Multiplex ligation-dependent probe amplification (MLPA) for simultaneous detection of DNA from sunflower,poppy, flaxseed,sesame and soy allergenic ingredients in commercial food products

This work describes a multiplex ligation-dependent probe amplification (MLPA) technique for the simultaneous detection of five food allergens: sunflower, poppy, flaxseed, sesame and soy. Species-specific MLPA half-probes were designed to detect the DNA from the targeted species. Ligated probes were amplified by polymerase chain reaction (PCR) and amplicons were detected using capillary electrophoresis. The specificity of the MLPA system was assessed against DNA from more than 50 plant and animal species. The limit of detection (LOD) of the assay was determined to be 10 mg kg⁻¹in a model cookie experimentally spiked with different concentrations of the target species. The applicability of the MLPA was demonstrated through the analysis of 56 different commercial products (breads, pastries, cereals, chocolates, drinks, etc.), evidencing the presence of one or more undeclared allergenic ingredients in some of the tested samples. Real-time PCR assays were also performed to confirm and complement MLPA results. The MLPA technique has proved as a qualified screening tool for determining the presence of low amounts of sunflower, poppy, flaxseed, sesame and soy in processed foods.     

Multi-walled carbon nanotubes-based magnetic solid-phase extraction for the determination of zearalenone and its derivatives in maize by ultra-high performance liquid chromatography-tandem mass spectrometry

A simple and rapid magnetic solid-phase extraction (M-SPE) procedure using multi-walled carbon nanotube-magnetic nanoparticles (MWCNT-MNPs) as sorbents was established for purification of zearalenone (ZEA), α-zearalenol (α-ZOL), β-zearalenol (β-ZOL), zearalanone (ZAN), α-zearalanol (α-ZAL) and β-zearalanol (β-ZAL) in maize. The main parameters affecting the clean-up efficiency were thoroughly investigated, and high purification efficiencies for all analytes were obtained. The resulting MWCNT-MNP-ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was validated for maize samples. The matrix effects were greatly minimized using the M-SPE approach, with signal suppression/enhancement values decreased from 69.9–127.6% to 92.1–103.8%. Consequently, complex matrix-matched calibration curves were not necessary and the calibrations constructed in acetonitrile could be applied for accurate quantification of the targeted mycotoxins in real samples. The average recoveries ranged from 75.8 to 104.1% and the inter- and intra-day precision values expressed as RSDs, were all lower than 14%. Limits of detection and quantification were in the range of 0.03–0.04 and 0.07–0.10 μg/kg, respectively. The analytical performance of the developed method was also successfully evaluated with maize samples, and this method was proved to be a powerful tool for monitoring ZEA and its derivatives in maize.     

《建筑环境通用规范》与《民用建筑工程室内环境污染控制标准》的理解及应用

GB 55016-2021《建筑环境通用规范》自2022年4月实施,为全文强制性工程建设规范,现行工程建设标准的相关强制性条文同时废止,其中GB 50325-2020《民用建筑工程室内环境污染控制标准》中的18条强制性条文废止,5.2.9升级为强制性条文后写入GB 55016-2021。GB 50325-2020中有关规定与GB 55016-2021不一致的,以GB 55016-2021为准。工程质量检测机构在进行室内环境污染物检测时,应注意依据标准的选择。     

广州市公园对比评价研究——基于社交媒体数据的文本分析

传统公园评价的研究大多集中在单个公园使用满意度方面,存在问卷样本量小、采集时间较集中等缺陷。大数据相关研究的快速发展为公园系统评价提供了新的契机。基于对社交媒体数据的文本分析,研究对比广州市 50 个公园的评价结果,同时探究公园评价与人口统计学特征、地理区位、评价时间以及公园属性之间的关系。研究发现, 1）公园正面评价主要集中在免费设施、环境和特色等方面,而负面评价多集中于公园卫生、交通成本、停车等管理服务方面,广州公园的管理服务水平亟待提升。 2）女性较男性更关注公园能否满足其对社交场所的需求,本地游客较外地游客更关注公园本身的服务质量而非公园的外部属性。 3）基干公园应更侧重其可达性和基本的服务功能,承担大众日常活动;特色公园应更注重满足特定人群的需求及特色打造;自然公园应更关注公园生态质量并能够承担需要较大场地的活动。 4） 2010—2018 年,人们越来越关注公园特色的打造,在公园中的活动类型也越来越多样,现代公园建设更应着力于文化服务质量的提升。研究突破传统公园研究方法的局限,将大数据的手段运用到多个公园的整体评价当中,有助于建立更普适、更有针对性的公园评价指标体系,具有较高的实践价值。     

