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VPD modifies CO_(2)fertilization effect on tomato plants via abscisic acid and jasmonic acid signaling pathways

Horticultural Plant Journal 2024年第5期10卷 1165-1176页

作者： Dalong Zhang huihua yang Xiaolu Chen Yan Li Yunzhou Li Hongye Liu Xulin Wu Min Wei College of Horticultural Science and Engineering Shandong Agricultural UniversityTai'anShandong 271018China College of Agriculture Guizhou UniversityGuiyangGuizhou 550025China

Atmospheric CO_(2)concentration is elevated globally,which has“CO_(2)fertilization effects”and potentially improves plant photosynthesis,yield,and *** the beneficial effect of CO_(2)fertilization being modulated by vapor pressure deficit(VPD),the underlying mechanism is highly *** the present study,the potential roles of hormones in determining CO_(2)fertilization effects under contrasting high and low VPD conditions were investigated by integrated physiological and transcriptomic *** CO_(2)fertilization effects were offset under high VPD conditions and were constrained by plant water stress and photosynthetic CO_(2)*** VPD induced a large passive water driving force,which disrupted the water balance and consequently caused plant water *** water potential,turgor pressure,and hydraulic conductance declined under high VPD *** physiological evidence combined with transcriptomic analyses demonstrated that abscisic acid(ABA)and jasmonic acid(JA)potentially acted as drought-signaling molecules in response to high VPD *** foliar ABA and JA content triggered stomatal closure to prevent excessive water loss under high VPD stress,which simultaneously increased the diffusion resistance for CO_(2)uptake from atmosphere to leaf intercellular *** VPD also significantly increased mesophyll resistance for CO_(2)transport from stomatal cavity to fixation site inside *** chloroplast“sink”CO_(2)availability was constrained by stomatal and mesophyll resistance under high VPD stress,despite the atmospheric“source”CO_(2)concentration being ***,ABA-and JA-mediated drought-resistant mechanisms potentially modified the beneficial effect of CO_(2)fertilization on photosynthesis,plant growth,and yield *** study provides valuable information for improving the utilization efficiency of CO_(2)fertilization and a better understanding of the physiological processes.

关键词： Abscisic acid CO_(2)fertilization Jasmonic acid Mesophyll conductance Stomatal conductance Vapor pressure deficit

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酚类化合物暴露与血脂关联的定群研究

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环境与职业医学 2024年第7期41卷 728-734页

作者：向敏杨慧花张梓骞张晓敏杨良乐华中科技大学同济医学院公共卫生学院劳动卫生与环境卫生学系湖北武汉430030

[背景]酚类化合物被广泛用作增塑剂、抗菌剂和防腐剂,对人体具有内分泌干扰作用。既往关于酚类化合物暴露与血脂的流行病学研究主要基于单次尿样检测,忽略了潜在的滞后效应,研究结论也并不一致。[目的]探讨不同滞后天数的酚类化合物短... 详细信息

[背景]酚类化合物被广泛用作增塑剂、抗菌剂和防腐剂,对人体具有内分泌干扰作用。既往关于酚类化合物暴露与血脂的流行病学研究主要基于单次尿样检测,忽略了潜在的滞后效应,研究结论也并不一致。[目的]探讨不同滞后天数的酚类化合物短期暴露对成人血脂水平的影响。[方法]采用固定群组研究设计,于2017—2018年招募143名武汉成人(男性43名,女性100名),分别在夏、秋、冬3季进行重复调查。每季连续收集4 d晨尿,第1天进行问卷调查,第4天进行体格检查和空腹血样采集。共纳入126人(340人次,1251份尿样)进行统计分析。采用超高效液相色谱-串联质谱联用仪测定尿样中6种酚类化合物[双酚A(BPA)、双酚S(BPS)、三氯生(TCS)、对羟基苯甲酸甲酯(MeP)、对羟基苯甲酸乙酯(EtP)和对羟基苯甲酸丙酯(PrP)]的浓度。运用线性混合效应模型(LMEs)、多源信息模型和广义线性模型分析个体三季不同滞后天数中,尿酚类化合物与甘油三酯(TG)、总胆固醇(TC)、高密度脂蛋白胆固醇(HDL-C)、低密度脂蛋白胆固醇(LDL-C)、TG与HDL-C的比值(TG/HDL-C)之间的关联,并依据不同个体特征进行分层分析。[结果]经协变量和多重校正后,LMEs表明,在体检当天(Lag 0 d),与BPA低浓度组(

