Association between the microbiomes of tonsil and saliva samples isolated from pediatric patients subjected to tonsillectomy for the treatment of tonsillar hyperplasia

Oral microbes have the capacity to spread throughout the gastrointestinal system and are strongly associated with multiple diseases. Given that tonsils are located between the oral cavity and the laryngopharynx at the gateway of the alimentary and respiratory tracts, tonsillar tissue may also be affected by microbiota from both the oral cavity (saliva) and the alimentary tract. Here, we analyzed the distribution and association of the microbial communities in the saliva and tonsils of Korean children subjected to tonsillectomy because of tonsil hyperplasia (n = 29). The microbiome profiles of saliva and tonsils were established via 16S rRNA gene sequencing. Based on the alpha diversity indices, the microbial communities of the two groups showed high similarities. According to Spearman’s ranking correlation analysis, the distribution of Treponema, the causative bacterium of periodontitis, in saliva and tonsils was found to have a significant positive correlation. Two representative microbes, Prevotella in saliva and Alloprevotella in tonsils, were negatively correlated, while Treponema 2 showed a strong positive correlation between saliva and tonsils. Taken together, strong similarities in the microbial communities of the tonsils and saliva are evident in terms of diversity and composition. The saliva microbiome is expected to significantly affect the tonsil microbiome. Furthermore, we suggest that our study creates an opportunity for tonsillar microbiome research to facilitate the development of novel microbiome-based therapeutic strategies.Subject terms: Comparative genomics, Metagenomics     

2020年电子电路技术热点

文章归纳了2020年电子电路产业一些技术热点,主要有5G电路板设计和基材,制造方面半加成法、3D打印、直接金属化孔电镀和垂直互连结构等技术,以及集成电路封装载板技术。     

Three-weight linear codes from Weil sums

Journal of Algebraic Combinatorics - By appropriately choosing a defining set, we define a class of linear codes and establish their complete weight enumerators and weight enumerators using Weil...     

Generalized Jacobi spectral Galerkin method for fractional pantograph differential equation

This work is concerned with the extension of the Jacobi spectral Galerkin method to a class of nonlinear fractional pantograph differential equations. First, the fractional differential equation is converted to a nonlinear Volterra integral equation with weakly singular kernel. Second, we analyze the existence and uniqueness of solutions for the obtained integral equation. Then, the Galerkin method is used for solving the equivalent integral equation. The error estimates for the proposed method are also investigated. Finally, illustrative examples are presented to confirm our theoretical analysis.     

蛋白质-多糖复合体系在活性物质传递中的应用

蛋白质-多糖复合体系作为生物活性物质传递系统的壁材,有着人工合成聚合物或无机物等其他材料不可比拟的多重优势。本文就蛋白质和多糖之间的连接方式及蛋白质-多糖复合体系形成传递系统的多种形式进行了综述,以及对此领域的发展趋势进行了展望。结合蛋白质和多糖的结构特点,二者之间的链接方式分为非共价结合的物理共聚,和共价结合的美拉德偶联、化学交联、酶催化交联等方式,文中分别对各种连接方式的原理和机理,以及其影响因素做了深入阐述。以蛋白质-多糖复合体系为壁材对活性物质的传递形式大体上分成乳化系统、胶束、纳米凝胶、分子复合物以及壳核结构等系统。不同的活性物质的特征和传递需求,可针对性地选择合适结构的蛋白质和多糖种类以及二者的连接方式和传递系统的形式。并且,随着研究的逐步发展和推进,此领域的发展趋势朝着智能化和靶向性的方向进行。目前活性物质的蛋白质-多糖复合体系的传递系统,还依然面临着系统设计、评价和应用等多方面的挑战,这就要求我们在更全面更深入了解认识其对活性物质影响和功效的基础上,安全合理地设计和深入细致地评价活性成分的传递系统。     

Sentinel-2卫星的多光谱轻量级船舶目标检测算法

近年来深度卷积神经网络在可见光船舶检测方面取得了显著的进展，然而，大多数相关研究是通过改进大型的网络结构来提高检测性能，因此加大了对更高计算机性能的需求。此外，可见光图像难以在云、雾、海杂波、黑夜等复杂场景检测到船舶。针对以上问题，提出了一种融合红（red, R）、绿（green, G）、蓝（blue, B）和近红外（NIR）4个波段光谱信息的由粗到精细的轻量型船舶检测算法。与现有的方法中根据光谱特性利用水体检测算法提取水体区域不同之处是该算法是利用改进的水体检测算法来提取船舶候选区域。为获取更准确的候选区域，对船舶、厚云、薄云、平静海面、杂波海面5种场景中4个波段的像素值进行了统计分析，选取近红外大于阈值作为辅助判断，并以其中心点获取候选区域32×32大小的切片，并对切片进行非极大值抑制，由此获得了船舶粗检测结果。随后构建了轻量级LSGFNet网络对船舶候选区域切片进行精细识别。构建的网络融合了1×1卷积提取的波谱特征与3×3的提取几何特征，为防止光谱特征与几何特征的信息在融合时“信息不流通”，在LSGFNet网络中引入了ShuffleNet中的通道打乱机制，并减小了模型结构，与典型的轻量级网络相比具有更好的效果且模型较小。最后，利用Sentinel-2卫星多光谱10 m分辨率数据构建了512×512大小的1 120组数据进行粗检测，以及32×32大小的6 014组数据进行精细网络训练，其中候选区域粗提取的查全率为98.99%，精细识别网络精确度为96.04%，不同场景下的平均精确度为92.98%。实验表明该算法在抑制云层、海浪杂波等干扰的复杂背景下具有较高的检测效率，且训练时间短、计算机性能需求低。     

An end-to-end denoising autoencoder-based deep neural network approach for fault diagnosis of analog circuit

Analog Integrated Circuits and Signal Processing - Fault diagnosis of analog circuit is critical to improve safety and reliability in electrical systems and reduce losses. Traditional fault...