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Dr. Yahu A. Liu Dr. Qihui Jin Qiang Ding Dr. Xueshi Hao Tingting Mo Shanshan Yan Dr. Yefen Zou Dr. Zhihong Huang Xiaoyue Zhang Wenqi Gao Dr. Tom Y.-H. Wu Chun Li Dr. Badry Bursalaya Dr. Michael Di Donato Dr. You-Qing Zhang Lisa Deaton Dr. Weijun Shen Dr. Brandon Taylor Anwesh Kamireddy Dr. George Harb Dr. Jing Li Dr. Yong Jia Dr. Andrew M. Schumacher Dr. Bryan Laffitte Dr. Richard Glynne Dr. Shifeng Pan Dr. Peter McNamara Dr. Valentina Molteni Dr. Jon Loren 《ChemMedChem》2020,15(16):1562-1570
Loss of β-cell mass and function can lead to insufficient insulin levels and ultimately to hyperglycemia and diabetes mellitus. The mainstream treatment approach involves regulation of insulin levels; however, approaches intended to increase β-cell mass are less developed. Promoting β-cell proliferation with low-molecular-weight inhibitors of dual-specificity tyrosine-regulated kinase 1A (DYRK1A) offers the potential to treat diabetes with oral therapies by restoring β-cell mass, insulin content and glycemic control. GNF4877, a potent dual inhibitor of DYRK1A and glycogen synthase kinase 3β (GSK3β) was previously reported to induce primary human β-cell proliferation in vitro and in vivo. Herein, we describe the lead optimization that lead to the identification of GNF4877 from an aminopyrazine hit identified in a phenotypic high-throughput screening campaign measuring β-cell proliferation. 相似文献
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In this research, the three‐dimensional structural and colorimetric modeling of three‐dimensional woven fabrics was conducted for accurate color predictions. One‐hundred forty single‐ and double‐layered woven samples in a wide range of colors were produced. With the consideration of their three‐dimensional structural parameters, three‐dimensional color prediction models, K/S‐, R‐, and L*a*b*‐based models, were developed through the optimization of previous two‐dimensional models which have been reported to be the three most accurate models for single‐layered woven structures. The accuracy of the new three‐dimensional models was evaluated by calculating the color differences ΔL*, ΔC*, Δh°, and ΔECMC(2:1) between the measured and the predicted colors of the samples, and then the error values were compared to those of the two‐dimensional models. As a result, there has been an overall improvement in color predictions of all models with a decrease in ΔECMC(2:1) from 10.30 to 5.25 units on average after the three‐dimensional modeling. 相似文献
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Yong Pan Chen Zhu Wen Bin Zeng Pei Fu Chi Chen Bao Ming Xu Zhong Feng Gao 《Chembiochem : a European journal of chemical biology》2021,22(24):3431-3436
Rapid and sensitive point-of-care testing (POCT) is an extremely critical mission in practical applications, especially for rigorous military medicine, home health care, and in the third world. Here, we report a visual POCT method for adenosine triphosphate (ATP) detection based on Taylor rising in the corner of quadratic geometries between two rod surfaces. We discuss the principle of Taylor rising, demonstrating that it is significantly influenced by contact angle, surface tension, and density of the sample, which are controlled by ATP-dependent rolling circle amplification (RCA). In the presence of ATP, RCA reaction effectively suppresses Taylor-rising behavior, due to the increased contact angle, density, and decreased surface tension. Without addition of ATP, untriggered RCA reaction is favorable for Taylor rising, resulting in a significant height. With this proposed method, visual sensitive detection of ATP without the aid of other instruments is realized with only a 5 μL droplet, which has good selectivity and a low detection limit (17 nM). Importantly, this visual method provides a promising POCT tool for user-friendly molecular diagnostics. 相似文献
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This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes. 相似文献