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Modeling the Long-term Antibody Response and Duration of Immune Protection Induced by an Inactivated,Preservative-free Hepatitis A Vaccine(Healive)in Children

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Biomedical and Environmental Sciences 2020年第7期33卷 484-492页

作者： YU Yong Pei CHEN jiang Ting jiang zhi wei WANG Ling YU Cheng Kai YAN Xiao Yan YAO Chen XIA Jie Lai College of Military Preventive Medicine the Fourth Military Medical UniversityXi'an 710032ShaanxiChina Peking University^Clinical Research Institute Peking University Health Science CenterBeijing 100191China Sinovac Biotech Beijing 100089China Beijing Keytech Statistical Consulting Beijing 100020China

Objective Long-term seroprotection via the hepatitis A vaccine is essential for the prevention of disease from the hepatitis A virus(HAV).Due to documented difficulties during decade-long follow-ups after receiving vaccines,statistical-modeling approaches have been applied to predict the duration of immune protection.Methods Based on five-year follow-up data from a randomized positive-controlled trial among Chinese children(1–8 years old)following a 0,6 months vaccination schedule,a power-law model accounting for the kinetics of B-cell turnover,as well as a modified power-law model considering a memory-B-cell subpopulation,were fitted to predict the long-term immune responses induced by HAV vaccination(Healive or Havrix).Anti-HAV levels of each individual and seroconversion rates up to 30 years after vaccination were predicted.Results A total of 375 participants who completed the two-dose vaccination were included in the analysis.Both models predicted that,over a life-long period,participants vaccinated with Healive would have close but slightly higher antibody titers than those of participants vaccinated with Havrix.Additionally,consistent with previous studies,more than 90%of participants were predicted to maintain seroconversion for at least 30 years.Moreover,the modified power-law model predicted that the antibody titers would reach a plateau level after nearly 15 years post-vaccination.Conclusions Based on the results of our modeling,Healive may adequately induce long-term immune responses following a 0,6 months vaccination schedule in children via induction of memory B cells to provide stable and durable immune protection.

关键词： Hepatitis A Inactivated hepatitis A vaccine Modeling Antibody persistence Long-term follow-up

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Assimilation of temporal-spatial leaf area index into the CERES-Wheat model with ensemble Kalman filter and uncertainty assessment for improving winter wheat yield estimation

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Journal of Integrative Agriculture 2017年第10期16卷 2283-2299页

作者： LI He jiang zhi-wei CHEN Zhong-xin REN Jian-qiang LIU Bin Hasituya Key Laboratory of Agricultural Remote Sensing Ministry of Agriculture/Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural Sciences National Meteorological Information Center China Meteorological Administration

To accurately estimate winter wheat yields and analyze the uncertainty in crop model data assimilations, winter wheat yield estimates were obtained by assimilating measured or remotely sensed leaf area index （LAI） values. The performances of the calibrated crop environment resource synthesis for wheat （CERES-Wheat） model for two different assimilation scenarios were compared by employing ensemble Kalman filter （EnKF）-based strategies. The uncertainty factors of the crop model data assimilation was analyzed by considering the observation errors, assimilation stages and temporal-spatial scales. Overalll the results indicated a better yield estimate performance when the EnKF-based strategy was used to comprehen- sively consider several factors in the initial conditions and observations. When using this strategy, an adjusted coefficients of determination （R2） of 0.84, a root mean square error （RMSE） of 323 kg ha-1, and a relative errors （RE） of 4.15% were obtained at the field plot scale and an R2 of 0.81, an RMSE of 362 kg ha-1, and an RE of 4.52% were obtained at the pixel scale of 30 mx30 m. With increasing observation errors, the accuracy of the yield estimates obviously decreased, but an acceptable estimate was observed when the observation errors were within 20%. Winter wheat yield estimates could be improved significantly by assimilating observations from the middle to the end of the crop growing seasons. With decreasing assimilation frequency and pixel resolution, the accuracy of the crop yield estimates decreased; however, the computation time decreased. It is important to consider reasonable temporal-spatial scales and assimilation stages to obtain tradeoffs between accuracy and computation time, especially in operational systems used for regional crop yield estimates.

