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Abstract Background Gut microbiota imbalances have been suggested as a contributing factor to atrial fibrillation (AF), but the causal relationship is not fully understood. Objectives To explore the causal relationships between the gut microbiota and AF using Mendelian randomization (MR) analysis. Methods Summary statistics were from genome-wide association studies (GWAS) of 207 gut microbial taxa (5 phyla, 10 classes, 13 orders, 26 families, 48 genera, and 105 species) (the Dutch Microbiome Project) and two large meta-GWASs of AF. The significant results were validated in FinnGen cohort and over 430,000 UK Biobank participants. Mediation MR analyses were conducted for AF risk factors, including type 2 diabetes, coronary artery disease (CAD), body mass index (BMI), blood lipids, blood pressure, and obstructive sleep apnea, to explore the potential mediation effect of these risk factors in between the gut microbiota and AF. Results Two microbial taxa causally associated with AF: species Eubacterium ramulus (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.04–1.12, P = 0.0001, false discovery rate (FDR) adjusted p-value = 0.023) and genus Holdemania (OR 1.15, 95% CI 1.07–1.25, P = 0.0004, FDR adjusted p-value = 0.042). Genus Holdemania was associated with incident AF risk in the UK Biobank. The proportion of mediation effect of species Eubacterium ramulus via CAD was 8.05% (95% CI 1.73% − 14.95%, P = 0.008), while the proportion of genus Holdemania on AF via BMI was 12.01% (95% CI 5.17% − 19.39%, P = 0.0005). Conclusions This study provided genetic evidence to support a potential causal mechanism between gut microbiota and AF and suggested the mediation role of AF risk factors.

Background and Purpose We investigated the causal relationships between the gut microbiota (GM), stroke, and potential metabolite mediators using Mendelian randomization (MR). Methods We leveraged the summary statistics of GM (n=18,340 in the MiBioGen consortium), blood metabolites (n=115,078 in the UK Biobank), and stroke (cases n=60,176 and controls n=1,310,725 in the Global Biobank Meta-Analysis Initiative) from the largest genome-wide association studies to date. We performed bidirectional MR analyses to explore the causal relationships between the GM and stroke, and two mediation analyses, two-step MR and multivariable MR, to discover potential mediating metabolites. Results Ten taxa were causally associated with stroke, and stroke led to changes in 27 taxa. In the two-step MR, Bifidobacteriales order, Bifidobacteriaceae family, Desulfovibrio genus, apolipoprotein A1 (ApoA1), phospholipids in high-density lipoprotein (HDL_PL), and the ratio of apolipoprotein B to ApoA1 (ApoB/ApoA1) were causally associated with stroke (all P

ObjectivesOur aim was to investigate the interactive causal effects between gut microbiota and host urate metabolism and explore the underlying mechanism using genetic methods.MethodsWe extracted summary statistics from the abundance of 211 microbiota taxa from the MiBioGen (N =18,340), 205 microbiota metabolism pathways from the Dutch Microbiome Project (N =7738), gout from the Global Biobank Meta-analysis Initiative (N =1,448,128), urate from CKDGen (N =288,649), and replication datasets from the Global Urate Genetics Consortium (N gout =69,374; N urate =110,347). We used linkage disequilibrium score regression and bidirectional Mendelian randomization (MR) to detect genetic causality between microbiota and gout/urate. Mediation MR and colocalization were performed to investigate potential mediators in the association between microbiota and urate metabolism.ResultsTwo taxa had a common causal effect on both gout and urate, whereas the Victivallaceae family was replicable. Six taxa were commonly affected by both gout and urate, whereas the Ruminococcus gnavus group genus was replicable. Genetic correlation supported significant results in MR. Two microbiota metabolic pathways were commonly affected by gout and urate. Mediation analysis indicated that the Bifidobacteriales order and Bifidobacteriaceae family had protective effects on urate mediated by increasing docosahexaenoic acid. These two bacteria shared a common causal variant rs182549 with both docosahexaenoic acid and urate, which was located within MCM6/LCT locus.ConclusionsGut microbiota and host urate metabolism had a bidirectional causal association, implicating the critical role of host-microbiota crosstalk in hyperuricemic patients. Changes in gut microbiota can not only ameliorate host urate metabolism but also become a foreboding indicator of urate metabolic diseases.

