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1.
Peter K. Windsor Stephen P. Plassmeyer Dominic S. Mattock Jonathan C. Bradfield Erika Y. Choi Bill R. Miller III Byung Hee Han 《International journal of molecular sciences》2021,22(6)
Deposition of amyloid β (Aβ) fibrils in the brain is a key pathologic hallmark of Alzheimer’s disease. A class of polyphenolic biflavonoids is known to have anti-amyloidogenic effects by inhibiting aggregation of Aβ and promoting disaggregation of Aβ fibrils. In the present study, we further sought to investigate the structural basis of the Aβ disaggregating activity of biflavonoids and their interactions at the atomic level. A thioflavin T (ThT) fluorescence assay revealed that amentoflavone-type biflavonoids promote disaggregation of Aβ fibrils with varying potency due to specific structural differences. The computational analysis herein provides the first atomistic details for the mechanism of Aβ disaggregation by biflavonoids. Molecular docking analysis showed that biflavonoids preferentially bind to the aromatic-rich, partially ordered N-termini of Aβ fibril via the π–π interactions. Moreover, docking scores correlate well with the ThT EC50 values. Molecular dynamic simulations revealed that biflavonoids decrease the content of β-sheet in Aβ fibril in a structure-dependent manner. Hydrogen bond analysis further supported that the substitution of hydroxyl groups capable of hydrogen bond formation at two positions on the biflavonoid scaffold leads to significantly disaggregation of Aβ fibrils. Taken together, our data indicate that biflavonoids promote disaggregation of Aβ fibrils due to their ability to disrupt the fibril structure, suggesting biflavonoids as a lead class of compounds to develop a therapeutic agent for Alzheimer’s disease. 相似文献
2.
Raquel Cano Jos L. Prez Liss Angarita Dvila ngel Ortega Yosselin Gmez Nereida Josefina Valero-Cedeo Heliana Parra Alexander Manzano Teresa Isabel Vliz Castro María P. Díaz Albornoz Gabriel Cano Joselyn Rojas-Quintero Maricarmen Chacín Valmore Bermúdez 《International journal of molecular sciences》2021,22(9)
Non-alcoholic fatty liver disease (NAFLD) is considered the most common liver disorder, affecting around 25% of the population worldwide. It is a complex disease spectrum, closely linked with other conditions such as obesity, insulin resistance, type 2 diabetes mellitus, and metabolic syndrome, which may increase liver-related mortality. In light of this, numerous efforts have been carried out in recent years in order to clarify its pathogenesis and create new prevention strategies. Currently, the essential role of environmental pollutants in NAFLD development is recognized. Particularly, endocrine-disrupting chemicals (EDCs) have a notable influence. EDCs can be classified as natural (phytoestrogens, genistein, and coumestrol) or synthetic, and the latter ones can be further subdivided into industrial (dioxins, polychlorinated biphenyls, and alkylphenols), agricultural (pesticides, insecticides, herbicides, and fungicides), residential (phthalates, polybrominated biphenyls, and bisphenol A), and pharmaceutical (parabens). Several experimental models have proposed a mechanism involving this group of substances with the disruption of hepatic metabolism, which promotes NAFLD. These include an imbalance between lipid influx/efflux in the liver, mitochondrial dysfunction, liver inflammation, and epigenetic reprogramming. It can be concluded that exposure to EDCs might play a crucial role in NAFLD initiation and evolution. However, further investigations supporting these effects in humans are required. 相似文献
3.
针对目前工业CT图像转换为3D打印G代码方法效率低的问题,提出一种基于邻层数据匹配的工业CT图像直接转换成G代码的方法。首先采用Canny算子提取工业CT图像的轮廓,然后处理轮廓分叉问题,实现邻层间几何信息数据匹配,其次进行邻层间轮廓插值以满足3D打印层间厚度要求,从而避免"阶梯效应",最后通过填充编码得到用于3D打印的G代码。使用本文提出的方法,轮毂CT图像转换为G代码的时间为10.5 s,耗时远小于其他间接转换方法;3D打印出的轮毂无"阶梯效应",平均尺寸误差率为0.25%。实验结果表明,该方法不涉及中间格式,转换效率高,转换误差与传统方法相当,适用于具有复杂内腔结构的零件。 相似文献
4.
Olga Azevedo Filipa Cordeiro Miguel Fernandes Gago Gabriel Miltenberger-Miltenyi Catarina Ferreira Nuno Sousa Damio Cunha 《International journal of molecular sciences》2021,22(9)
Fabry disease (FD) is an X-linked lysosomal storage disorder caused by mutations of the GLA gene that result in a deficiency of the enzymatic activity of α-galactosidase A and consequent accumulation of glycosphingolipids in body fluids and lysosomes of the cells throughout the body. GB3 accumulation occurs in virtually all cardiac cells (cardiomyocytes, conduction system cells, fibroblasts, and endothelial and smooth muscle vascular cells), ultimately leading to ventricular hypertrophy and fibrosis, heart failure, valve disease, angina, dysrhythmias, cardiac conduction abnormalities, and sudden death. Despite available therapies and supportive treatment, cardiac involvement carries a major prognostic impact, representing the main cause of death in FD. In the last years, knowledge has substantially evolved on the pathophysiological mechanisms leading to cardiac damage, the natural history of cardiac manifestations, the late-onset phenotypes with predominant cardiac involvement, the early markers of cardiac damage, the role of multimodality cardiac imaging on the diagnosis, management and follow-up of Fabry patients, and the cardiac efficacy of available therapies. Herein, we provide a comprehensive and integrated review on the cardiac involvement of FD, at the pathophysiological, anatomopathological, laboratory, imaging, and clinical levels, as well as on the diagnosis and management of cardiac manifestations, their supportive treatment, and the cardiac efficacy of specific therapies, such as enzyme replacement therapy and migalastat. 相似文献
5.
