Gene associations of lipid traits, lipid-lowering drug-target genes and endometriosis.

RESEARCH QUESTION: Does the observed correlation between dyslipidaemia and endometriosis indicate a bidirectional causal association? DESIGN: Bidirectional Mendelian randomization was used to investigate the causal association between lipid traits and endometriosis. Drug-target Mendelian randomization was used to explore potential drug-target genes for managing endometriosis. In cases where lipid-mediated effects via specific drug targets were significant, aggregate analyses, such as summary-data-based Mendelian randomization and colocalization methods, were introduced to validate the outcomes. Mediation analyses supplemented these evaluations. RESULTS: The bidirectional Mendelian randomization results suggested that genetically predicted triglyceride (OR 1.15, 95% CI 1.08-1.23), high-density lipoprotein cholesterol (OR 0.87, 95% CI 0.81-0.94), low-density lipoprotein cholesterol (OR 1.20, 95% CI 1.06-1.34) and apolipoprotein A (OR 0.90, 95% CI 0.83-0.96) concentrations were causally associated with endometriosis. Reverse Mendelian randomization results revealed that genetically proxied endometriosis was causally associated with triglyceride concentration (OR 1.02, 95% CI 1.01-1.02). In drug-target Mendelian randomization, genetic mimicry in proprotein convertase subtilisin/kexin type 9 (PCSK9) (OR 1.40, 95% CI 1.13-1.72), apolipoprotein B (APOB) (OR 1.49, 95% CI 1.21-1.86) and angiopoietin-related protein 3 (ANGPTL3) (OR 1.57, 95% CI 1.14-2.16) was significantly associated with the risk of endometriosis stages 1-2. CONCLUSION: There is a potential bidirectional causal association between endometriosis and dyslipidaemia. Genetic mimicry of PCSK9, APOB and ANGPTL3 is associated with the risk of early-stage endometriosis. The development of lipid-lowering drugs to treat endometriosis is of potential clinical interest.

Artificial Heterointerfaces with Regulated Charge Distribution of Ni Active Sites for Urea Oxidation Reaction.

In contrast to the thermodynamically unfavorable anodic oxygen evolution reaction, the electrocatalytic urea oxidation reaction (UOR) presents a more favorable thermodynamic potential. However, the practical application of UOR has been hindered by sluggish kinetics. In this study, hierarchical porous nanosheet arrays featuring abundant Ni-WO3 heterointerfaces on nickel foam (Ni-WO3/NF) is introduced as a monolith electrode, demonstrating exceptional activity and stability toward UOR. The Ni-WO3/NF catalyst exhibits unprecedentedly rapid UOR kinetics (200 mA cm-2 at 1.384 V vs. RHE) and a high turnover frequency (0.456 s-1), surpassing most previously reported Ni-based catalysts, with negligible activity decay observed during a durability test lasting 150 h. Ex situ X-ray photoelectron spectroscopy and density functional theory calculations elucidate that the WO3 interface significantly modulates the local charge distribution of Ni species, facilitating the generation of Ni3+ with optimal affinity for interacting with urea molecules and CO2 intermediates at heterointerfaces during UOR. This mechanism accelerates the interfacial electrocatalytic kinetics. Additionally, in situ Fourier transform infrared spectroscopy provides deep insights into the substantial contribution of interfacial Ni-WO3 sites to UOR electrocatalysis, unraveling the underlying molecular-level mechanisms. Finally, the study explores the application of a direct urea fuel cell to inspire future practical implementations.

Understanding activity-stability tradeoffs in biocatalysts by enzyme proximity sequencing.

Understanding the complex relationships between enzyme sequence, folding stability and catalytic activity is crucial for applications in industry and biomedicine. However, current enzyme assay technologies are limited by an inability to simultaneously resolve both stability and activity phenotypes and to couple these to gene sequences at large scale. Here we present the development of enzyme proximity sequencing, a deep mutational scanning method that leverages peroxidase-mediated radical labeling with single cell fidelity to dissect the effects of thousands of mutations on stability and catalytic activity of oxidoreductase enzymes in a single experiment. We use enzyme proximity sequencing to analyze how 6399 missense mutations influence folding stability and catalytic activity in a D-amino acid oxidase from Rhodotorula gracilis. The resulting datasets demonstrate activity-based constraints that limit folding stability during natural evolution, and identify hotspots distant from the active site as candidates for mutations that improve catalytic activity without sacrificing stability. Enzyme proximity sequencing can be extended to other enzyme classes and provides valuable insights into biophysical principles governing enzyme structure and function.

