Introduction: Type I interferons are pivotal in the activation of autoimmune response in systemic lupus erythematous. However, the pathogenic role of interferon-alpha in patients affected by lupus nephritis remains uncertain. The aim of our study was to investigate the presence of a specific interferon signature in lupus nephritis and the effects of interferon-alpha at renal level. Methods: We performed immunohistochemical analysis for MXA-protein and in situ hybridization to detect interferon-alpha signature and production in human lupus nephritis. Through microarray studies, we analyzed the gene expression profile of renal tubular epithelial cells, stimulated with interferon-alpha. We validated microarray results through real-time polymerase chain reaction, flow cytometry on renal tubular epithelial cells, and through immunohistochemical analysis and confocal microscopy on renal biopsies. Results: Type I interferons signature was characterized by MXA-specific staining in renal tubular epithelial cells; in addition, in situ hybridization showed that renal tubular epithelial cells were the major producers of interferon-alpha, indicating a potential autocrine effect. Whole-genome expression profile showed interferon-alpha induced up-regulation of genes involved in innate immunity, protein ubiquitination and switching to immunoproteasome. In accordance with the in vitro data, class IV lupus nephritis showed up-regulation of the immunoproteasome subunit LMP7 in tubular epithelial cells associated with type I interferon signature. Conclusions: Our data indicate that type I interferons might have a pathogenic role in lupus nephritis characterized by an autocrine effect of interferon-alpha on renal tubular epithelial cells. Therefore we hypothesize that inhibition of type I interferons might represent a therapeutic target to prevent tubulo-interstitial damage in patients with lupus nephritis.

The evaluation of kidney biopsies performed by expert pathologists is a crucial process for assessing if a kidney is eligible for transplantation. In this evaluation process, an important step consists of the quantification of global glomerulosclerosis, which is the ratio between sclerotic glomeruli and the overall number of glomeruli. Since there is a shortage of organs available for transplantation, a quick and accurate assessment of global glomerulosclerosis is essential for retaining the largest number of eligible kidneys. In the present paper, the authors introduce a Computer-Aided Diagnosis (CAD) system to assess global glomerulosclerosis. The proposed tool is based on Convolutional Neural Networks (CNNs). In particular, the authors considered approaches based on Semantic Segmentation networks, such as SegNet and DeepLab v3+. The dataset has been provided by the Department of Emergency and Organ Transplantations (DETO) of Bari University Hospital, and it is composed of 26 kidney biopsies coming from 19 donors. The dataset contains 2344 non-sclerotic glomeruli and 428 sclerotic glomeruli. The proposed model consents to achieve promising results in the task of automatically detecting and classifying glomeruli, thus easing the burden of pathologists. We get high performance both at pixel-level, achieving mean F-score higher than 0.81, and Weighted Intersection over Union (IoU) higher than 0.97 for both SegNet and Deeplab v3+ approaches, and at object detection level, achieving 0.924 as best F-score for non-sclerotic glomeruli and 0.730 as best F-score for sclerotic glomeruli.

Background. The mechanisms underlying the development of proteinuria in renal-transplant recipients converted from calcineurin inhibitors to sirolimus are still unknown. Methods. This is a single-center cohort study. One hundred ten kidney transplant recipients converted from calcineurin inhibitors to sirolimus in the period from September 2000 to December 2005 were included in the study. All patients underwent a graft biopsy before conversion (T0) and a second protocol biopsy 2 years thereafter (T2), according to our standard clinical protocol. On the basis of the changes observed in proteinuria between T0 and T2 (median 70%), the patients were divided into two groups: group I (70%). The authors blinded the sirolimus blood trough levels. We investigated in vivo the effects of sirolimus on nephrin, podocin, CD2ap, and actin protein expression. Slit diaphragm (SD)-associated protein expressions were evaluated in T0 and T2 biopsies. The same analysis was performed in cultured human podocytes treated with different doses of sirolimus (5, 10, 20, and 50 ng/mL). Results. The SD protein expression in group II T2 biopsies was significantly reduced compared with the T0 biopsies and with T2 group I biopsies. In addition, sirolimus blood trough levels directly and significantly correlated with the SD protein expression at T2 graft biopsies. Group II patients presented significantly higher sirolimus blood levels than group I. In vitro study confirmed that sirolimus effect on podocytes was dose dependent. Conclusions. Our data suggest that sirolimus-induced proteinuria may be a dose-dependent effect of the drug on key podocyte structures.

