Enhanced Pharmacokinetics of Celastrol via Long-Circulating Liposomal Delivery for Intravenous Administration.

Background: Rheumatoid Arthritis (RA) involves prolonged inflammation of the synovium, damaging joints and causing stiffness and deformity. Celastrol (Cel), derived from the Chinese herbal medicine Tripterygium wilfordii Hook F, offers immunosuppressive effects for RA treatment but is limited by poor solubility and bioavailability. Purpose: In this study, long-circulating Cel-loaded liposomes (Cel-LPs) were used to increase the pharmacokinetics of Cel, thereby improving drug delivery and efficacy for the treatment of RA. Methods: Cel-LPs were prepared and administered orally and intravenously to compare the elimination half-life of drugs and bioavailability of Cel. Cel-LPs were prepared using the lipid thin-layer-hydration-extrusion method. Human rheumatoid arthritis synovial (MH7A) cells were used to investigate the compatibility of Cel-LPs. The pharmacokinetic studies were performed on male Sprague-Dawley (SD) rats. Results: The Cel-LPs had an average size of 72.20 ± 27.99 nm, a PDI of 0.267, a zeta potential of -31.60 ± 6.81 mV, 78.77 ± 5.69% drug entrapment efficiency and sustained release (5.83 ± 0.42% drug loading). The cytotoxicity test showed that liposomes had excellent biocompatibility and the fluorescence microscope diagram indicated that liposome entrapment increased intracellular accumulation of Rhodamine B by MH7A cells. Furthermore, the results exhibited that Cel-LPs improved the pharmacokinetics of Cel by increasing the elimination half-life (t1/2) to 11.71 hr, mean residence time (MRT(0-∞)) to 7.98 hr and apparent volume of distribution (Vz/F) to 44.63 L/kg in rats, compared to the Cel solution. Conclusion: In this study, liposomes were demonstrated to be effective in optimizing the delivery of Cel, enabling the formulation of Cel-LPs with prolonged blood circulation and sustained release characteristics. This formulation enhanced the intravenous solubility and bioavailability of Cel, developing a foundation for its clinical application in RA and providing insights on poorly soluble drug management.

PfgPDI: Pocket feature-enabled graph neural network for protein-drug interaction prediction.

Biomolecular interaction recognition between ligands and proteins is an essential task, which largely enhances the safety and efficacy in drug discovery and development stage. Studying the interaction between proteins and ligands can improve the understanding of disease pathogenesis and lead to more effective drug targets. Additionally, it can aid in determining drug parameters, ensuring proper absorption, distribution, and metabolism within the body. Due to incomplete feature representation or the model's inadequate adaptation to protein-ligand complexes, the existing methodologies suffer from suboptimal predictive accuracy. To address these pitfalls, in this study, we designed a new deep learning method based on transformer and GCN. We first utilized the transformer network to grasp crucial information of the original protein sequences within the smile sequences and connected them to prevent falling into a local optimum. Furthermore, a series of dilation convolutions are performed to obtain the pocket features and smile features, subsequently subjected to graphical convolution to optimize the connections. The combined representations are fed into the proposed model for classification prediction. Experiments conducted on various protein-ligand binding prediction methods prove the effectiveness of our proposed method. It is expected that the PfgPDI can contribute to drug prediction and accelerate the development of new drugs, while also serving as a valuable partner for drug testing and Research and Development engineers.

ZnIn2S4-based multi-interface coupled photocatalyst for efficient photothermal synergistic catalytic hydrogen evolution.

