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Liraglutide, a glucagon-like peptide-1 receptor agonist, has been shown to regulate blood sugar and control body weight, but its ability to treat obesity-related nephropathy has been poorly studied. Therefore, this study was designed to observe the characteristics and potential mechanism of liraglutide against obesity-related kidney disease. Thirty-six C57BL/6J male mice were randomly divided into six groups (n = 6 per group). Obesity-related nephropathy was induced in mice by continuous feeding of high-fat diet (HFD) for 12 weeks. After 12 weeks, liraglutide (0.6 mg/kg) and AMP-activated protein kinase (AMPK) agonists bortezomib (200 μg/kg) were injected for 12 weeks, respectively. Enzyme-linked immunosorbent assay was employed to detect the levels of total cholesterol, triglycerides, low-density lipoprotein cholesterol, blood urea nitrogen, creatinine in serum, as well as urinary protein in urine. Besides, hematoxylin–eosin staining and periodic acid-Schiff staining were used to observe the pathological changes of kidney tissue; immunohistochemistry, western blot, and real-time quantitative PCR to assess the calmodulin-dependent protein kinase kinase beta (CaMKKβ)/AMPK signaling pathway activation. Liraglutide significantly reduced serum lipid loading, improved kidney function, and relieved kidney histopathological damage and glycogen deposition in the mouse model of obesity-related kidney disease induced by HFD. In addition, liraglutide also significantly inhibited the CaMKKβ/AMPK signaling pathway in kidney tissue of HFD-induced mice. However, bortezomib partially reversed the therapeutic effect of liraglutide on HDF-induced nephropathy in mice. Liraglutide has a therapeutic effect on obesity-related kidney disease, and such an effect may be achieved by inhibiting the CaMKKβ/AMPK signaling pathway in kidney tissue. [ABSTRACT FROM AUTHOR]

Airborne lidar has a wide range of applications in mapping, exploration and so on. Its data processing uses the ranging data of LiDAR and the position and orientation information to obtain high precision surface models. In order to meet the real-time requirements of airborne LiDAR points position cloud calculation, a software-hardware co-design based method is used to design and implement the SoC of points position cloud calculation. A high-performance hardware accelerator is realized by using the AXI-4-based DMA high-speed transmission and using pipeline optimization and storage optimization methods. The experimental results show that the proposed SoC of points position cloud calculation can meet the real-time processing requirements of the airborne platform.

Introduction: Blood glucose monitoring was vitally important in diabetic kidney disease (DKD) patients for preventing complications and improving survival rates. The associations between glycemic variability and blood biochemical indicators were underestimated in patients with DKD undergoing hemodialysis. Therefore, we primarily aimed to investigate the glycemic variability and 1-year risk of cardiovascular disease events in diabetic hemodialysis patients. And we secondarily aimed to explore the association between glycemic variability and blood biochemical indicators. Methods: In total, 27 patients were included in the final analysis. Continuous glucose monitoring (CGM) was used to evaluate glucose variability for 14 days. Patients were divided into two groups by the cutoff level of time in range (TIR; >70% or ≤70%). The three-point major adverse cardiovascular event (3P MACE) was recorded within 1 year. Results: After 1 year of follow-up, 4 patients in the high-TIR group and 3 patients in the low-TIR group had 3p MACE. Higher low blood glucose index (LBGI) level in diabetic hemodialysis patients increased the risk of 3p MACE outcomes (HR = 2.37, p = 0.018). And the level of albumin was positively associated with LBGI (β = 0.51, p = 0.036). The plasma levels of albumin, glycosylated hemoglobin, and hemoglobin were positively associated with other CGM parameters. Conclusion: LBGI during 14 days was positively associated with the risk of cardiovascular events in diabetic hemodialysis patients. [ABSTRACT FROM AUTHOR]