Abstract Background Serum electrolytes were found to associate with type 2 diabetes. Our study aimed to stratify nondiabetes by clusters based on multiple serum electrolytes and evaluate their associations with risk of developing diabetes and longitudinal changes in glucose and lipid metabolic traits. Methods We performed a data‐driven cluster analysis in 4937 nondiabetes individuals aged ≥40 years at baseline from a cohort follow‐up for an average of 4.4 years. Cluster analysis was based on seven commonly measured serum electrolytes (iron, chlorine, magnesium, sodium, potassium, calcium, and phosphorus) by using the k‐means method. Results A total of 4937 nondiabetes individuals were classified into three distinct clusters, with 1635 (33.1%) assigned to Cluster A, 1490 (30.2%) to Cluster B, and 1812 (36.7%) to Cluster C. Individuals in Cluster A had higher serum chlorine, were older, and more were women. Individuals in Cluster B had higher serum iron and body mass index (BMI). Individuals in Cluster C had higher serum phosphorus, were younger, and had lower BMI. Cluster B had 1.41‐fold higher risk of developing diabetes and Cluster C’s risk was 1.33‐fold higher compared with Cluster A. Over an average follow‐up of 4.4 years, Cluster A showed a moderate and stable BMI, Cluster B showed an accelerated deterioration in glucose metabolism, and Cluster C showed the most sharply increased serum low‐density lipoprotein cholesterol level. Conclusions Clusters based on seven common serum electrolytes differed in diabetes risk and progression of glucose and lipid metabolic traits. Serum electrolytes clusters could provide a powerful tool to differentiate individuals into different risk stratification for developing type 2 diabetes.

Abstract Background We aimed to define refined body shapes by using multiple anthropometric traits that represent fat distribution, and evaluate their associations with risk of insulin resistance (IR) and cardiometabolic disorders in a Chinese population. Methods We performed a cross-sectional analysis in 6570 community-based participants aged ≥ 40 years. Four body circumferences (neck, waist, hip, and thigh) and their ratios were put simultaneously into an open-source Waikato Environment for Knowledge Analysis platform to select the worthiest indicators in determining IR. The ratio of the top 3 fat distribution indicators was used to define the refined body shapes. Results We defined 8 distinct body shapes based on sex-specific combinations of waist-to-hip ratio (WHR), waist-to-thigh ratio (WTR), and waist-to-neck ratio (WNR), which differed in participants’ distribution and risk of IR and related cardiometabolic disorders. In women, as compared to the low WHR-low WTR-low WNR shape, all body shapes were significantly associated with IR and related cardiometabolic disorders; while in men, the low WHR-high WTR-high WNR shape and the higher WHR related shapes were significantly associated with IR and related cardiometabolic disorders. Stratified by WHR, the results were consistent in women; however, no significant associations were detected in men. Conclusions We defined 8 distinct body shapes by taking WHR, WTR, and WNR, simultaneously into account, which differed in association with the risk of IR and related cardiometabolic disorders in women. This study suggests that body shapes defined by multiple anthropometric traits could provide a useful, convenient, and easily available method for identifying cardiometabolic risk.

Researchers use underwater acoustic equipment to explore the unknown ocean environment, which is one of the important means to understand and utilize the ocean. For underwater acoustic equipment, the application of underwater acoustic metamaterials is the premise to ensure and improve the performance of underwater acoustic communication, acoustic stealth, and sonar detection. Due to the limitations of mass density law and high hydrostatic pressure, traditional underwater acoustic materials cannot effectively absorb low-frequency sound waves and have low efficiency of elastic energy conversion. The sound absorption effect is poor under low frequency and high hydrostatic pressure. In recent years, with the development of acoustic metamaterials technology, all kinds of underwater acoustic metamaterials have also been proposed. Compared with sound waves propagating in the air, underwater sound is more difficult to control than air sound with the same frequency, so the design of underwater acoustic metamaterials is more complicated. This paper reviews the basic characteristics, development history of sound absorption, sound insulation decoupling, and underwater acoustic guided metamaterials, then the existing problems and the future development direction of underwater acoustic metamaterials are discussed.

BackgroundArtificial intelligence technology has become a mainstream trend in the development of medical informatization. Because of the complex structure and a large amount of medical data generated in the current medical informatization process, big data technology to assist doctors in scientific research and analysis and obtain high-value information has become indispensable for medical and scientific research.MethodsThis study aims to discuss the architecture of diabetes intelligent digital platform by analyzing existing data mining methods and platform building experience in the medical field, using a large data platform building technology utilizing the Hadoop system, model prediction, and data processing analysis methods based on the principles of statistics and machine learning. We propose three major building mechanisms, namely the medical data integration and governance mechanism (DCM), data sharing and privacy protection mechanism (DPM), and medical application and medical research mechanism (MCM), to break down the barriers between traditional medical research and digital medical research. Additionally, we built an efficient and convenient intelligent diabetes model prediction and data analysis platform for clinical research.ResultsResearch results from this platform are currently applied to medical research at Shanghai T Hospital. In terms of performance, the platform runs smoothly and is capable of handling massive amounts of medical data in real-time. In terms of functions, data acquisition, cleaning, and mining are all integrated into the system. Through a simple and intuitive interface operation, medical and scientific research data can be processed and analyzed conveniently and quickly.ConclusionsThe platform can serve as an auxiliary tool for medical personnel and promote the development of medical informatization and scientific research. Also, the platform may provide the opportunity to deliver evidence-based digital therapeutics and support digital healthcare services for future medicine.

