Hemodynamic insight into the iliac vein after stent intervention: Mind the persistent compression of iliac vein stent.

This study hypothesizes that lumbar spine and iliac artery compression of veins persists after stenting, rendering the iliac vein susceptible to restenosis, thrombosis, and other clinical complications. To examine this hypothesis, a vascular model post-iliac vein stenting was constructed based on vein images from patients with iliac vein compression syndrome. This model facilitated the examination of how varying degrees of compression affect the hemodynamic environment of the host vasculature post-stenting.

Enhancing polarization contrast with depolarization mechanism using PS-OCT.

The most direct way to improve the efficiency and accuracy of tissue identification is to enhance the image contrast of multiple polarization parameters at the same time. Unlike the widely used enhancement method of single parameter, the expressions of non-depolarizing parameters are combined considering the depolarization mechanism. These derived parameters are then applied to imaging ex-vivo mouse skin through PS-OCT system, which breaks through the limitations of high surface brightness and blurred deep tissue boundaries.

Praseodymium-regulated microregion electron structures of BiWO nanosheets to construct non-radical platforms for the photocatalytic decontamination of water by hydrogen peroxide activation.

HO-based photo-Fenton-like systems are promising technologies for the generation of singlet oxygen (O) aimed at water decontamination. However, in conventional systems, the yield of O is relatively low owing to competition among free radicals. The oriented construction of a non-radical system could address this issue but challenging.

Effects of ozonation sludge reduction on nutrient removal and microbial community diversity of conventional A/O and reversed A/O processes.

To optimise ozonation sludge reduction in the activated sludge process, it is crucial to monitor nutrient removal and pay particular attention to the influential biological species. This study employed high-throughput sequencing to examine the microbial composition and diversity in the anaerobic-anoxic-oxic (A/O) process, the A/O process with ozonation, and the reversed A/O process with ozonation. The diversity analysis aimed to identify discrepancies and similarities in microbial communities among these groups, thereby elucidating the varying biological efficiencies.

Natural product sennoside B disrupts liquid-liquid phase separation of SARS-CoV-2 nucleocapsid protein by inhibiting its RNA-binding activity.

The nucleocapsid protein (NP) of SARS-CoV-2, an RNA-binding protein, is capable of undergoing liquid-liquid phase separation (LLPS) during viral infection, which plays a crucial role in virus assembly, replication, and immune regulation. In this study, we developed a homogeneous time-resolved fluorescence (HTRF) method for identifying inhibitors of the SARS-CoV-2 NP-RNA interaction. Using this HTRF-based approach, we identified two natural products, sennoside A and sennoside B, as effective blockers of this interaction.

Research on the Layout Design of Auxiliary Support Modules for Suppressing Machining Chatter in Thin-Walled Beams.

A well-designed clamping layout significantly enhances the dynamic stiffness of a manufacturing system, improving its stability and suppressing cutting chatter in workpieces. This paper focuses on the machining of thin-walled beams, which are prone to vibration and have low stiffness, especially under hydraulic floating clamping conditions. By analyzing the system stability domain, we propose a method to improve system stiffness through strategic design of support module layouts.

Enhancing PI3Kγ inhibitor discovery: a machine learning-based virtual screening approach integrating pharmacophores, docking, and molecular descriptors.

PI3Kγ is a lipid kinase that is expressed primarily in leukocytes and plays a significant role in tumors, inflammation, and autoimmune diseases. Consequently, considerable attention has been given to the development of pharmacological inhibitors of PI3Kγ. Recently, machine learning-based virtual screening approaches have been increasingly applied in new drug discovery research, potentially providing innovative strategies for the development of PI3Kγ inhibitors.

Silkworm pupae protein-based odorless food ingredient: Rutin-facilitated modification for off-odor volatile removal.

Silkworm (Bombyx mori) pupae are a popular insect-based food source, particularly in Southeast Asia. However, their off-flavors can hinder their widespread acceptance in food applications. To further develop insects as viable food resources, it is crucial to identify and eliminate the off-odor volatile compounds present.

E3Docker: a docking server for potential E3 binder discovery.