Micro-milling is an extensively used micro-machining process for producing high precision 3D components from varied materials. However, tool wear in micro-tools is a big concern, as component accuracy directly depends on it. Also, size effects limit the monitoring by the naked eye, but it can be compensated by implying a proper wear monitoring mechanism. Various direct and indirect methods have earlier been used for monitoring purposes, and considering the needs of the fourth industrial revolution, one of the direct methods, machine vision, when combined with image processing algorithms, can play a more prominent role. Current work focuses on creating a wear monitoring algorithm based on fuzzy c-means clustering technique directly implied on acquired colour micro-tool images. The proposed algorithm has three steps: the first step is Region of Interest (ROI) extraction, where the background is removed, orientation correction is done, and ROI on each tooth is extracted from micro-tool colour images. The second uses the fuzzy c-means technique on ROI to cluster them, from which wear cluster is chosen and morphologically enhanced. The last step performs pixel level measurement and results in numerical wear width. Overall, quantitative results at each step are correlation coefficient of 99 % after image registration, segmentation accuracy of 92 % and wear measurement accuracy of 97 %. A comparison is also made between the proposed algorithm, k-means clustering and RGB thresholding technique, where the proposed algorithm outshines. Lastly, the wear measurement error of the proposed algorithm is less than 5 %, indicating its repeatable, reliable, and robust nature. 相似文献
6.
Rasheed A. Bailey Derek L. Beahm I. Martha Skerrett 《International journal of molecular sciences》2021,22(5)
Glycine is an amino acid with unique properties because its side chain is composed of a single hydrogen atom. It confers conformational flexibility to proteins and conserved glycines are often indicative of protein domains involving tight turns or bends. All six beta-type connexins expressed in human epidermis (Cx26, Cx30, Cx30.3, Cx31, Cx31.1 and Cx32) contain a glycine at position 12 (G12). G12 is located about halfway through the cytoplasmic amino terminus and substitutions alter connexin function in a variety of ways, in some cases altering protein interactions and leading to cell death. There is also evidence that alteration of G12 changes the structure of the amino terminus in connexin- and amino acid- specific ways. This review integrates structural, functional and physiological information about the role of G12 in connexins, focusing on beta-connexins expressed in human epidermis. The importance of G12 substitutions in these beta-connexins is revealed in two hereditary skin disorders, keratitis ichthyosis and erythrokeratodermia variabilis, both of which result from missense mutations affecting G12. 相似文献
7.
8.
针对现有医学图像处理方法在人体复杂结构组织器官分割中的不足,提出复用低层特征信息的Mask R-CNN网络。该网络可对特定组织器官识别时同时进行分割,为了提高包含较多细节信息的低层特征层的利用率,将低层的特征信息添加到高层的特征中,使低层与高层特性优劣互补,将原始图像首次长宽压缩两次后的特征层定义为C1层,而后分别通过复用C1层和复用依次卷积的C1层这两种方法实现。并将主干网络进行了精简,以加快网络的训练速度,降低识别和分割的时间。以下颌骨作为应用对象,自建包含1?064张下颌骨CT图片的数据集,按9∶1的比例划分为训练集和验证集进行训练,使得复用依次卷积C1层的Mask R-CNN网络的训练损失降至2.8%,验证损失降至6.6%,表明该网络在下颌骨的识别和分割上具有很高的准确率。 相似文献
9.
针对已有的航运监控图像识别模型C3D里中级表征学习能力有限,有效特征的提取容易受到噪声的干扰,且特征的提取忽视了整体特征与局部特征之间关系的问题,提出了一种新的基于注意力机制网络的航运监控图像识别模型。该模型基于卷积神经网络(CNN)框架,首先,通过特征提取器提取图像的浅层次特征;然后,基于CNN对不同区域激活特征的不同响应强度,生成注意力信息并实现对局部判别性特征的提取;最后,使用多分支的CNN结构融合局部判别性特征和图像全局纹理特征,从而利用局部判别性特征和图像全局纹理特征的交互关系提升CNN学习中级表征的能力。实验结果表明,所提出的模型在航运图像数据集上的识别准确率达到91.8%,相较于目前的C3D模型提高了7.2个百分点,相较于判别滤波器组卷积神经网络(DFL-CNN)模型提高了0.6个百分点。可见所提模型能够准确判断船舶的状态,可以有效应用于航运监控项目。 相似文献
10.
Recently, single image super-resolution (SISR) has been widely applied in the fields of underwater robot vision and obtained remarkable performance. However, most current methods generally suffered from the problem of a heavy burden on computational resources with large model sizes, which limited their real-world underwater robotic applications. In this paper, we introduce and tackle the super resolution (SR) problem for underwater robot vision and provide an efficient solution for near real-time applications. We present a novel lightweight multi-stage information distillation network, named MSIDN, for better balancing performance against applicability, which aggregates the local distilled features from different stages for more powerful feature representation. Moreover, a novel recursive residual feature distillation (RRFD) module is constructed to progressively extract useful features with a modest number of parameters in each stage. We also propose a channel interaction & distillation (CI&D) module that employs channel split operation on the preceding features to produce two-part features and utilizes the inter channel-wise interaction information between them to generate the distilled features, which can effectively extract the useful information of current stage without extra parameters. Besides, we present USR-2K dataset, a collection of over 1.6K samples for large-scale underwater image SR training, and a testset with an additional 400 samples for benchmark evaluation. Extensive experiments on several standard benchmark datasets show that the proposed MSIDN can provide state-of-the-art or even better performance in both quantitative and qualitative measurements. 相似文献