In recent years, Graph Neural Networks (GNNs), which can naturally integrate node information and topological structure, have been demonstrated to be powerful in learning on graph data. These advantages of GNNs provide great potential to advance social recommendation since data in social recommender systems can be represented as user-user social graph and user-item graph; and learning latent factors of users and items is the key. However, building social recommender systems based on GNNs faces challenges. For example, the user-item graph encodes both interactions and their associated opinions; social relations have heterogeneous strengths; users involve in two graphs (e.g., the useruser social graph and the user-item graph). To address the three aforementioned challenges simultaneously, in this paper, we present a novel graph neural network framework (GraphRec) for social recommendations. In particular, we provide a principled approach to jointly capture interactions and opinions in the user-item graph and propose the framework GraphRec, which coherently models two graphs and heterogeneous strengths. Extensive experiments on two real-world datasets demonstrate the effectiveness of the proposed framework GraphRec. Our code is available at https: //github.com/wenqifan03/GraphRec-WWW19
The gut microbiota (GM) is related to obesity and other metabolic diseases. To detect GM markers for obesity in patients with different metabolic abnormalities and investigate their relationships with clinical indicators, 1,914 Chinese adults were enrolled for 16S rRNA gene sequencing in this retrospective study. Based on GM composition, Random forest classifiers were constructed to screen the obesity patients with (Group OA) or without metabolic diseases (Group O) from healthy individuals (Group H), and high accuracies were observed for the discrimination of Group O and Group OA (areas under the receiver operating curve (AUC) equal to 0.68 and 0.76, respectively). Furthermore, six GM markers were shared by obesity patients with various metabolic disorders (Bacteroides, Parabacteroides, Blautia, Alistipes, Romboutsia and Roseburia). As for the discrimination with Group O, Group OA exhibited low accuracy (AUC = 0.57). Nonetheless, GM classifications to distinguish between Group O and the obese patients with specific metabolic abnormalities were not accurate (AUC values from 0.59 to 0.66). Common biomarkers were identified for the obesity patients with high uric acid, high serum lipids and high blood pressure, such as Clostridium XIVa, Bacteroides and Roseburia. A total of 20 genera were associated with multiple significant clinical indicators. For example, Blautia, Romboutsia, Ruminococcus2, Clostridium sensu stricto and Dorea were positively correlated with indicators of bodyweight (including waistline and body mass index) and serum lipids (including low density lipoprotein, triglyceride and total cholesterol). In contrast, the aforementioned clinical indicators were negatively associated with Bacteroides, Roseburia, Butyricicoccus, Alistipes, Parasutterella, Parabacteroides and Clostridium IV. Generally, these biomarkers hold the potential to predict obesity-related metabolic abnormalities, and interventions based on these biomarkers might be beneficial to weight loss and metabolic risk improvement.
Many viruses interact with the host cell division cycle to favor their own growth. In this study, we examined the ability of influenza A virus to manipulate cell cycle progression. Our results show that influenza A virus A/WSN/33 (H1N1) replication results in G0/G1-phase accumulation of infected cells and that this accumulation is caused by the prevention of cell cycle entry from G0/G1 phase into S phase. Consistent with the G0/G1-phase accumulation, the amount of hyperphosphorylated retinoblastoma protein, a necessary active form for cell cycle progression through late G1 into S phase, decreased after infection with A/WSN/33 (H1N1) virus. In addition, other key molecules in the regulation of the cell cycle, such as p21, cyclin E, and cyclin D1, were also changed and showed a pattern of G0/G1-phase cell cycle arrest. It is interesting that increased viral protein expression and progeny virus production in cells synchronized in the G0/G1 phase were observed compared to those in either unsynchronized cells or cells synchronized in the G2/M phase. G0/G1-phase cell cycle arrest is likely a common strategy, since the effect was also observed in other strains, such as H3N2, H9N2, PR8 H1N1, and pandemic swine H1N1 viruses. These findings, in all, suggest that influenza A virus may provide favorable conditions for viral protein accumulation and virus production by inducing a G0/G1-phase cell cycle arrest in infected cells.
It has not been established which specific measures of obesity might be most appropriate for predicting CVD risk in Asians. The objectives of the present study were to determine the associations of BMI, waist circumference (WC) and waist:height ratio (WHtR) with CVD risk factors and to evaluate the optimal cut-off values to define overweight or obesity in Chinese adults. Data collected from seven nationwide health examination centres during 2008 and 2009 were analysed. The BMI, WC and WHtR of 244 266 Chinese adults aged $20 years included in the study were measured. Logistic regression models were fit to evaluate the OR of each CVD risk factor according to various anthropometric indices. Receiver operating characteristic (ROC) analyses were conducted to assess the optimal cut-off values to predict the risk of diabetes, hypertension, dyslipidaemia and the metabolic syndrome. WHtR had the largest areas under the ROC curve for all CVD risk factors in both sexes, followed by WC and BMI. The optimal cut-off values were approximately 24·0 and 23·0 kg/m 2 for BMI, 85·0 and 75·0 cm for WC, and 0·50 and 0·48 for WHtR for men and women, respectively. According to well-established cut-off values, BMI was found to be a more sensitive indicator of hypertension in both men and women, while WC and WHtR were found to be better indicators of diabetes and dyslipidaemia. A combination of BMI and central obesity measures was found to be associated with greater OR of CVD risk factors than either of them alone in both sexes. The present study demonstrated that WHtR and WC may be better indicators of CVD risk factors for Chinese people than BMI.
Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m 2 . In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, the...
Obesity has been increasing worldwide. Data on obesity status among men of reproductive age are scarce. This study aimed to assess the national prevalence and trend of overweight and obesity among reproductive-age men in rural China. In the nationwide population-based study, data were obtained from the National Free Preconception Health Examination Project in rural China from 2010 to 2014. Weight and height were measured in 16 161 982 men aged 15–49 years and their female partners (15 997 739 participants aged 15–49 years) before conception, and body mass index (BMI) was calculated. We found that the prevalence of combined overweight and obesity among men was 33.8% (33.7–33.9%) according to Chinese criteria (BMI ≥ 24.0 kg/m2), the corresponding rates of obesity were 6.3% (6.2–6.4%; BMI ≥ 28.0 kg/m2), respectively. The prevalence varied in different ethnic groups, geographic regions, age, education and GDP levels, and increasing trend was observed over the 5-year study period. In addition, 45.8% of couples had at least one of them as overweight or obesity. About one third of men aged 15–49 years before conception in rural China are overweight or obese. Overweight/obesity clusters in families, which highlights the importance of family involvement of early prevention of obesity in China.
These results suggest that OLP is associated with dysbiosis of the oral microbiome. Further studies should be taken to elucidate the inner relationship between these observed changes and OLP development.
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