Serum Uric Acid as a Predictor for Development of Diabetic Nephropathy in Type 1 Diabetes: An Inception Cohort Study

OBJECTIVE—Experimental and clinical studies have suggested that uric acid may contribute to the development of hypertension and kidney disease. Whether uric acid has a causal role in the development of diabetic nephropathy is not known. The objec-tive of the present study is to evaluate uric acid as a predictor of persistent micro- and macroalbuminuria. RESEARCH DESIGN AND METHODS—This prospective ob-servational follow-up study consisted of an inception cohort of 277 patients followed from onset of type 1 diabetes. Of these, 270 patients had blood samples taken at baseline. In seven cases, uric acid could not be determined; therefore, 263 patients (156 men) were available for analysis. Uric acid was measured 3 years after onset of diabetes and before any patient developed microalbuminuria. RESULTS—During a median follow-up of 18.1 years (rang

Dark blood ischemic LGE segmentation using a deep learning approach

The extent of ischemic scar detected by Cardiac Magnetic Resonance (CMR) with late gadolinium enhancement (LGE) is linked with long-term prognosis, but scar quantification is time-consuming. Deep Learning (DL) approaches appear promising in CMR segmentation. Purpose: To train and apply a deep learning approach to dark blood (DB) CMR-LGE for ischemic scar segmentation, comparing results to 4-Standard Deviation (4-SD) semi-automated method. Methods: We trained and validated a dual neural network infrastructure on a dataset of DB-LGE short-axis stacks, acquired at 1.5T from 33 patients with ischemic scar. The DL architectures were an evolution of the U-Net Convolutional Neural Network (CNN), using data augmentation to increase generalization. The CNNs worked together to identify and segment 1) the myocardium and 2) areas of LGE. The first CNN simultaneously cropped the region of interest (RoI) according to the bounding box of the heart and calculated the area of myocardium. The cropped RoI was then processed by the second CNN, which identified the overall LGE area. The extent of scar was calculated as the ratio of the two areas. For comparison, endo- and epi-cardial borders were manually contoured and scars segmented by a 4-SD technique with a validated software. Results: The two U-Net networks were implemented with two free and open-source software library for machine learning. We performed 5-fold cross-validation over a dataset of 108 and 385 labelled CMR images of the myocardium and scar, respectively. We obtained high performance (> ∼0.85) as measured by the Intersection over Union metric (IoU) on the training sets, in the case of scar segmentation. With regards to heart recognition, the performance was lower (> ∼0.7), although improved (∼ 0.75) by detecting the cardiac area instead of heart boundaries. On the validation set, performances oscillated between 0.8 and 0.85 for scar tissue recognition, and dropped to ∼0.7 for myocardium segmentation. We believe that underrepresented samples and noise might be affecting the overall performances, so that additional data might be beneficial. Figure1: examples of heart segmentation (upper left panel: training; upper right panel: validation) and of scar segmentation (lower left panel: training; lower right panel: validation). Conclusion: Our CNNs show promising results in automatically segmenting LV and quantify ischemic scars on DB-LGE-CMR images. The performances of our method can further improve by expanding the data set used for the training. If implemented in a clinical routine, this process can speed up the CMR analysis process and aid in the clinical decision-making

Uric Acid Induces Renal Inflammation via Activating Tubular NF-κB Signaling Pathway

Inflammation is a pathologic feature of hyperuricemia in clinical settings. However, the underlying mechanism remains unknown. Here, infiltration of T cells and macrophages were significantly increased in hyperuricemia mice kidneys. This infiltration of inflammatory cells was accompanied by an up-regulation of TNF-α, MCP-1 and RANTES expression. Further, infiltration was largely located in tubular interstitial spaces, suggesting a role for tubular cells in hyperuricemia-induced inflammation. In cultured tubular epithelial cells (NRK-52E), uric acid, probably transported via urate transporter, induced TNF-α, MCP-1 and RANTES mRNA as well as RANTES protein expression. Culture media of NRK-52E cells incubated with uric acid showed a chemo-attractive ability to recruit macrophage. Moreover uric acid activated NF-κB signaling. The uric acid-induced up-regulation of RANTES was blocked by SN 50, a specific NF-κB inhibitor. Activation of NF-κB signaling was also observed in tubule of hyperuricemia mice. These results suggest that uric acid induces renal inflammation via activation of NF-κB signaling

Lack of increases in methylation at three CpG-rich genomic loci in non-mitotic adult tissues during aging