关键词：酚类化合物血脂线性混合效应模型成人固定群组研究

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果菜秸秆生物炭吸附设施土壤硝态氮性能与机制研究

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农业机械学报 2024年第5期55卷 386-394页

作者：杨慧华刘红叶张晗王仕娟翟合生魏珉张大龙山东农业大学园艺科学与工程学院泰安271018 山东省莘县农业农村局莘县252423

在农业生产中,过量偏施氮肥导致的硝酸盐富集是次生盐渍化、酸化等土壤障碍的重要诱因。生物炭因良好的吸附特性逐渐成为缓解盐渍化的土壤调理剂,但果菜秸秆生物炭对硝酸盐等离子的吸附研究鲜见报道。以甜椒、番茄和茄子3种果菜秸秆为... 详细信息

在农业生产中,过量偏施氮肥导致的硝酸盐富集是次生盐渍化、酸化等土壤障碍的重要诱因。生物炭因良好的吸附特性逐渐成为缓解盐渍化的土壤调理剂,但果菜秸秆生物炭对硝酸盐等离子的吸附研究鲜见报道。以甜椒、番茄和茄子3种果菜秸秆为原料热解制备生物炭,进行硝态氮吸附试验。通过扫描电镜(SEM)和傅里叶近红外光谱(FTIR)等技术对生物炭吸附前、后表面形貌、官能团等进行表征分析,利用吸附动力学模型和等温吸附模型等进行拟合分析,综合模型参数和形貌表征解析果菜秸秆生物炭的吸附性能和机制。研究结果表明,3种果菜秸秆生物炭对硝态氮均具有一定吸附能力,茄子秸秆生物炭吸附能力最强,最大理论平衡吸附量为114.788 mg/g,其次为番茄(29.736 mg/g)和甜椒(9.759 mg/g);茄子和甜椒秸秆生物炭吸附性能优于玉米、稻壳等大田作物秸秆生物炭,吸附过程符合准二级动力学模型,受化学键吸附、表面吸附和内扩散吸附过程的控制,番茄秸秆生物炭吸附过程符合准一级动力学模型,主要为物理吸附;FTIR分析显示,3种生物炭均含有羟基、甲基、亚甲基、羧基和羰基官能团,除此之外,甜椒和茄子秸秆生物炭还含有醚键,番茄秸秆生物炭含有醇羟基。因此,3种果菜秸秆生物炭对硝态氮均具有吸附能力,茄子秸秆生物炭吸附能力最强,受孔隙填充、官能团和络合作用等多种理化机制的影响,具有消减土壤次生盐渍化的潜力。本研究对盐渍化土壤修复和果菜秸秆资源化利用具有理论意义。

关键词：果菜秸秆生物炭硝态氮动力学等温吸附模型设施土壤次生盐渍化

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Drug discrimination of Near Infrared spectroscopy based on the scaled convex hull classifier

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Journal of Innovative Optical Health Sciences 2014年第4期7卷 101-110页

作者： Zhenbing Liu Shujie Jiang huihua yang School of Electronic Engineering and AutomationGuilin University of Electronic Technology No.1 Jinji Road GuilinP.R.China

Near Infrared spectroscopy(NIRS)has been widely used in the discrimination(classification)of pharmaceutical *** real applications,however,the class imbalance of the drug samples,i.e.,the number of one drug sample may be much larger than the number of the other drugs,deceasesdrastically the discrimination performance of the classification *** address this classimbalance problem,a new computational method--the scaled convex hull(SCH)-basedmaximum margin classifier is proposed in this *** a suitable selection of the reductionfactor of the SCHs generated by the two classes of drug samples,respectively,the maximalmargin classifier bet ween SCHs can be constructed which can obtain good classification *** an optimization of the parameters involved in the modeling by Cuckoo Search,a satisfied model is achieved for the classification of the *** experiments on spectra samplesproduced by a pharmaceutical company show that the proposed method is more effective androbust than the existing ones.

