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predictive ability of the SYNergy Between Percutaneous Coronary Intervention with TAXus and Cardiac Surgery Score Ⅱ for Long-term Mortality in Patients with Three-vessel Coronary Artery Disease Undergoing Percutaneous Coronary Intervention Treated

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Chinese Medical Journal 2015年第16期128卷 2176-2182页

作者： Ji-Qiang He Xian-Peng Yu Cheng Peng Quan Li Ya-Wei Luo Yue-Chun Gao Xiao-Ling Zhang Chang-Yan Wu Hua Zhao Yu-Chen Zhang Jing-Hua Liu Shu-Zheng Lyu Fang Chen Department of Cardiology Beijing Anzhen Hospital Capital Medical University and Institution of Beijing Heart Lung and Vascular Disease Beijing 100029 China

Background：The SYNergy between percutaneous coronary intervention with TAXus and cardiac surgery Score Ⅱ （SS-Ⅱ） can well predict 4-year mortality in patients with complex coronary artery disease （CAD）,and guide decision-making between coronary artery bypass graft surgery and percutaneous coronary intervention （PCI）.However,there is lack of data regarding the utility of the SS-Ⅱ in patients with three-vessel CAD undergoing PCI treated with second-generation drug-eluting stents （DES）.The purpose of the present study was to evaluate the ability of the SS-Ⅱ to predict long-term mortality in patients with three-vessel CAD undergoing PCI with second-generation DES.Methods：Totally,573 consecutive patients with de novo three-vessel CAD who underwent PCI with second-generation DES were retrospectively studied.According to the tertiles of the SS-Ⅱ,the patients were divided into three groups：The lowest SS-Ⅱ tertile （SS-Ⅱ ≤20）,intermediate SS-Ⅱ tertile （SS-Ⅱ of 21-31）,and the highest SS-Ⅱ tertile （SS-Ⅱ ≥32）.The survival curves of the different groups were estimated by the Kaplan-Meier method.Univariate and multivariate Cox proportional hazard regression analyses were performed to evaluate the relationship between the SS-Ⅱ and 5-year mortality.The performance of the SS-Ⅱ with respect to predicting the rate of mortality was studied by calculating the area under the receiver operator characteristic （ROC） curve.The predictive ability of the SS-Ⅱ for 5-year mortality was evaluated and compared with the SS alone.Results：The overall SS-Ⅱ was 27.6 ± 9.0.Among patients in the lowest,intermediate and the highest SS-Ⅱ tertiles,the 5-year rates of mortality were 1.6%,3.2%,and 8.6%,respectively （P =0.003）;the cardiac mortality rates were 0.5%,1.9%,and 5.2%,respectively （P =0.014）.By multivariable analysis,adjusting for the potential confounders,the SS-Ⅱ was an independent predictor of 5-year mortality （hazard ratio：2.45,95% confidence interval：1.38-4.36;P=0.002）.The SS-Ⅱ demonstrated a higher predictive accuracy for 5-year mortality comp

关键词： Mortality Percutaneous Coronary Intervention predictive ability Second-generation Drug-eluting Stents SYNTAX Score II Three-vessel Coronary Artery Disease

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A promising resilience parameter for breeding:the use of weight and feed trajectories in growing pigs

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Journal of Animal Science and Biotechnology 2023年第6期14卷 2363-2382页

作者： Wim Gorssen Carmen Winters Roel Meyermans Lea Chapard Katrijn Hooyberghs Steven Janssens Abe Huisman Katrijn Peeters Han Mulder Nadine Buys Center for Animal Breeding and Genetics Department of BiosystemsKU LeuvenKasteelpark Arenberg 30–Box 24723001 LeuvenBelgium. Laboratory for Biological Psychology KU LeuvenTiensestraat 102‑Box 37143000 LeuvenBelgium. Hendrix Genetics P.O.Box 1145830 AC BoxmeerThe Netherlands. Research Animal Breeding and Genomics Wageningen UniversityP.O.Box 3386700 AH Wageningenthe Netherlands

