Search

• A CQDs/BiVO 4 S-scheme piezo-photocatalyst was successfully constructed. • CQDs/BiVO 4 displayed efficient piezo-photocatalytic degradation of TC. • C–O–Bi bonds provided an atomic-level interfacial channel for facilitating charge separation. • The possible piezo-photocatalytic degradation mechanism of CQDs/BiVO 4 was proposed. Reasonable design of an efficient S-scheme photocatalyst remains an ongoing challenge due to the limitation of interfacial charge separation efficiency. Herein, CQDs/BiVO 4 S-scheme heterojunction with Bi–O–C bond was synthesized by introducing carbon quantum dots (CQDs) growth on BiVO 4 piezo-photocatalyst and absorbed visible light up to 750 nm. Under light + ultrasonic conditions, the reaction rate constant (k) of BVO/C-0.10 reached 0.0517 min−1 on tetracycline (TC) degradation, which was 2.24 and 4.04 times higher than those of BiVO 4 and CQDs, respectively. The enhanced performance was attributed to the improved efficiency of the photogenerated carrier separation, originating from the combination of piezoelectric effect and S-scheme heterojunction with Bi–O–C bond. The Bi–O–C bond at the CQDs (3–8 nm) and BiVO 4 interfaces connected the two semiconductor materials and provided an atomic-level interface channel for carrier migration. The piezoelectric properties of the composites were investigated by piezo−response force microscopy (PFM). Based on Mott−Schottky curves, X-ray photoelectron spectroscopy (XPS), and scavenging experiments, the possible piezo-photocatalytic mechanism was proposed in combination with the band structures and characteristics of CQDs and BiVO 4. This work furnishes unique insights into developing efficient S-scheme piezo-photocatalysts for purifying wastewater. [Display omitted] [ABSTRACT FROM AUTHOR]

Detecting genes that affect specific traits (such as human diseases and crop yields) is important for treating complex diseases and improving crop quality. A genome-wide association study (GWAS) provides new insights and directions for understanding complex traits by identifying important single nucleotide polymorphisms. Many GWAS summary statistics data related to various complex traits have been gathered recently. Studies have shown that GWAS risk loci and expression quantitative trait loci (eQTLs) often have a lot of overlaps, which makes gene expression gradually become an important intermediary to reveal the regulatory role of GWAS. In this review, we review three types of gene-trait association detection methods of integrating GWAS summary statistics and eQTLs data, namely colocalization methods, transcriptome-wide association study-oriented approaches, and Mendelian randomization-related methods. At the theoretical level, we discussed the differences, relationships, advantages, and disadvantages of various algorithms in the three kinds of gene-trait association detection methods. To further discuss the performance of various methods, we summarize the significant gene sets that influence high-density lipoprotein, low-density lipoprotein, total cholesterol, and triglyceride reported in 16 studies. We discuss the performance of various algorithms using the datasets of the four lipid traits. The advantages and limitations of various algorithms are analyzed based on experimental results, and we suggest directions for follow-up studies on detecting gene-trait associations.

Electrocatalytic conversion of waste nitrogen oxide (NOx) into value-added nitrogenous chemicals, especially amino acid, is an emerging strategy to alleviate NOxpollution. However, this process suffers from the coexistence of multiple competitive reactions leading to complex product distribution and low efficiency, and thus the rational design and modulation of efficient catalysts remains a formidable challenge. Herein, well-designed Co nanoparticles encapsulated in hollow carbon nanofiber (Co-HCNF) were constructed to promote the amino acid electrosynthesis viadealing waste NOxcoupling with biomass-derived keto acids. Ascribed to the rapid reactant diffusion, electron transport and efficient contact with abundant accessible Co catalytic sites stemmed from the unique hollow nanotubular structure, Co-HCNF manifested impressive glycine synthesis performance in one-pot adopting NO as the nitrogen source with Faradaic efficiency (FE) of 41.7% and a corresponding yield rate of 222.3 µmol h−1as well as 120 h robust stability. Interestingly, it also demonstrates an excellent performance with the FE of 42.8% for NO3−solution as the nitrogen source. Specially, this strategy displays a broad universality for the synthesis of other amino acids. This work not only highlights the importance of hollow-structuring electrocatalyst towards upgrading wasted NOxspecies into amino acids, but also promotes the further development of electrosynthetic systems for high-valued N-containing organic chemicals.

