A partner-matching framework for social activity communities

A lot of daily activities require more than one person to participate and collaborate with each other; however, for many people, it is not easy to find good partners to engage in activities with one another. With the rapid growth of social network applications, more and more people get used to creating connections with people on the social network. Therefore, designing social network framework for partner-matching is significant in helping people to easily find good partners. In this paper, we proposed a framework which can match partners for an active community. In order to improve the matching performance, all users are divided into groups based on a specific classification tree that is built for a specific activity. The optimization goal of the partner-matching is to maintain as many stable partnerships as possible in the community. To achieve the goal, various factors are considered to design matching functions. The simulation results show that the proposed framework can help most people find stable partners quickly

NeutronOrch: Rethinking Sample-based GNN Training under CPU-GPU Heterogeneous Environments

Graph Neural Networks (GNNs) have demonstrated outstanding performance in various applications. Existing frameworks utilize CPU-GPU heterogeneous environments to train GNN models and integrate mini-batch and sampling techniques to overcome the GPU memory limitation. In CPU-GPU heterogeneous environments, we can divide sample-based GNN training into three steps: sample, gather, and train. Existing GNN systems use different task orchestrating methods to employ each step on CPU or GPU. After extensive experiments and analysis, we find that existing task orchestrating methods fail to fully utilize the heterogeneous resources, limited by inefficient CPU processing or GPU resource contention. In this paper, we propose NeutronOrch, a system for sample-based GNN training that incorporates a layer-based task orchestrating method and ensures balanced utilization of the CPU and GPU. NeutronOrch decouples the training process by layer and pushes down the training task of the bottom layer to the CPU. This significantly reduces the computational load and memory footprint of GPU training. To avoid inefficient CPU processing, NeutronOrch only offloads the training of frequently accessed vertices to the CPU and lets GPU reuse their embeddings with bounded staleness. Furthermore, NeutronOrch provides a fine-grained pipeline design for the layer-based task orchestrating method, fully overlapping different tasks on heterogeneous resources while strictly guaranteeing bounded staleness. The experimental results show that compared with the state-of-the-art GNN systems, NeutronOrch can achieve up to 11.51x performance speedup

Decreased Glycogenolysis by miR-338-3p Promotes Regional Glycogen Accumulation Within the Spinal Cord of Amyotrophic Lateral Sclerosis Mice

Metabolic dysfunction is a hallmark of age-related neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS). But the crosstalk between metabolic alteration and disease progression in ALS is still largely unknown. Glycogen, a branched polymer of glucose residues, is universally recognized as the energy reserve of the central nervous system (CNS), where its aberrant accumulation instigates neurodegeneration. Glycogen was reported to be accumulated in both CNS and visceral organs of SOD1G93A mice, a well-known ALS model, and contributes to the pathological process of ALS. However, the accumulative patterns and mechanisms are not well elucidated. Here, we provide extensive evidence to demonstrate that glycogen accumulated in the lumbar spinal cord of ALS mice along with the disease progression, but not in the motor cortex. This regional accumulation of glycogen was caused by deteriorated glycogenolysis, which was triggered by decreased glycogen phosphorylase, brain form (PYGB). Moreover, miR-338-3p, an elevated miRNA in the spinal cord of SOD1G93A mice, directly targeted PYGB and was responsible for the decreased glycogenolysis and subsequent glycogen accumulation. Our work is helpful for better understanding of of of metabolic dysfunctions in ALS and provides novel targets for the therapeutic intervention in the future

Single Endemic Genotype of Measles Virus Continuously Circulating in China for at Least 16 Years

The incidence of measles in China from 1991 to 2008 was reviewed, and the nucleotide sequences from 1507 measles viruses (MeV) isolated during 1993 to 2008 were phylogenetically analyzed. The results showed that measles epidemics peaked approximately every 3 to 5 years with the range of measles cases detected between 56,850 and 140,048 per year. The Chinese MeV strains represented three genotypes; 1501 H1, 1 H2 and 5 A. Genotype H1 was the predominant genotype throughout China continuously circulating for at least 16 years. Genotype H1 sequences could be divided into two distinct clusters, H1a and H1b. A 4.2% average nucleotide divergence was found between the H1a and H1b clusters, and the nucleotide sequence and predicted amino acid homologies of H1a viruses were 92.3%–100% and 84.7%–100%, H1b were 97.1%–100% and 95.3%–100%, respectively. Viruses from both clusters were distributed throughout China with no apparent geographic restriction and multiple co-circulating lineages were present in many provinces. Cluster H1a and H1b viruses were co-circulating during 1993 to 2005, while no H1b viruses were detected after 2005 and the transmission of that cluster has presumably been interrupted. Analysis of the nucleotide and predicted amino acid changes in the N proteins of H1a and H1b viruses showed no evidence of selective pressure. This study investigated the genotype and cluster distribution of MeV in China over a 16-year period to establish a genetic baseline before MeV elimination in Western Pacific Region (WPR). Continuous and extensive MeV surveillance and the ability to quickly identify imported cases of measles will become more critical as measles elimination goals are achieved in China in the near future. This is the first report that a single endemic genotype of measles virus has been found to be continuously circulating in one country for at least 16 years

Genetic diversity fuels gene discovery for tobacco and alcohol use

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury(1-4). These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries(5). Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.Peer reviewe

Correlation between Serum Cytokeratin 19 Fragment and the Clinicopathological Features and Prognosis of Thymic Epithelial Tumors

Background and objective So far there’s no tumor maker applied in diagnosis and treatment of thymic epithelial tumors. This study is to assess the correlation between serum cytokine 19 fragment (Cyfra 21-1) and clinicopathological features and prognosis of thymic epithelial tumors (TETs). Methods The clinical data of 159 patients with TETs in Shanghai Chest Hospital was retrospectively analysed. Patients were divided into groups according to different tumor stages and histotypes. Serum Cyfra 21-1 was thus compared. In addition, the possible relationship between perioperative serum Cyfra 21-1 level and the recurrent status was carrid out. Results Preoperative Cyfra 21-1 serum concentrations in patiants with advanced stage (T4) and thymic carcinomas were significantly higher than that in others (P<0.001, P<0.001, respectively). When the preoperative serum level exceeds the out-off of 1.66 ng/mL, it possibly indicates the recurrence during follow up. Furthermore, the sensitivity, specificity, and positive as well as negative predictive value (PPV and NPV) of postoperative Cyfra 21-1 to predict tumor recurrence were evaluated. At a cut-off of Cyfra 21-1 of 2.66 ng/mL, the sensitivity was 0.7, the specificity was 0.925, the PPV was 0.5 and the NPV was 0.966. Conclusion The elevated level of preoperative serum Cyfra 21-1 indicates an advanced stage of tumor or a more malignant histotype (thymic carcinoma). It also probably suggests a higher risk of tumor recurrence. During the oncological follow up, in addition to regular imaging examinations, the blood test of serum Cyfra 21-1 is also suggested to improve the diagnosis of tumor recurrence in order to improve the prognosis