In vitro antiproliferative activity of glabridin derivatives and their in silico target identification

Abstract

Novel Mannich base derivatives of glabridin were synthesized and their antiproliferative activity were performed along with our previously reported glabridin-chalcone hybrids molecules (GCHMs) against various human cell lines MDA-MB-231 (breast adenocarcinoma), HEK-293 (embryonic kidney cell line), K562 (leukemia), MCF-7 (breast adenocarcinoma), HeLa (cervix adenocarcinoma), HepG2 (hepatocellular carcinoma) and WRL-68 (hepatic carcinoma). The result showed that the glabridin significantly reduced cell proliferation with IC₅₀ ranges from 3.67 to 58.30?µM against all the tested cell lines. The remarkable reduction in antiproliferative activity 2’,4’-dimethoxyglabridin and GCHMs compounds with phenolic OH groups protected by methoxy (OCH₃) groups suggested that the free OH groups are essential factor for the antiproliferative activity of glabridin and its derivatives. The Mannich base derivatives of glabridin showed moderate activity IC₅₀ (2.20–>95.78?µM). Furthermore, in silico target identification analysis revealed that AKT1, DECR1 and NOS1 are the potential targets for glabridin and their derivatives.     

基于支座反力影响线曲率差分的等截面连续梁损伤识别方法

为了实现仅采用损伤状态信息对等截面连续梁进行损伤识别,通过推导三跨不等跨连续梁在移动荷载作用下的支座反力影响线,发现支座反力影响线求曲率并作差分后的曲线在损伤位置会发生突变,基于该现象提出了一种损伤定位方法,进一步建立了损伤程度计算方法,可对损伤程度进行较精确的定量。通过一三跨连续梁和一四跨连续梁工程实例的仿真分析,证明了支座反力影响线曲率差分指标损伤定位和相应的损伤程度定量方法对等截面连续梁损伤识别具有可行性。     

EMD与神经网络在气液两相流流型识别中的应用

本文提出了EMD与Elman神经网络相结合的气液两相流流型识别的新方法.将压差波动信号经验模态分解(EMD)后的固有模态函数(IMF)进行分析、提取IMF能量作为Elman神经网络的输入特征向量,对水平管内的气液两相流流型进行识别.实验结果表明:该方法优于BP网络且稳定、识别率高,具有可行性.     

基于深度学习的太赫兹时域光谱识别研究

太赫兹时域光谱技术,由于其具有物质"指纹谱"特性,是一种可以快速无损地鉴别物质的重要手段,在毒品和爆炸物的无损检测等方面有广阔的应用前景.其中,光谱识别是太赫兹时域光谱技术应用研究的重要方向之一.现有的光谱识别方法多是依靠手工选取特征后进行机器学习分类,或是通过设置吸收峰阈值门限进行判断.由于一些物质在太赫兹波段内并没...     

On Regularization of a Source Identification Problem in a Parabolic PDE and its Finite Dimensional Analysis

We consider the inverse problem of identifying a general source term, which is a function of both time variable and the spatial variable, in a parabolic PDE from the knowledge of boundary measurements of the solution on some portion of the lateral boundary. We transform this inverse problem into a problem of solving a compact linear operator equation. For the regularization of the operator equation with noisy data, we employ the standard Tikhonov regularization, and its finite dimensional realization is done using a discretization procedure involving the space $L^2(0,\tau;L^2(Ω))$. For illustrating the specification of an a priori source condition, we have explicitly obtained the range space of the adjoint of the operator involved in the operator equation.     