Background Increasing resilience is a priority in modern pig breeding.Recent research shows that general resilience can be quantified via variability in longitudinal data.The collection of such longitudinal data on weight,feed intake and feeding behaviour in pigs has been facilitated by the development of technologies such as automated feeding stations.The goal of this study was to investigate resilience traits,which were estimated as deviations from longitudinal weight,feed intake and feeding behaviour data during the finishing phase.A dataset with 324,207 records between the age of 95 and 155 days on 5,939 Pietrain pigs with known pedigree and genomic information was used.We provided guidelines for a rigid quality control of longitudinal body weight data,as we found that outliers can significantly affect results.Gompertz growth curve analysis,linear modelling and trajectory analyses were used for quantifying resilience traits.Results To our knowledge,this is the first study comparing resilience traits from longitudinal body weight,feed intake and feeding behaviour data in pigs.We demonstrated that the resilience traits are lowly to moderately heritable for deviations in body weight(h2=2.9%–20.2%),in feed intake(9.4%–23.3%)and in feeding behaviour(16.2%–28.3%).Additionally,these traits have good predictive abilities in cross-validation analyses.Deviations in individual body weight and feed intake trajectories are highly correlated(rg=0.78)with low to moderate favourable genetic correlations with feed conversion ratio(rg=0.39–0.49).Lastly,we showed that some resilience traits,such as the natural logarithm of variances of observed versus predicted body weights(lnvarweight),are more robust to lower observation frequencies and are repeatable over three different time periods of the finishing phase.Conclusions Our results will help future studies investigating resilience traits and resilience-related traits.Moreover,our study provides first results on standardization of quality control and efficient data sampling fro

关键词： Deviations Genetics Gompertz growth curves Heritability Pigs predictive ability Resilience Trajectory analysis

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Validation and evaluation of clinical prediction systems for first and repeated transarterial chemoembolization in unresectable hepatocellular carcinoma: A Chinese multicenter retrospective study

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World Journal of Gastroenterology 2020年第6期26卷 657-669页

作者： Zhe-Xuan Wang En-Xin Wang Wei Bai Dong-Dong Xia Wei Mu Jing Li Qiao-Yi Yang Ming Huang Guo-Hui Xu Jun-Hui Sun Hai-Liang Li Hui Zhao Jian-Bing Wu Shu-Fa Yang Jia-Ping Li Zi-Xiang Li Chun-Qing Zhang Xiao-Li Zhu Yan-Bo Zheng Qiu-He Wang Jing Li Jie Yuan Xiao-Mei Li Jing Niu Zhan-Xin Yin Jie-Lai Xia Dai-Ming Fan Guo-Hong Han China HCC-TACE Study Group Department of Liver Disease and Digestive Interventional Radiology National Clinical Research Center for Digestive Diseases and Xijing Hospital of Digestive DiseasesFourth Military Medical UniversityXi’an 710032Shaanxi ProvinceChina Department of Radiology the Southwest HospitalThird Military Medical UniversityChongqing 400037China Department of Hepatobiliary Surgery the Second Affiliated Hospital of Third Military Medical UniversityChongqing 400037China Department of Minimally Invasive International Therapy the Third Affiliated Hospital of Kunming UniversityTumor Hospital of Yunnan ProvinceKunming 650000Yunnan ProvinceChina Department of Interventional Radiology Tumor Hospital of Sichuan ProvinceChengdu 610000Sichuan ProvinceChina Department of Hepatobiliary and Pancreatic Interventional Cancer the First Affiliated HospitalSchool of MedicineZhejiang UniversityHangzhou 310003Zhejiang ProvinceChina Department of Interventional Radiology Henan Cancer Hospitalthe Affiliated Cancer Hospital of Zhengzhou UniversityZhengzhou 450008Henan ProvinceChina Department of Interventional Radiology the Affiliated Hospital of Nantong UniversityNantong 226001Jiangsu ProvinceChina Department of Oncology the Second Affiliated Hospital of Nanchang UniversityNanchang 330000Jiangxi ProvinceChina Department of Interventional Radiology the Affiliated Tumor Hospital of Xinjiang Medical UniversityUrumqi 830001Xinjiang Uygur Autonomous RegionChina Department of Interventional Radiology the First Affiliated Hospital of Sun Yatsen UniversityGuangzhou 510080Guangdong ProvinceChina Department of Interventional Medical Center the Affiliated Hospital of Qingdao UniversityQingdao 266000Shandong ProvinceChina Department of Gastroenterology and Hepatology Shandong Province Hospital affiliated to Shandong UniversityJinan 250021Shandong ProvinceChina Department of Interventional Radiology The First Affiliated Hospital of Soochow UniversitySuzhou 215006Jiangsu ProvinceChina Department of Interventional Radi