Late-stage gem-difluoroallylation of phenol in bioactive molecules and peptides with 3,3-difluoroallyl sulfonium salts.

An efficient method for the late-stage selective O-fluoroalkylation of tyrosine residues with a stable yet highly reactive fluoroalkylating reagent, 3,3-difluoroallyl sulfonium salts (DFASs), has been developed. The reaction proceeds in a mild basic aqueous buffer (pH = 11.6) with high efficiency, high biocompatibility, and excellent regio- and chemoselectivity. Various oligopeptides and phenol-containing bioactive molecules, including carbohydrates and nucleosides, could be selectively O-fluoroalkylated. The added vinyl and other functional groups from DFASs can be valuable linkers for successive modification, significantly expanding the chemical space for further bioconjugation. The synthetic utility of this protocol has been demonstrated by the fluorescently labeled anti-cancer drug and the synthesis of O-link type 1,4,7,10-tetraazacyclododecane-N,N',N,N'-tetraacetic acid-tyrosine3-octreotate (DOTA-TATE), showing the prospect of the method in medicinal chemistry and chemical biology.

Learning From Human Educational Wisdom: A Student-Centered Knowledge Distillation Method.

Existing studies on knowledge distillation typically focus on teacher-centered methods, in which the teacher network is trained according to its own standards before transferring the learned knowledge to a student one. However, due to differences in network structure between the teacher and the student, the knowledge learned by the former may not be desired by the latter. Inspired by human educational wisdom, this paper proposes a Student-Centered Distillation (SCD) method that enables the teacher network to adjust its knowledge transfer according to the student network's needs. We implemented SCD based on various human educational wisdom, e.g., the teacher network identified and learned the knowledge desired by the student network on the validation set, and then transferred it to the latter through the training set. To address the problems of current deficiency knowledge, hard sample learning and knowledge forgetting faced by a student network in the learning process, we introduce and improve Proportional-Integral-Derivative (PID) algorithms from automation fields to make them effective in identifying the current knowledge required by the student network. Furthermore, we propose a curriculum learning-based fuzzy strategy and apply it to the proposed PID control algorithm, such that the student network in SCD can actively pay attention to the learning of challenging samples after with certain knowledge. The overall performance of SCD is verified in multiple tasks by comparing it with state-of-the-art ones. Experimental results show that our student-centered distillation method outperforms existing teacher-centered ones.

Theoretical and experimental investigation of Al3+ ion-suppressed phase-separation structures in rare-earth-doped high-phosphorus silica glasses.

Rare-earth-doped silica-based composite glasses (Re-SCGs) are widely used as high-quality laser gain media in defense, aerospace, energy, power, and medical applications. The variable regional chemical environments of Re-SCGs can induce new photoluminescence properties of rare-earth ions but can cause the selective aggregation of rare-earth ions, limiting the application of Re-SCGs in the field of high-power lasers. Here, topological engineering is proposed to adjust the degree of cross-linking of phase-separation network chains in Re-SCGs. A combination of experimental and theoretical characterization techniques suggested that the selective aggregation of rare-earth ions originates from the formation of phase-separated structures in glasses. The decomposition of nanoscale phase separation structures to the sub-nanometer scale, enabled by incorporating Al3+ ions, not only maintains the high luminescence efficiency of rare earth ions but also increases light transmittance and reduces light scattering. Furthermore, our investigation encompassed the exploration of the inhibitory mechanism of Al3+ ions on phase-separation structures, as well as their influence on the spectral characteristics of Re-SCGs. This work provides a new design concept for composite glass materials doped with rare-earth ions and could broaden their application in the field of high-power lasers.