Photothermal synergistic catalysis is a novel technology that converts energy. In this study, ZnIn2S4 with S-vacancy (ZIS-Vs) is combined with Nickel, Nickle Oxide and Carbon Nanofiber aggregates (Ni-NiO@CNFs) to create a multi-interface coupled photocatalyst with double Schottky barrier, double channel and mixed photothermal conversion effect. Theoretical calculation confirms that the Gibbs free energy (ΔG*H) of the S-scheme heterojunction in the composite material is -0.07 eV, which is close to 0. This promotes the adsorption of H* and accelerates the formation of H2. Internal photothermal catalysis is achieved by visible-near infrared (Vis-NIR, RT) irradiation. The internal photothermal catalytic hydrogen production rate of the best sample (0.9Ni-NiO@CNFs/ZIS-Vs) is as high as 17.24 mmol·g-1·h-1, and its photothermal conversion efficiency (η) is as high as 61.42 %. Its hydrogen production efficiency is 20.52 times that of ZIS-Vs (0.84 mmol·g-1·h-1) under visible light (Vis, RT) conditions. When the Vis-NIR light source is combined with external heating (75 ℃), the hydrogen production efficiency is further improved, and the hydrogen production efficiency (29.16 mmol·g-1·h-1) is 26.75 times that of ZIS-Vs (1.09 mmol·g-1·h-1, Vis-NIR, RT). Further analysis shows that the increase in hydrogen production resulted from the apparent activation energy (Ea) of the catalyst decreasing from 16.7 kJ·mol-1 to 9.28 kJ·mol-1. This study provides a valuable prototype for the design of an efficient photothermal synergistic catalytic system.

TransVAE-DTA: Transformer and variational autoencoder network for drug-target binding affinity prediction.

BACKGROUND AND OBJECTIVE: Recent studies have emphasized the significance of computational in silico drug-target binding affinity (DTA) prediction in the field of drug discovery and drug repurposing. However, existing DTA prediction approaches suffer from two major deficiencies that impede their progress. Firstly, while most methods primarily focus on the feature representations of drug-target binding affinity pairs, they fail to consider the long-distance relationships of proteins. Furthermore, many deep learning-based DTA predictors simply model the interaction of drug-target pairs through concatenation, which hampers the ability to enhance prediction performance. METHODS: To address these issues, this study proposes a novel framework named TransVAE-DTA, which combines the transformer and variational autoencoder (VAE). Inspired by the early success of VAEs, we aim to further investigate the feasibility of VAEs for drug structure encoding, while utilizing the transformer architecture for target feature representation. Additionally, an adaptive attention pooling (AAP) module is designed to fuse the drug and target encoded features. Notably, TransVAE-DTA is proven to maximize the lower bound of the joint likelihood of drug, target, and their DTAs. RESULTS: Experimental results demonstrate the superiority of TransVAE-DTA in drug-target binding affinity prediction assignments on two public Davis and KIBA datasets. CONCLUSIONS: In this research, the developed TransVAE-DTA opens a new avenue for engineering drug-target interactions.

Actinoplanes sandaracinus sp. nov., a novel ligninase- producing and cellulose-degrading actinobacterium isolated from soil.

A novel ligninase-producing and cellulose-degrading actinobacterium, designated strain NEAU-A12T, was isolated from a soil sample collected from Aohan banner, Chifeng City, Inner Mongolia Autonomous Region, PR China. A polyphasic taxonomic study was used to establish the status of strain NEAU-A12T. 16S rRNA gene sequence analysis revealed that strain NEAU-A12T belonged to the genus Actinoplanes and showed the highest similarity (98.3 %) to Actinoplanes palleronii DSM 43940T, while showing less than 98.3 % similarity to other members of the genus Actinoplanes. The phospholipid profile contained diphosphatidylglycerol, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylinositol and glycosylphosphatidylinositol. The diagnostic sugars in cell hydrolysates were determined to be arabinose, glucose and xylose. The cell wall contained meso-diaminopimelic acid as the diagnostic diamino acid. The predominant menaquinones were MK-9(H4), MK-9(H6) and MK-9(H2). The major fatty acids were C15 : 0, C16 : 0, C16 : 1 ω7c and C17 : 0. Meanwhile, genomic analysis revealed a genome size of 10 192 524 bp and a DNA G+C content of 70.6 mol%, and indicated that strain NEAU-A12T had the potential to degrade lignin and cellulose, as well as produce bioactive compounds. In addition, the average nucleotide identity values between strain NEAU-A12T and its reference strains A. palleronii DSM 43940T, Actinoplanes regularis DSM 43151T, Actinoplanes philippinensis DSM 43019T, Actinoplanes xinjiangensis DSM 45184T and Actinoplanes italicus DSM 43146T were 80.3, 80.3, 84.1, 84.3 and 84.0 %, respectively. The levels of digital DNA-DNA hybridization between them were found to be 23.6 % (21.3-26.1 %), 23.8 % (21.5-26.3 %), 28.3 % (25.9-30.8 %), 28.6 % (26.0-30.9 %) and 28.4 % (26.2-31.1 %), respectively. Based on phenotypic, chemotaxonomic and genotypic data, strain NEAU-A12T is considered to represent a novel species of the genus Actinoplanes, for which the name Actinoplanes sandaracinus sp. nov. is proposed, with NEAU-A12T (=CCTCC AA 2020039T=DSM 112043T) as the type strain.