关键词： winter wheat yield estimates crop model data assimilation ensemble Kalman filter uncertainty leaf area index

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Comparative analysis of GF-1,HJ-1,and Landsat-8 data for estimating the leaf area index of winter wheat

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Journal of Integrative Agriculture 2017年第2期16卷 266-285页

作者： LI He CHEN Zhong-xin jiang zhi-wei WU Wen-bin REN Jian-qiang LIU Bin Tuya Hasi Key Laboratory of Agri-informatics Ministry of Agriculture/Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural Sciences National Meteorological Information Center China Meteorological Administration

Using simultaneously collected remote sensing data and field measurements, this study firstly assessed the consistency and applicability of China high-resolution earth observation system satellite 1 （GF-1） wide field of view （WFV） camera, environment and disaster monitoring and forecasting satellite （H J-l） charge coupled device （CCD）, and Landsat-8 opera- tional land imager （OLI） data for estimating the leaf area index （LAI） of winter wheat via reflectance and vegetation indices （VIs）. The accuracies of these LAI estimates were then assessed through comparison with an empirical model and the PROSAIL radiative transfer model. The effects of radiation calibration, spectral response functions, and spatial resolution on discrepancies in the LAI estimates between the different sensors were also analyzed. The results yielded the following observations：（1） The correlation between reflectance from different sensors is relative good, with the adjusted coefficients of determination （R2） between 0.375 to 0.818. The differences in reflectance are ranging from 0.002 to 0.054. The correlation between VIs from different sensors is high with the R2 between 0.729 and 0.933. The differences in the VIs are ranging from 0.07 to 0.156. These results show the three sensors＇ images can all be used for cross calibration of the reflectance and VIs. （2） The four VIs from the three sensors are all demonstrated to be highly correlated with LAI （R2 between 0.703 and 0.849）. The linear models associated with the 2-band enhanced vegetation index （EVI2）, which feature the highest R2 （higher than 0.746） and the lowest root mean square errors （RMSE）（less than 0.21）, were selected to estimate the winter wheat LAI. The accuracy of the estimated LAI from Landsat-8 was the highest, with the relative errors （RE） of 2.18% and an RMSE of 0.13, while the H J-1 was the lowest, with the RE of 2.43% and the RMSE of 0.15. （3） The inversion errors in the different sensors＇ LAI estimates using the PROSAIL model are small. The accuracy of the GF-1 is the hig

关键词： GF-1 WFV H J-1 CCD Landsat-80LI leaf area index PROSAIL vegetation indices

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人工湿地植物对药品和个人护理品的去除机制与影响因素

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湿地科学与管理 2024年第3期20卷 2-7,19页

作者：杨成段金江冯媛橼李鸿栎蒋芷苇张涵陈孟立西南交通大学环境科学与工程学院四川成都611700

人工湿地具有良好的PPCPs去除效能,湿地植物在其中发挥了重要作用,大多数已发表的综述研究均集中在填料和微生物的作用上,缺乏湿地植物对PPCPs去除机制的报道。本研究系统总结了人工湿地植物在PPCPs去除中的作用,包括植物根系的吸收和... 详细信息

人工湿地具有良好的PPCPs去除效能,湿地植物在其中发挥了重要作用,大多数已发表的综述研究均集中在填料和微生物的作用上,缺乏湿地植物对PPCPs去除机制的报道。本研究系统总结了人工湿地植物在PPCPs去除中的作用,包括植物根系的吸收和降解、为微生物提供适宜的定殖环境以及通过植物根系分泌物塑造根际微生物群落,增强PPCPs的去除效率。文章解析了人工湿地植物去除PPCPs的影响因素,包括温度、氧化还原电位和pH值等,并提出了未来的研究可集中于湿地植物的不同组织对PPCPs的去除作用以及量化每个组织的贡献率,这对于全面揭示人工湿地对PPCPs的去除机制具有重要意义。

