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BACKGROUND Suicide is the fifth most important cause of death in China, but the reasons for the high rate and unique pattern of characteristics of those who kill themselves are unknown. METHODS We pretested, and then administered a comprehensive interview to family members and close associates of 519 people who committed suicide and of 536 people who died(More)
Approximately 10% of patients with amyotrophic lateral sclerosis (ALS) have familial ALS (FALS), and 20% of FALS are caused by mutations of superoxide dismutase type 1 (MTSOD1). The fact that some MTSOD1s that cause FALS have full dismutase activity (e.g. G37R) and others no dismutase activity (e.g. G85R) suggests that MTSOD1 causes FALS due to toxicity of(More)
Approximately 10% of amyotrophic lateral sclerosis (ALS) cases are familial (FALS), and approximately 25% of FALS cases are caused by mutations in Cu/Zn superoxide dismutase type 1 (SOD1). Mutant (MT) SOD1 is thought to be pathogenic because it misfolds and aggregates. A number of transgenic mice have been generated that express different MTSOD1s as(More)
Mutant superoxide dismutase type 1 (MTSOD1), the most common known cause of familial amyotrophic lateral sclerosis (FALS), is believed to cause FALS as a result of a toxicity of the protein. MTSOD1s with full dismutase enzymatic activity (e.g., G37R) and without any enzymatic activity (e.g., G85R) cause FALS, demonstrating that the ability of MTSOD1 to(More)
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioinformatics. However, data coclustering without any prior knowledge or background information is still a challenging problem. In this paper, we propose a Semisupervised Non-negative(More)
This paper presents a saliency detection algorithm by integrating both local estimation and global search. In the local estimation stage, we detect local saliency by using a deep neural network (DNN-L) which learns local patch features to determine the saliency value of each pixel. The estimated local saliency maps are further refined by exploring the high(More)
We propose a new approach for general object tracking with fully convolutional neural network. Instead of treating convolutional neural network (CNN) as a black-box feature extractor, we conduct in-depth study on the properties of CNN features offline pre-trained on massive image data and classification task on ImageNet. The discoveries motivate the design(More)
Genetic mapping and QTL detection are powerful methodologies in plant improvement and breeding. Construction of a high-density and high-quality genetic map would be of great benefit in the production of superior grapes to meet human demand. High throughput and low cost of the recently developed next generation sequencing (NGS) technology have resulted in(More)
Grapes are a major fruit crop around the world. Heat stress can significantly reduce grape yield and quality. Changes at the molecular level in response to heat stress and subsequent recovery are poorly understood. To elucidate the effect of heat stress and subsequent recovery on expression of genes by grape leaves representing the classic heat stress(More)
High temperature is a major environmental factor limiting grape yield and affecting berry quality. Thermotolerance includes the direct response to heat stress and the ability to recover from heat stress. To better understand the mechanism of the thermotolerance of Vitis, we combined a physiological analysis with iTRAQ-based proteomics of Vitis vinifera cv(More)