Association between plasma maresin 1 and the risk of atherosclerotic cardiovascular disease in Chinese adults: A community-based cohort study.

BACKGROUND AND AIMS: It has been reported that maresin 1 (MaR1) is able to protect against the development of atherogenesis in cellular and animal models. This study was performed to investigate whether plasma MaR1 is associated with the risk of atherosclerotic cardiovascular disease (ASCVD) at the population level. METHODS AND RESULTS: The study included 2822 non-ASCVD participants from a community-based cohort who were followed for about 8 years. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) for ASCVD events according to baseline MaR1 quartiles were calculated using the Cox proportional hazards model. During follow-up, a total of 290 new ASCVD cases were identified. The restricted cubic spline analysis indicated a linear dose-response association between plasma MaR1 and incident ASCVD. In addition, the adjusted-HR (95% CI) for ASCVD events associated with one standard deviation increase in MaR1 was 0.79 (0.68-0.91). Moreover, the adjusted-HRs (95% CIs) for ASCVD events associated with the second, third and fourth quartiles versus the first quartile of plasma MaR1 were 1.00, 1.04 (0.76, 1.42), 0.88 (0.64, 1.22) and 0.58 (0.41, 0.84), respectively. Mediation analyses showed that the association between MaR1 and incident ASCVD was partially mediated by small dense low-density lipoprotein cholesterol, with a mediation proportion of 9.23%. Further, the net reclassification improvement and integrated discrimination improvement of ASCVD risk were significantly improved when MaR1 was added to basic model established by conventional risk factors (all p < 0.01). CONCLUSIONS: Elevated plasma MaR1 concentrations are associated with a lower risk of ASCVD development.

Efficient K-Storage of Fe-Coupled Organic Molecule Anode in Ether-Based Electrolytes.

Given these advantages of widely designable structures and environmentally friendly characteristics, organic electrode materials (OEMs) are considered to be promising electrode materials for alkaline metal-ion batteries. However, their large-scale application is hampered by insufficient specific capacity and rate performance. Here, Fe2+ is coupled to the anhydride molecule NTCDA to form a novel K-storage anode Fe-NTCDA. In this way, the working potential of Fe-NTCDA anode is reduced, which makes it more suitable to be used as an anode material. Meanwhile, the electrochemical performance is significantly improved due to the increase in K-storage sites. Moreover, electrolytes regulation is implemented to optimize the K-storage behavior, resulting into a high specific capacity of 167 mAh/g after 100 cycles at 50 mA/g and 114 mAh/g even at 500 mA/g in the 3 M KFSI/DME electrolytes.

Fine-mapping and QTL tissue-sharing information improves the reliability of causal gene identification.

The integration of transcriptomic studies and genome-wide association studies (GWAS) via imputed expression has seen extensive application in recent years, enabling the functional characterization and causal gene prioritization of GWAS loci. However, the techniques for imputing transcriptomic traits from DNA variation remain underdeveloped. Furthermore, associations found when linking eQTL studies to complex traits through methods like PrediXcan can lead to false positives due to linkage disequilibrium between distinct causal variants. Therefore, the best prediction performance models may not necessarily lead to more reliable causal gene discovery. With the goal of improving discoveries without increasing false positives, we develop and compare multiple transcriptomic imputation approaches using the most recent GTEx release of expression and splicing data on 17,382 RNA-sequencing samples from 948 post-mortem donors in 54 tissues. We find that informing prediction models with posterior causal probability from fine-mapping (dap-g) and borrowing information across tissues (mashr) can lead to better performance in terms of number and proportion of significant associations that are colocalized and the proportion of silver standard genes identified as indicated by precision-recall and receiver operating characteristic curves. All prediction models are made publicly available at predictdb.org.

A Statistical Framework for Mapping Risk Genes from De Novo Mutations in Whole-Genome-Sequencing Studies.