Iridium-Catalysed Transfer Hydrogenation of 1,8-Naphthyridine with Indoline: Access to Functionalized N-Heteroarenes.

An iridium-catalysed hydrogen transfer strategy, enabling straightforward access to tetrahydro pyridine derivatives from aryl-1,8-naphthyridines and indolines, was developed. This method proceeds with unprecedented synthetic effectiveness including high step-economic fashion together with the advantages of having no by-product and no need for external high-pressure H2 gas, offering an important basis for the transformation of 1,8-naphthyridines and indolines into functionalized products.

High-Value Oil-Water Separation Materials Prepared from Waste Polyethylene Terephthalate.

As one of the most common forms of waste, waste PET is a serious pollutant in natural and human living environments. There is an urgent need to recycle PET. For this study, the complete degradation of PET was realized at a low temperature. A lipophilic hydrophobic membrane was formed on the surface of a stainless steel mesh (SSM) using a simple dip coating method, and an oil-water separation material was successfully prepared. After loading with degradation products, the surface roughness of SSM increased from 19.09 µm to 62.33 µm. The surface changed from hydrophilic to hydrophobic, and the water contact angle increased to 123°. The oil-water separation flux of the modified SSM was 9825 L/(m2·h), and the separation efficiency was 98.99%. The modified SSM had good reuse performance. This hydrophobic modification method can also be used to modify other porous substrates, such as activated carbon, filter paper, foam, and other materials. The porous substrate modified by the degradation product of waste PET was used to prepare oil-water separation materials, not only solving the problem of white pollution but also reducing the dependence on non-renewable resources in the conventional methods used for the preparation of oil-water separation materials. This study provides new raw materials and methods for the industrial production of oil-water separation materials, which have important application prospects.

Recent Advances in the Reverse Water-Gas Conversion Reaction.

The increase in carbon dioxide emissions has significantly impacted human society and the global environment. As carbon dioxide is the most abundant and cheap C1 resource, the conversion and utilization of carbon dioxide have received extensive attention from researchers. Among the many carbon dioxide conversion and utilization methods, the reverse water-gas conversion (RWGS) reaction is considered one of the most effective. This review discusses the research progress made in RWGS with various heterogeneous metal catalyst types, covering topics such as catalyst performance, thermodynamic analysis, kinetics and reaction mechanisms, and catalyst design and preparation, and suggests future research on RWGS heterogeneous catalysts.

Bismuth nanoparticles and oxygen vacancies synergistically modified HNb3O8 nanosheets for enhanced photocatalytic N2 reduction towards NH3.

Due to the high stability of the N2 molecule and the low charge separation efficiency, the photocatalytic reduction of N2 to high-value chemicals (NH3) under mild conditions remains a great challenge. Herein, a composite photocatalyst (Bi/HNb3O8-Vo nanosheets) with Bi nanoparticles modified the HNb3O8-Vo nanosheets are designed for the conversion of N2 into NH3. In this design, the introduction of oxygen vacancies on the catalyst surface facilitates the formation of defective energy levels within the band gap of HNb3O8-Vo NS, which promotes the absorption of visible light, and enhances the charge carrier transport and separation. Bi nanoparticles co-catalyst not only facilitates the separation and migration of photogenerated charges, but also acts as reaction sites to adsorb and activate N2 molecule. Consequently, the optimized 5 % Bi/HNb3O8-Vo photocatalysts show a NH3 yield of 372.7 µmol/L g-1h-1 under full spectral irradiation without sacrificial agent, which is much higher than that of HNb3O8 NS (92.2 µmol/L g-1h-1). This work provides a new way for the design of efficient N2 reduction photocatalysts through the synergistic effect of surface vacancies and metal co-catalysts.

