BackgroundDiabetes mellitus (DM), either preexisting or developing after transplantation, remains a crucial clinical problem in kidney transplantation. To obtain insights into the molecular mechanisms underlying PTDM development and early glomerular damage before the development of histologically visible diabetic kidney disease, we comparatively analysed the proteome of histologically normal glomeruli from patients with PTDM and normoglycaemic (NG) transplant recipients. Moreover, to assess specificities inherent in PTDM, we also comparatively evaluated glomerular proteomes from transplant recipients with preexisting type 2 DM (T2DM).MethodsProtocol biopsies were obtained from adult NG, PTDM and T2DM patients one year after kidney transplantation. Biopsies were formalin-fixed and embedded in paraffin, and glomerular cross-sections were microdissected. A total of 4 NG, 7 PTDM and 6 T2DM kidney biopsies were used for the analysis. The proteome was determined by liquid chromatography-tandem mass spectrometry. Relative differences in protein abundance and significantly dysregulated pathways were analysed.ResultsProteins involved in cell adhesion, immune response, leukocyte transendothelial filtration, and cell localization and organization were less abundant in glomeruli from PTDM patients than in those from NG patients, and proteins associated with supramolecular fibre organization and protein-containing complex binding were more abundant in PTDM patients. Overall, proteins related to adherens and tight junctions and those related to the immune system, including leukocyte transendothelial migration, were more abundant in NG patients than in transplanted patients with DM, irrespective of the timing of its development. However, proteins included in cell‒cell junctions and adhesion, insulin resistance, and vesicle-mediated transport were all less abundant in PTDM patients than in T2DM patients.ConclusionsThe glomerular proteome profile differentiates PTDM from NG and T2DM, suggesting specific pathogenetic mechanisms. Further studies are warranted to validate these results, potentially leading to an improved understanding of PTDM kidney transplant pathophysiology and to the identification of novel biomarkers.

BackgroundPulse wave analysis may be useful to assess fistula function. We aimed to prospectively evaluate if convenient oscillometric devices are applicable to detect flow below 500 ml/min in a real life clinical setting.MethodsPulse waves were recorded ambilaterally with the vicorder® device at the brachial artery in 53 patients on haemodialysis with native fistula. Primary variables consisted of the mean slope between the systolic maximum and the diacrotic notch (Slope2), the sum of the mean slopes in the four characteristic sections of pulse waves (Slope∑) and the amplitude of relative volumetric change in the measuring cuff at the upper arm (AMP). Fistula flow was measured with the use of duplex sonography using a standardized approach.ResultsParameter values above or below the median indicated measurement at the non-fistula side, with sensitivities/specificities of 0.79/0.79 (p < 0.001) for Slope 2, 0.64/0.64 (p = 0.003) for Slope∑ and 0.81/0.81 (p < 0.001) for AMP if measurements at the fistula and non-fistula arm were considered. ROC-analyses of parameter values measured at the fistula to detect low flow demonstrated AUCs (with CI) of 0.652 (0.437–0.866, p = 0.167) for Slope2, 0.732 (0.566–0.899, p = 0.006) for Slope∑ and 0.775 (0.56–0.991, p = 0.012) for AMP. The point with maximal youden’s index was regarded as optimal cut-off, which corresponded to sensitivities and specificities of 0.8/0.56 for slope2, 0.86/ 0.56 for Slope∑ and 0.93/0.78 for AMP.ConclusionFunctional surveillance with oscillometry is a promising clinical application to detect a low fistula flow. Among all investigated pulse wave parameters AMP revealed the highest diagnostic accuracy.Graphical Abstract

