netherlands, and on ten transplant biopsies from an external center for validation. We also fully segmented 15 nephrectomy samples and calculated the network’s glomerular detection rates and compared network-based measures with visually scored histologic components (Banff classification) in 82 kidney transplant biopsies.ResultsThe weighted mean Dice coefficients of all classes were 0.80 and 0.84 in ten kidney transplant biopsies from the Radboud center and the external center, respectively. The best segmented class was “glomeruli” in both data sets (Dice coefficients, 0.95 and 0.94, respectively), followed by “tubuli combined” and “interstitium.” The network detected 92.7% of all glomeruli in nephrectomy samples, with 10.4% false positives. In whole transplant biopsies, the mean intraclass correlation coefficient for glomerular counting performed by pathologists versus the network was 0.94. We found significant correlations between visually scored histologic components and network-based measures.ConclusionsThis study presents the first convolutional neural network for multiclass segmentation of PAS-stained nephrectomy samples and transplant biopsies. Our network may have utility for quantitative studies involving kidney histopathology across centers and provide opportunities for deep learning applications in routine diagnostics.
Diabetes, hypertension and cardiovascular disease have been listed as risk factors for severe coronavirus disease 2019 (COVID-19) since the first report of the disease in January 2020. However, this report did not mention chronic kidney disease (CKD) nor did it provide information on the relevance of estimated glomerular filtration rate (eGFR) or albuminuria. As the disease spread across the globe, information on larger populations with greater granularity on risk factors emerged. The recently published OpenSAFELY project analysed factors associated with COVID-19 death in 17 million patients. The picture that arose differs significantly from initial reports. For example, hypertension is not an independent risk factor for COVID-19 death [adjusted hazard ratio (aHR) 0.89], but renal disease very much is. Dialysis (aHR 3.69), organ transplantation (aHR 3.53) and CKD (aHR 2.52 for patients with eGFR <30 mL/min/1.73 m2) represent three of the four comorbidities associated with the highest mortality risk from COVID-19. The risk associated with CKD Stages 4 and 5 is higher than the risk associated with diabetes mellitus (aHR range 1.31–1.95, depending upon glycaemic control) or chronic heart disease (aHR 1.17). In another recent publication, the Global Burden of Disease collaboration identified that worldwide, CKD is the most prevalent risk factor for severe COVID-19. Moreover, the distribution of risk factors for COVID-19 mortality appears to be different in patients with CKD when compared with the general population. The high prevalence of CKD in combination with the elevated risk of mortality from COVID-19 in CKD necessitates urgent action for this group of patients. This article defines essential action points (summarized in Box 1), among which is advocating the inclusion of CKD patients in clinical trials testing the efficacy of drugs and vaccines to prevent severe COVID-19.
Background. In kidney patients COVID-19 is associated with severely increased morbidity and mortality. A comprehensive comparison of the immunogenicity, tolerability, and safety of COVID-19 vaccination in different cohorts of kidney patients and a control cohort is lacking. Methods. This investigator driven, prospective, controlled multicenter study included 162 participants with chronic kidney disease (CKD) stages G4/5 (eGFR < 30 mL/min/1.73m2), 159 participants on dialysis, 288 kidney transplant recipients, and 191 controls. Participants received 2 doses of the mRNA-1273 COVID-19 vaccine (Moderna). The primary endpoint was seroconversion. Results. Transplant recipients had a significantly lower seroconversion rate when compared with controls (56.9% versus 100%, P < 0.001), with especially mycophenolic acid, but also, higher age, lower lymphocyte concentration, lower eGFR, and shorter time after transplantation being associated with nonresponder state. Transplant recipients also showed significantly lower titers of neutralizing antibodies and T-cell responses when compared with controls. Although a high seroconversion rate was observed for participants with CKD G4/5 (100%) and on dialysis (99.4%), mean antibody concentrations in the CKD G4/5 cohort and dialysis cohort were lower than in controls (2405 [interquartile interval 1287-4524] and 1650 versus 3186 [1896-4911] BAU/ mL, P = 0.06 and P < 0.001, respectively). Dialysis patients and especially kidney transplant recipients experienced less systemic vaccination related adverse events. No specific safety issues were noted. Conclusions. The immune response following vaccination in patients with CKD G4/5 and on dialysis is almost comparable to controls. In contrast, kidney transplant recipients have a poor response. In this latter, patient group development of alternative vaccination strategies are warranted.
Objective— An excessive release and impaired degradation of neutrophil extracellular traps (NETs) leads to the continuous exposure of NETs to the endothelium in a variety of hematologic and autoimmune disorders, including lupus nephritis. This study aims to unravel the mechanisms through which NETs jeopardize vascular integrity. Approach and Results— Microvascular and macrovascular endothelial cells were exposed to NETs, and subsequent effects on endothelial integrity and function were determined in vitro and in vivo. We found that endothelial cells have a limited capacity to internalize NETs via the receptor for advanced glycation endproducts. An overflow of the phagocytic capacity of endothelial cells for NETs resulted in the persistent extracellular presence of NETs, which rapidly altered endothelial cell–cell contacts and induced vascular leakage and transendothelial albumin passage through elastase-mediated proteolysis of the intercellular junction protein VE-cadherin. Furthermore, NET-associated elastase promoted the nuclear translocation of junctional β-catenin and induced endothelial-to-mesenchymal transition in cultured endothelial cells. In vivo, NETs could be identified in kidney samples of diseased MRL/lpr mice and patients with lupus nephritis, in whom the glomerular presence of NETs correlated with the severity of proteinuria and with glomerular endothelial-to-mesenchymal transition. Conclusions— These results indicate that an excess of NETs exceeds the phagocytic capacity of endothelial cells for NETs and promotes vascular leakage and endothelial-to-mesenchymal transition through the degradation of VE-cadherin and the subsequent activation of β-catenin signaling. Our data designate NET-associated elastase as a potential therapeutic target in the prevention of endothelial alterations in diseases characterized by aberrant NET release.
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