Serum uric acid and metabolic risk factors in three ethnic groups : Asian Indians and Creoles in Mauritius and Chinese in Qingdao, China

In humans with a loss of uricase the final oxidation product of purine catabolism is uric acid (UA). The prevalence of hyperuricemia has been increasing around the world accompanied by a rapid increase in obesity and diabetes. Since hyperuricemia was first described as being associated with hyperglycemia and hypertension by Kylin in 1923, there has been a growing interest in the association between elevated UA and other metabolic abnormalities of hyperglycemia, abdominal obesity, dyslipidemia, and hypertension. The direction of causality between hyperuricemia and metabolic disorders, however, is unceartain. The association of UA with metabolic abnormalities still needs to be delineated in population samples. Our overall aims were to study the prevalence of hyperuricemia and the metabolic factors clustering with hyperuricemia, to explore the dynamical changes in blood UA levels with the deterioration in glucose metabolism and to estimate the predictive capability of UA in the development of diabetes. Four population-based surveys for diabetes and other non-communicable diseases were conducted in 1987, 1992, and 1998 in Mauritius, and in 2001-2002 in Qingdao, China. The Qingdao study comprised 1 288 Chinese men and 2 344 women between 20-74, and the Mauritius study consisted of 3 784 Mauritian Indian and Mauritian Creole men and 4 442 women between 25-74. In Mauritius, re-exams were made in 1992 and/or 1998 for 1 941 men (1 409 Indians and 532 Creoles) and 2 318 non pregnant women (1 645 Indians and 673 Creoles), free of diabetes, cardiovascular diseases, and gout at baseline examinations in 1987 or 1992, using the same study protocol. The questionnaire was designed to collect demographic details, physical examinations and standard 75g oral glucose tolerance tests were performed in all cohorts. Fasting blood UA and lipid profiles were also determined. The age-standardized prevalence in Chinese living in Qingdao was 25.3% for hyperuricemia (defined as fasting serum UA > 420 μmol/l in men and > 360 μmol/l in women) and 0.36% for gout in adults between 20-74. Hyperuricemia was more prevalent in men than in women. One standard deviation increase in UA concentration was associated with the clustering of metabolic risk factors for both men and women in three ethnic groups. Waist circumference, body mass index, and serum triglycerides appeared to be independently associated with hyperuricemia in both sexes and in all ethnic groups except in Chinese women, in whom triglycerides, high-density lipoprotein cholesterol, and total cholesterol were associated with hyperuricemia. Serum UA increased with increasing fasting plasma glucose levels up to a value of 7.0 mmol/l, but significantly decreased thereafter in mainland Chinese. An inverse relationship occurred between 2-h plasma glucose and serum UA when 2-h plasma glucose higher than 8.0 mmol/l. In the prospective study in Mauritius, 337 (17.4%) men and 379 (16.4%) women developed diabetes during the follow-up. Elevated UA levels at baseline increased 1.14-fold in risk of incident diabetes in Indian men and 1.37-fold in Creole men, but no significant risk was observed in women. In conclusion, the prevalence of hyperuricemia was high in Chinese in Qingdao, blood UA was associated with the clustering of metabolic risk factors in Mauritian Indian, Mauritian Creole, and Chinese living in Qingdao, and a high baseline UA level independently predicted the development of diabetes in Mauritian men. The clinical use of UA as a marker of hyperglycemia and other metabolic disorders needs to be further studied. Keywords: Uric acid, Hyperuricemia, Risk factors, Type 2 Diabetes, Incidence, Mauritius, ChineseEi saatavill

Psychometric evaluation of the Chinese version of the subjective happiness scale: Evidence from the Hong Kong FAMILY cohort

BACKGROUND: With China's rapid economic growth in the past few decades, there is currently an emerging focus on happiness. Cross-cultural validity studies have indicated that the four-item Subjective Happiness Scale (SHS) has high internal consistency and stable reliability. However, the psychometric characteristics of the SHS in broader Chinese community samples are unknown. PURPOSE: We evaluated the factor structure and psychometric properties of the SHS in the Hong Kong general population. METHODS: The Chinese SHS was derived using forward-backward translation. Of the Cantonese-speaking participants aged >/=15 years, 2,635 were randomly selected from the random sample component of the FAMILY Cohort, a territory-wide cohort study in Hong Kong. In addition to the SHS, a single-item overall happiness scale, the Patient Health Questionnaire-9 (PHQ-9), the Family Adaptation, Partnership, Growth, Affection, Resolve (APGAR) scale, and the Medical Outcomes Study 12-item short-form version 2 (SF-12) mental and physical health scales were administered. RESULTS: Exploratory and confirmatory factor analyses supported a single factor with high loadings for the four SHS items. Multiple group analyses indicated factor invariance across sex and age groups. Cronbach's alpha was 0.82, and 2-week test-retest reliability (n = 191) was 0.70. The SHS correlated significantly with single-item overall happiness (Spearman's rho [rho] = 0.57), Family APGAR (rho = 0.26), PHQ-9 (rho = -0.34), and mental health-related quality of life (rho = 0.40) but showed a lower correlation with physical health (rho = 0.15). A regression model that included the PHQ-9 and Family APGAR scores explained 37 % of the variance in SF-12 mental health scores; adding the SHS raised the variance explained to 41 %. CONCLUSIONS: Our results support the reliability and validity of the SHS as a relevant component in the measurement battery for mental well-being in a Chinese general population.published_or_final_versio

