Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingda...Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.展开更多
At present, the Tibetan Mastiff is the oldest and most ferocious dog in the world. However, the origin of the Tibetan Mastiff and its phylogenetic relationship with other large breed dogs such as Saint Bernard are unc...At present, the Tibetan Mastiff is the oldest and most ferocious dog in the world. However, the origin of the Tibetan Mastiff and its phylogenetic relationship with other large breed dogs such as Saint Bernard are unclear. In this study, the primers were designed accord- ing to the mitochondrial genome sequence of the domestic dog, and the 2,525 bp mitochondrial sequence, containing the whole sequence of Cytochrome b, tRNA-Thr, tRNA-Pro, and control region of the Tibetan Mastiff, was obtained. Using grey wolves and coyotes as out- groups, the Tibetan Mastiff and 12 breeds of domestic dogs were analyzed in phylogenesis. Tibetan Mastiff, domestic dog breeds, and grey wolves were clustered into a group and coyotes were clustered in a group separately. This indicated that the Tibetan Mastiff and the other domestic dogs originated from the grey wolf, and the Tibetan Mastiff belonged to Carnivora, Canidae, Canis, Canis lupus, Canis lupus familiaris on the animal taxonomy. In domestic dogs, the middle and small breed dogs were clustered at first; German Sheepdog, Swedish Elkhound, and Black Russian Terrier were clustered into one group, and the Tibetan Mastiff, Old English Sheepdog, Leonberger, and Saint Bernard were clustered in another group. This confirmed the viewpoint that many of the famous large breed dogs worldwide such as Saint Bernard possibly had the blood lineage of the Tibetan Mastiff, based on the molecular data. According to the substitution rate, we concluded that the approximate divergence time between Tibetan Mastiff and grey wolf was 58,000 years before the present (YBP), and the approximate divergence time between other domestic dogs and grey wolf was 42,000 YBP, demonstrating that the time of origin of the Tibetan Mastiff was earlier than that of the other domestic dogs.展开更多
1Introduction and main contributions In the field of social networks and knowledge graphs,semi-supervised learning models based on graph convolutional networks have achieved great success in node classification[1],ind...1Introduction and main contributions In the field of social networks and knowledge graphs,semi-supervised learning models based on graph convolutional networks have achieved great success in node classification[1],inductive node embedding[2],link prediction[3],and recommend.These semi-supervised models based on graph convolutional network(GCN)[4]expect to obtain more feature information of a graph or accelerate the training.展开更多
基金supported by the Chinese Field Epidemiology Training Program,the Research and Development of Standards and Standardization of Nomenclature in the Field of Public Health-Research Project on the Development of the Disciplines of Public Health and Preventive Medicine[242402]the Shandong Medical and Health Science and Technology Development Plan[202112050731].
文摘Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.
文摘At present, the Tibetan Mastiff is the oldest and most ferocious dog in the world. However, the origin of the Tibetan Mastiff and its phylogenetic relationship with other large breed dogs such as Saint Bernard are unclear. In this study, the primers were designed accord- ing to the mitochondrial genome sequence of the domestic dog, and the 2,525 bp mitochondrial sequence, containing the whole sequence of Cytochrome b, tRNA-Thr, tRNA-Pro, and control region of the Tibetan Mastiff, was obtained. Using grey wolves and coyotes as out- groups, the Tibetan Mastiff and 12 breeds of domestic dogs were analyzed in phylogenesis. Tibetan Mastiff, domestic dog breeds, and grey wolves were clustered into a group and coyotes were clustered in a group separately. This indicated that the Tibetan Mastiff and the other domestic dogs originated from the grey wolf, and the Tibetan Mastiff belonged to Carnivora, Canidae, Canis, Canis lupus, Canis lupus familiaris on the animal taxonomy. In domestic dogs, the middle and small breed dogs were clustered at first; German Sheepdog, Swedish Elkhound, and Black Russian Terrier were clustered into one group, and the Tibetan Mastiff, Old English Sheepdog, Leonberger, and Saint Bernard were clustered in another group. This confirmed the viewpoint that many of the famous large breed dogs worldwide such as Saint Bernard possibly had the blood lineage of the Tibetan Mastiff, based on the molecular data. According to the substitution rate, we concluded that the approximate divergence time between Tibetan Mastiff and grey wolf was 58,000 years before the present (YBP), and the approximate divergence time between other domestic dogs and grey wolf was 42,000 YBP, demonstrating that the time of origin of the Tibetan Mastiff was earlier than that of the other domestic dogs.
基金the National Natural Science Foundation of China(Grant Nos.61272209,61872164)in part by the Program of Science and Technology Development Plan of Jilin Province of China(20190302032GX)in part by the Fundamental Research Funds for the Central Universities(Jilin University).
文摘1Introduction and main contributions In the field of social networks and knowledge graphs,semi-supervised learning models based on graph convolutional networks have achieved great success in node classification[1],inductive node embedding[2],link prediction[3],and recommend.These semi-supervised models based on graph convolutional network(GCN)[4]expect to obtain more feature information of a graph or accelerate the training.