Development and visualization of a risk prediction model for metabolic syndrome: a longitudinal cohort study based on health check-up data in China

AimOur study aimed to construct a practical risk prediction model for metabolic syndrome (MetS) based on the longitudinal health check-up data, considering both the baseline level of physical examination indicators and their annual average cumulative exposure, and to provide some theoretical basis for the health management of Mets.MethodsThe prediction model was constructed in male and female cohorts, separately. The shared set of predictive variables screened out from 49 important physical examination indicators by the univariate Cox model, Lasso-Cox model and the RSF algorithm collectively was further screened by Cox stepwise regression method. The screened predictors were used to construct prediction model by the Cox proportional hazards regression model and RSF model, respectively. Subsequently, the better method would be selected to develop final MetS predictive model according to comprehensive comparison and evaluation. Finally, the optimal model was validated internally and externally by the time-dependent ROC curve (tdROC) and concordance indexes (C-indexes). The constructed predictive model was converted to a web-based prediction calculator using the “shiny” package of the R4.2.1 software.ResultsA total of 15 predictors were screened in the male cohort and 9 predictors in the female cohort. In both male and female cohorts, the prediction error curve of the RSF model was consistently lower than that of the Cox proportional hazards regression model, and the integrated Brier score (IBS) of the RSF model was smaller, therefore, the RSF model was used to develop the final prediction model. Internal validation of the RSF model showed that the area under the curve (AUC) of tdROC for 1 year, 3 years and 5 years in the male cohort were 0.979, 0.991, and 0.983, and AUCs in the female cohort were 0.959, 0.975, and 0.978, respectively, the C-indexes calculated by 500 bootstraps of the male and female cohort RSF models are above 0.7. The external validation also showed that the model has good predictive ability.ConclusionThe risk predictive model for MetS constructed by RSF in this study is more stable and reliable than Cox proportional hazards regression model, and the model based on multiple screening of routine physical examination indicators has performed well in both internal and external data, and has certain clinical application value

Improving Hypoxia Adaption Causes Distinct Effects on Growth and Bioactive Compounds Synthesis in an Entomopathogenic Fungus Cordyceps militaris

Cordyceps militaris is an entomopathogenic fungus producing a variety of bioactive compounds. To meet the huge demand for medicinal and edible products, industrialized fermentation of mycelia and cultivation of stromata have been widely developed in China. The content of bioactive metabolites of C. militaris, such as cordycepin, is higher when cultivated on silkworm pupae than on rice or in broth. However, compared with other cultivation methods, C. militaris grows more slowly and accumulates less biomass. The hypoxic environment in pupa hemocoel is one of environmental factor which is not existed in other cultivation methods. It is suggested that hypoxia plays an important role on the growth and the synthesis of bioactive compounds in C. militaris. Here, we demonstrated that the distinct effects on the growth and synthesis of bioactive compounds employing different strategies of improving hypoxia adaption. The introduction of Vitreoscilla hemoglobin enhanced growth, biomass accumulation, and crude polysaccharides content of C. militaris. However, cordycepin production was decreased to 9–15% of the control group. Meanwhile, the yield of adenosine was increased significantly. Nonetheless, when the predicted bHLH transcription factor of sterol regulatory element binding proteins (SREBPs) was overexpressed in C. militaris to improve the hypoxia adaption of fungal cells, cordycepin content was significantly increased more than two-fold. These findings reveal the role of SREBPs on growth and bioactive compounds synthesis. And it also provides a scientific basis for rationally engineering strains and optimization strategies of air supply in cultivation and fermentation

On the Periodic Orbits of Four-Particle Time-Dependent FPU Chains

We study the existence of the periodic orbits for four-particle time-dependent FPU chains. To begin with, taking an orthogonal transformation and dropping two variables, we put the system into a lower dimensional system. In this case, the unperturbed system has the linear spectra 2 and 2, which are rational independent. Therefore, the classical averaging theory cannot be applied directly, and the existence and multiplicity of periodic orbits for four-particle FPU chains is proved by using a new result from averaging theory by Buică, Francoise, and Llibre

A High-Fidelity Parametric Model for Tropical Cyclone Boundary Layer Wind Field by Considering Effects of Land Cover and Terrain