Nanoinformatics: Emerging Databases and Available Tools

Nanotechnology has arisen as a key player in the field of nanomedicine. Although the use of engineered nanoparticles is rapidly increasing, safety assessment is also important for the beneficial use of new nanomaterials. Considering that the experimental assessment of new nanomaterials is costly and laborious, in silico approaches hold promise. Several major challenges in nanotechnology indicate a need for nanoinformatics. New database initiatives such as ISA-TAB-Nano, caNanoLab, and Nanomaterial Registry will help in data sharing and developing data standards, and, as the amount of nanomaterials data grows, will provide a way to develop methods and tools specific to the nanolevel. In this review, we describe emerging databases and tools that should aid in the progress of nanotechnology research.     

基于特征地图的改进回环检测算法

为提高移动机器人回环检测模块的准确率和实时性,提出一种基于特征地图的改进回环检测算法。在传 统模型的基础上,对关键帧的特征点进行筛选,选取高效特征点构建特征地图,利用视觉字典树对特征地图和关键 帧进行场景描述;对词袋模型进行改进,将场景分割用在图像信息的提取和特征聚类上;建立基于分层K++均值的 视觉字典树,得到改进的基于分层金字塔TF-IDF(term frequency–inverse document frequency)的匹配方法。实验结果 证明：相比FAB-MAP(fast appearance-based mapping)和RGB-D SLAM v2,改进算法在特征点规模、实时性、召回 率方面性能更优。     

彩超顺序分段分析法对矫正型大动脉转位的诊断价值

目的：探讨彩色多普勒超声心动图顺序分段分析法对矫正型大动脉转位（CTGA）的诊断价值。方法对11例 CTGA 患者采用彩色多普勒超声心动图顺序分段分析法判定心脏位置、连接关系及心内结构、功能和血流信号的变化。结果11例 CTGA 患者中,彩色多普勒超声心动图顺序分段分析法对 CTGA 的诊断符合率达100．0％（11/11）。SLL 型（心脏位置正常）9例（81．8％）,IDD 型（镜面右位心）2例（18．1％）。SLL 型合并室间隔缺损9例、合并肺动脉狭窄7例和合并解剖三尖瓣中度反流8例;合并房间隔缺损4例,其中 SLL 型3例,IDD 型1例;IDD 型合并室间隔缺损、肺动脉狭窄和解剖三尖瓣中度反流1例。均经手术证实。结论CTGA 的超声表现错综复杂,心房与心室连接不一致和心室与大动脉连接不一致是诊断 CTGA 的关键,运用其特征性能有效提高诊断符合率,部分替代心血管造影等检查,为心胸外科提供重要的诊断依据。     

Word-Representation-Based Method for Extracting Organizational Events from Online Media

Online social media exhibit massive organizational event relevant messages, and the well categorized event information can be useful in many real-world applications. In this paper, we propose a research framework to extract high quality event information from massive online media data. The main contributions lie in two aspects: First, we present an event-extraction and event-categorization system for online media data; second, we present a novel approach for both discovering important event categories and classifying extracted events based on word representation and clustering model. Experimental results with real dataset show that the proposed framework is effective to extract high quality event information.     

Agriculture satellite image segmentation using a modified artificial Hopfield neural network

Beekeeping plays an important role in increasing and diversifying the incomes of many rural communities in Kingdom of Saudi Arabia. However, despite the region’s relatively good rainfall, which results in better forage conditions, bees and beekeepers are greatly affected by seasonal shortages of bee forage. Because of these shortages, beekeepers must continually move their colonies in search of better forage. The aim of this paper is to determine the actual bee forage areas with specific characteristics like population density, ecological distribution, flowering phenology based on color satellite image segmentation. Satellite images are currently used as an efficient tool for agricultural management and monitoring. It is also one of the most difficult image segmentation problems due to factors like environmental conditions, poor resolution and poor illumination. Pixel clustering is a popular way of determining the homogeneous image regions, corresponding to the different land cover types, based on their spectral properties. In this paper Hopfield neural network (HNN) is introduced as Pixel clustering based segmentation method for agriculture satellite images.