Ni3B as p-Block Element-Modulated Cocatalyst for Efficient Photocatalytic CO2 Reduction.

Due to the multiple electron and proton transfer processes involved, the photogenerated charges are easily recombined during the photocatalytic reduction of CO2, making the generation of the eight-electron product CH4 kinetically more difficult. Herein, Ni3B nanoparticles modulated by p-block element were combined with TiO2 nanosheets to construct a novel Schottky junction photocatalyst (Ni3B/TiO2) for the selective photocatalytic conversion of CO2 to CH4. The formed Ni3B/TiO2 photocatalyst with Schottky junction ensures a transfer pathway of photogenerated electrons from TiO2 to Ni3B, which facilitates the accumulation of electrons on the surface of Ni3B and subsequently improves the activity of photocatalytic CO2 reduction to CH4. The optimized Ni3B/TiO2 Schottky junction shows an improved CH4 yield of 30.03 µmol g-1 h-1, which was much higher than those of TiO2 (1.62 µmol g-1 h-1), NiO/TiO2 (2.44 µmol g-1 h-1), and Ni/TiO2 (4.3 µmol g-1 h-1). This work demonstrated that the introduction of p-block elements can alleviate the scaling relationship effect of pure metal cocatalysts to a certain extent, and the modified Ni3B can be used as a promising new cocatalyst to effectively improve the selective photocatalytic of CO2 to CH4.

Epicoccum spp. Causing Maize Leaf Spot in Heilongjiang Province, China.

Maize leaf spot occurs worldwide and affects maize production. Maize can be infected by several pathogens causing leaf spot, such as Bipolaris zeicola, Bipolaris maydis, Curvularia species, Alternaria species, etc. In the current study, 30 Epicoccum isolates recovered from symptomatic maize leaves were identified based on morphological characteristics, pathogenicity, and multilocus sequence analyses of nuLSU, ITS, tub2, and rpb2. These maize isolates were grouped into five Epicoccum species, including E. nigrum, E. layuense, E. sorghinum, E. latusicollum, and E. pneumoniae. Pathogenicity tests showed that all five Epicoccum species could produce small ellipse- and spindle-shaped spots on maize leaves. The lesion center was grayish yellow to dark gray and surrounded by a chlorotic area. Furthermore, the Epicoccum isolates exhibited high pathogenicity to 20 main maize varieties of Heilongjiang Province but showed different sensitivities to the commonly used fungicides carbendazim and tebuconazole. In addition, these Epicoccum isolates showed different production capacity of pectinase, cellulase, protease, amylase, laccase, and gelatinase, but all showed high lipase activity. This is the first report globally of E. layuense, E. latusicollum, and E. pneumoniae as causal agents of maize leaf spot. E. pneumoniae was first reported as a plant pathogen.

Photocatalytic reduction of CO2 into CH4 over Ru-doped TiO2: Synergy of Ru and oxygen vacancies.

Photocatalytic conversion of CO2 and H2O into CH4 is an intriguing approach to achieve solar energy utilization and CO2 conversion, yet remains challenging in conversion efficiency. In this study, we present a synthesis of defected TiO2 nanocrystal with oxygen vacancies (Vo) by a facile Ru doping-induced strategy under hydrothermal condition. The synergistic effect of Ru and oxygen vacancies contributed to the enhanced photocatalytic reduction of CO2 toward CH4. Oxygen vacancies and doped Ru not only can synergistically promote the separation of photogenerated carriers, but also promote the CO2 adsorption, thus enhancing the photocatalytic activities. The optimal Ru-doped TiO2 (denoted as 1% Ru-TiO2-x) exhibited a remarkable enhanced photocatalytic performance with a CH4 yield of 31.63 µmol·g-1·h-1, which is significantly higher than Ru-TiO2 and TiO2-x counterparts. This study systematically investigates the multiple roles of Ru in CO2 reduction and provides new insights for the construction of metal oxide photocatalysts with oxygen vacancies by simple doping of metal ions.

Co-N-Si/AC Catalyst for Aerobic Oxidation of Benzyl Alcohols to Esters under Mild Conditions.

