多模态影像学检查在诊断早期强直性脊柱炎骶髂关节疾病中的效果

目的:探究在早期强直性脊柱炎骶髂关节疾病诊断中不同放射影像学检查方法的应用效果。方法:抽取2018年5月-2020年1月本院收治的早期强直性脊柱炎骶髂关节疾病患者65例作为研究对象,所有患者均开展X线、CT、MRI影像学检查,对比三种不同影像学检查方法的检出率、影像学特征。结果:X线、CT、MRI检出率分别为38.46%(25/65)、60.00%(39/65)、76.92%(50/65),检出率相比,MRI、CT明显高于X线,P<0.05;X线、CT、MRI影像学特征,发现关节间隙出现不同的异常,如关节面出现侵蚀、骨质囊变现象,关节面下骨质出现硬化与关节软骨出现肿胀,其中MRI、CT检查,阳性率高于X线,P<0.05。而对于软组织肿胀、骨髓水肿、滑膜炎症、关节滑膜增厚等现象,只能通过MRI检查才能诊断。结论:在早期强直性脊柱炎骶髂关节疾病诊断中,X线、CT、MRI影像学检查均具有一定的指导意义,而MRI不仅可以提高检出率,还能准确反映微小病灶及其软组织病变,对于早期发现骶髂关节炎值得推荐。     

Sub-band coding of hexagonal images

According to the circle-packing theorem, the packing efficiency of a hexagonal lattice is higher than an equivalent square tessellation. Consequently, in several contexts, hexagonally sampled images compared to their Cartesian counterparts are better at preserving information content. In this paper, novel mapping techniques alongside the wavelet compression scheme are presented for hexagonal images. Specifically, we introduce two tree-based coding schemes, referred to as SBHex (spirally-mapped branch-coding for hexagonal images) and BBHex (breadth-first block-coding for hexagonal images). Both of these coding schemes respect the geometry of the hexagonal lattice and yield better compression results. Our empirical results show that the proposed algorithms for hexagonal images produce better reconstruction quality at low bits per pixel representations compared to the tree-based coding counterparts for the Cartesian grid.     

MicroRNAs,Parkinson’s Disease,and Diabetes Mellitus

Parkinson’s disease (PD) is a neurodegenerative disorder that affects 1% of the population over the age of 60. Diabetes Mellitus (DM) is a metabolic disorder that affects approximately 25% of adults over the age of 60. Recent studies showed that DM increases the risk of developing PD. The link between DM and PD has been discussed in the literature in relation to different mechanisms including mitochondrial dysfunction, oxidative stress, and protein aggregation. In this paper, we review the common microRNA (miRNA) biomarkers of both diseases. miRNAs play an important role in cell differentiation, development, the regulation of the cell cycle, and apoptosis. They are also involved in the pathology of many diseases. miRNAs can mediate the insulin pathway and glucose absorption. miRNAs can also regulate PD-related genes. Therefore, exploring the common miRNA biomarkers of both PD and DM can shed a light on how these two diseases are correlated, and targeting miRNAs is a potential therapeutic opportunity for both diseases.     

Opportunities,Challenges and Pitfalls of Using Cannabidiol as an Adjuvant Drug in COVID-19 †

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection may lead to coronavirus disease 2019 (COVID-19) which, in turn, may be associated with multiple organ dysfunction. In this review, we present advantages and disadvantages of cannabidiol (CBD), a non-intoxicating phytocannabinoid from the cannabis plant, as a potential agent for the treatment of COVID-19. CBD has been shown to downregulate proteins responsible for viral entry and to inhibit SARS-CoV-2 replication. Preclinical studies have demonstrated its effectiveness against diseases of the respiratory system as well as its cardioprotective, nephroprotective, hepatoprotective, neuroprotective and anti-convulsant properties, that is, effects that may be beneficial for COVID-19. Only the latter two properties have been demonstrated in clinical studies, which also revealed anxiolytic and antinociceptive effects of CBD (given alone or together with Δ⁹-tetrahydrocannabinol), which may be important for an adjuvant treatment to improve the quality of life in patients with COVID-19 and to limit post-traumatic stress symptoms. However, one should be aware of side effects of CBD (which are rarely serious), drug interactions (also extending to drugs acting against COVID-19) and the proper route of its administration (vaping may be dangerous). Clearly, further clinical studies are necessary to prove the suitability of CBD for the treatment of COVID-19.     

One-step to prepare high-performance gas diffusion layer (GDL) with three different functional layers for proton exchange membrane fuel cells (PEMFCs)

Gas diffusion layer (GDL) is one of the most important components of fuel cells. In order to improve the fuel cell performance, GDL has developed from single layer to dual layers, and then to multiple layers. However, dual or multi layers in GDL are usually prepared by layer-by-layer methods, which cost too much time, energy, and resources. In this work, we successfully developed a facile one-step method to prepare a GDL with three functional layers by utilizing the different sedimentation rates and filtration rates of short carbon fiber (CF) and carbon nanotube (CNT). The treatment temperature for this GDL is much lower than that of traditional method. The thickness of the GDL can be effectively controlled from as thin as 50 μm to more than 200 μm by simply adjusting the content of CF. The GDL with high flexibility is suitable to develop high performance flexible electronics. The fuel cell with the GDL has the maximum power density 1021 mW cm^?2, which shows 19% improvement comparing to the conventional one. Therefore, this work breaks the traditional concept that GDL for fuel cells only can be prepared by very complex and high-cost procedure.     