The development of smart metamaterials has brought changes to human society, and various new products based on smart metamaterials are emerging endlessly. In recent years, smart electromagnetic metamaterials, smart acoustic metamaterials, smart mechanical metamaterials, smart thermal metamaterials and machine learning have attracted much attention in metamaterials. These fields share similar theories, such as multiphysics coupling fields, novel artificial cells and programmability. Through theoretical and technical research, smart metamaterials will show exquisite applications in many fields, such as antenna and optical communication systems, microwave imaging, acoustic stealth, thermal camouflage, etc. In particular, the characteristics of the personalized microstructure design of smart metamaterials perfectly match the characteristics of 3D printing. The combination of them leads the development of metamaterials, which are undoubtedly of great value. In this paper, focusing on the representative key technologies, we review the development history, main research directions and latest applications of smart metamaterials. Finally, the possible development direction of metamaterials is predicted.

As an important tool for monitoring the marine environment, safeguarding maritime rights and interests and building a smart ocean, underwater equipment has developed rapidly in recent years. Due to the problems of seawater corrosion, excessive deep-sea static pressure and noise interference in the marine environment and economy, the applicability of manufacturing materials must be considered at the beginning of the design of underwater equipment. Piezoelectric metamaterial is widely used in underwater equipment instead of traditional materials because the traditional materials can not meet the application requirements. In this paper, according to the application range of piezoelectric metamaterials in underwater equipment, the current application of piezoelectric metamaterials is reviewed from the aspects of sound insulation and energy conversion. On this basis, the future development prospect of piezoelectric metamaterials in underwater equipment is introduced.

Acoustic metamaterials, artificial composite structures with exotic material properties used to control elastic waves, have become a new frontier in physics, materials science, engineering and chemistry. In this paper, the research progress and development prospect of acoustic metamaterials are reviewed. Related studies on passive acoustic metamaterials and active acoustic metamaterials are introduced and compared. Additionally, we discuss approaches to material structure design, including topology optimization approaches, as well as bio-inspired and fractal geometry-based approaches to structure design. Finally, we summarize and look forward to the prospects and directions of acoustic metamaterial research. With the development of additive manufacturing technology, the research potential of acoustic metamaterials is huge.

Abstract Context Body composition may explain partially why non-obese individuals still at the risk of developing non-alcoholic fatty liver disease (NAFLD). The ratio of fat mass to fat-free mass (FM/FFM) has been proposed to assess the combined effect of different body compositions. Objective We aimed to investigate the associations of FM/FFM ratio with the risk of developing NAFLD and fibrosis and to identify the potential mediators according to obesity status. Methods This cohort study comprised 3419 adults age ≥ 40 years and free of NAFLD at baseline. Body composition was measured by bioelectrical impedance analysis. NAFLD was ascertained by ultrasonography and fibrosis was assessed by non-invasive score systems. Results For each 1 standard deviation increment in FM/FFM ratio, the odds ratio for the risk of NAFLD was 1.55 (95% confidence interval [CI] 1.23–1.95) in non-obese men, 1.33 (95% CI 1.08–1.65) in obese men, 1.42 (95% CI 1.44–1.67) in non-obese women, and 1.29 (95% CI 1.12–1.50) in obese women. Similar associations were also found between FM/FFM ratio and NAFLD with fibrosis. Mediation analysis showed that insulin resistance, triglycerides, high-density lipoprotein cholesterol, white blood cells, and total cholesterol mediated the association of FM/FFM ratio with NAFLD risk in specific sex and obesity subgroups. Conclusions The FM/FFM ratio significantly associated with the NAFLD and fibrosis risk in both non-obese and obese individuals. Different factors may mediate the association between body composition and NAFLD risk according to different obesity status.

