Education and metabolic syndrome: a Mendelian randomization study.

Aims: The metabolic syndrome (MetS), a collection of conditions that heighten the risk of disease development and impose economic burdens on patients. However, the causal relationship between education and MetS was uncertain. In this study, the Mendelian randomization (MR) method was employed to elucidate the potential causal link between education and the MetS and its components.

Accelerating Toluene Oxidation over Boron-Titanium-Oxygen Interface: Steric Hindrance of the Methyl Group Induced by the Plane-Adsorption Configuration.

Elimination of dilute gaseous toluene is one of the critical concerns within the field of indoor air remediation. The typical degradation route on titanium-based catalysts, "toluene-benzaldehyde-carbon dioxide", necessitates the oxidation of the methyl group as a prerequisite for photocatalytic toluene oxidation. However, the inherent planar adsorption configuration of toluene molecules, dominated by the benzene rings, leads to significant steric hindrance for the methyl group.

CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolution.

Recently, deep convolution neural networks (CNNs) steered face super-resolution methods have achieved great progress in restoring degraded facial details by joint training with facial priors. However, these methods have some obvious limitations. On the one hand, multi-task joint learning requires additional marking on the dataset, and the introduced prior network will significantly increase the computational cost of the model.

A near infrared fluorescent probe for rapid sensing of peroxynitrite in living cells and breast cancer mice.

Peroxynitrite (ONOO) plays an essential role in numerous physiological and pathological processes owing to its strong oxidation and nitrification. Many studies have shown that ONOO abnormalities are associated with inflammatory diseases, even cancer, such as arthritis, hepatitis, pneumonia, and breast cancer. Thus, developing a trustworthy technology to monitor ONOO levels is critical in inflammatory or cancer illnesses.

Successful Management of Late Sinus Graft Infection via Functional Endoscopic Sinus Surgery and Press-Fit Block Bone Graft: A Case Report.

The purpose of this case report is to feature an interesting case where a staged approach was used to manage a failed implant site that led to a late sinus graft infection and sinusitis with an oroantral fistula (OAF), by using functional endoscopic sinus surgery (FESS) and an intraoral press-fit block bone graft technique. Sixteen years ago, a 60-year-old female patient underwent maxillary sinus augmentation (MSA) with 3 implants placed simultaneously in the right atrophic ridge. However, No.

Zirconium and Yttrium Co-Doped BaCoZrYO: A New Mixed-Conducting Perovskite Oxide-Based Membrane for Efficient and Stable Oxygen Permeation.

Oxygen permeation membranes (OPMs) are regarded as promising technology for pure oxygen production. Among various materials for OPMs, perovskite oxides with mixed electron and oxygen-ion (e/O) conducting capability have attracted particular interest because of the high O conductivity and structural/compositional flexibility. However, BaCoO-based perovskites as one of the most investigated OPMs suffer from low oxygen permeation rate and inferior structural stability in CO-containing atmospheres.

Reconstruction and analysis of genome-scale metabolic model for thermophilic fungus Myceliophthora thermophila.

Myceliophthora thermophila, a thermophilic fungus that can degrade and utilize all major polysaccharides in plant biomass, has great potential in biotechnological industries. Here, the first manually curated genome-scale metabolic model iDL1450 for M. thermophila was reconstructed using an autogenerating pipeline with thorough manual curation.

Bifunctional Single-Atom Cobalt Electrocatalysts with Dense Active Sites Prepared via a Silica Xerogel Strategy for Rechargeable Zinc-Air Batteries.

The N-doped cobalt-based (Co) bifunctional single atom catalyst (SAC) has emerged as one of the most promising candidates to substitute noble metal-based catalysts for highly efficient bifunctionality. Herein, a facile silica xerogel strategy is elaborately designed to synthesize uniformly dispersed and dense Co-N active sites on N-doped highly porous carbon networks (Co-N-C SAC) using economic biomass materials. This strategy promotes the generation of massive mesopores and micropores for substantially improving the formation of Co-N moieties and unique network architecture.

Compensating Complete Loss of Signal Recognition Particle During Co-translational Protein Targeting by the Translation Speed and Accuracy.

Signal recognition particle (SRP) is critical for delivering co-translational proteins to the bacterial inner membrane. Previously, we identified SRP suppressors in that inhibit translation initiation and elongation, which provided insights into the mechanism of bypassing the requirement of SRP. Suppressor mutations tended to be located in regions that govern protein translation under evolutionary pressure.

Signal Recognition Particle Suppressor Screening Reveals the Regulation of Membrane Protein Targeting by the Translation Rate.

