Associations of polygenic risk scores with risks of stroke and its subtypes in Chinese

Background and purpose Previous studies, mostly focusing on the European population, have reported polygenic risk scores (PRSs) might achieve risk stratification of stroke. We aimed to examine the association strengths of PRSs with risks of stroke and its subtypes in the Chinese population. Methods Participants with genome-wide genotypic data in China Kadoorie Biobank were split into a potential training set (n=22 191) and a population-based testing set (n=72 150). Four previously developed PRSs were included, and new PRSs for stroke and its subtypes were developed. The PRSs showing the strongest association with risks of stroke or its subtypes in the training set were further evaluated in the testing set. Cox proportional hazards regression models were used to estimate the association strengths of different PRSs with risks of stroke and its subtypes (ischaemic stroke (IS), intracerebral haemorrhage (ICH) and subarachnoid haemorrhage (SAH)). Results In the testing set, during 872 919 person-years of follow-up, 8514 incident stroke events were documented. The PRSs of any stroke (AS) and IS were both positively associated with risks of AS, IS and ICH (p<0.05). The HR for per SD increment (HRSD) of PRSAS was 1.10 (95% CI 1.07 to 1.12), 1.10 (95% CI 1.07 to 1.12) and 1.13 (95% CI 1.07 to 1.20) for AS, IS and ICH, respectively. The corresponding HRSD of PRSIS was 1.08 (95% CI 1.06 to 1.11), 1.08 (95% CI 1.06 to 1.11) and 1.09 (95% CI 1.03 to 1.15). PRSICH was positively associated with the risk of ICH (HRSD=1.07, 95% CI 1.01 to 1.14). PRSSAH was not associated with risks of stroke and its subtypes. The addition of current PRSs offered little to no improvement in stroke risk prediction and risk stratification. Conclusions In this Chinese population, the association strengths of current PRSs with risks of stroke and its subtypes were moderate, suggesting a limited value for improving risk prediction over traditional risk factors in the context of current genome-wide association study under-representing the East Asian population

“Island-bridge”-structured nanofluidic membranes for high-performance aqueous energy conversion and storage

The attainment of carbon neutrality requires the development of aqueous energy conversion and storage devices. However, these devices exhibit limited performance due to the permeability–selectivity trade-off of permselective membranes as core components. Herein, we report the application of a synergistic approach utilizing two-dimensional nanoribbons-entangled nanosheets to rationally balance the permeability and selectivity in permselective membranes. The nanoribbons and nanosheets can be self-assembled into a nanofluidic membrane with a distinctive “island-bridge” configuration, where the nanosheets serve as isolated islands offering adequate ionic selectivity owing to their high surface charge density, meanwhile bridge-like nanoribbons with low surface charge density but high aspect ratio remarkably enhance the membrane’s permeability and water stability, as verified by molecular simulations and experimental investigations. Using this approach, we developed a high-performance graphene oxide (GO) nanosheet/GO nanoribbon (GONR) nanofluidic membrane and achieved an ultrahigh power density of 18.1 W m–2 in a natural seawater|river water osmotic power generator, along with a high Coulombic efficiency and an extended lifespan in zinc metal batteries. The validity of our island-bridge structural design is also demonstrated for other nanosheet/nanoribbon composite membranes, providing a promising path for developing reliable aqueous energy conversion and storage devices

Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank

Background: Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population. Methods: Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training (n = 28,490) and testing sets (n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21–I23 and fatal I20–I25) and soft CAD (all fatal or nonfatal I20–I25) were analyzed separately. Results: In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19–1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (–0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4–6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model. Conclusions: In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little to no improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction

Social Exclusion and Switching Behaviour of Green Products: The Mediating role of Control Demand

This study examined the impact of social exclusion and green product conversion behaviour. One study has conducted the result showed that consumers who experienced social exclusion showed more switching behaviour of green product than those who not feel excluded. This effect is mediated by the control demand, while the individual’s self-construction type plays a moderate role

Research on the function of single jersey based on the 3D channel structure

The main purpose of this experimental study is to determine the thermal properties and the moisture conduction function of a single jersey with a three-dimensional channel structure. As the channel structure of single jersey is gradually applied in the functional sportswear sector, the channel structure has been knitted by single jacquard technology for research purposes. Firstly, the formation principle and the structural unit of knitted fabric with the channel structure were explained. Then, the effects of channel structure with different sizes on thermal insulation, quick-drying, wicking height, and moisture management performance of the fabrics were investigated. Finally, the performance characteristics of the channel structure fabric were analyzed through the channel structure model. The analysis obtains that the channel structure of the sample holds more stagnant air and a large evaporation area. Moreover, as the courses or wales of structural units increase, the thermal insulation rate and the evaporation rate of the fabric improve accordingly. Also, it has a superior effect on the improvement of the wicking effect and the unidirectional transmission of the fabrics. However, when the structural unit exceeds a particular value, the fabric structure begins to deform, which makes its wicking height and unidirectional transmission properties decline. It provides a reference for the design and development of the 3D channel structure of the functional knitted fabric