Targeted protein degradation (TPD) has emerged as a promising therapeutic strategy for modulating protein levels in cells. Proteolysis-targeting chimeras and molecular glues facilitate the formation of a complex between the protein of interest (POI) and a specific E3 ligase, leading to POI ubiquitination and subsequent degradation by the proteasome. Considering over 600 E3s in the human genome, it is of great potential to find novel E3 binders and recruit new E3 ligase for TPD related drug discovery.

Research on optimal heat input parameter for TIG welding of thin plate 5083 aluminum alloy.

Heat input represents a critical process parameter that significantly influences the quality of tungsten inert gas (TIG) welding. In this study, a comprehensive investigation of heat input effects on the welding quality of thin-gauge aluminum alloy was conducted through integrated theoretical analysis and experimental validation. The research established an optimal heat input range of 296-321 J/mm for 3 mm thick 5083 aluminum alloy plates in TIG welding applications, within which welded joints demonstrated minimal defect formation and superior mechanical performance.

Characterization and source apportionment of brown carbon via online measurements in a typical industrial-polluted city in eastern China.

Brown carbon (BrC) significantly influences atmospheric chemical reactions through its strong absorption properties at near ultraviolet wavelengths. To advance targeted mitigation strategies for secondary air pollution, understanding anthropogenic contributions to BrC remains critical. In this study, a year-long continuous campaign combining aerosol optical properties and chemical composition measurements was conducted in a typical polluted industrial city.

Monolithic silicon carbide metasurfaces for engineering arbitrary 3D perfect vector vortex beams.

Perfect vector vortex beams (PVVBs) can precisely control the light's polarization and phase along tailored intensity profiles, offering significant potential for advanced applications such as optical trapping and optical encryption. Extending PVVBs from 2D to 3D configurations would provide an additional spatial control dimension and enhance their information capacity. However, a compact and low-loss solution to generating 3D PVVBs remains unresolved.

Nonbonding Electron Inversion-Driven Structural Engineering: Synergistic Enhancement of Linear and Nonlinear Optical Properties.

The simultaneous optimization of large birefringence (Δn, a linear optical property) and strong second-harmonic generation (SHG, a nonlinear optical (NLO) property) in a single crystal remains a significant challenge due to the inherently distinct structural requirements for these properties. Although nonbonding electrons have been extensively studied in oxides and chalcogenides, research has predominantly focused on their role along polar axes, leaving their influence along axes in tetrahedral stacking largely unexplored. Herein, we propose a nonbonding electron-inversion strategy to overcome phase-matching limitations in defect diamond-like structures.

The prediction of RNA-small molecule binding sites in RNA structures based on geometric deep learning.

Biological interactions between RNA and small-molecule ligands play a crucial role in determining the specific functions of RNA, such as catalysis and folding, and are essential for guiding drug design in the medical field. Accurately predicting the binding sites of ligands within RNA structures is therefore of significant importance. To address this challenge, we introduced a computational approach named RLBSIF (RNA-Ligand Binding Surface Interaction Fingerprints) based on geometric deep learning.

Molecular surfaces modeling: Advancements in deep learning for molecular interactions and predictions.

Molecular surface analysis can provide a high-dimensional, rich representation of molecular properties and interactions, which is crucial for enabling powerful predictive modeling and rational molecular design across diverse scientific and technological domains. With remarkable successes achieved by artificial intelligence (AI) in different fields such as computer vision and natural language processing, there is a growing imperative to harness AI's potential in accelerating molecular discovery and innovation. The integration of AI techniques with molecular surface analysis has opened up new frontiers, allowing researchers to uncover hidden patterns, relationships, and design principles that were previously elusive.

Unveiling LDL dynamics post-stent intervention: a deep dive into transport and accumulation.

The endovascular stent implantation is a significant and efficacious cardiovascular interventional treatment. However, the underlying mechanisms behind in-stent neoarteriosclerosis and restenosis following the intervention remain unclear. Our hypothesis posits that stent implantation may impact the transportation of low-density lipoproteins (LDL) within the host artery, thereby disrupting its concentration distribution and leading to adverse clinical events.

Access to C5-Sulfonylated Tetrahydropyridazines via Photoinduced Cascade Sulfonylation-Cyclization of -Cinnamyl Aldehyde Hydrazones.