In Vitro Anti-Diabetic Activities and UHPLC-ESI-MS/MS Profile of Muntingia calabura Leaves Extract

Anti-diabetic compounds from natural sources are now being preferred to prevent or treat diabetes due to adverse effects of synthetic drugs. The decoction of Muntingia calabura leaves was traditionally consumed for diabetes treatment. However, there has not been any published data currently available on the processing effects on this plant’s biological activity and phytochemical profile. Therefore, this study aims to evaluate the effect of three drying methods (freeze-drying (FD), air-drying (AD), and oven-drying (OD)) and ethanol:water ratios (0, 50, and 100%) on in vitro anti-diabetic activities of M. calabura leaves. In addition, an ultrahigh-performance-liquid chromatography–electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) method was used to characterize the metabolites in the active extract. The FD M. calabura leaves, extracted with 50% ethanol, is the most active extract that exhibits a high α-glucosidase and α-amylase inhibitory activities with IC₅₀ values of 0.46 ± 0.05 and 26.39 ± 3.93 µg/mL, respectively. Sixty-one compounds were tentatively identified by using UHPLC-ESI-MS/MS from the most active extract. Quantitative analysis, by using UHPLC, revealed that geniposide, daidzein, quercitrin, 6-hydroxyflavanone, kaempferol, and formononetin were predominant compounds identified from the active extract. The results have laid down preliminary steps toward developing M. calabura leaves extract as a potential source of bioactive compounds for diabetic treatment.     

基于中心-射线模型的印鉴识别方法及其应用

支票中的有效印鉴是支票流通有效性的重要体现。通过对支票印鉴有效性的识别来达到对支票流通有效性识别的目的。根据我国支票图像的特点提出了基于中心_射线模型的有效印鉴识别方法。该方法是通过对印鉴各成份区域之间拓扑关系的识别来达到对有效印鉴识别的目的。在将该方法用于我国支票印鉴识别的同时,还利用了印鉴的色彩特征。实验结果表明,该方法可有效地识别我国支票中的有效印鉴,有效印鉴识别的错误排除率为0%,错误接收率为23.8%。     

基于灰度曲面匹配的虹膜识别方法

目前的虹膜识别都是采用在图像上提取特征点,并将特征点编码为固定长度的特征数据用于匹配的方式。这种方式使虹膜识别系统易受攻击。为了进一步提高虹膜识别系统的安全性和识别速度,提出了一种基于灰度曲面匹配的虹膜识别方法。该方法抛弃了特征提取和编码等传统操作,在特征分析的基础上直接利用了灰度曲面匹配的思想,首先对两幅图像中的像素灰度做差,得到灰度差曲面,然后求出该灰度差曲面的方差。将此方差作为衡量两个虹膜特征曲面之间距离的依据,并据此判定两个虹膜是否来自同一只眼睛。在给定阈值为40的前提下,正确识别率为96.89%,识别时间为53.2 ms。实验结果证明,该方法识别准确率高,识别速度快。     

基于改进云推理算法的塔架结构损伤识别

为了解决塔架结构的损伤识别问题,提出了基于应变能和改进云推理算法的损伤识别方法。首先描述了云模型的基本理论和数字特征,并给出了模态应变能的基本公式;然后分析了X条件云发生器和Y条件云发生器的基本算法和运行步骤,借助灰云模型建立相应的前件云和后件云规则,考虑了测量噪声的影响,利用云发生器生成多组云滴,并利用多模式下云滴的确定度和生成值构建了基本云推理算法及其损伤识别指标。基本云推理算法中常会产生不均匀发散的云滴,从而使计算结果产生一定的偏差,为了降低云滴发散产生的偏差影响,提出了基于损伤模式数量加权的云推理改进策略。计算结果表明:云推理算法可以较好地应用于塔架结构的损伤识别,其识别结果明显优于传统的应变能耗散率指标方法;而改进云推理算法进一步提高了识别的精度,优于基本云推理算法。     

近红外光谱分析技术在茶叶鉴别中的应用研究

茶叶快速准确鉴别方法研究是当前茶叶行业亟待解决的一个重要课题。该研究采用近红外光谱结合主成分-马氏距离模式识别方法鉴别了龙井、碧螺春、毛峰和铁观音4种中国名茶。研究结果表明,在6 500～5 300 cm-1波数范围内的光谱,通过MSC预处理方法,用8个主成分建立的模型最好,模型对校正集样本和预测集样本的鉴别率分别达到98.75%和95%。该研究为快速准确鉴别茶叶提供了一种新思路。