3-D Simulation of Double-Bar Plush Fabrics with Jacquard Patterns

A realistic computerized simulation of double-bar plush fabrics can result in a time-saving development process with high quality. Based on basic analysis of jacquard principles, a fast 3-D simulation method of warp-knitted plush fabrics is proposed by using a geometry shader on GPU. Firstly, pile areas and non-pile areas are identified according to the jacquard design graphs and chain notations. According to the directions of observation and raised pile, two layered chips are formed in the geometry shader with an approach of multi-layered textures. To ensure that the simulated piles resemble the real ones, the directions of the piles are randomized with the Perlin noise method. One pile is generated along its length with numerous layers in the plush fabric model. Simulation results of piles on both the technical face and technical back are obtained via the model built above, which is confirmed with practicability and efficiency. This 3D simulation approach improves the visualization appearance of piles just as they are actually raised

Simplified Relation Model of Soil Saturation Permeability Coefficient and Air-Entry Value and Its Application

Based on the Tao and Kong (TK) model and the fractal model of the soil–water characteristic curve, a simplified model of the relationship between the saturated permeability coefficient and the air-entry value is established in this study: ks = k0ψa−2. It is shown that the saturated permeability coefficient of soil is determined by its maximum pore size. In order to facilitate the mutual prediction of saturation permeability coefficient and air-entry value, based on the data of five types of soil in the UNSODA database, the comprehensive proportionality constant k0 of the five types of soil were obtained: sand k0 = 0.03051; clay k0 = 0.001878; loam k0 = 0.001426; sandy loam k0 = 0.009301; and silty clay loam k0 = 0.0007055. Based on the obtained comprehensive proportionality constant k0 and the relationship model between saturated permeability coefficient and air intake value, the air-entry value of five kinds of soils in the existing literature and the SoilVision database were calculated. Comparing the calculated air-entry value with the measured one, the results showed that the model simplifies the traditional air-entry value prediction method to some extent and can effectively predict the air-entry value of different types of soil. On the whole, the model better predicts the air-entry value for sandy, clay, and silty clay loam than loam and sandy loam

Seamless Weft Knit Vest with Integrated Needle Sensing Zone for Monitoring Shoulder Movement: A First Methodological Study

The integration of textile-based flexible sensors and electronic devices has accelerated the development of wearable textiles for posture monitoring. The complexity of the processes required to create a complete monitoring product is currently reflected in three main areas. The first is the sensor production process, which is complex. Second, the integration of the sensor into the garment requires gluing or stitching. Finally, the production of the base garment requires cutting and sewing. These processes deteriorate the user experience and hinder the commercial mass production of wearable textiles. In this paper, we knitted a one-piece seamless knitted vest (OSKV) utilizing the one-piece seamless knitting technique and positioned an embedded needle sensing zone (EHSZ) with good textile properties and electrical performance for monitoring human shoulder activity. The EHSZ was knitted together with the OSKV, eliminating the need for an integration process. The EHSZ exhibited good sensitivity (GF = 2.23), low hysteresis (0.29 s), a large stretch range (200%), and excellent stability (over 300 cycles), satisfying the requirement to capture a wide range of deformation signals caused by human shoulder movements. The OSKV described the common vest process structure without the stitching process. Furthermore, OSKV fulfilled the demand for seamless and trace-free monitoring while effortlessly and aesthetically satisfying the knitting efficiency of commercial garments

Simplified Relation Model of Soil Saturation Permeability Coefficient and Air-Entry Value and Its Application

Based on the Tao and Kong (TK) model and the fractal model of the soil–water characteristic curve, a simplified model of the relationship between the saturated permeability coefficient and the air-entry value is established in this study: ks = k0ψa−2. It is shown that the saturated permeability coefficient of soil is determined by its maximum pore size. In order to facilitate the mutual prediction of saturation permeability coefficient and air-entry value, based on the data of five types of soil in the UNSODA database, the comprehensive proportionality constant k0 of the five types of soil were obtained: sand k0 = 0.03051; clay k0 = 0.001878; loam k0 = 0.001426; sandy loam k0 = 0.009301; and silty clay loam k0 = 0.0007055. Based on the obtained comprehensive proportionality constant k0 and the relationship model between saturated permeability coefficient and air intake value, the air-entry value of five kinds of soils in the existing literature and the SoilVision database were calculated. Comparing the calculated air-entry value with the measured one, the results showed that the model simplifies the traditional air-entry value prediction method to some extent and can effectively predict the air-entry value of different types of soil. On the whole, the model better predicts the air-entry value for sandy, clay, and silty clay loam than loam and sandy loam