The proper simulation of the tropical cyclone (TC) boundary layer wind field is essential to predict the maximum wind speed, the imposed wind loading on civil structures, and the related potential disasters. A high-fidelity parametric model is developed to produce the wind field and to study the wind characteristics of TCs in the boundary layer. This model adopts a widely used boundary layer turbulence closure scheme and is built on a terrain-following coordinate system, which can consider various land cover and terrain effects. To improve the computational efficiency, a nested grid system is adopted. The developed model is implemented to reproduce the wind fields of Hurricane Isabel (2003), Hurricane Katrina (2005), Hurricane Irene (2011), Typhoon Hagupit (2008), Typhoon Hato (2017), and Typhoon Mangkhut (2018). Different types of observation datasets are used to validate the developed model, including the Hurricane Research Division\u27s H*Wind snapshots, the National Data Buoy Center\u27s wind records, and several meteorological sounding stations\u27 observations. The spatial wind fields and the wind speed time series are presented. The influence of land cover and terrain on the behavior of TC is investigated. The simulation results demonstrate the high-fidelity and computational efficiency of the developed model, implying its potential applications for TC hazard modeling

Atmospheric Thermal and Dynamic Vertical Structures of Summer Hourly Precipitation in Jiulong of the Tibetan Plateau

It is an important to study atmospheric thermal and dynamic vertical structures over the Tibetan Plateau (TP) and their impact on precipitation by using long-term observation at representative stations. This study exhibits the observational facts of summer precipitation variation on subdiurnal scale and its atmospheric thermal and dynamic vertical structures over the TP with hourly precipitation and intensive soundings in Jiulong during 2013–2020. It is found that precipitation amount and frequency are low in the daytime and high in the nighttime, and hourly precipitation greater than 1 mm mostly occurs at nighttime. Weak precipitation during the daytime may be caused by air advection, and strong precipitation at nighttime may be closely related with air convection. Both humidity and wind speed profiles show obvious fluctuation when precipitation occurs, and the greater the precipitation intensity, the larger the fluctuation. Moreover, the fluctuation of wind speed is small in the morning, large at noon and largest at night, presenting a similar diurnal cycle to that of convective activity over the TP, which is conductive to nighttime precipitation. Additionally, the inverse layer is accompanied by the inverse humidity layer, and wind speed presents multi-peaks distribution in its vertical structure. Both of these are closely related with the underlying surface and topography of Jiulong. More studies on physical mechanism and numerical simulation are necessary for better understanding the atmospheric phenomenon over the TP

Table_1_Transition patterns of metabolism-weight phenotypes over time: A longitudinal study using the multistate Markov model in China.DOCX

BackgroundA change in weight or metabolic status is a dynamic process, yet most studies have focused on metabolically healthy obesity (MHO) and the transition between MHO and metabolically unhealthy obesity (MUO); therefore, they have not fully revealed the nature of all possible transitions among metabolism-weight phenotypes over the years.MethodsThis was a longitudinal study based on a retrospective health check-up cohort. A total of 9,742 apparently healthy individuals aged 20–60 years at study entry were included and underwent at least two health check-ups. Six metabolism-weight phenotypes were cross-defined by body mass index (BMI) categories and metabolic status as follows: metabolically healthy normal weight (MHNW), metabolically healthy overweight (MHOW), MHO, metabolically unhealthy normal weight (MUNW), metabolically unhealthy overweight (MUOW), and MUO. A multistate Markov model was used to analyse all possible transitions among these phenotypes and assess the effects of demographic and blood indicators on the transitions.ResultsThe transition intensity from MUNW to MHNW was the highest (0.64), followed by the transition from MHO to MUO (0.56). The greatest sojourn time appeared in the MHNW state (3.84 years), followed by the MUO state (2.34 years), and the shortest sojourn time appeared in the MHO state (1.16 years). Transition intensities for metabolic improvement gradually decreased with BMI level as follows: 0.64 for MUNW to MHNW, 0.44 for MUOW to MHNW, and 0.27 for MUO to MHO; however, transition intensities for metabolic deterioration, including MHNW to MUNW, MHOW to MUOW, and MHO to MUO, were 0.15, 0.38, and 0.56, respectively. In the middle-aged male group, elevated alanine aminotransferase (ALT), aspartate aminotransferase (AST), and uric acid (UA) increased the risk of deterioration in weight and metabolic status and decreased the possibility of improvement.ConclusionMaintaining a normal and stable BMI is important for metabolic health. More attention should be given to males and elderly people to prevent their progression to an unhealthy metabolic and/or weight status. MHO is the most unstable phenotype and is prone to convert to the MUO state, and individuals with abnormal ALT, AST and UA are at an increased risk of transitioning to an unhealthy weight and/or metabolic status; therefore, we should be alert to abnormal indicators and MHO. Intervention measures should be taken early to maintain healthy weight and metabolic status.</p