Analysis of de novo mutations (DNMs) from sequencing data of nuclear families has identified risk genes for many complex diseases, including multiple neurodevelopmental and psychiatric disorders. Most of these efforts have focused on mutations in protein-coding sequences. Evidence from genome-wide association studies (GWASs) strongly suggests that variants important to human diseases often lie in non-coding regions. Extending DNM-based approaches to non-coding sequences is challenging, however, because the functional significance of non-coding mutations is difficult to predict. We propose a statistical framework for analyzing DNMs from whole-genome sequencing (WGS) data. This method, TADA-Annotations (TADA-A), is a major advance of the TADA method we developed earlier for DNM analysis in coding regions. TADA-A is able to incorporate many functional annotations such as conservation and enhancer marks, to learn from data which annotations are informative of pathogenic mutations, and to combine both coding and non-coding mutations at the gene level to detect risk genes. It also supports meta-analysis of multiple DNM studies, while adjusting for study-specific technical effects. We applied TADA-A to WGS data of ∼300 autism-affected family trios across five studies and discovered several autism risk genes. The software is freely available for all research uses.

Atomic-Scale Dispersed Fe-Based Catalysts Confined on Nitrogen-Doped Graphene for Li-S Batteries: Polysulfides with Enhanced Conversion Efficiency.

Lithium-sulfur batteries have been considered as potential electrochemical energy-storage devices owing to their satisfactory theoretical energy density. Nonetheless, the inferior conversion efficiency of polysulfides in essence leads to fast capacity decay during the discharge/charge cycle. In this work, it is successfully demonstrated that the conversion efficiency of lithium polysulfides is remarkably enhanced by employing a well-distributed atomic-scale Fe-based catalyst immobilized on nitrogen-doped graphene (Fe@NG) as a coating of separator in lithium-sulfur batteries. The quantitative electrocatalytic efficiency of the conversion of lithium polysulfides is determined through cyclic voltammetry. It is also proven that the Fe-NX configuration with highly catalytic activity is quite beneficial for the conversion of lithium polysulfides. In addition, the adsorption and permeation experiments distinctly indicate that the strong anchoring effect, originated from the charge redistribution of N doping into the graphene matrix, inhibits the movement of lithium polysulfides. Thanks to these advantages, if the as-prepared Fe@NG catalyst is combined with polypropylene and applied as a separator (Fe@NG/PP) in Li-S batteries, a high initial capacity (1616 mA h g-1 at 0.1 C), excellent capacity retention (93 % at 0.2 C, 70 % at 2 C), and superb rate performance (820 mA h g-1 at 2 C) are achieved.

Optimal Configuration of N-Doped Carbon Defects in 2D Turbostratic Carbon Nanomesh for Advanced Oxygen Reduction Electrocatalysis.

The charge redistribution strategy driven by heteroatom doping or defect engineering has been developed as an efficient method to endow inert carbon with significant oxygen reduction reaction (ORR) activity. The synergetic effect between the two approaches is thus expected to be more effective for manipulating the charge distribution of carbon materials for exceptional ORR performance. Herein we report a novel molecular design strategy to achieve a 2D porous turbostratic carbon nanomesh with abundant N-doped carbon defects (NDC). The molecular level integration of aromatic rings as the carbon source and urea units as the N source and sacrificial template into the novel precursor of polyurea (PU) promises the formation of abundant carbon edge defects and N doping sites. A special active site-a carbon edge defect doped with a graphitic valley N atom-was revealed to be responsible for the exceptional ORR performance of NDC material.

Gold Nanoparticle-Induced Photocurrent Quenching and Recovery of Polymer Dots: Toward Signal-On Energy-Transfer-Based Photocathodic Bioanalysis of Telomerase Activity in Cell Extracts.