基于乙酰胆碱酯酶和氧化应激研究海胆酮对阿尔茨海默症的作用机制

海胆酮是一种酮式类胡萝卜素，主要从海胆及藻类等海洋生物中提取。本文研究海胆酮对乙酰胆碱酯酶（acetylcholinesterase，AChE）的抑制作用，应用酶动力学、荧光光谱、圆二色光谱和分子对接技术研究海胆酮对AChE的抑制机理，并用淀粉样β蛋白片段25～35（amyloid beta-peptide 25-35，Aβ25-35）诱导大鼠肾上腺嗜铬细胞瘤细胞（PC12细胞）建立阿尔茨海默症（Alzheimer’s disease，AD）模型，研究海胆酮对AD细胞模型氧化应激损伤的作用。结果表明，海胆酮有很强的AChE抑制活性，其半抑制质量浓度为（16.29±0.97）μg/mL，抑制常数Ki为3.82 μg/mL，表现为竞争性抑制；海胆酮可诱导AChE二级结构改变，更容易与AChE活性中心氨基酸Ser200、His440、Trp84和Tyr121结合，阻碍底物碘代硫代乙酰胆碱（acetylthiocholine iodide，ATCI）与酶结合，从而引起酶活力降低。海胆酮能有效抑制Aβ25-35诱导PC12细胞的AChE活力，降低丙二醛含量，增加超氧化物歧化酶、过氧化氢酶和谷胱甘肽过氧化物酶活力，减轻Aβ25-35诱导的PC12细胞氧化应激损伤。本研究基于AChE和氧化应激阐明了海胆酮对AD的潜在作用机制，为海胆酮在功能食品、生物医药等领域的应用提供了数据支持和理论根据。     

基于改进残差特征蒸馏的轻量级超分辨率网络

基于深度学习的图像超分辨率算法通常采用递归的方式或参数共享的策略来减少网络参数，这将增加网络的深度，使得运行网络花费大量的时间，从而很难将模型部署到现实生活中。为了解决上述问题，本文设计一种轻量级超分辨率网络，对中间特征的关联性及重要性进行学习，且在重建部分结合高分辨率图像的特征信息。首先，引入层间注意力模块，通过考虑层与层之间的相关性，自适应地分配重要层次特征的权重。其次，使用增强重建模块提取高分辨率图像中更精细的特征信息，以此得到更加清晰的重建图片。通过大量的对比实验表明，本文设计的网络与其他轻量级模型相比，有更小的网络参数量，并且在重建精度和视觉效果上都有一定的提升。     

Glycaemic response of pseudocereal-based gluten-free food products: a review

Rapid digestion and absorption of carbohydrates have become a health issue (high glycaemic index, GI), which can be a matter of greater concern when consumed in large quantities. Depending upon the influence of carbohydrates on the blood sugar levels, GI classifies carbohydrates (on a scale of 100) as low (<55), medium (55–70) and high (>70) GI foods. Among the pseudocereals, chia seed possesses relatively lower GI (28.53), as compared to buckwheat (52.35), amaranth (47.65) and quinoa (61.50). Consumers now prefer foods with a high GI over the ones with low GI to prevent various metabolic alterations. Celiac disease is a lifelong disorder prevalent worldwide and can only be controlled by following a strict lifelong gluten-free diet. Therefore, pseudocereals could be a potential alternate for low GI food and developing gluten-free food products, including bread, cookies, noodles and pasta. This review synthesises the recently published literatures on pseudocereals as a lowering GI and healthy food option. This review also gives insights into developing pseudocereals as a potential and novel ingredient for gluten-free food applications and the latest research conducted worldwide.     

Improving accuracy of automatic optical inspection with machine learning

Electronic devices require the printed circuit board(PCB)to support the whole structure,but the assembly of PCBs suffers from welding problem of the electronic components such as surface mounted devices(SMDs)resistors.The automated optical inspection(AOI)machine,widely used in industrial production,can take the image of PCBs and examine the welding issue.However,the AOI machine could commit false negative errors and dedicated technicians have to be employed to pick out those misjudged PCBs.This paper proposes a machine learning based method to improve the accuracy of AOI.In particular,we propose an adjacent pixel RGB value based method to pre-process the image from the AOI machine and build a customized deep learning model to classify the image.We present a practical scheme including two machine learning procedures to mitigate AOI errors.We conduct experiments with the real dataset from a production line for three months,the experimental results show that our method can reduce the rate of misjudgment from 0.3%–0.5%to 0.02%–0.03%,which is meaningful for thousands of PCBs each containing thousands of electronic components in practice.     

Investigation of fabrication of gas diffusion substrate for proton exchange membrane fuel cells

The gas diffusion substrate (GDS) is essential in the proton exchange membrane fuel cells. Its fabrication techniques affect the performance significantly and are worthy of investigation. In this study, a manufacturing process of the GDS is proposed to understand the formation process of GDS and promote its structure and performance more pertinently. Different states during the preparation process, raw carbon paper, pre-curing, curing, carbonation, and graphitization, are characterized and measured. Experimental and numerical methods are employed to determine the relationships between microstructure, transport, and mechanical performance variation with the fabricating processes. The results show that its porosity, average pore size, and effective diffusivity decrease first and increase after curing. These parameters after graphitization are lower than that of the carbon paper (CP). The electrical resistivity increases dramatically while pre-curing and decreases gradually after curing, carbonation, and graphitization, and it is much reduced after graphitization. Moreover, mechanical measurement results show that both the picks of tensile strength and flexural modulus occur after curing. Its tensile strength shows little change after graphitization compared to the initial paper's. In contrast, the flexural modulus is improved significantly.