关键词：人工湿地 PPCPs 植物去除机理影响因素

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High Speed Sintering:Assessing the Influence of Energy Input on Microstructure and Mechanical Properties of Polyether Block Amide(PEBA)Parts

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Chinese Journal of Polymer Science 2024年第5期42卷 675-682,I0004,I0010页

作者： jiang-Tao Sun zhi-Yong Fan Yi-wei Mao wei Li wei Zhu Dao-Sheng Cai Qing-Song wei State Key Laboratory of Materials Processing and Die&Mould Technology Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan430074China National Engineering Research Centre for High Efficiency Grinding Hunan UniversityChangsha410082China Wuhan EasyMFG Technology CO. LTDWuhan430074China

High speed sintering,a new powder-bed fusion additive manufacturing technology,utilizes infrared lights(IR)to intensely heat and melt polymer powders.The presence of defects such as porosity,which is associated with particle coalescence,is highly dependdent on the level of energy input.This study investigate the influcence of energy input on porosity and its subsequent effects on the mechanical properties and microstructures of PEBA parts.The parts were manufactured with a variety of lamp powers,resulting in a range of energy input levels spanning from low to high.Subsequebtly,they underwent testing using Archimedes’method,followed by tensile testing.The porosity,mechanical characteristics,and energy input exhibit a strong correlation;inadequate energy input was the primary cause of pore formation.Using the reduced IR light power resulted in the following outcomes:porosity,ultimate tensile strength,and elongation of 1.37%,7.6 MPa,and 194.2%,respectively.When the energy input was further increased,the porosity was reduced to as low as 0.05%and the ultimate tensile strength and elongation were increased to their peak values of 233.8%and 9.1 MPa,respectively.

关键词： High speed sintering Additive manufacturing Energy input Powder bed fusion PEBA

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Development and validation of a machine learning-based early prediction model for massive intraoperative bleeding in patients with primary hepatic malignancies

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World Journal of Gastrointestinal Oncology 2024年第1期16卷 90-101页

作者： Jin Li Yu-Ming Jia zhi-Lei Zhang Cheng-Yu Liu Zhan-Wu jiang zhi-wei Hao Li Peng Department of Hepatological Surgery The Fourth Hospital of Hebei Medical UniversityShijiazhuang 050011Hebei ProvinceChina Department of General Surgery II Baoding First Central HospitalBaoding 071000Hebei ProvinceChina

BACKGROUND Surgical resection remains the primary treatment for hepatic malignancies,and intraoperative bleeding is associated with a significantly increased risk of death.Therefore,accurate prediction of intraoperative bleeding risk in patients with hepatic malignancies is essential to preventing bleeding in advance and providing safer and more effective treatment.AIM To develop a predictive model for intraoperative bleeding in primary hepatic malignancy patients for improving surgical planning and outcomes.METHODS The retrospective analysis enrolled patients diagnosed with primary hepatic malignancies who underwent surgery at the Hepatobiliary Surgery Department of the Fourth Hospital of Hebei Medical University between 2010 and 2020.Logistic regression analysis was performed to identify potential risk factors for intraoperative bleeding.A prediction model was developed using Python programming language,and its accuracy was evaluated using receiver operating characteristic(ROC)curve analysis.RESULTS Among 406 primary liver cancer patients,16.0%(65/406)suffered massive intraoperative bleeding.Logistic regression analysis identified four variables as associated with intraoperative bleeding in these patients:ascites[odds ratio(OR):22.839;P<0.05],history of alcohol consumption(OR:2.950;P<0.015),TNM staging(OR:2.441;P<0.001),and albumin-bilirubin score(OR:2.361;P<0.001).These variables were used to construct the prediction model.The 406 patients were randomly assigned to a training set(70%)and a prediction set(30%).The area under the ROC curve values for the model’s ability to predict intraoperative bleeding were 0.844 in the training set and 0.80 in the prediction set.CONCLUSION The developed and validated model predicts significant intraoperative blood loss in primary hepatic malignancies using four preoperative clinical factors by considering four preoperative clinical factors:ascites,history of alcohol consumption,TNM staging,and albumin-bilirubin score.Consequently,this model holds promise for enhancing individ