Energy transfer (ET) in photoelectrochemical (PEC) bioanalysis is usually generated between noble metal nanoparticles (NPs) and traditional inorganic quantum dots (QDs). Using the innovative polymer dot (Pdot)-involved ET, this work reports the first signal-on and cathodic PEC bioanalysis toward telomerase (TE) activity in cell extracts. Specifically, the sequential binding of capture DNA (cDNA), telomerase primer sequence (TS), and Au NP-labeled probe DNA (Au NP-pDNA) on the electrode would place the Au NPs in close proximity of the Pdots, leading to obvious quenching of the cathodic photocurrent. The subsequent extension of the TS by TE in the presence of deoxyribonucleoside triphosphates (dNTPs) would then release the Ag NP-pDNA from the electrode, leading to the recovery of the photocurrent. On the basis of the Au NP-induced photocurrent quenching and the recovery of Pdots, a sensitive biosensor could thus be developed by tracking the photocurrents to probe the TE activity. This strategy allows for signal-on and cathodic PEC bioanalysis of TE, which can be easily extended for numerous other targets of interest. We believe this work could offer a new perspective for the rational implementation of Pdot-involved ET for advanced PEC bioanalysis.

Semiconducting CuO Nanotubes: Synthesis, Characterization, and Bifunctional Photocathodic Enzymatic Bioanalysis.

This work reports the synthesis, characterization, and application of bifunctional semiconducting CuO nanotubes (NTs) electrode for innovative synergized cathodic photoelectrochemical (PEC) enzymatic bioanalysis. Specifically, CuO NTs electrode was fabricated by surface oxidation of the copper foil in an alkaline aqueous solution with (NH4)2S2O8 and then annealed in air at 200 °C. After the subsequent coupling with the model enzyme of xanthine oxidase (XOD), the resulted photocathodic enzyme biosensor exhibited good analytical performance of rapid response, high stability, and good sensitivity. Especially, due to the unique catalytic property of CuO toward H2O2, a novel enzymatic cascade design between biological catalyst (XOD as natural enzyme) and biomimetic catalyst (CuO as the peroxidase mimetics) was constructed, and the dual-catalyst system with special synergy effect could achieve the cathodic PEC guanine bioanalysis with enhanced efficiency. In the determination, the cathodic photocurrent was found to be proportional to the guanine concentration, which was different from the commonly observed O2-dependent suppression of the photocurrent. In all, such a bifunctional CuO NTs-based PEC bioassay format has not been reported. The success of this work can offer great chances for further development and implementation of novel CuO-based PEC bioanalytical systems. More importantly, the strategy proposed here could contribute to the development of an original prototype for general PEC enzymatic bioanalysis.

Controllable Construction of Core-Shell Polymer@Zeolitic Imidazolate Frameworks Fiber Derived Heteroatom-Doped Carbon Nanofiber Network for Efficient Oxygen Electrocatalysis.

Designing rational nanostructures of metal-organic frameworks based carbon materials to promote the bifunctional catalytic activity of the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is highly desired but still remains a great challenge. Herein, an in situ growth method to achieve 1D structure-controllable zeolitic imidazolate frameworks (ZIFs)/polyacrylonitrile (PAN) core/shell fiber (PAN@ZIFs) is developed. Subsequent pyrolysis of this precursor can obtain a heteroatom-doped carbon nanofiber network as an efficient bifunctional oxygen electrocatalyst. The electrocatalytic performance of derived carbon nanofiber is dominated by the structures of PAN@ZIFs fiber, which is facilely regulated by efficiently controlling the nucleation and growth process of ZIFs on the surface of polymer fiber as well as optimizing the components of ZIFs. Benefiting from the core-shell structures with appropriate dopants and porosity, as-prepared catalysts show brilliant bifunctional ORR/OER catalytic activity and durability. Finally, the rechargeable Zn-air battery assembled from the optimized catalyst (CNF@Zn/CoNC) displays a peak power density of 140.1 mW cm-2 , energy density of 878.9 Wh kgZn-1 , and excellent cyclic stability over 150 h, giving a promising performance in realistic application.

MOF-Based Metal-Doping-Induced Synthesis of Hierarchical Porous CuN/C Oxygen Reduction Electrocatalysts for Zn-Air Batteries.