BackgroundThe widening supply–demand imbalance for kidneys necessitates finding ways to reduce rejection and improve transplant outcomes. Human leukocyte antigen (HLA) epitope compatibility between donor and recipient may minimize premature graft loss and prolong survival, but incorporating this strategy to deceased donor allocation criteria prioritizes transplant outcomes over wait times. An online public deliberation was held to identify acceptable trade-offs when implementing epitope compatibility to guide Canadian policymakers and health professionals in deciding how best to allocate kidneys fairly.MethodsInvitations were mailed to 35,000 randomly-selected Canadian households, with over-sampling of rural/remote locations. Participants were selected for socio-demographic diversity and geographic representation. Five two-hour online sessions were held from November–December 2021. Participants received an information booklet and heard from expert speakers prior to deliberating on how to fairly implement epitope compatibility for transplant candidates and governance issues. Participants collectively generated and voted on recommendations. In the final session, kidney donation and allocation policymakers engaged with participants. Sessions were recorded and transcribed.ResultsThirty-two individuals participated and generated nine recommendations. There was consensus on adding epitope compatibility to the existing deceased donor kidney allocation criteria. However, participants recommended including safeguards/flexibility around this (e.g., mitigating declining health). They called for a transition period to epitope compatibility, including an ongoing comprehensive public education program. Participants unanimously recommended regular monitoring and public sharing of epitope-based transplant outcomes.ConclusionsParticipants supported adding epitope compatibility to kidney allocation criteria, but advised safeguards and flexibility around implementation. These recommendations provide guidance to policymakers about incorporating epitope-based deceased donor allocation criteria.

BackgroundElectron microscopy is important in the diagnosis of renal disease. For immune-mediated renal disease diagnosis, whether the electron-dense granule is present in the electron microscope image is of vital importance. Deep learning methods perform well at feature extraction and assessment of histologic images. However, few studies on deep learning methods for electron microscopy images of renal biopsy have been published. This study aimed to develop a deep learning-based multi-model to automatically detect whether the electron-dense granule is present in the TEM image of renal biopsy, and then help diagnose immune-mediated renal disease.MethodsThree deep learning models are trained to classify whether the electron-dense granule is present using 910 electron microscopy images of renal biopsies. We proposed two novel methods to improve the model accuracy. One model uses the pre-trained ResNet convolutional layers for feature extraction with transfer learning which was firstly improved with skip architecture, then uses Support Vector Machine as the classifier. We developed a multi-model to combine the traditional ResNet model with the improved one to further improve the accuracy.ResultsDeep learning-based multi-model has the highest model accuracy, and the average accuracy is about 88%. The improved ReseNet + SVM model performance is much better than the traditional ResNet model. The average accuracy of the improved ResNet + SVM model is 83%, while the traditional ResNet model accuracy is only 58%.ConclusionsThis study presents the first models for electron microscopy image classification of Renal Biopsy. Identifying whether the electron-dense granule is present plays an important role in the diagnosis of immune complex nephropathy. This study made it possible for Artificial Intelligence models assist to analyze complex electron microscopy images for disease diagnosis.

BackgroundSerum cystatin C (ScysC) may help predicting cardiovascular outcome not only through its ability to detect renal dysfunction but also through its potential connection to others factors that are directly related to cardiovascular diseases. We explored the potential association of ScysC with arterial stiffness - a major contributor to cardiovascular disease - in renal transplant recipients (RTR).MethodsTraditional and non-traditional cardio-vascular risk factors were collected from 215 stable RTR whom arterial stiffness was evaluated by the measure of the augmentation index of central pressure (AIx) determined by the arteriograph device. Serum creatinine and ScysC were measured the same day using standardized methods. Association between ScysC and AIx was examined in univariate and multivariate linear regression analysis.ResultsIn univariate analysis, ScysC was strongly associated with AIx. This relationship was not confounded by age, gender, length of time spent on dialysis and transplantation vintage. Adjustment on the level of GFR estimated by the MDRD Study equation attenuated but did not abolish the association between ScysC and AIx.ConclusionsIn conclusion, ScysC is an independent predictor of AIx in RTR. Our data suggest that arterial stiffness may partially mediate the association between ScysC and cardiovascular risk in renal transplantation.