Pan-Genomic Study of Mycobacterium tuberculosis Reflecting the Primary/Secondary Genes, Generality/Individuality, and the Interconversion Through Copy Number Variations

Tuberculosis (TB) has surpassed HIV as the leading infectious disease killer worldwide since 2014. The main pathogen, Mycobacterium tuberculosis (Mtb), contains ~4,000 genes that account for ~90% of the genome. However, it is still unclear which of these genes are primary/secondary, which are responsible for generality/individuality, and which interconvert during evolution. Here we utilized a pan-genomic analysis of 36 Mtb genomes to address these questions. We identified 3,679 Mtb core (i.e., primary) genes, determining their phenotypic generality (e.g., virulence, slow growth, dormancy). We also observed 1,122 dispensable and 964 strain-specific secondary genes, reflecting partially shared and lineage-/strain-specific individualities. Among which, five L2 lineage-specific genes might be related to the increased virulence of the L2 lineage. Notably, we discovered 28 Mtb “Super Core Genes” (SCGs: more than a copy in at least 90% strains), which might be of increased importance, and reflected the “super phenotype generality.” Most SCGs encode PE/PPE, virulence factors, antigens, and transposases, and have been verified as playing crucial roles in Mtb pathogenicity. Further investigation of the 28 SCGs demonstrated the interconversion among SCGs, single-copy core, dispensable, and strain-specific genes through copy number variations (CNVs) during evolution; different mutations on different copies highlight the delicate adaptive-evolution regulation amongst Mtb lineages. This reflects that the importance of genes varied through CNVs, which might be driven by selective pressure from environment/host-adaptation. In addition, compared with Mycobacterium bovis (Mbo), Mtb possesses 48 specific single core genes that partially reflect the differences between Mtb and Mbo individuality

Exploring relationship satisfaction between global professional service firms and local clients in emerging markets

Extending the perspective of agency theory, this study incorporates both professional and local knowledge asymmetry into a model of relationship satisfaction between global professional service firms and their local clients. The model also includes learning orientation and adaptation that are theorized to regulate the impact of knowledge asymmetry on goal incongruence, which ultimately affects relationship satisfaction. China was selected as the setting of the study because it is the largest emerging market, has seen double-digit growth of advertising expenditures for the past two decades, and is home to many multinational advertising agencies that have increasingly pursued local clients as revenue sources. Multiple informants from 177 domestic Chinese firms and their multinational advertising agencies were personally interviewed, and the dyadic data were used to test the model. Results show that both types of knowledge asymmetry lead to goal incongruence, which causes client dissatisfaction. The role of learning orientation varies, as does the role of adaptation, in moderating the impact of knowledge asymmetry on goal incongruence and the impact of goal incongruence on relationship satisfaction. Theoretical and managerial implications of the findings are discussed, along with the limitations of the study and future research directions.

Multi-Variables-Driven Model Based on Random Forest and Gaussian Process Regression for Monthly Streamflow Forecasting

Due to the inherent non-stationary and nonlinear characteristics of original streamflow and the complicated relationship between multi-scale predictors and streamflow, accurate and reliable monthly streamflow forecasting is quite difficult. In this paper, a multi-scale-variables-driven streamflow forecasting (MVDSF) framework was proposed to improve the runoff forecasting accuracy and provide more information for decision-making. This framework was realized by integrating random forest (RF) and Gaussian process regression (GPR) with multi-scale variables (hydrometeorological and climate predictors) as inputs and is referred to as RF-GPR-MV. To validate the effectiveness and superiority of the RF-GPR-MV model, it was implemented for multi-step-ahead monthly streamflow forecasts with horizons of 1 to 12 months for two key hydrological stations in the Jinsha River basin, Southwest China. Other MVDSF models based on the Pearson correlation coefficient (PCC) and GPR with/without multi-scale variables or the PCC and a backpropagation neural network (BP) or general regression neural network (GRNN), with only previous streamflow and precipitation, namely, PCC-GPR-MV, PCC-GPR-QP, PCC-BP-QP, and PCC-GRNN-QP, respectively, were selected as benchmarks. Experimental results indicated that the proposed model was superior to the other benchmark models in terms of the Nash–Sutcliffe efficiency (NSE) for almost all forecasting scenarios, especially for forecasting with longer lead times. Additionally, the results also confirmed that the addition of large-scale climate and circulation factors was beneficial for promoting the streamflow forecasting ability, with an average contribution rate of about 15%. The RF in the MVDSF framework improved the forecasting performance, with an average contribution rate of about 25%. This improvement was more pronounced when the lead time exceeded 3 months. Moreover, the proposed model could also provide prediction intervals (PIs) to characterize forecast uncertainty, as supplementary information to further help decision makers in relevant departments to avoid risks in water resources management