A transition-metal-nitrogen/carbon (TM-N/C, TM = Fe, Co, Ni, etc.) system is a popular, nonprecious-metal oxygen reduction reaction (ORR) electrocatalyst for fuel cell and metal-air battery applications. However, there remains a lack of comprehensive understanding about the ORR electrocatalytic mechanism on these catalysts, especially the roles of different forms of metal species on electrocatalytic performance. Here, a novel CuN/C ORR electrocatalyst with a hybrid Cu coordination site is successfully fabricated with a simple but efficient metal-organic-framework-based, metal-doping-induced synthesis strategy. By directly pyrolyzing Cu-doped zeolitic-imidazolate-framework-8 polyhedrons, the obtained CuN/C catalyst can achieve a high specific surface area of 1182 m2 g-1 with a refined hierarchical porous structure and a high surface N content of 11.05 at%. Moreover, regulating the Cu loading can efficiently tune the states of Cu(II) and Cu0 , resulting in the successful construction of a highly active hybrid coordination site of NCu(II)Cu0 in derived CuN/C catalysts. As a result, the optimized 25% CuN/C catalyst possesses a high ORR activity and stability in 0.1 m KOH solution, as well as excellent performance and stability in a Zn-air battery.

Inverted U-Shaped Association of Plasma Resolvin D2 With Atherosclerotic Cardiovascular Disease and the Mediation Effects of Serum Cholesterol: A Chinese Community-Based Study.

BACKGROUND: Resolvin D2 (RvD2) has been reported to protect against the development of atherosclerosis in animal models. The objective of this study was to examine the prospective association between plasma RvD2 and the risk of atherosclerotic cardiovascular disease (ASCVD) at the population level. METHODS AND RESULTS: A cohort of 2633 community-dwelling individuals aged 35-60 years was followed for 8 years in this study. Adjusted hazard ratios and 95% CIs for ASCVD outcomes according to baseline RvD2 levels were calculated using Cox proportional hazards models. Mediation analysis was used to test the indirect effect of serum cholesterol indicators on the association between RvD2 and ASCVD probability. In total, 284 new cases of ASCVD were identified during follow-up. An inverted U-shaped association between natural log (ln)-transformed RvD2 and incident ASCVD was determined, and the threshold value for lnRvD2 was 3.87. Below the threshold, each unit increase in lnRvD2 was associated with a 2.05-fold increased risk of ASCVD (95% CI, 1.13-3.74; P=0.019). Above the threshold, each unit increase in lnRvD2 was associated with a 36% reduced risk of ASCVD (95% CI, 0.51-0.80; P<0.001). In addition, the association between RvD2 and ASCVD probability was partially mediated by high-density lipoprotein cholesterol (15.81%) when lnRvD2 <3.87, but by total cholesterol (30.23%) and low-density lipoprotein cholesterol (30.13%) when lnRvD2 ≥3.87. CONCLUSIONS: Both lower and higher RvD2 levels are associated with a reduced risk of ASCVD, forming an inverted U-shaped relationship. Furthermore, this association is partially mediated by total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol.

On the problem of inflation in transcriptome-wide association studies.

Hundreds of thousands of loci have been associated with complex traits via genome-wide association studies (GWAS), but an understanding of the mechanistic connection between GWAS loci and disease remains elusive. Genetic predictors of molecular traits are useful for identifying the mediating roles of molecular traits and prioritizing actionable targets for intervention, as demonstrated in transcriptome-wide association studies (TWAS) and related studies. Given the widespread polygenicity of complex traits, it is imperative to understand the effect of polygenicity on the validity of these mediator-trait association tests. We found that for highly polygenic target traits, the standard test based on linear regression is inflated Eχtwas2>1. This inflation has implications for all TWAS and related methods where the complex trait can be highly polygenic-even if the mediating trait is sparse. We derive an asymptotic expression of the inflation, estimate the inflation for gene expression, metabolites, and brain image derived features, and propose a solution to correct the inflation.

Screening Nickel-Doped Mo2 C Nanorod Arrays for Ultrastable and Efficient Hydrogen Evolution over a Wide pH Range.

