Nonalcoholic fatty liver disease is a rapidly rising problem in the 21st century and is a leading cause of chronic liver disease that can lead to end-stage liver diseases, including cirrhosis and hepatocellular cancer. Despite this rising epidemic, no pharmacological treatment has yet been established to treat this disease. The rapidly increasing prevalence of nonalcoholic fatty liver disease and its aggressive form, nonalcoholic steatohepatitis (NASH), requires novel therapeutic approaches to prevent disease progression. Alterations in microbiome dynamics and dysbiosis play an important role in liver disease and may represent targetable pathways to treat liver disorders. Improving microbiome properties or restoring normal bile acid metabolism may prevent or slow the progression of liver diseases such as NASH. Importantly, aberrant systemic circulation of bile acids can greatly disrupt metabolic homeostasis. Bile acid sequestrants are orally administered polymers that bind bile acids in the intestine, forming nonabsorbable complexes. Bile acid sequestrants interrupt intestinal reabsorption of bile acids, decreasing their circulating levels. We determined that treatment with the bile acid sequestrant sevelamer reversed the liver injury and prevented the progression of NASH, including steatosis, inflammation, and fibrosis in a Western diet–induced NASH mouse model. Metabolomics and microbiome analysis revealed that this beneficial effect is associated with changes in the microbiota population and bile acid composition, including reversing microbiota complexity in cecum by increasing Lactobacillus and decreased Desulfovibrio. The net effect of these changes was improvement in liver function and markers of liver injury and the positive effects of reversal of insulin resistance.

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Image-based machine learning tools hold great promise for clinical applications in nephropathology and kidney research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often face prohibitive challenges in using these tools to their full potential, including the lack of technical expertise, suboptimal user interface, and limited computation power. We have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis. By segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in murine models of aging, diabetic nephropathy, and HIV associated nephropathy. The ability to access this tool over the internet will facilitate widespread use by computational non-experts. Histo-Cloud is open source and adaptable for segmentation of any histological structure regardless of stain. Histo-Cloud will greatly accelerate and facilitate the generation of datasets for machine learning in the analysis of kidney histology, empowering computationally novice end-users to conduct deep feature analysis of tissue slides.

We sought to delineate the retinal features associated with the high-fat diet (HFD) mouse, a widely used model of obesity. C57BL/6 mice were fed either a high-fat (60% fat; HFD) or low-fat (10% fat; LFD) diet for up to 12 months. The effect of HFD on body weight and insulin resistance were measured. The retina was assessed by electroretinogram (ERG), fundus photography, permeability studies, and trypsin digests for enumeration of acellular capillaries. The HFD cohort experienced hypercholesterolemia when compared to the LFD cohort, but not hyperglycemia. HFD mice developed a higher body weight (60.33 g vs. 30.17g, p < 0.0001) as well as a reduced insulin sensitivity index (9.418 vs. 62.01, p = 0.0002) compared to LFD controls. At 6 months, retinal functional testing demonstrated a reduction in a-wave and b-wave amplitudes. At 12 months, mice on HFD showed evidence of increased retinal nerve infarcts and vascular leakage, reduced vascular density, but no increase in number of acellular capillaries compared to LFD mice. In conclusion, the HFD mouse is a useful model for examining the effect of prediabetes and hypercholesterolemia on the retina. The HFD-induced changes appear to occur slower than those observed in type 2 diabetes (T2D) models but are consistent with other retinopathy models, showing neural damage prior to vascular changes.

Although renin-angiotensin blockade has shown the beneficial outcomes in patients with diabetes, renal injury progresses in most of these patients. Therefore, there remains a need for new therapeutic targets in diabetic kidney disease. Enhancement of vasoactive peptides, such as natriuretic peptides, via neprilysin inhibition, has been a new approach. A first-in-class drug sacubitril/valsartan (Sac/Val), a combination of angiotensin II receptor blocker valsartan and neprilysin inhibitor prodrug sacubitril, has been shown more effective than renin-angiotensin blockade alone in the treatment of heart failure with reduced ejection fraction. In this study we tested the effects of Sac/Val in the diabetic kidney disease. We administered Sac/Val or valsartan to two type 2 diabetes mouse models, db/db mice or KKAy mice. After 3-month treatment, Sac/Val attenuated the progression of proteinuria, glomerulosclerosis, and podocyte loss in both models of diabetic mice. Valsartan shared the similar improvement but to a lesser degree in some parameters compared to Sac/Val. Sac/Val but not valsartan decreased the blood glucose level in KKAy mice. Sac/Val exerted renal protection through coordinated effects on anti-oxidative stress and anti-inflammation. In both diabetic models, we revealed a new mechanism to cause inflammation, self DNA activated cGAS-STING signaling, which was activated in diabetic kidneys and prevented by Sac/Val or valsartan treatment. Present data suggest that Sac/Val has sufficient therapeutical potential to counter the pathophysiological effects of diabetic kidney disease and its effectiveness could be better than valsartan alone.