Minor alkaloids from an aqueous extract of the hook-bearing stem of Uncaria rhynchophylla.

Seven new monoterpene alkaloids (1 - 7), along with 16 known analogues, were isolated from an aqueous decoction of the hook-bearing stems of Uncaria rhynchophylla (Gou-teng). Their structures were determined by spectroscopic data analysis, single crystal X-ray diffraction, and electronic circular dichroism (ECD) calculations. Compounds 1 and 2 are stereoisomers belonging to a novel type of pseudoindoxyl monoterpene alkaloids, 3 is the first monoterpene furoindole alkaloid from nature, and 4 - 7 are derivatives of the known monoterpene alkaloids featuring different structures.

Enabling Internal Electric Field in Heterogeneous Nanosheets to Significantly Accelerate Alkaline Hydrogen Electrocatalysis.

Efficient bifunctional hydrogen electrocatalysis, encompassing both hydrogen evolution reaction (HER) and hydrogen oxidation reaction (HOR), is of paramount significance in advancing hydrogen-based societies. While non-precious-metal-based catalysts, particularly those based on nickel (Ni), are essential for alkaline HER/HOR, their intrinsic catalytic activity often falls short of expectations. Herein, an internal electric field (IEF) strategy is introduced for the engineering of heterogeneous nickel-vanadium oxide nanosheet arrays grown on porous nickel foam (Ni-V2 O3 /PNF) as bifunctional electrocatalysts for hydrogen electrocatalysis. Strikingly, the Ni-V2 O3 /PNF delivers 10 mA cm-2 at an overpotential of 54 mV for HER and a mass-specific kinetic current of 19.3 A g-1 at an overpotential of 50 mV for HOR, placing it on par with the benchmark 20% Pt/C, while exhibiting enhanced stability in alkaline electrolytes. Density functional theory calculations, in conjunction with experimental characterizations, unveil that the interface IEF effect fosters asymmetrical charge distributions, which results in more thermoneutral hydrogen adsorption Gibbs free energy on the electron-deficient Ni side, thus elevating the overall efficiency of both HER and HOR. The discoveries reported herein guidance are provided for further understanding and designing efficient non-precious-metal-based electrocatalysts through the IEF strategy.

A lightweight speech recognition method with target-swap knowledge distillation for Mandarin air traffic control communications.

Miscommunications between air traffic controllers (ATCOs) and pilots in air traffic control (ATC) may lead to catastrophic aviation accidents. Thanks to advances in speech and language processing, automatic speech recognition (ASR) is an appealing approach to prevent misunderstandings. To allow ATCOs and pilots sufficient time to respond instantly and effectively, the ASR systems for ATC must have both superior recognition performance and low transcription latency. However, most existing ASR works for ATC are primarily concerned with recognition performance while paying little attention to recognition speed, which motivates the research in this article. To address this issue, this article introduces knowledge distillation into the ASR for Mandarin ATC communications to enhance the generalization performance of the light model. Specifically, we propose a simple yet effective lightweight strategy, named Target-Swap Knowledge Distillation (TSKD), which swaps the logit output of the teacher and student models for the target class. It can mitigate the potential overconfidence of the teacher model regarding the target class and enable the student model to concentrate on the distillation of knowledge from non-target classes. Extensive experiments are conducted to demonstrate the effectiveness of the proposed TSKD in homogeneous and heterogeneous architectures. The experimental results reveal that the generated lightweight ASR model achieves a balance between recognition accuracy and transcription latency.

Self-Powered Hydrogen Production with Improved Energy Efficiency via Polysulfides Redox.