Green hydrogen, using sustainable energy to decompose water to produce hydrogen, is regarded as the ideal and effective connection to convert electricity into chemical energy. Herein, well designed Ni-doped Mo2 C nanorod electrodes self-supported on three types of substrates (Ni foam, Cu foam and stainless steel wire mesh) with outstanding gas resistance and prominent corrosion resistance were assembled together to build up a wide pH applicable electrode for Hydrogen Evolution. In particular, Ni-doped Mo2 C nanorod arrays on stainless steel wire mesh donated as Ni-Mo2 C@SSW exhibited remarkable electrocatalytic properties towards hydrogen evolution reaction with superior overpotentials both in 1 M KOH and 0.5 M H2 SO4 (102 mV and 106 mV at the current density of 10 mA cm-2 ) and incomparable continuous durability. This work provides the possibility for the realization of low cost, high activity and ultra-stable durability HER electrocatalysts in practical industrial application.

Defective Carbon Derived Using a Dissolution-Recrystallization Strategy for Oxygen Reduction Electrocatalysis.

Dopant-free defective carbon electrocatalysts have been considered as promising alternatives to traditional precious metal electrocatalysts recently. Compared with precious metal catalysts and transition-metal catalysts, since there are no metals doped, electrochemical devices assembled with dopant-free defective carbons are free from environmental pollution and subsequent recovery problems. In order to obtain abundant carbon defects with high-intrinsic catalytic activity, the synthesis of dopant-free defective carbons requires complex and harsh preparation conditions. Therefore, the construction of active defects with efficient utilization, especially through a simple process, is still a great challenge for the development of dopant-free defective carbon electrocatalysts. Herein, dissolution-recrystallization strategy was employed to design Zn-MOF-74 precursors for the synthesis of dopant-free defective carbons, realizing the synchronous manipulation of high ratio of carbon defects and highly exposed mass transfer channels. One-dimensional porous defective carbon nanorods (d-CNRs), which exhibited excellent oxygen reduction reaction (ORR), electrocatalytic activity, and molecular selectivity, were synthesized by directly carbonizing rodlike Zn-MOF-74 precursors. Attributed to the dissolution-recrystallization strategy, with the activation of in situ-formed ZnO, the synthesized d-CNRs exhibited unique pore-crack nested porous structures, which carried abundant defects as activity sites for ORR and showed a surprisingly high specific surface area of 2459 m2/g with a high ratio of mesopores. d-CNRs also showed promising applications in Zn-air batteries with a stable long-term discharge of no obvious voltage drop after 60 h. The dissolution-recrystallization strategy provided a simple controllable pathway for the efficient construction of dopant-free defective carbon electrocatalysts.

Molecular Simulation of Electron Traps in Epoxy Resin/Graphene Oxide Nanocomposites.

Trapped space charges in epoxy composite distort the electric field, which will induce the failure of the insulation system, and nano graphene oxide may inhibit the curing behavior of epoxy resin matrix. This paper analyzes how the two interfaces affect the electron traps of epoxy resin/graphene oxide systems with different nanofiller contents. The electron affinity energy of epoxy resin matrix and nano filler molecules in the epoxy resin/graphene oxide system is calculated based on quantum chemistry. It is found that nano graphene oxide has a strong electron affinity energy and is easier to capture electrons. Then the influence of the interface formed by the epoxy resin matrix and the nano graphene oxide on the electron transfer ability is calculated. The epoxy resin matrix contains the electron transfer ability of interfaces formed by nano graphene oxide and the molecular chain is different from that of unreacted molecules. The results can provide a reference for the modification of epoxy resin/graphene oxide nanocomposites.

Polygenic transcriptome risk scores (PTRS) can improve portability of polygenic risk scores across ancestries.

BACKGROUND: Polygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance in populations of non-European ancestry. RESULTS: We introduce the polygenic transcriptome risk score (PTRS), which is based on predicted transcript levels (rather than SNPs), and explore the portability of PTRS across populations using UK Biobank data. CONCLUSIONS: We show that PTRS has a significantly higher portability (Wilcoxon p=0.013) in the African-descent samples where the loss of performance is most acute with better performance than PRS when used in combination.

Decoupling layer metal-organic frameworks via ligand regulation to achieve ultra-thin carbon nanosheets for oxygen reduction electrocatalysis.