关键词： Drug classification Near Infrared spectroscopy class imbalance scaled convex hulls

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基于机器视觉的分切刀具豁口检测

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智能计算机与应用 2024年第3期14卷 147-153页

作者：宋明望赵文义杨牧杨辉华桂林电子科技大学计算机与信息安全学院广西桂林541004 北京邮电大学人工智能学院北京100876 钛玛科(北京)工业科技有限公司北京100176

新能源电池极片毛刺是导致电池短路爆炸的重要因素之一,其主要是生产过程中使用带有豁口的刀具进行分切导致,因此本文研究分切刀具豁口的高精度、快速检测算法,用于检测分切刀具豁口。首先,本文依托于一套分切刀具图像采集装置采集分切... 详细信息

新能源电池极片毛刺是导致电池短路爆炸的重要因素之一,其主要是生产过程中使用带有豁口的刀具进行分切导致,因此本文研究分切刀具豁口的高精度、快速检测算法,用于检测分切刀具豁口。首先,本文依托于一套分切刀具图像采集装置采集分切刀具边缘显微图像;其次,在刀具边缘提取方面,提出了一种改进的Zernike矩亚像素边缘算子,实现亚像素级的边缘提取,有效保留分切刀具刃口边缘特征;最后,在刀具豁口检测方面,提出了一种基于四次Hermite插值的豁口检测算子,通过预推理分切刀具初始边缘,实现分切刀具豁口检测。将本文提出的算法与PreNet检测算法和基于三次样条插值的检测算法进行对比实验,实验结果表明:本文算法实现了亚像素级别分切刀具边缘提取,速度更快,分切刀具豁口检测准确度更高。

关键词： Zernike矩边缘提取 Hermite插值豁口检测

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自噬在人肝癌细胞Huh7对仑伐替尼耐药中的调节作用

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中国药房 2024年第8期35卷 961-966页

作者：陈大红吴亚菲刁文婧杨蕙华毛鹏娟李琴上海交通大学医学院附属第一人民医院临床药学科上海200080

目的研究自噬在人肝癌细胞Huh7对仑伐替尼耐药中的调节作用。方法以人肝癌细胞Huh7为对象,采用低浓度逐渐递增联合长期给药的方式构建仑伐替尼耐药细胞模型Huh7-LR,以CCK-8实验和流式细胞术检测亲本细胞Huh7及耐药细胞Huh7-LR对仑伐替... 详细信息

目的研究自噬在人肝癌细胞Huh7对仑伐替尼耐药中的调节作用。方法以人肝癌细胞Huh7为对象,采用低浓度逐渐递增联合长期给药的方式构建仑伐替尼耐药细胞模型Huh7-LR,以CCK-8实验和流式细胞术检测亲本细胞Huh7及耐药细胞Huh7-LR对仑伐替尼的敏感性,以Westernblot实验和GFP-mCherry-LC3质粒转染实验分别检测细胞中自噬效应蛋白Beclin-1、自噬接头蛋白sequestosome1(又名p62)、微管相关蛋白1轻链3(LC3)的表达水平和细胞自噬水平。通过饥饿诱导构建自噬激活细胞模型,以Westernblot实验和GFP-mCherry-LC3质粒转染实验分别检测细胞中p62蛋白表达水平和细胞自噬水平,以流式细胞术检测自噬激活对仑伐替尼敏感性的影响。结果与亲本细胞相比,Huh7-LR细胞的耐药指数为6.2,其p62蛋白的表达水平显著升高,凋亡率、Beclin-1蛋白的表达水平和LC3Ⅱ/LC3Ⅰ比值均显著降低(P<0.05或P<0.01),自噬水平有所下降。自噬激活可显著升高Huh7-LR细胞中p62蛋白的表达水平(P<0.05)和自噬水平,并显著升高其凋亡率(P<0.05)。结论自噬参与了仑伐替尼耐药,激活自噬可一定程度逆转肝癌细胞对仑伐替尼耐药。