In the pursuit of efficient solar-driven electrocatalytic water splitting for hydrogen production, the intrinsic challenges posed by the sluggish kinetics of anodic oxygen evolution and intermittent sunlight have prompted the need for innovative energy systems. Here, we introduce an approach by coupling the polysulfides oxidation reaction with the hydrogen evolution reaction for energy-saving H2 production, which could be powered by an aqueous zinc-polysulfides battery to construct a self-powered energy system. This unusual hybrid water electrolyzer achieves 300 mA cm-2 at a low cell voltage of 1.14 V, saving electricity consumption by 100.4% from 5.47 to 2.73 kWh per m3 H2 compared to traditional overall water splitting. Benefiting from the favorable reaction kinetics of polysulfides oxidation/reduction, the aqueous zinc-polysulfides battery exhibits an energy efficiency of approximately 89% at 1.0 mA cm-2. Specially, the zinc-polysulfide battery effectively stores intermittent solar energy as chemical energy during light reaction by solar cells. Under an unassisted light reaction, the batteries could release energy to drive H2 production through a hybrid water electrolyzer for uninterrupted hydrogen production. Therefore, the aim of simultaneously generating H2 and eliminating the restrictions of intermittent sunlight is realized by combining the merits of polysulfides redox, an aqueous metal-polysulfide battery, and solar cells. We believe that this concept and utilization of polysulfides redox will inspire further fascinating attempts for the development of sustainable energy via electrocatalytic reactions.

MiR-337-3p improves metabolic-associated fatty liver disease through regulation of glycolipid metabolism.

Epigenetic regulations play crucial roles in the pathogenesis of metabolic-associated fatty liver disease; therefore, elucidating the biological functions of differential miRNAs helps us to understand the pathogenesis. Herein, we discovered miR-337-3p was decreased in patients with NAFLD from Gene Expression Omnibus dataset, which was replicated in various cell and mouse models with lipid disorders. Subsequently, overexpression of miR-337-3p in vivo could ameliorate hepatic lipid accumulation, reduce fasting blood glucose, and improve insulin resistance. Meanwhile, we determined miR-337-3p might influence multiple genes involved in glycolipid metabolism through mass spectrometry detection, bioinformatics analysis, and experimental verification. Finally, we selected HMGCR as a representative example to investigate the molecular mechanism of miR-337-3p regulating these genes, where the seed region of miR-337-3p bound to 3'UTR of HMGCR to inhibit HMGCR translation. In conclusion, we discovered a new function of miR-337-3p in glycolipid metabolism and that might be a new therapeutic target of MAFLD.

Protocol for preparing patterned superlattice structures by printing assembly technology for multi-channel detection.

The transformation of superlattice structures into functional devices requires high-quality preparation. Inkjet printing is potentially a cutting-edge technology for nanofabrication. Here, we present a protocol to prepare inks for constructing patterned superlattice structures using print assembly techniques. We describe steps for preparing oleophobic substrates, optimizing ink parameters, and preparing the patterned superlattice array. We then detail procedures for preparing a multichannel surface-enhanced Raman scattering sensor and evaluating its performance. This protocol can potentially facilitate the commercialization of superlattice-related devices. For complete details regarding the use and execution of this protocol, please refer to Zhao et al.1.

High-entropy alloys in electrocatalysis: from fundamentals to applications.

High-entropy alloys (HEAs) comprising five or more elements in near-equiatomic proportions have attracted ever increasing attention for their distinctive properties, such as exceptional strength, corrosion resistance, high hardness, and excellent ductility. The presence of multiple adjacent elements in HEAs provides unique opportunities for novel and adaptable active sites. By carefully selecting the element configuration and composition, these active sites can be optimized for specific purposes. Recently, HEAs have been shown to exhibit remarkable performance in electrocatalytic reactions. Further activity improvement of HEAs is necessary to determine their active sites, investigate the interactions between constituent elements, and understand the reaction mechanisms. Accordingly, a comprehensive review is imperative to capture the advancements in this burgeoning field. In this review, we provide a detailed account of the recent advances in synthetic methods, design principles, and characterization technologies for HEA-based electrocatalysts. Moreover, we discuss the diverse applications of HEAs in electrocatalytic energy conversion reactions, including the hydrogen evolution reaction, hydrogen oxidation reaction, oxygen reduction reaction, oxygen evolution reaction, carbon dioxide reduction reaction, nitrogen reduction reaction, and alcohol oxidation reaction. By comprehensively covering these topics, we aim to elucidate the intricacies of active sites, constituent element interactions, and reaction mechanisms associated with HEAs. Finally, we underscore the imminent challenges and emphasize the significance of both experimental and theoretical perspectives, as well as the potential applications of HEAs in catalysis. We anticipate that this review will encourage further exploration and development of HEAs in electrochemistry-related applications.