Multi-Variables-Driven Model Based on Random Forest and Gaussian Process Regression for Monthly Streamflow Forecasting

Due to the inherent non-stationary and nonlinear characteristics of original streamflow and the complicated relationship between multi-scale predictors and streamflow, accurate and reliable monthly streamflow forecasting is quite difficult. In this paper, a multi-scale-variables-driven streamflow forecasting (MVDSF) framework was proposed to improve the runoff forecasting accuracy and provide more information for decision-making. This framework was realized by integrating random forest (RF) and Gaussian process regression (GPR) with multi-scale variables (hydrometeorological and climate predictors) as inputs and is referred to as RF-GPR-MV. To validate the effectiveness and superiority of the RF-GPR-MV model, it was implemented for multi-step-ahead monthly streamflow forecasts with horizons of 1 to 12 months for two key hydrological stations in the Jinsha River basin, Southwest China. Other MVDSF models based on the Pearson correlation coefficient (PCC) and GPR with/without multi-scale variables or the PCC and a backpropagation neural network (BP) or general regression neural network (GRNN), with only previous streamflow and precipitation, namely, PCC-GPR-MV, PCC-GPR-QP, PCC-BP-QP, and PCC-GRNN-QP, respectively, were selected as benchmarks. Experimental results indicated that the proposed model was superior to the other benchmark models in terms of the Nash–Sutcliffe efficiency (NSE) for almost all forecasting scenarios, especially for forecasting with longer lead times. Additionally, the results also confirmed that the addition of large-scale climate and circulation factors was beneficial for promoting the streamflow forecasting ability, with an average contribution rate of about 15%. The RF in the MVDSF framework improved the forecasting performance, with an average contribution rate of about 25%. This improvement was more pronounced when the lead time exceeded 3 months. Moreover, the proposed model could also provide prediction intervals (PIs) to characterize forecast uncertainty, as supplementary information to further help decision makers in relevant departments to avoid risks in water resources management

Fast and Efficient Removal of Uranium onto a Magnetic Hydroxyapatite Composite: Mechanism and Process Evaluation

The exploration and rational design of easily separable and highly efficient sorbents with satisfactory capability of extracting radioactive uranium (U)-containing compound(s) are of paramount significance. In this study, a novel magnetic hydroxyapatite (HAP) composite (HAP@ CoFe2O4), which was coupled with cobalt ferrite (CoFe2O4), was rationally designed for uranium(VI) removal through a facile hydrothermal process. The U(VI) ions were rapidly removed using HAP@ CoFe2O4 within a short time (i.e., 10 min), and a maximum U(VI) removal efficiency of 93.7% was achieved. The maximum adsorption capacity (Qmax) of the HAP@CoFe2O4 was 338 mg/g, which demonstrated the potential of as-prepared HAP@CoFe2O4 in the purification of U(VI) ions from nuclear effluents. Autunite [Ca(UO2)2(PO4)2(H2O)6] was the main crystalline phase to retain uranium, wherein U(VI) was effectively extracted and immobilized in terms of a relatively stable mineral. Furthermore, the reacted HAP@CoFe2O4 can be magnetically recycled. The results of this study reveal that the suggested process using HAP@CoFe2O4 is a promising approach for the removal and immobilization of U(VI) released from nuclear effluents

The “Gate Keeper” Role of Trp222 Determines the Enantiopreference of Diketoreductase toward 2-Chloro-1-Phenylethanone

<div><p>Trp222 of diketoreductase (DKR), an enzyme responsible for reducing a variety of ketones to chiral alcohols, is located at the hydrophobic dimeric interface of the C-terminus. Single substitutions at DKR Trp222 with either canonical (Val, Leu, Met, Phe and Tyr) or unnatural amino acids (UAAs) (4-cyano-L-phenylalanine, 4-methoxy-L-phenylalanine, 4-phenyl-L-phenyalanine, <i>O</i>-<i>tert</i>-butyl-L-tyrosine) inverts the enantiotope preference of the enzyme toward 2-chloro-1-phenylethanone with close side chain correlation. Analyses of enzyme activity, substrate affinity and ternary structure of the mutants revealed that substitution at Trp222 causes a notable change in the overall enzyme structure, and specifically in the entrance tunnel to the active center. The size of residue 222 in DKR is vital to its enantiotope preference. Trp222 serves as a “gate keeper” to control the direction of substrate entry into the active center. Consequently, opposite substrate-binding orientations produce respective alcohol enantiomers.</p></div