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[学术文献] A dual electrochemical/colorimetric magnetic nanoparticle/peptide-based platform for the detection of Staphylococcus aureus 进入全文

ANALYST

Point-of-care facile and economical detection of Staphylococcus aureus(S. aureus), one of the main causes of food-borne illness, is highly demanded for the early diagnosis and control of infections. Herein, inspired by the proteolytic activity of S. aureus protease on a specific peptide substrate, we developed a rapid, simple and cost-effective biosensor for S. aureus using dual colorimetric and electrochemical detection on the same platform. In this approach, gold screen printed electrodes were used on which specific peptide sequences coupled to magnetic nanoparticles were immobilized giving the black color of the sensor surface. The addition of the S. aureus protease solution on the electrode surface causes cleavage of the peptide sequence and the release of the magnetic nanoparticles revealing the golden colour of the electrode which can be easily seen by the naked eye. Furthermore, square wave voltammetric signals can be detected on the same electrode in the ferro/ferricyanide redox couple. The change in the peak current after peptide cleavage was directly proportional to the concentration of S. aureus. The detection limit of the electrochemical assay was 3 CFU ml-1after 1 min. Moreover, the biosensor was capable of specifically distinguishing S. aureus from other food- and water-borne bacteria such as E. coli and Listeria using the dual mode colorimetric and electrochemical detection. The biosensor was also tested in spiked milk and water samples showing very good recovery percentages. Thus, we believe that this dual mode biosensing platform enables the easy and accurate determination of S. aureus and holds great promise for point-of-care diagnosis.

[前沿资讯] Space to grow, or grow in space -- how vertical farms could be ready to take-off 进入全文

EurekAlert

Vertical farms with their soil-free, computer-controlled environments may sound like sci-fi. But there is a growing environmental and economic case for them, according to new research laying out radical ways of putting food on our plates. The interdisciplinary study combining biology and engineering sets down steps towards accelerating the growth of this branch of precision agriculture, including the use of aeroponics which uses nutrient-enriched aerosols in place of soil. Carried out by the John Innes Centre, the University of Bristol and the aeroponic technology provider LettUs Grow, the study identifies future research areas needed to accelerate the sustainable growth of vertical farming using aeroponic systems. Dr Antony Dodd, a group leader at the John Innes Centre and senior author of the study, says: "By bringing fundamental biological insights into the context of the physics of growing plants in an aerosol, we can help the vertical farming business become more productive more quickly, while producing healthier food with less environmental impact." Jack Farmer, Chief Scientific Officer at LettUs Grow and one of the authors of the study, adds: "Climate change is only going to increase the demand for this technology. Projected changes in regional weather patterns and water availability are likely to impact agricultural productivity soon. Vertical farming offers the ability to grow high value nutritious crops in a climate resilient manner all year round, proving a reliable income stream for growers." Vertical farming is a type of indoor agriculture where crops are cultivated in stacked systems with water, lighting and nutrient sources carefully controlled. It is part of a rapidly growing sector supported by artificial intelligence in which machines are taught to manage day to day horticultural tasks. The industry is set to grow annually by 21% by 2025 according to one commercial forecast (Grand View Research, 2019). Green benefits include better use of space because vertical farms can be sited in urban locations, fewer food miles, isolation from pathogens, reduction in soil degradation and nutrient and water recapturing and recycling. Vertical farms also allow product consistency, price stabilization, and cultivation at latitudes incompatible with certain crops such as the desert or arctic. "Vertical systems allow us to extend the latitude range on which crops can be grown on the planet, from the deserts of Dubai to the 4-hour winter days of Iceland. In fact, if you were growing crops on Mars you would need to use this kind of technology because there is no soil," says Dr Dodd. The study, which appears in the journal New Phytologist, lays out seven steps - strategic areas of future research needed to underpin increased productivity and sustainability of aeroponic vertical farms. These seek to understand: Why aeroponic cultivation can be more productive than hydroponic or soil cultivation. The relationship between aeroponic cultivation and 24-hour circadian rhythms of plants. Root development of a range of crops in aeroponic conditions. The relationship between aerosol droplet size and deposition and plant performance. How we can establish frameworks for comparing vertical farming technologies for a range of crops. How aeroponic methods affect microbial interactions with plant roots. The nature of recycling of root exudates (fluids secreted by the roots of plants) within the nutrient solutions of closed aeroponic systems. The report argues that a driver of technological innovation in vertical farms is minimizing operation costs whilst maximizing productivity - and that investment in fundamental biological research has a significant role. Dr Dodd's research area covers circadian rhythms - biological clocks which align plant physiology and molecular processes to the day to day cycle of light and dark. He recently completed a year-long Royal Society Industry Fellowship with LettUs Grow. This involved combining Dr Dodd's expertise in circadian rhythms and plant physiology with the work of LettUs Grow's team of biologists and engineers to design optimal aeroponic cultivation regimens. This is a key area of investigation as these molecular internal timers will perform differently in vertical farms. Aeroponic platforms are often used to grow high value crops such as salads, pak choi, herbs, small brassica crops, pea shoots and bean shoots. LettUs Grow are also working on growth regimens for fruiting and rooting crops such as strawberries and carrots, as well as aeroponic propagation of trees for both fruit and forestry. John Innes Centre researchers have bred a line of broccoli adapted to grow indoors for a major supermarket and one of the aims of research will be to test how we can genetically tune more crops to grow in the controlled space of vertical farms. Bethany Eldridge, a researcher at the University of Bristol studying root-environment interactions and first author of the study adds: "Given that 80% of agricultural land worldwide is reported to have moderate or severe erosion, the ability to grow crops in a soilless system with minimal fertilizers and pesticides is advantageous because it provides an opportunity to grow crops in areas facing soil erosion or other environmental issues such as algal blooms in local water bodies that may have been driven by traditional, soil-based, agriculture." Lilly Manzoni, Head of Research and Development at LettUs Grow and one the authors of the study says, "This paper is unique because it is broader than a typical plant research paper, it combines the expertise of engineers, aerosol scientists, plant biologists and horticulturalists. The wonderful thing about controlled environment agriculture and aeroponics is that it is truly interdisciplinary"