The signal recognition particle (SRP) is conserved in all living organisms, and it cotranslationally delivers proteins to the inner membrane or endoplasmic reticulum. Recently, SRP loss was found not to be lethal in either the eukaryote or the prokaryote In , the role of SRP in mediating inner membrane protein (IMP) targeting has long been studied. However, the essentiality of SRP remains a controversial topic, partly hindered by the lack of strains in which SRP is completely absent.

Genomic, transcriptomic, and metabolic characterizations of Escherichia coli adapted to branched-chain higher alcohol tolerance.

Microbial-produced branched-chain higher alcohols (BCHAs), such as isopropanol, isobutanol, and isopentanol in Escherichia coli, have emerged as promising alternative biofuels under development. Elucidating and improving the tolerance of E. coli to BCHAs are important issues for microbial production of BCHAs due to their physiological inhibitory effect.

Find_tfSBP: find thermodynamics-feasible and smallest balanced pathways with high yield from large-scale metabolic networks.

Biologically meaningful metabolic pathways are important references in the design of industrial bacterium. At present, constraint-based method is the only way to model and simulate a genome-scale metabolic network under steady-state criteria. Due to the inadequate assumption of the relationship in gene-enzyme-reaction as one-to-one unique association, computational difficulty or ignoring the yield from substrate to product, previous pathway finding approaches can't be effectively applied to find out the high yield pathways that are mass balanced in stoichiometry.

Profiling of Saccharomyces cerevisiae transcription factors for engineering the resistance of yeast to lignocellulose-derived inhibitors in biomass conversion.

Background: Yeast transcription factors (TFs) involved in the regulation of multidrug resistance (MDR) were investigated in experiments with deletion mutants, transformants overexpressing synthetic genes encoding TFs, and toxic concentrations of lignocellulose-derived substances added to cultures as complex mixtures or as specific compounds, viz. coniferyl aldehyde, 5-hydroxymethylfurfural, and furfural.

Results: In the presence of complex mixtures of toxic substances from spruce wood, transformants overexpressing YAP1 and STB5, TFs involved in oxidative stress response, exhibited enhanced relative growth rates amounting to 4.

High-throughput metagenomic analysis of petroleum-contaminated soil microbiome reveals the versatility in xenobiotic aromatics metabolism.

The soil with petroleum contamination is one of the most studied soil ecosystems due to its rich microorganisms for hydrocarbon degradation and broad applications in bioremediation. However, our understanding of the genomic properties and functional traits of the soil microbiome is limited. In this study, we used high-throughput metagenomic sequencing to comprehensively study the microbial community from petroleum-contaminated soils near Tianjin Dagang oilfield in eastern China.

ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.

Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP) based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming.

Analysis of enhanced current-generating mechanism of Geobacter sulfurreducens strain via model-driven metabolism simulation.

Microbial fuel cells (MFCs) are a class of ideal technologies that function via anaerobic respiration of electricigens, which bring current generation and environmental restoration together. An in-depth understanding of microbial metabolism is of great importance in engineering microbes to further improve their respiration. We employed flux balance analysis and selected Fe(iii) as a substitute for the electrode to simulate current-generating metabolism of Geobacter sulfurreducens PCA with a fixed acetate uptake rate.

Construction and analysis of the model of energy metabolism in E. coli.

Genome-scale models of metabolism have only been analyzed with the constraint-based modelling philosophy and there have been several genome-scale gene-protein-reaction models. But research on the modelling for energy metabolism of organisms just began in recent years and research on metabolic weighted complex network are rare in literature. We have made three research based on the complete model of E.

Development of thermodynamic optimum searching (TOS) to improve the prediction accuracy of flux balance analysis.

Flux balance analysis (FBA) has been widely used in calculating steady-state flux distributions that provide important information for metabolic engineering. Several thermodynamics-based methods, for example, quantitative assignment of reaction directionality and energy balance analysis have been developed to improve the prediction accuracy of FBA. However, these methods can only generate a thermodynamically feasible range, rather than the most thermodynamically favorable solution.

Genome-scale analysis to the impact of gene deletion on the metabolism of E. coli: constraint-based simulation approach.

Background: Genome-scale models of metabolism have only been analyzed with the constraint-based modelling philosophy. Some gene deletion studies on in silico organism models at genome-scale have been made, but most of them were from the aspects of distinguishing lethal and non-lethal genes or growth rate. The impact of gene deletion on flux redistribution, the functions and characters of key genes, and the performance of different reactions in entire gene deletion still lack research.