关键词：自噬仑伐替尼肝癌细胞耐药

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A Method for Crude Oil Selection and Blending Optimization Based on Improved Cuckoo Search Algorithm

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China Petroleum Processing & Petrochemical Technology 2014年第4期16卷 70-78页

作者： yang huihua Ma Wei Zhang Xiaofeng Li Hu Tian Songbai Guangxi Experiment Center of Information Science Guilin University of Electronic Technology Research Institute of Petroleum Processing SINOPEC

Refineries often need to find similar crude oil to replace the scarce crude oil for stabilizing the feedstock property. We introduced the method for calculation of crude blended properties firstly, and then created a crude oil selection and blending optimization model based on the data of crude oil property. The model is a mixed-integer nonlinear programming(MINLP) with constraints, and the target is to maximize the similarity between the blended crude oil and the objective crude oil. Furthermore, the model takes into account the selection of crude oils and their blending ratios simultaneously, and transforms the problem of looking for similar crude oil into the crude oil selection and blending optimization problem. We applied the Improved Cuckoo Search(ICS) algorithm to solving the model. Through the simulations, ICS was compared with the genetic algorithm, the particle swarm optimization algorithm and the CPLEX solver. The results show that ICS has very good optimization efficiency. The blending solution can provide a reference for refineries to find the similar crude oil. And the method proposed can also give some references to selection and blending optimization of other materials.

关键词： crude oil similarity crude oil selection blending optimization mixed-integer nonlinear programming CuckooSearch algorithm

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SpectraTr:A novel deep learning model for qualitative analysis of drug spectroscopy based on transformer structure

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Journal of Innovative Optical Health Sciences 2022年第3期15卷 107-117页

作者： Pengyou Fu Yue Wen Yuke Zhang Lingqiao Li Yanchun Feng Lihui Yin huihua yang School of Computer Science and Information Security Guilin University of Electronic Technology 1 Jinji Road Guilin 541004P.R.China School of Artīcial Intelligence Beijing University of Posts and Telecommunications 10 Xitucheng Road Beijing 100876P.R.China School of International Beijing University of Posts and Telecommunications 10 Xitucheng Road Beijing 100876P.R.China National Institutes for Food and Drug Control 10 Tiantanxili Road Beijing 100050P.R.China

The drug supervision methods based on near-infrared spectroscopy analysis are heavily dependent on the chemometrics model which characterizes the relationship between spectral data and drug *** preliminary application of convolution neural network in spectral analysis demonstrates excellent end-to-end prediction ability,but it is sensitive to the hyper-parameters of the *** transformer is a deep-learning model based on self-attention mechanism that compares convolutional neural networks(CNNs)in predictive performance and has an easy-todesign model ***,a novel calibration model named SpectraTr,based on the transformer structure,is proposed and used for the qualitative analysis of drug *** experimental results of seven classes of drug and 18 classes of drug show that the proposed SpectraTr model can automatically extract features from a huge number of spectra,is not dependent on pre-processing algorithms,and is insensitive to model *** the ratio of the training set to test set is 8:2,the prediction accuracy of the SpectraTr model reaches 100%and 99.52%,respectively,which outperforms PLS DA,SVM,SAE,and *** model is also tested on a public drug data set,and achieved classification accuracy of 96.97%without preprocessing algorithm,which is 34.85%,28.28%,5.05%,and 2.73%higher than PLS DA,SVM,SAE,and CNN,*** research shows that the SpectraTr model performs exceptionally well in spectral analysis and is expected to be a novel deep calibration model after Autoencoder networks(AEs)and CNN.