[前沿资讯] 我专家提出多源光学传感器的应用是作物表型鉴定研究的重要发展方向 进入全文

中国农业科学院

7月1日,中国农业科学院作物科学研究所作物栽培与生理创新团队在《地球科学与遥感(IEEE Geoscience and Remote Sensing Magazine)》上,在线发表了该研究团队联合全球多位作物表型领域国际知名专家,历时三年关于作物表型鉴定研究的系统综述文章。文章对当前作物表型鉴定的起源、概念、使用传感器类型以及对应的作物表型性状鉴定难点问题和解决办法进行系统整理和总结,提出了将多源光学传感器与地面和航空作物表型鉴定平台有效整合是未来重要发展方向。 据金秀良研究员介绍,近年来,利用基因组学辅助育种的方法已成为新品种培育和作物提质增产的重要手段,如何更好地将作物表型组和基因组数据进行关联分析,快速准确地筛选目标性状和基因,对于提高育种效率,保证全球粮食安全具有重要意义。目前,高通量的基因测序和分析技术已经比较成熟,但高通量作物表型精准鉴定能力仍有待提升。 文章系统阐述了当前光学传感器在作物表型性状鉴定研究领域的发展现状,重点介绍了地面和航空作物表型性状鉴定平台在田间不同氮素、水分和病虫害等生物胁迫和非生物胁迫的作物表型性状鉴定的研究应用进展,讨论了作物表型性状鉴定研究未来的新机遇、新方向和技术发展。文章指出,高通量表型鉴定技术利用新型传感器、先进的自动化平台和图像处理系统,可以在温室、大田等不同条件下快速、准确筛选出目标性状突出的优异资源和材料。今后,基于新研发的光学传感器、作物表型平台、影像处理技术和大数据管理方法的有机融合,高通量作物表型性状鉴定技术将提高标准化作物表型性状鉴定的估算精度并进一步加速作物育种计划中新作物表型性状的鉴定效率。该文章为作物表型技术的应用提供了系统理论参考,为优质新品种培育提供了新思路、新方法。 该研究得到“十三五”国家重点研发计划、国家自然科学基金和中国农科院科技创新工程等项目资助。(通讯员 卫斐) 原文链接:https://ieeexplore.ieee.org/document/9130745

[相关专利] INTEGRATED TEST CARTRIDGE FOR MEASURING ANALYTE CONCENTRATION 进入全文

世界知识产权组织

A multiplex aptamer sensor platform for determining the concentration of a target analyte in sample. Aptamers are modified with redox-active molecule and selected to exhibit conformational change in the presence of target analyte, so that faradic discharge can be sampled at the electrode surface. Faradic discharge is converted to digital signal for calculation of the analyte concentration. The platform is attached to a test cartridge utilizing a vertical connection to a reader device. Sensor electrodes are manufactured using PCB techniques yet the platform is both accurate and commercially usable. No mixing, microfluidics or calibration are required.

[相关专利] SYSTEM AND METHOD FOR INTEGRATED SENSOR CARTRIDGE 进入全文

世界知识产权组织

A microfluidic apparatus (100) can include a PCB (110), a biological chip (120) overlying the PCB (110), and a microfluidic housing (130) overlying the biological chip (120) and the PCB (110). The microfluidic apparatus (100) also has a first adhesive layer (141) attaching the microfluidic housing (130) to the biological chip (120) and a second adhesive layer (142) attaching the microfluidic housing (130) to the PCB (110). The second adhesive layer (142) is thicker than the first adhesive layer (141). The first adhesive layer (141) comprises a first adhesive material, and the second adhesive layer (142) comprises a second adhesive material.

[学术文献] 表示学习技术研究进展及其在植物表型中应用分析 进入全文

农业机械学报

表示学习是一种将研究对象的内在信息表示为稠密低维实值向量的方法,其基本思路是找到对原始数据更好的表达。表示学习凭借其自动提取特征的能力,在处理大量人为先验理解有限的数据时表现出高效性。有监督以及无监督的表示学习模型在文本、图像、三维点云等植物表型数据的分析研究中获得了运用。随着近年来数据量的迅速增长以及基因组学研究的快速发展,植物表型研究数据具有高通量、高精度等特征,表示学习模型在海量高维植物表型数据的分析任务中获得了关注。本文简述了表示学习的相关概念和表示学习技术研究进展,对有监督和无监督的表示学习模型进行对比分析,阐述了植物表型数据概念及其处理方法,重点从植物种类识别、病虫害检测分析、产量预测、基因研究和形态结构表型数据计算等方面,探讨了表示学习在植物表型中的研究应用意义及其存在的问题。最后,指出表示学习在植物表型应用中的发展方向:开发能够适用于分析不同种植物表型数据的表示学习模型,实现高整合度、高通用性的目标;提高表示学习模型的实时性及准确度,以增强其实用性;多模态表型数据的表示学习可为学科的交叉数据分析研究提供统一的数据视图。

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