Bioresponsive Chimaeric Polymersomes Mediate Sustained and Liver-Specific siRNA Transfection In Vivo.

The silencing of disease-causing genes with small interfering RNA (siRNA) offers a particularly effective therapeutic strategy for different disorders; however, its clinical efficacy relies on the development of nontoxic and tissue-specific delivery vehicles. Herein, we report that bioresponsive chimaeric polymersomes (BCP) with short poly(ethylenimine) as inner shell mediate highly efficacious, sustained, and liver-specific siRNA transfection in vivo. BCP exhibited remarkable encapsulation efficiencies of siRNA (95-100%) at siRNA-feeding contents of 15-25 wt %, to afford stable, small-sized (55-64 nm), and neutral-charged BCP-siRNA. siApoB-Loaded BCP (BCP-siApoB) outperformed lipofectamine counterparts and silenced 93% of ApoB mRNA in HepG2 cells at 50 nM siApoB without inducing cytotoxicity. Intriguingly, the in vivo studies using wild-type C57BL/6 mice revealed that BCP-siApoB preferentially accumulated in the liver, and a single dose of 4.5 mg/kg achieved over 90% downregulation of ApoB mRNA for at least 10 days. The systemic administration of BCP-siApoB at 4.5 mg/kg every 2 weeks or 1.5 mg/kg weekly in diet-induced obese mice could also achieve up to 80% silencing of ApoB mRNA. The liver specificity and silencing efficacy of BCP-siApoB could further be improved by decorating it with the trivalent N-acetylgalactosamine (TriGalNAc) ligand. These bioresponsive and liver-specific chimaeric polymersomes provide an enabling technology for siRNA therapy of various liver-related diseases.

Phosphoproteomic Analysis Reveals the Predominating Cellular Processes and the Involved Key Phosphoproteins Essential for the Proliferation of Toxoplasma gondii.

PURPOSE: To explore the essential roles of phosphorylation in mediating the proliferation of T. gondii in its cell lytic life. METHODS: We profiled the phosphoproteome data of T. gondii residing in HFF cells for 2 h and 6 h, representing the early- and late-stages of proliferation (ESP and LSP) within its first generation of division. RESULTS: We identified 70 phosphoproteins, among which 8 phosphoproteins were quantified with the phosphorylation level significantly regulated. While only two of the eight phosphoproteins, GRA7 and TGGT1_242070, were significantly down-regulated at the transcriptional level in the group of LSP vs. ESP. Moreover, GO terms correlated with host membrane component were significantly enriched in the category of cellular component, suggesting phosphoprotein played important roles in acquiring essential substance from host cell via manipulating host membrane. Further GO analysis in the categories of molecular function and biological process and pathway analysis revealed that the cellular processes of glucose and lipid metabolism were regulated by T. gondii phosphoproteins such as PMCAA1, LIPIN, Pyk1 and ALD. Additionally, several phosphoproteins were enriched at the central nodes in the protein-protein interaction network, which may have essential roles in T. gondii proliferation including GAP45, MLC1, fructose-1,6-bisphosphate aldolase, GRAs and so on. CONCLUSION: This study revealed the main cellular processes and key phosphoproteins crucial for the intracellular proliferation of T. gondii, which would provide clues to explore the roles of phosphorylation in regulating the development of tachyzoites and new insight into the mechanism of T. gondii development in vitro.

Anti­PD­1/PD­L1 and anti­CTLA­4 associated checkpoint inhibitor pneumonitis in non­small cell lung cancer: Occurrence, pathogenesis and risk factors (Review).

