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| 1 | Association of assisted reproductive technology, germline de novo mutations and congenital heart defects in a prospective birth cohort study显示文摘Emerging evidence suggests that children conceived through assisted reproductive technology(ART)have a higher risk of congenital heart defects(CHDs)even when there is no family history.De novo mutation(DNM)is a well-known cause of sporadic congenital diseases;however,whether ART procedures increase the number of germline DNM(gDNM)has not yet been well studied.Here,we performed whole-genome sequencing of 1137 individuals from 160 families conceived through ART and 205 families conceived spontaneously.Children conceived via ART carried 4.59 more gDNMs than children conceived spontaneously,including 332 paternal and 1.26 maternal DNMs,after correcting for parental age at conception,cigarette smoking,alcohol drinking,and exercise behaviors.Paternal DNMs in offspring conceived via ART are characterized by C>T substitutions at CpG sites,which potentially affect protein-coding genes and are significantly associated with the increased risk of CHD.In addition,the accumulation of non-coding functional mutations was independently associated with CHD and 87.9% of the mutations were originated from the father.Among ART offspring,infertility of the father was associated with elevated paternal DNMs;usage of both recombinant and urinary follicle-stimulating hormone and high-dosage human chorionic gonadotropin trigger was associated with an increase of maternal DNMs.In sum,the increased gDNMs in offspring conceived by ART were primarily originated from fathers,indicating that ART itself may not be a major reason for the accumulation of gDNMs.Our findings emphasize the importance of evaluating the germline status of the fathers in families with the use of ART. | Cheng Wang Hong Lv Xiufeng Ling Hong Li Feiyang Diao Juncheng Dai Jiangbo Du Ting Chen Qi Xi Yang Zhao Kun Zhou Bo Xu Xiumei Han Xiaoyu Liu Meijuan Peng Congcong Chen Shiyao Tao Lei Huang Cong Liu Mingyang Wen Yangqian Jiang Tao Jiang Chuncheng Lu Wei Wu Di Wu Minjian Chen Yuan Lin Xuejiang Guo Ran Huo Jiayin Liu Hongxia Ma Guangfu Jin Yankai Xia Jiahao Sha Hongbing Shen Zhibin Hu | 2021 | Cell Research2021，31，8： | 2 |
| 2 | Plant Diversity of Maoershan National Forest Park显示文摘There are a wide variety of wild plants in Maoershan National Forest Park.According to a fiveyear survey,the plants are found to include 557 species belonging to 116 families and 335 genera.There are 10 dominant families,such as Asteraceae,Ranunculaceae,Rosaceae,Fabaceae,and Chenopodiaceae,including 251 species,accounting for 46.06% of the total.There are 9 dominant genera,such as Polygonum,Potentilla ,Viola ,Artemisia ,and Corydalis ,which include 82 species of plants,accounting for 14.72% of the total.This study statistically analyzed the diversity and function of plants in the park and classified useful plants to provide a basis for the conservation and development of plant resources in Maoershan National Forest Park. | ZHANG Meiping CONG Mingyang HAN Wenge GUO Xiaohong | 2019 | Journal of Landscape Research2019，11，5： | 0 |
| 3 | Time-series surface water reconstruction method(TSWR)based on spatial distance relationship of multi-stage water boundaries显示文摘Spatiotemporal continuity of surface water datasets widely known for its significance in the surface water dynamic monitoring and assessments,are faced with drawbacks like cloud influence,which hinders the direct extraction of data from time-series remote sensing images.This study proposes a Time-series Surface Water Reconstruction method(TSWR).The initial stage of this method involves the effective use of remote sensing images to automatically construct multi-stage surface water boundaries based on Google Earth Engine(GEE).Then,we reconstructed regions the reconstruction of regions with missing water pixels using the distance relationship between the multi-stage water boundaries in previous and later periods.When applied to 10 large rivers around the world,this method yielded an overall accuracy of 98%for water extraction,an RMSE of 0.41 km2.Furthermore,time-series reconstruction tests conducted in 2020 on the Lancang and Danube rivers revealed a significant improvement in the image availability.These findings demonstrated that this method could not only be used to accurately reconstruct the surface water distribution missing water images,but also to depict a more pronounced time variation characteristic.The successful application of this method on GEE demonstrates its importance for use on large scales or in global studies. | Mingyang Li Shanlong Lu Cong Du Yong Wang Chun Fang Xinru Li Hailong Tang Muhammad Hasan Ali Baig Harrison Odion Ikhumhen | 2022 | International Journal of Digital Earth2022，15，1： | 0 |
| 4 | Regional Renewable Energy Optimization Based on Economic Benefits and Carbon Emissions显示文摘With increasing renewable energy utilization,the industry needs an accurate tool to select and size renewable energy equipment and evaluate the corresponding renewable energy plans.This study aims to bring new insights into sustainable and energy-efficient urban planning by developing a practical method for optimizing the production of renewable energy and carbon emission in urban areas.First,we provide a detailed formulation to calculate the renewable energy demand based on total energy demand.Second,we construct a dual-objective optimization model that represents the life cycle cost and carbon emission of renewable energy systems,after which we apply the differential evolution algorithmto solve the optimization result.Finally,we conduct a case study in Qingdao,China,to demonstrate the effectiveness of this optimizationmodel.Compared to the baseline design,the proposedmodel reduced annual costs and annual carbon emissions by 14.39%and 72.65%,respectively.These results revealed that dual-objective optimization is an effective method to optimize economic benefits and reduce carbon emissions.Overall,this study will assist energy planners in evaluating the impacts of urban renewable energy projects on the economy and carbon emissions during the planning stage. | Cun Wei Yunpeng Zhao Mingyang Cong Zhigang Zhou Jingzan Yan Ruixin Wang Zhuoyang Li Jing Liu | 2023 | Energy Engineering2023，120，6： | 0 |
| 5 | Taxonomic bias in occurrence information of angiosperm species in China显示文摘Taxonomic bias is a well-known shortcoming of species occurrence databases.Understanding the causes of taxonomic bias facilitates future biological surveys and addresses current knowledge gaps.Here,we investigate the main drivers of taxonomic bias in occurrence data of angiosperm species in China.We used a database including 5,936,768 records for 28,968 angiosperm species derived from herbarium specimens and literature sources.Generalized additive models(GAMs)were applied to investigate explanatory powers of 17 variables on the variation in record numbers of species.Five explanatory variables were selected for a multi-predictor GAM that explained 69%of the variation in record numbers:plant height,range size,elevational range,numbers of scientific publications and web pages.Range size was the most important predictor in the model and positively correlated with number of records.Morphological and phenological traits and social-economic factors including economic values and conservation status had weak explanatory powers on record numbers of plant species,which differs from the findings in animals,suggesting that causes of taxonomic bias in occurrence databases may vary between taxonomic groups.Our results suggest that future floristic surveys in China should more focus on range-restricted and socially or scientifically less'interesting'species. | Wenjing Yang Dandan Liu Qinghui You Bin Chen Minfei Jian Qiwu Hu Mingyang Cong Keping Ma | 2021 | Science China(Life Sciences)2021，64，4： | 0 |
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