In April 2012, a group of nephrologists organized a consensus conference in Cambridge (UK) on type II membranoproliferative glomerulonephritis and decided to use a new terminology, “C3 glomerulopathy” (C3 GP). Further knowledge on the complement system and on kidney biopsy contributed toward distinguishing this disease into three subgroups: dense deposit disease (DDD), C3 glomerulonephritis (C3 GN), and the CFHR5 nephropathy. The persistent presence of microhematuria with or without light or heavy proteinuria after an infection episode suggests the potential onset of C3 GP. These nephritides are characterized by abnormal activation of the complement alternative pathway, abnormal deposition of C3 in the glomeruli, and progression of renal damage to end-stage kidney disease. The diagnosis is based on studying the complement system, relative genetics, and kidney biopsies. The treatment gap derives from the absence of a robust understanding of their natural outcome. Therefore, a specific treatment for the different types of C3 GP has not been established. Recommendations have been obtained from case series and observational studies because no randomized clinical trials have been conducted. Current treatment is based on corticosteroids and antiproliferative drugs (cyclophosphamide, mycophenolate mofetil), monoclonal antibodies (rituximab) or complement inhibitors (eculizumab). In some cases, it is suggested to include sessions of plasma exchange.

The histological assessment of glomeruli is fundamental for determining if a kidney is suitable for transplantation. The Karpinski score is essential to evaluate the need for a single or dual kidney transplant and includes the ratio between the number of sclerotic glomeruli and the overall number of glomeruli in a kidney section. The manual evaluation of kidney biopsies performed by pathologists is time-consuming and error-prone, so an automatic framework to delineate all the glomeruli present in a kidney section can be very useful. Our experiments have been conducted on a dataset provided by the Department of Emergency and Organ Transplantations (DETO) of Bari University Hospital. This dataset is composed of 26 kidney biopsies coming from 19 donors. The rise of Convolutional Neural Networks (CNNs) has led to a realm of methods which are widely applied in Medical Imaging. Deep learning techniques are also very promising for the segmentation of glomeruli, with a variety of existing approaches. Many methods only focus on semantic segmentation—which consists in segmentation of individual pixels—or ignore the problem of discriminating between non-sclerotic and sclerotic glomeruli, so these approaches are not optimal or inadequate for transplantation assessment. In this work, we employed an end-to-end fully automatic approach based on Mask R-CNN for instance segmentation and classification of glomeruli. We also compared the results obtained with a baseline based on Faster R-CNN, which only allows detection at bounding boxes level. With respect to the existing literature, we improved the Mask R-CNN approach in sliding window contexts, by employing a variant of the Non-Maximum Suppression (NMS) algorithm, which we called Non-Maximum-Area Suppression (NMAS). The obtained results are very promising, leading to improvements over existing literature. The baseline Faster R-CNN-based approach obtained an F-Measure of 0.904 and 0.667 for non-sclerotic and sclerotic glomeruli, respectively. The Mask R-CNN approach has a significant improvement over the baseline, obtaining an F-Measure of 0.925 and 0.777 for non-sclerotic and sclerotic glomeruli, respectively. The proposed method is very promising for the instance segmentation and classification of glomeruli, and allows to make a robust evaluation of global glomerulosclerosis. We also compared Karpinski score obtained with our algorithm to that obtained with pathologists’ annotations to show the soundness of the proposed workflow from a clinical point of view.

Glomerulonephritis (GN) continues to be one of the main causes of end-stage kidney disease (ESKD) with an incidence rating from 10.5% to 38.2%. Therefore, recurrent GN, previously considered to be a minor contributor to graft loss, is the third most common cause of graft failure 10 years after renal transplantation. However, the incidence, pathogenesis, and natural course of recurrences are still not completely understood. This review focuses on the most frequent diseases that recur after renal transplantation, analyzing rate of recurrence, epidemiology and risk factors, pathogenesis and bimolecular mechanisms, clinical presentation, diagnosis, and therapy, taking into consideration the limited data available in the literature. First of all, the risk for recurrence depends on the type of glomerulonephritis. For example, recipient patients with anti-glomerular basement membrane (GBM) disease present recurrence rarely, but often exhibit rapid graft loss. On the other hand, recipient patients with C3 glomerulonephritis present recurrence in more than 50% of cases, although the disease is generally slowly progressive. It should not be forgotten that every condition that can lead to chronic graft dysfunction should be considered in the differential diagnosis of recurrence. Therefore, a complete workup of renal biopsy, including light, immunofluorescence and electron microscopy study, is essential to provide the diagnosis, excluding alternative diagnosis that may require different treatment. We will examine in detail the biomolecular mechanisms of both native and transplanted kidney diseases, monitoring the risk of recurrence and optimizing the available treatment options.