关键词： Primary liver cancer Intraoperative bleeding Machine learning Model

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Patients Administered Neoadjuvant Chemotherapy Could be Enrolled into an Enhanced Recovery after Surgery Program for Locally Advanced Gastric Cancer

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Chinese Medical Journal 2018年第4期131卷 413-419页

作者： Jian Zhao Gang Wang zhi-wei jiang Chuan-wei jiang jiang Liu Can-Can Xia Jie-Shou Li Research Institute of General Surgery Jinling Hospital Medical School of Nanjing University Nanjing Jiangsu 210002 China

Background： Most studies on enhanced recovery after surgery （ERAS） for gastric cancer exclude patients who received neoadjuvant chemotherapy. Here, we aimed to evaluate whether patients who received neoadjuvant chemotherapy can be enrolled into the ERAS program for locally advanced gastric cancer. Methods： From April 2015 to July 2017, 114 patients who received neoadjuvant chemotherapy for locally advanced gastric cancer were randomized into ERAS and standard care （SC） groups. Postoperative length of stay, complications, bowel function, and nutritional status were recorded. Results： The postoperative length of stay of the ERAS group was shorter compared with that of the SC group （5.9 ± 5.6 vs. 8.1 ± 5.3 days, P=0.037）.The postoperative complication rate was 9.3% in the ERAS group and 11.5% in the SC group（P=0.700）.The time to first flatus （2.7 ± 2.0 vs. 4.5 ± 4.6 days, P = 0.010） and time to a semi-liquid diet （3.2 ± 2.1 vs. 6.3 ± 4.9 days, P 〈 0.001） in the ERAS group were shorter compared with those in the SC group. On the 10thday after surgery, the values of weight, total protein, albumin, and prealbumin of the ERAS group were lower compared with those of the SC group. Conclusions： Patients who received neoadjuvant chemotherapy could be enrolled into ERAS programs for locally advanced gastric cancer. The nutritional status of these patients was not adversely affected.

关键词： Advanced Gastric Cancer Enhanced Recovery after Surgery Gastrectomy Length of Stay Neoadjuvant Chemotherapy

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Highly homogeneous zero-index metamaterials make devices more compact and perform better

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Light(Science & Applications) 2024年第5期13卷 806-807页

作者： wei-Xiang jiang State Key Laboratory of Milimeter Waves School of Information Science and EngineeringSoutheast University210096 NanjingChina

A highly homogeneous microwave zero-index metamaterial based on high-permittivity SrTiO3 ceramics is demonstrated to realize the small-aperture high-directivity antenna.Such a novel technique is a remarkable step forw... 详细信息

关键词： ceramics SrTiO3 Highly

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Classifying Chinese Medicine Constitution Using Multimodal Deep-Learning Model

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Chinese Journal of Integrative Medicine 2024年第2期30卷 163-170页

作者： GU Tian-yu YAN Zhuang-zhi jiang Jie-hui School of Communication&Information Engineering Shanghai UniversityShanghai(200444)China School of Life Science Shanghai UniversityShanghai(200444)China