ObjectivesWe aimed to investigate the association of circulating retinol-binding protein-4 (RBP4) levels with long-term cardiometabolic risk profiles and whether sex disparity mattered.MethodsWe included 784 non-diabetic participants aged 40 years and above from a well-defined community-based cohort at baseline in 2005 and they were invited to attend the on-site follow-up examination for two consecutive times with 3-year intervals in 2008 and 2011, respectively. Serum RBP4 was measured at baseline, and the anthropometry and biochemical measurements were performed at each visit. Generalized estimating equation models were used to assess the association of serum RBP4 levels with the dynamic changes in adiposity and glucolipid profile.ResultsBased on all the baseline and the 3- and 6-year follow-up data, baseline serum RBP4 levels (each 1-unit of log10RBP4) were significantly associated with waist circumference [β=3.12, 95% confidence interval (CI) (0.77, 5.47), P=0.01], fasting, and 2-h post-loading glucose [β=0.26 (0.05, 0.47), P=0.02, and 1.70 (1.29, 2.12), P< 0.0001], serum triglycerides [β=0.75, 95% CI (0.54, 0.96), P< 0.0001], total cholesterol [β=0.47, 95% CI [0.23 0.70], P

Lipoprotein (a) [Lp(a)] is a well-known risk factor for cardiovascular disease, but analysis on Lp(a) and renal dysfunction is scarce. We aimed to investigate prospectively the association of serum Lp(a) with the risk of reduced renal function, and further investigated whether diabetic or hypertensive status modified such association. Six thousand two hundred and fifty-seven Chinese adults aged ≤40 years and free of reduced renal function at baseline were included in the study. Reduced renal function was defined as estimated glomerular filtration rate 25 mg/dl), indicating a combined effect of diabetes and high Lp(a) on the reduced renal function risk. An elevated Lp(a) level was independently associated with risk of incident reduced renal function, especially in diabetic or hypertensive patients.

The vibration of flexible structures in spacecraft, such as large space deployable reflectors, solar panels and large antenna structure, has a great impact on the normal operation of spacecraft. Accurate vibration control is necessary, and the control of angular displacement is a difficulty of accurate control. In the traditional control method, the mode space control has a good effect on suppressing low-order modes, but there is control overflow. The effect of traveling wave control on low-order modes is worse than the former, but it has the characteristics of broadband control. It can better control high-order modes and reduce control overflow. In view of the advantages and disadvantages of the two control methods, based on Timoshenko beam theory, this paper uses vector mode function to analyze the modal of spacecraft cantilever beam structure, establishes the system dynamic equation, and puts forward an optimized traveling wave control method. As a numerical example, three strategies of independent mode space control, traditional traveling wave control and optimized traveling wave control are used to control the active vibration of beam angle. By comparing the numerical results of the three methods, it can be seen that the optimal control method proposed in this paper not only effectively suppresses the vibration, but also improves the robustness of the system, reflecting good control performance. An innovation of this paper is that the Timoshenko beam model is adopted, which considers the influence of transverse shear deformation and moment of inertia on displacement and improves the accuracy of calculation, which is important for spacecraft accessory structures with high requirements for angle control. Another innovation is that the optimized traveling wave control method is exquisite in mathematical processing and has good results in global and local vibration control, which is not available in other methods.

Background: Prolonged heart rate corrected QT (QTc) interval was reported to be associated with cardiovascular diseases (CVDs). Objective: There exists little data on the association between QTc interval and cardiovascular risk in Asian populations. We prospectively investigated the association of QTc interval with CVDs and vascular traits in a large cohort of Chinese adults. Methods: A total of 7,605 participants aged 40 years or older from a well-defined community without CVDs at baseline were included and followed up for an average of 4.5 years. Association of baseline QTc interval with incident CVDs was evaluated using Cox regression analysis. Associations of QTc interval with brachial-ankle pulse wave velocity (baPWV), carotid intima-media thickness (CIMT), and risk of microalbuminuria and peripheral arterial diseases (PAD) were secondarily examined. Results: Prolonged QTc interval (≥460 ms in women and ≥450 ms in men) was associated with 51% higher risk of total major CVDs (hazard ratio [HR] = 1.51, 95% confidence interval [CI] [1.20, 1.90]), particularly, 48% increased risk of stroke (95% CI [1.16, 1.88]). Prolonged QTc interval was positively associated with baPWV (β = 38.10 cm/s, standard error [SE] = 8.04, 'P' < 0.0001) and CIMT (β = 0.01 mm, SE = 0.01, P = 0.04). Prolonged QTc interval was associated with increased risk of incident microalbuminuria (odds ratio [OR] = 1.65, 95% CI [1.21, 2.24]) and PAD (2.49, 95% CI [1.35, 4.59]). Conclusions: Prolonged QTc interval is positively and significantly associated with increased risk of CVDs and related vascular traits in Chinese population.