A stable, earth-abundant, reusable cobalt-based heterogeneous catalyst is developed for the oxidative esterification of alcohols under ambient conditions, featuring broad substrate scope, providing good to excellent product yields. This protocol enables easy recyclability of the catalyst, measured up to five times without significant loss of efficiency. The active sites of Co-N-Si/AC are proposed to be Co-N species.

COVID-19 Detection Based on Image Regrouping and Resnet-SVM Using Chest X-Ray Images.

As the COVID-19 spread worldwide, countries around the world are actively taking measures to fight against the epidemic. To prevent the spread of it, a high sensitivity and efficient method for COVID-19 detection is necessary. By analyzing the COVID-19 chest X-ray images, a combination method of image regrouping and ResNet-SVM was proposed in this study. The lung region was segmented from the original chest X-ray images and divided into small pieces, and then the small pieces of lung region were regrouped into a regular image randomly. Furthermore the regrouped images were fed into the deep residual encoder block for feature extraction. Finally the extracted features were as input into support vector machine for recognition. The visual attention was introduced in the novel method, which paid more attention to the features of COVID-19 without the interference of shapes, rib and other related noises. The experimental results showed that the proposed method achieved 93% accuracy without large number of training data, outperformed the existing COVID-19 detection models.

Synergistic Integration of AuCu Co-Catalyst with Oxygen Vacancies on TiO2 for Efficient Photocatalytic Conversion of CO2 to CH4.

Photocatalytic reduction of CO2 toward eight-electron CH4 product with simultaneously high conversion efficiency and selectivity remains great challenging owing to the sluggish charge separation and transfer kinetics and lack of active sites for the adsorption and activation of reactants. Herein, a defective TiO2 nanosheet photocatalyst simultaneously equipped with AuCu alloy co-catalyst and oxygen vacancies (AuCu-TiO2-x NSs) was rationally designed and fabricated for the selective conversion of CO2 into CH4. The experimental results demonstrated that the AuCu alloy co-catalyst not only effectively promotes the separation of photogenerated electron-hole pairs but also acts as synergistic active sites for the reduction of CO2. The oxygen vacancies in TiO2 contribute to the separation of charge carriers and, more importantly, promote the oxidation of H2O, thus providing rich protons to promote the deep reduction of CO2 to CH4. Consequently, the optimal AuCu-TiO2-x nanosheets (NSs) photocatalyst achieves a CO2 reduction selectivity toward CH4 up to 90.55%, significantly higher than those of TiO2-x NSs (31.82%), Au-TiO2-x NSs (38.74%), and Cu-TiO2-x NSs (66.11%). Furthermore, the CH4 evolution rate over the AuCu-TiO2-x NSs reaches 22.47 µmol·g-1·h-1, which is nearly twice that of AuCu-TiO2 NSs (12.10 µmol·g-1·h-1). This research presents a unique insight into the design and synthesis of photocatalyst with oxygen vacancies and alloy metals as the co-catalyst for the highly selective deep reduction of CO2.

Low-temperature grown vertically aligned carbon nanotube array for an optimal infrared bolometer.

Vertically aligned carbon nanotube (VACNT) arrays have been explored as an absorber of thermal-type photodetectors. A long and dense VACNT array absorbs a wide spectral range of incident light with high absorption rate, but has a high thermal mass that results in a low response speed. To achieve a small thermal mass, a shorter and less dense VACNT array is needed. In addition, the high temperature needed to grow the VACNTs is detrimental to the functional sensing materials of the photodetector. The height, density, and growth temperature of VACNTs need to be optimized to achieve a working absorber that has high absorption rate and a high response speed. In this work, a low-temperature plasma enhanced chemical vapor deposition process is used to prepare various VACNT arrays with different heights and densities by controlling the CNT growth parameters. The absorption coefficients of the resulting samples are measured with Fourier transform infrared spectroscopy. An effective medium theory (EMT) is adopted to establish a working model of the VACNTs. Using experimentally extracted CNT density and height as fitting parameters, the EMT model is fitted to obtain theoretical absorption coefficients, which are found to be comparable to the experimentally measured absorption coefficients. Our experimental and theoretical investigations pave the way for future studies to integrate CNTs with infrared photodetectors.

Oxygen-doped hollow, porous NiCoP nanocages derived from Ni-Co prussian blue analogs for oxygen evolution.