BACKGROUND The treatment outcome of transarterial chemoembolization(TACE)in unresectable hepatocellular carcinoma(HCC)varies greatly due to the clinical heterogeneity of the patients.Therefore,several prognostic systems have been proposed for risk stratification and candidate identification for first TACE and repeated TACE(re-TACE).AIM To investigate the correlations between prognostic systems and radiological response,compare the predictive abilities,and integrate them in sequence for outcome prediction.METHODS This nationwide multicenter retrospective cohort consisted of 1107 unresectable HCC patients in 15 Chinese tertiary hospitals from January 2010 to May 2016.The Hepatoma Arterial-embolization Prognostic(HAP)score system and its modified versions(mHAP,mHAP2 and mHAP3),as well as the six-and-twelve criteria were compared in terms of their correlations with radiological response and overall survival(OS)prediction for first TACE.The same analyses were conducted in 912 patients receiving re-TACE to evaluate the ART(assessment for re-treatment with TACE)and ABCR(alpha-fetoprotein,Barcelona Clinic Liver Cancer,Child-Pugh and Response)systems for post re-TACE survival(PRTS).RESULTS All the prognostic systems were correlated with radiological response achieved by first TACE,and the six-and-twelve criteria exhibited the highest correlation(Spearman R=0.39,P=0.026)and consistency(Kappa=0.14,P=0.019),with optimal performance by area under the receiver operating characteristic curve of 0.71[95%confidence interval(CI):0.68-0.74].With regard to the prediction of OS,the mHAP3 system identified patients with a favorable outcome with the highest concordance(C)-index of 0.60(95%CI:0.57-0.62)and the best area under the receiver operating characteristic curve at any time point during follow-up;whereas,PRTS was well-predicted by the ABCR system with a C-index of 0.61(95%CI:0.59-0.63),rather than ART.Finally,combining the mHAP3 and ABCR systems identified candidates suitable for TACE with an improved median PRTS of 36.6 mo,compa

关键词： Transarterial chemoembolization Hepatocellular carcinoma Prognostic system Radiological response Overall survival predictive ability

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Genomic selection: A breakthrough technology in rice breeding

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The Crop Journal 2021年第3期9卷 669-677页

作者： Yang Xu Kexin Ma Yue Zhao Xin Wang Kai Zhou Guangning Yu Cheng Li Pengcheng Li Zefeng Yang Chenwu Xu Shizhong Xu Key Laboratory of Plant Functional Genomics of the Ministry of Education/Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops College of AgricultureYangzhou UniversityYangzhou 225009JiangsuChina Department of Botany and Plant Sciences University of CaliforniaRiversideCA 92507USA