<p>Abstract</p> <p>Background</p> <p>Cell division occurs during normal human development and aging. Despite the likely importance of cell division to human pathology, it has been difficult to infer somatic cell mitotic ages (total numbers of divisions since the zygote) because direct counting of lifetime numbers of divisions is currently impractical. Here we attempt to infer relative mitotic ages with a molecular clock hypothesis. Somatic genomes may record their mitotic ages because greater numbers of replication errors should accumulate after greater numbers of divisions. Mitotic ages will vary between cell types if they divide at different times and rates.</p> <p>Methods</p> <p>Age-related increases in DNA methylation at specific CpG sites (termed "epigenetic molecular clocks") have been previously observed in mitotic human epithelium like the intestines and endometrium. These CpG rich sequences or "tags" start unmethylated and potentially changes in methylation during development and aging represent replication errors. To help distinguish between mitotic versus time-associated changes, DNA methylation tag patterns at 8–20 CpGs within three different genes, two on autosomes and one on the X-chromosome were measured by bisulfite sequencing from heart, brain, kidney and liver of autopsies from 21 individuals of different ages.</p> <p>Results</p> <p>Levels of DNA methylation were significantly greater in adult compared to fetal or newborn tissues for two of the three examined tags. Consistent with the relative absence of cell division in these adult tissues, there were no significant increases in tag methylation after infancy.</p> <p>Conclusion</p> <p>Many somatic methylation changes at certain CpG rich regions or tags appear to represent replication errors because this methylation increases with chronological age in mitotic epithelium but not in non-mitotic organs. Tag methylation accumulates differently in different tissues, consistent with their expected genealogies and mitotic ages. Although further studies are necessary, these results suggest numbers of divisions and ancestry are at least partially recorded by epigenetic replication errors within somatic cell genomes.</p

Parathyroidectomy and survival in a cohort of Italian dialysis patients: results of a multicenter, observational, prospective study

Background: Severe secondary hyperparathyroidism (SHPT)&nbsp;is associated with mortality in end stage kidney disease (ESKD). Parathyroidectomy (PTX) becomes necessary when medical therapy fails, thus highlighting the interest to compare biochemical and clinical outcomes of patients receiving either medical treatment or surgery. Methods: We aimed to compare overall survival and biochemical control of hemodialysis patients with severe hyperparathyroidism, treated by surgery or medical&nbsp;therapy&nbsp;followed-up for 36&nbsp;months.&nbsp;Inclusion criteria were age older than 18&nbsp;years, renal failure requiring dialysis treatment (hemodialysis or peritoneal dialysis) and ability to sign the consent form. A control group of&nbsp;418 patients treated in the same centers,&nbsp;who did not undergo parathyroidectomy was selected after matching&nbsp;for&nbsp;age, sex, and dialysis vintage. Results: From 82 Dialysis units in Italy, we prospectively collected data of 257 prevalent patients&nbsp;who underwent parathyroidectomy (age&nbsp;58.2 ± 12.8 years; M/F: 44%/56%, dialysis&nbsp;vintage: 15.5 ± 8.4 years) and of 418 control patients who did not undergo parathyroidectomy (age&nbsp;60.3 ± 14.4 years; M/F 44%/56%; dialysis vintage 11.2 ± 7.6 y). The survival rate was higher in the group&nbsp;that underwent&nbsp;parathyroidectomy (Kaplan–Meier log rank test = 0.002). Univariable analysis (HR 0.556, CI: 0.387–0.800, p = 0.002) and multivariable analysis (HR 0.671, CI:0.465–0.970, p = 0.034), identified parathyroidectomy as a&nbsp;protective factor of overall survival. The prevalence of patients at KDOQI targets for PTH was lower in patients&nbsp;who underwent parathyroidectomy&nbsp;compared to controls (PTX vs non-PTX: PTH &lt; 150&nbsp;pg/ml: 59% vs 21%, p = 0.001; PTH at target: 18% vs 37% p = 0.001; PTH &gt; 300&nbsp;pg/ml 23% vs 42% p = 0.001). The control group received more intensive medical treatment&nbsp;with higher prevalence of vitamin D (65% vs 41%, p = 0.0001), calcimimetics (34% vs 14%, p = 0.0001) and phosphate binders (77% vs 66%,&nbsp;p = 0.002). Conclusions: Our data suggest that parathyroidectomy is associated with survival rate&nbsp;at 36 months, independently of biochemical control. Lower exposure to high PTH levels could represent an advantage in the long term. Graphical abstract: [Figure not available: see fulltext.]