关键词： Near-infrared spectroscopy analysis drug supervision transformer structure deep learning chemometrics

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Application of near-infrared spectroscopy for the rapid analysis of Lonicerae Japonicae Flos solution extracted by water

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Journal of Innovative Optical Health Sciences 2014年第4期7卷 42-50页

作者： Xue Xiao Jinfang Ma Fahuan Ge Xiangdong Zhang huihua yang Qionghin Liang Yiming Wang Guoan Luo Nansha Research Institute Sun Yat-Sen.University Guang zhou 511458 P.R.China Department of Chemistry Tsinghua University Beijing 100084P.R.China

A rapid quantitative analytical method for three components of Lonicerae Japornicae Flos solution(Lonicera Japonica Thumb.)extracted by water was developed using near-infrared(NIR)spectroscopy and the partial least-squares(PLS)*** NIR spectra of 81 samples collected from a production line were *** concentrations of secologanic acid,chlorogenicacid and galuteolin were detemmined by using high-performance liquid chromatography-diodearray detection as the reference *** pretreatment methods for the NIR spectra wereusedi during PLS *** most appropriate latent variable number of the PLS factor wasselected based on the standard error of cross-validation(SECV).The performance of the finalPLS models was evaluated according to SECV,standard error of predliction(SEP)and deter-mination coeficient(R^(2)).The compounds secologanic acid,chlorogenic acid and galuteolin hadSEP values of 0.030,0.061 and 1.668μg/mL,respectively and R^(2) values over *** workshows that NIR spectroscopy is a rapid and convenient method for the analysis of LoniceraeJaponicae Flos solution extracted by *** proposed method can help in the application ofprocs analytical technology in the pha maceutical industry,particularly in tra ditional Chinesemedicine injections.

关键词： Lonicerae Japonicae Flos Qingkailing injection near-infrared partial least-squares rapid analysis

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Multi-manufacturer drug identification based on near infrared spectroscopy and deep transfer learning

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Journal of Innovative Optical Health Sciences 2020年第4期3卷 39-50页

作者： Lingqiao Li Xipeng Pan Wenli Chen Manman Wei Yanchun Feng Lihui Yin Changqin Hu huihua yang School of Automation Beijing University of Posts and Telecommunications 10 Xitucheng Road Beijing 100876P.R.China School of Computer Science and Information Security Guilin University of Electronic Technology 1 Jinji Road Guilin 541004P.R.China National Institutes for Food and Drug Control 10 Tiantanxili Road Beijing 100050 P.R.China

Near infrared(NIR)spectrum analysis technology has outstanding advantages such as rapid,nondestructive,pollution-free,and is widely used in food,pharmaceutical,petrochemical,agricultural products production and testing *** neural network(CNN)is one of the most successful methods in big data analysis because of its powerful feature ex-traction and abstraction ability,and it is especially suitable for solving multi-classification ***-based transfer learning is a machine learning technique,which migrates para-meters of trained model to the new one to improve the *** transfer learning strategy can speed up the learning efficiency of the model instead of learning from *** view of the difficulty in acquisition of drug NIR spectral data and high labeling cost,this paper proposes three simple but very effective transfer learning methods for multi-manufacturer identification of drugs based on one-dimensional *** with the original CNN,the transfer learning method can achieve better classification performance with fewer NIR spectral data,which greatly reduces the dependence on labeled NIR spectral *** the same time,this paper also compares and discusses three different transfer learning methods,and selects the most suitable transfer learning model for drug NIR spectral data *** with the current popular methods,such as SVM,BP,AE and ELM,the proposed method achieves higher classification accuracy and scalability in multi-variety and multi-manufacturer NIR spectrum classification experiments.

关键词： Near-infrared spectroscopy transfer learning drug identification multi-manufacturer

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