2D imidazole MOFs are considered to be ideal carbon precursors for oxygen reduction reactions owing to their adjustable ligand components and durable coordination mode. Due to the massive electron delocalization in the lamella, the conjugative effect among 2D MOF layers immensely restricts the exposure of catalytic sites after carbonization, which makes the decoupling layer extremely important on the premise of ensuring activity. Herein, atomic thickness ultra-thin zinc-imidazole MOF precursors were prepared through a bottom-up ligand regulated strategy to achieve the aim of lamellar decoupling. The introduction of heterologous ligands excites stable delocalized electrons, resulting in a decrease in the interlayer force of 2D zinc-imidazole MOF precursors. Subsequent salt template-supported ammonia pyrolysis assisted the MOF-derived carbon sheets to grow along the transverse direction and optimize pore size distribution as did the doping nitrogen type. The MOF-derived carbon sheets demonstrated increasing mesopores and fringe graphitic N which could significantly promote the mass transfer and electron transfer speed during the oxygen reduction reaction. In addition, the obtained ultra-thin carbon delivered an outstanding onset potential (0.98 V vs. RHE) and durability (retaining 91% of the initial current after 12000 s of operation), showing tremendous commercial prospects in sustainable energy.

A scalable unified framework of total and allele-specific counts for cis-QTL, fine-mapping, and prediction.

Genetic studies of the transcriptome help bridge the gap between genetic variation and phenotypes. To maximize the potential of such studies, efficient methods to identify expression quantitative trait loci (eQTLs) and perform fine-mapping and genetic prediction of gene expression traits are needed. Current methods that leverage both total read counts and allele-specific expression to identify eQTLs are generally computationally intractable for large transcriptomic studies. Here, we describe a unified framework that addresses these needs and is scalable to thousands of samples. Using simulations and data from GTEx, we demonstrate its calibration and performance. For example, mixQTL shows a power gain equivalent to a 29% increase in sample size for genes with sufficient allele-specific read coverage. To showcase the potential of mixQTL, we apply it to 49 GTEx tissues and find 20% additional eQTLs (FDR < 0.05, per tissue) that are significantly more enriched among trait associated variants and candidate cis-regulatory elements comparing to the standard approach.

Balance of N-Doping Engineering and Carbon Chemistry to Expose Edge Graphitic N Sites for Enhanced Oxygen Reduction Electrocatalysis.

Nitrogen-doped nanocarbon materials (NCMs) have been developed as promising metal-free oxygen reduction reaction (ORR) electrocatalysts. However, insufficient attention on the balance of N-doping engineering and carbon chemistry significantly suppressed the revelation of the real active configurations as well as the ORR mechanism for NCMs. Herein, 1,4-phenylenediurea (BDU) with multifunctional blocks was designed for the synthesis of NCMs, realizing synchronous manipulation of N-doping engineering and carbon chemistry. The good balance between N-doping engineering (especially graphitic edge N configurations) and carbon chemistry (including the specific surface area, porosity distribution, and graphitization degree) at a pyrolysis temperature of 1000 °C resulted in the best ORR performance for obtaining N-doped carbon nanorod (NCR) materials. A general descriptor χ was then proposed for evaluating the balance states between N-doping engineering and carbon chemistry. The prediction of the ORR performance of NCMs from their physical properties as well as searching for the optimal active configuration from the relationships between ORR performance and different configurations can be realized from such a practical descriptor, which can also be extended to other nanocarbon-based metal-free electrocatalytic reactions for deeply understanding their electrocatalytic mechanisms.

Exploiting the GTEx resources to decipher the mechanisms at GWAS loci.

The resources generated by the GTEx consortium offer unprecedented opportunities to advance our understanding of the biology of human diseases. Here, we present an in-depth examination of the phenotypic consequences of transcriptome regulation and a blueprint for the functional interpretation of genome-wide association study-discovered loci. Across a broad set of complex traits and diseases, we demonstrate widespread dose-dependent effects of RNA expression and splicing. We develop a data-driven framework to benchmark methods that prioritize causal genes and find no single approach outperforms the combination of multiple approaches. Using colocalization and association approaches that take into account the observed allelic heterogeneity of gene expression, we propose potential target genes for 47% (2519 out of 5385) of the GWAS loci examined.