Immune checkpoint inhibitors (ICIs) play a significant anti­tumor role in the management of non­small cell lung cancer. The most broadly used ICIs are anti­programmed death 1 (PD­1), anti­programmed cell death­ligand 1, and anti­cytotoxic T lymphocyte­associated antigen­4 monoclonal antibody. Compared with traditional chemotherapy, ICIs have the advantages of greater efficiency and more specific targeting. However, the resulting immune­related adverse events limit the clinical application of ICIs, especially checkpoint inhibitor pneumonitis (CIP). CIP chiefly occurs within 6 months of administration of ICIs. Excessive activation and amplification of cytotoxic T lymphocytes, helper T cells, downregulation of regulatory T cells, and over­secretion of pro­inflammatory cytokines are the dominant mechanisms underlying the pathophysiology of CIP. The dysregulation of innate immune cells, such as an increase in inflammatory monocytes, dendritic cells, neutrophils and M1 polarization of macrophages, an increase in IL­10 and IL­35, and a decrease in eosinophils, may underlie CIP. Although contested, several factors may accelerate CIP, such as a history of previous respiratory disease, radiotherapy, chemotherapy, administration of epidermal growth factor receptor tyrosine kinase inhibitors, PD­1 blockers, first­line application of ICIs, and combined immunotherapy. Interestingly, first­line ICIs plus chemotherapy may reduce CIP. Steroid hormones remain the primary treatment strategy against grade ≥2 CIP, although cytokine blockers are promising therapeutic agents. Herein, the current research on CIP occurrence, clinical and radiological characteristics, pathogenesis, risk factors, and management is summarized to further expand our understanding, clarify the prognosis, and guide treatment.

Layered double hydroxides - poloxamer 188 nanocomposites based on exfoliation reassembling for improved cellular uptake and controlled delivery of methotrexate.

Exploitation of advanced methotrexate (MTX) delivery with nanocomposites has important clinical application value. Poloxamer 188 micelle and layered double hydroxide loaded with MTX (LDH-MTX) by exfoliation reassembling were used to prepare LDH-MTX-poloxamer 188 nanocomposites with good dispersibility and efficient cellular uptake for controlled drug delivery. The LDH-MTX-poloxamer 188 nanocomposites with sphere-like morphology, of which the average hydrodynamic diameter was <100 nm, were shown to have better dispersion state than naked LDH-MTX. Importantly, the LDH-MTX-poloxamer 188 nanocomposites could achieve significant sustained drug release and have obvious pH dependent responsive release ability. In addition, these nanocomposites also exhibited long-term and excellent in vitro antitumor efficacy as opposed to pure MTX or LDH-MTX as evident from cell viability. More interestingly, compared to pure FITC used to simulate MTX, LDH nanocomposites labeled with FITC were considered to have better cell adhesion through cell uptake. Therefore, the studied nanocomposites of LDH-MTX-poloxamer 188 can be further used as a new advanced MTX delivery nanovehicles with desired properties in future therapeutic aspects.

An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method.

Introduction: Efficiently recognizing emotions is a critical pursuit in brain-computer interface (BCI), as it has many applications for intelligent healthcare services. In this work, an innovative approach inspired by the genetic code in bioinformatics, which utilizes brain rhythm code features consisting of δ, θ, α, ß, or γ, is proposed for electroencephalography (EEG)-based emotion recognition. Methods: These features are first extracted from the sequencing technique. After evaluating them using four conventional machine learning classifiers, an optimal channel-specific feature that produces the highest accuracy in each emotional case is identified, so emotion recognition through minimal data is realized. By doing so, the complexity of emotion recognition can be significantly reduced, making it more achievable for practical hardware setups. Results: The best classification accuracies achieved for the DEAP and MAHNOB datasets range from 83-92%, and for the SEED dataset, it is 78%. The experimental results are impressive, considering the minimal data employed. Further investigation of the optimal features shows that their representative channels are primarily on the frontal region, and associated rhythmic characteristics are typical of multiple kinds. Additionally, individual differences are found, as the optimal feature varies with subjects. Discussion: Compared to previous studies, this work provides insights into designing portable devices, as only one electrode is appropriate to generate satisfactory performances. Consequently, it would advance the understanding of brain rhythms, which offers an innovative solution for classifying EEG signals in diverse BCI applications, including emotion recognition.