Rice(Oryza sativa)provides a staple food source for more than half the world population.However,the current pace of rice breeding in yield growth is insufficient to meet the food demand of the everincreasing global population.Genomic selection(GS)holds a great potential to accelerate breeding progress and is cost-effective via early selection before phenotypes are measured.Previous simulation and experimental studies have demonstrated the usefulness of GS in rice breeding.However,several affecting factors and limitations require careful consideration when performing GS.In this review,we summarize the major genetics and statistical factors affecting predictive performance as well as current progress in the application of GS to rice breeding.We also highlight effective strategies to increase the predictive ability of various models,including GS models incorporating functional markers,genotype by environment interactions,multiple traits,selection index,and multiple omic data.Finally,we envision that integrating GS with other advanced breeding technologies such as unmanned aerial vehicles and open-source breeding platforms will further improve the efficiency and reduce the cost of breeding.

关键词： Genomic selection Rice Hybrid predictive ability Model

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Genomic Prediction of Arsenic Tolerance and Grain Yield in Rice: Contribution of Trait-Specific Markers and Multi-Environment Models

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Rice science 2021年第3期28卷 268-278页

作者： Nourollah AHMADI Tuong-Vi CAO Julien FROUIN Gareth J.NORTON Adam H.PRICE Institute of Genetic Improvement and Adaptation of Mediterranean and Tropical Plants French Agricultural Research and International Cooperation OrganizationMontpellier F-34398France University of Montpellier National Research Institute for AgricultureFood and EnvironmentFrench Agricultural Research and International Cooperation OrganizationMontpellier SupAgroMontpellier 34090France School of Biological Sciences University of AberdeenAberdeen AB243UUScotland

Many rice-growing areas are affected by high concentrations of arsenic(As).Rice varieties that prevent As uptake and/or accumulation can mitigate As threats to human health.Genomic selection is known to facilitate rapid selection of superior genotypes for complex traits.We explored the predictive ability(PA)of genomic prediction with single-environment models,accounting or not for trait-specific markers,multi-environment models,and multi-trait and multi-environment models,using the genotypic(1600K SNPs)and phenotypic(grain As content,grain yield and days to flowering)data of the Bengal and Assam Aus Panel.Under the base-line single-environment model,PA of up to 0.707 and 0.654 was obtained for grain yield and grain As content,respectively;the three prediction methods(Bayesian Lasso,genomic best linear unbiased prediction and reproducing kernel Hilbert spaces)were considered to perform similarly,and marker selection based on linkage disequilibrium allowed to reduce the number of SNP to 17K,without negative effect on PA of genomic predictions.Single-environment models giving distinct weight to trait-specific markers in the genomic relationship matrix outperformed the base-line models up to 32%.Multi-environment models,accounting for genotype×environment interactions,and multi-trait and multi-environment models outperformed the base-line models by up to 47%and 61%,respectively.Among the multi-trait and multi-environment models,the Bayesian multi-output regressor stacking function obtained the highest predictive ability(0.831 for grain As)with much higher efficiency for computing time.These findings pave the way for breeding for As-tolerance in the progenies of biparental crosses involving members of the Bengal and Assam Aus Panel.Genomic prediction can also be applied to breeding for other complex traits under multiple environments.

关键词： genomic prediction model genomic selection complex trait arsenic tolerance rice predictive ability

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The Clinical Value of Artery Umbilical Cord Blood Gas in Predicting Neonate Condition:A Prospective Cohort Study

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Maternal-Fetal Medicine 2021年第3期3卷 176-184页

作者： Xing Xin Weixin Lu Chunhua Ye Hongyan Du Shaoshuai Wang Ling Feng Department of Obstetrics and Gynecology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanHubei 430030China Department of Neurosurgery Second Hospital of Lanzhou UniversityLanzhou UniversityLanzhouGansu 730000China Department of Obstetrics and Gynecology Tujia Autonomous County Maternal and Child Health HospitalYichangHubei 443000China