Direct installation of a sulfonyl functional group into the C5-position of tetrahydropyridazine was achieved using '-benzylidene--cinnamylacetohydrazide as a new building skeleton via the photocatalytic carbosulfonylation/annulation procedure. Various substituted C5-sulfonylated tetrahydropyridazines were obtained in good to excellent yields employing aryl- or alkylsulfonyl chlorides as the sulfonyl radical sources. This reaction was realized through the selective addition of sulfonyl radical to the C2 position of cinnamyl followed by the 6 annulation to the hydrazone CH═N bond.

Synergistic Conversion of Hydrogen Peroxide and Benzaldehyde in Air by Silver Single-Atom Modified Thiophene-Functionalized g-CN.

This study reports the synthesis of silver single-atom-loaded thiophene-conjugated carbon nitride (Ag@T─CN), a material with high carrier concentration and efficient carrier separation. Under visible light, Ag@T─CN catalyzes hydrogen peroxide (HO) production and benzyl alcohol oxidation to benzaldehyde, achieving production rates of 4729.82 µmol·g·h for HO and 19.

Development of a wearable microfluidic amperometric sensor based on spatial three-electrode system for sweat glucose analysis.

Most amperometric glucose sensors utilize nanomaterials to increase the surface area of the working electrode for sensitivity enhancement. However, this approach not only increases the cost and complicates the fabrication process, but also results in functional surfaces with limited durability. We propose a wearable microfluidic amperometric sensor featuring a spatially arranged three-electrode system (TES) for sweat glucose analysis.

Identify natural compounds as novel phosphodiesterase-2A inhibitors.

Phosphodiesterase-2A (PDE2A) is a potential therapeutic target for the treatment of ganglion dysfunction-related diseases such as Alzheimer's disease, schizophrenia, cognitive impairment, anxiety, and depression. However, most current PDE2A inhibitors have moderate selectivity compared to other PDEs. In this study, we described the discovery of 6 novel PDE2A inhibitors by bioassays, molecular docking, and molecular dynamics simulations.

Zero-Dimensional Oxyselenide Ba[(GaOSe)(SiO)]: Enhanced Optical Anisotropy through Heteroanionic Engineering.

The rational design of chalcogenides with exceptional optical properties remains a significant challenge. Here, we employ heteroanionic engineering to incorporate selenium into the celsian-type BaGaSiO, synthesizing a novel zero-dimensional oxyselenide, Ba[(GaOSe)(SiO)]. It crystallizes in the hexagonal space group 6/ and features isolated [SiO] and [GaOSe] clusters, balanced by Ba cations.

The effect of doll blind box uncertainty on consumers' irrational consumption behavior: the role of instant gratification, Gambler's fallacy, and perceived scarcity.

Background: The uncertainty associated with doll blind boxes has sparked a consumer frenzy in China. However, it remains unclear how the allure of uncertain rewards influences the irrational consumption behavior of blind box consumers. This study aimed to elucidate the internal mechanisms underlying this process.

The Applications of Computational Tools in PROTAC Development.

The increasing importance of PROTACs (proteolysis-targeting chimeras) has attracted significant attention from both the academic community and industry. PROTACs are heterobifunctional small molecules that can bind to both the protein of interest (POI) and the E3 ubiquitin ligase (E3), inducing ubiquitinated degradation of POI. The unique mechanisms of PROTACs, such as event-driven pharmacology and modulation of protein degradation, provide novel therapeutic modalities for various diseases, including oncology, antiviral therapies, neurodegenerative diseases, acne, and others.

Experiment study on UAV target detection algorithm based on YOLOv8n-ACW.

To address the challenges associated with dense and occluded targets in small target detection utilizing unmanned aerial vehicle (UAV), we propose an enhanced detection algorithm referred as the YOLOv8n-ACW. Building upon the YOLOv8n baseline network model, we have integrated Adown into the Backbone and developed a CCDHead to further improve the drone's capability to recognize small targets. Additionally, WIoU-V3 has been introduced as the loss function.

Improved thermoelectric properties of α-phase CuSe thin films through multiphase nanostructuring.

Copper selenide (CuSe) has been extensively studied due to its promising thermoelectric properties in bulk form. However, the miniaturization of thermoelectric devices using thin films is highly desired for smart applications. To date, there are few reports on composite thin films of CuSe for thermoelectric applications, primarily due to their lower conversion efficiency.