An oxygen-doped, hollow, porous NiCoP nanocage (O-NiCoP Cages) electrocatalyst was synthesized derived from Ni-Co Prussian blue analogs. O-NiCoP Cages exhibited an overpotential of 310 mV at 10 mA cm-2 and a Tafel slope of 84 mV dec-1, significantly higher than that of undoped NiCoP nanocages, and also better than that of RuO2 and several reported phosphide electrocatalysts. This work provides a new strategy for the design of highly efficient oxygen evolution reaction (OER) electrocatalysts based on hollow, nanostructured and heteroatom-doped metal phosphides.

Oxygen vacancy engineering of BiOBr/HNb3O8 Z-scheme hybrid photocatalyst for boosting photocatalytic conversion of CO2.

Photo-chemical conversion of CO2 into solar fuels by photocatalysts is a promising and sustainable strategy in response to the ever-increasing environmental problems and imminent energy crisis. However, it is unavoidably impeded by the insufficient active site, undesirable inert charge transfer and fast recombination of photogenerated charge carriers on semiconductor photocatalysts. In this work, all these challenges are overcome by construction of a novel defect-engineered Z-scheme hybrid photocatalyst, which is comprised of three-dimensional (3D) BiOBr nanoflowers assembled by nanosheets with abundant oxygen vacancies (BiOBr-VO) and two-dimensional (2D) HNb3O8 nanosheets (HNb3O8 NS). The special 3D-2D architecture structure is beneficial to preventing photocatalyst stacking and providing more active sites, and the introduced oxygen vacancies not only broaden the light absorption range but also enhance the electrical conductivity. More importantly, the constructed Z-scheme photocatalytic system could accelerate the charge carriers transfer and separation. As a result, the optimal BiOBr-VO/HNb3O8 NS (50%-BiOBr-VO/HNb3O8 NS) shows a high CO production yield of 164.6 µmol·g-1 with the selectivity achieves to 98.7% in a mild gas-solid system using water as electron donors. Moreover, the BiOBr-VO/HNb3O8 NS photocatalyst keeps high photocatalytic activity after five cycles under the identical experimental conditions, demonstrating its excellent long-term durability. This work provided an original strategy to design a new hybrid structure photocatalyst involved VOs, thus guiding a new way to further enhance CO2 reduction activity of photocatalyst.

Synthesis of Vertical Carbon Nanotube Interconnect Structures Using CMOS-Compatible Catalysts.

Synthesis of the vertically aligned carbon nanotubes (CNTs) using complementary metal-oxide-semiconductor (CMOS)-compatible methods is essential to integrate the CNT contact and interconnect to nanoscale devices and ultra-dense integrated nanoelectronics. However, the synthesis of high-density CNT array at low-temperature remains a challenging task. The advances in the low-temperature synthesis of high-density vertical CNT structures using CMOS-compatible methods are reviewed. Primarily, recent works on theoretical simulations and experimental characterizations of CNT growth emphasized the critical roles of catalyst design in reducing synthesis temperature and increasing CNT density. In particular, the approach of using multilayer catalyst film to generate the alloyed catalyst nanoparticle was found competent to improve the active catalyst nanoparticle formation and reduce the CNT growth temperature. With the multilayer catalyst, CNT arrays were directly grown on metals, oxides, and 2D materials. Moreover, the relations among the catalyst film thickness, CNT diameter, and wall number were surveyed, which provided potential strategies to control the tube density and the wall density of synthesized CNT array.

Breaking symmetry in device design for self-driven 2D material based photodetectors.

The advent of graphene and other two-dimensional (2D) materials offers great potential for optoelectronic applications. Various device structures and novel mechanisms have been proposed to realize photodetectors with unique detecting properties. In this minireview, we focus on a self-driven photodetector that has great potential for low-power or even powerless operation required in the internet of things and wearable electronics. To address the general principle of self-driven properties, we propose and elaborate the concept of symmetry breaking in 2D material based self-driven photodetectors. We discuss various mechanisms of breaking symmetry for self-driven photodetectors, including asymmetrical contact engineering, field-induced asymmetry, PN homojunctions, and PN heterostructures. Typical device examples based on these mechanisms are reviewed and compared. The performance of current self-driven photodetectors is critically assessed and future directions are discussed towards the target application fields.