Objective:To evaluate the predictive ability of neonate condition through the traditional parameters and artery umbilical cord blood gas(aUCBG).Methods:A prospective cohort study was conducted in obstetrics and gynecology department between October 2017 and August 2018 at Tongji Hospital in Wuhan,China,and 360 aUCBG samples were collected.The average age of pregnant women was(29.50±4.42)years,range from 19 to 48 years old.The gestational age range from 28+4 weeks to 41+3 weeks at admission.Logistic regression and area under the curve(AUC)from Receiver operating characteristic curves were used to identify risk factors,such as,premature rupture of membranes(PROM),high blood pressure,premature delivery(PD),low 1-minute Apgar scores(Apgar 1),low 5-minute Apgar scores(Apgar 5),pH,base excess,bicarbonate,neonatal blood sugar(NBS),and so on,to predict neonatal condition and evaluate the predictive ability of traditional and aUCBG parameters.Results:In all cases,PROM,PD,Apgar 1,Apgar 5,pH,base excess,bicarbonate,total carbon dioxide,and neonatal blood sugar were risk factors and were associated with poor condition of neonate.Apgar 1 were an independent risk factor.Combined traditional and aUCBG parameters had higher AUC of 0.895(95%confidence interval(C/):0.830-0.960,P<0.001).In cesarean section subgroup,high blood pressure,PD,and Apgar 1 were risk factors and were associated with poor condition of neonate.Apgar 1 and low pH were the independent risk factors.Combined traditional and aUCBG parameters had highest AUC of 0.940(95%C/:0.886-0.993,P<0.001).In vaginal delivery subgroup,maternal age above 35 years,PROM,PD,Apgar 1,Apgar 5,and male newborn were risk factors and were associated with poor condition of neonate.Maternal age above 35 years was an independent risk factor.Combined traditional and aUCBG parameters had highest AUC of 0.897(95%Cl:0.828-0.965,P<0.001).For pregnant women without comorbidities and complications of pregnancy,aUCBG may not be necessat7.Conclusion:In high-risk pregnancies,especially lower Apgar s

关键词： Apgar score Artery umbilical cord blood gas(aUCBG) High-risk Neonate condition pH predictive ability Pregnancy Risk factor

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Validation of a Technique for Estimating Alfalfa (Medicago sativa) Biomass from Canopy Volume

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American Journal of Plant Sciences 2016年第1期7卷 238-245页

作者： Christopher G. Misar Lan Xu Arvid Boe Roger N. Gates Patricia S. Johnson Andrew E. Olson Northern Crop Science Laboratory USDA-ARS Fargo ND USA Department of Natural Resource Management South Dakota State University Brookings SD USA Department of Plant Science South Dakota State University Brookings SD USA Department of Natural Resource Management WRAC South Dakota State University Rapid City SD USA

Determining biomass production of individual alfalfa (Medicago sativa L.) plants in space planted evaluation studies is generally not feasible. Clipping plants is time consuming, expensive, and often not possible if the plants are subjected to grazing. A regression function (B′ = 0.72558 + 0.11638 × V′) was developed from spaced plants growing on rangeland in northwestern South Dakota near Buffalo to nondestructively estimate individual plant biomass (B) from canopy volume (V). However, external validation is necessary to effectively apply the model to other environments. In the summer of 2015, new data to validate the model were collected from spaced plants near Brookings, South Dakota. Canopy volume and clipped plant biomass were obtained from ten alfalfa populations varying in genetic background, growth habit, and growth stage. Fitted models for the model-building and validation data sets had similar estimated regression coefficients and attributes. Mean squared prediction errors (MSPR) were similar to or smaller than error mean square (MSE) of the model-building regression model, indicating reasonable predictive ability. Validation results indicated that the model reliably estimated biomass of plants in another environment. However, the technique should not be utilized where individual plants are not easily distinguished, such as alfalfa monocultures. Estimating biomass from canopy volume values that are extrapolations (>2.077 × 106 cm3) of the model-building data set is not recommended.

关键词： Forage Production Forage Yield Lucerne Phytomass predictive ability

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