Objective:To develop a multimodal deep-learning model for classifying Chinese medicine constitution,i.e.,the balanced and unbalanced constitutions,based on inspection of tongue and face images,pulse waves from palpation,and health information from a total of 540 subjects.Methods:This study data consisted of tongue and face images,pulse waves obtained by palpation,and health information,including personal information,life habits,medical history,and current symptoms,from 540 subjects(202 males and 338 females).Convolutional neural networks,recurrent neural networks,and fully connected neural networks were used to extract deep features from the data.Feature fusion and decision fusion models were constructed for the multimodal data.Results:The optimal models for tongue and face images,pulse waves and health information were ResNet18,Gate Recurrent Unit,and entity embedding,respectively.Feature fusion was superior to decision fusion.The multimodal analysis revealed that multimodal data compensated for the loss of information from a single mode,resulting in improved classification performance.Conclusions:Multimodal data fusion can supplement single model information and improve classification performance.Our research underscores the effectiveness of multimodal deep learning technology to identify body constitution for modernizing and improving the intelligent application of Chinese medicine.

关键词： Chinese medicine constitution classification multimodal deep learning tongue image face image pulsewave health information

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Uridine diphosphate glucuronosyltransferase 1A1 prevents the progression of liver injury

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World Journal of Gastroenterology 2024年第9期30卷 1189-1212页

作者： Jin-Lian jiang Yi-Yang Zhou wei-wei Zhong Lin-Yan Luo Si-Ying Liu Xiao-Yu Xie Mao-Yuan Mu zhi-Gang jiang Yuan Xue Jian Zhang Yi-Huai He Department of Infectious Diseases Affiliated Hospital of Zunyi Medical UniversityZunyi 563000Guizhou ProvinceChina Department of Infectious Diseases Jingmen Central HospitalJingmen 448000Hubei ProvinceChina Department of Respiratory Medicine Anshun People’s HospitalAnshun 561099Guizhou ProvinceChina Department of General Practice Affiliated Hospital of Zunyi Medical UniversityZunyi 563000Guizhou ProvinceChina Department of Intervention Radiology Affiliated Hospital of Zunyi Medical UniversityZunyi 563000Guizhou ProvinceChina School of Public Health Zunyi Medical UniversityZunyi 563099Guizhou ProvinceChina Department of Liver Diseases Third People’s Hospital of ChangzhouChangzhou 213000Jiangsu ProvinceChina Department of Digestion Dafang County People’s HospitalBijie 551600Guizhou ProvinceChina

BACKGROUND Uridine diphosphate glucuronosyltransferase 1A1(UGT1A1)plays a crucial role in metabolizing and detoxifying endogenous and exogenous substances.However,its contribution to the progression of liver damage remains unclear.AIM To determine the role and mechanism of UGT1A1 in liver damage progression.METHODS We investigated the relationship between UGT1A1 expression and liver injury through clinical research.Additionally,the impact and mechanism of UGT1A1 on the progression of liver injury was analyzed through a mouse model study.RESULTS Patients with UGT1A1 gene mutations showed varying degrees of liver damage,while patients with acute-onchronic liver failure(ACLF)exhibited relatively reduced levels of UGT1A1 protein in the liver as compared to patients with chronic hepatitis.This suggests that low UGT1A1 levels may be associated with the progression of liver damage.In mouse models of liver injury induced by carbon tetrachloride(CCl_(4))and concanavalin A(ConA),the hepatic levels of UGT1A1 protein were found to be increased.In mice with lipopolysaccharide or liver steatosis-mediated liver-injury progression,the hepatic protein levels of UGT1A1 were decreased,which is consistent with the observations in patients with ACLF.UGT1A1 knockout exacerbated CCl_(4)-and ConA-induced liver injury,hepatocyte apoptosis and necroptosis in mice,intensified hepatocyte endoplasmic reticulum(ER)stress and oxidative stress,and disrupted lipid metabolism.CONCLUSION UGT1A1 is upregulated as a compensatory response during liver injury,and interference with this upregulation process may worsen liver injury.UGT1A1 reduces ER stress,oxidative stress,and lipid metabolism disorder,thereby mitigating hepatocyte apoptosis and necroptosis.

关键词： Uridine diphosphate glucuronosyltransferase 1A1 Liver injury progression Endoplasmic reticulum stress Oxidative stress Lipid metabolism disorders

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