Reinforcement learning (RL) has emerged as a key technique for designing dialogue policies. However, action space inflation in dialogue tasks has led to a heavy decision burden and incoherence problems for dialogue policies. In this paper, we propose a novel decomposed deep Q-network (D2Q) that exploits the natural structure of dialogue actions to perform decomposition on Q-function, realizing efficient and coherent dialogue policy learning. Instead of directly evaluating the Q-function, it consists of two separate estimators, one for the abstract action-value functions and the other for the specific action-value functions, both sharing a common feature layer. The abstract action-value function determines the speech act of the system action, while the specific action-value function focuses on the concrete action. This structure establishes a logical relationship between the user and the system on speech actions, avoiding the problem of incoherence. Moreover, the abstract action-value function shields unreasonable specific actions in the inflated action space, reducing the decision complexity. Our results show that the problem of incoherence is prevalent in existing approaches, which significantly impacts the efficiency and quality of dialogue policy learning. Our D2Q architecture alleviates this problem and performs significantly better than competitive baselines in both evaluated and human experiments. Further experiments validate the generality of our method. It can be easily extended to other RL-based dialogue policy approaches.

An unprecedented copper and in situ-generated triflic acid relay-promoted four-component cascade reaction of cyanamides, diaryliodonium triflates, propargylic amines, and H2O was established for rapid and concise construction of diverse five-membered cycloguanidines. Copper-catalyzed guanidination/intramolecular hydroamination and in situ-generated HOTf-accelerated hydration proceeded sequentially with high level of chemoselectivity and regioselectivity, and six new bonds were simultaneously built in high yields. Thus, diaryliodonium triflates served not only as an arylation reagent but also as an internal acid promoter, establishing an alternative strategy for highly efficient utilization of diaryliodonium trifates.

Hydrogen evolution production viaelectrolysis of water in alkaline solution is a promising mean of industrial hydrogen production. However, inefficiency and high cost restrict its industrialization development. Based on extensive studies of experimental and theoretical investigations, two-dimensional (2D) materials are promising substitute of noble metals for hydrogen evolution reaction (HER) with low cost and high-efficiency. Herein, recent progress in 2D metal-organic frameworks (MOFs) for HER in alkaline electrolyte is systematically discussed and summarized. This review describes the strategies about how to design and optimize the structure of 2D MOF-based materials as HER electrocatalysts with well performance and aims to provide potential avenues for industrial hydrogen production. Additionally, the challenges and future directions ahead in this field are also proposed.

Ultrasmall metal nanoparticles (NPs) show high catalytic activity in heterogeneous catalysis but are prone to reunion and loss during the catalytic process, resulting in low chemoselectivity and poor efficiency. Herein, a locking effect strategy is proposed to synthesize high-loading and ultrafine metal NPs in metal–organic frameworks (MOFs) for efficient chemoselective catalysis with high stability. Briefly, the MOF ZIF-90 with aldehyde groups cooperating with diamine chains via aldimine condensation was interlocked, which was employed to confine in situformation of Au NPs, denoted as Au@L-ZIF-90. The optimized Au@La-ZIF-90 has highly dispersed Au NPs (2.60 ± 0.81 nm) with a loading amount around 22 wt % and shows a great performance toward 3-aminophenylacetylene (3-APA) from the selective hydrogenation of 3-nitrophenylacetylene (3-NPA) with a high yield (99%) and excellent durability (over 20 cycles), far superior to contrast catalysts without chains locking and other reported catalysts. In addition, experimental characterization and systematic density functional theory calculations further demonstrate that the locked MOF modulates the charge of Au nanoparticles, making them highly specific for nitro group hydrogenation to obtain 3-APA with high selectivity (99%). Furthermore, this locking effect strategy is also applicable to other metal nanoparticles confined in a variety of MOFs, and all of these catalysts locked with chains show great selectivity (≥90%) of 3-APA. The proposed strategy in this work provides a novel and universal method for precise control of the inherent activity of accessible metal nanoparticles with a programmable MOF microenvironment toward highly specific catalysis.

This study aimed to identify the main medicinal active components of Panax ginseng(P. ginseng) in the compatibility environment of clinical application. For this purpose, the anti-inflammatory ingredients of P. ginsengwere investigated based on its therapeutic effect in Sijunzi Decoction (SJD) which is a widely used traditional Chinese formula.

Objective: Diabetes is considered a significant risk factor for the development of atrial fibrillation/flutter (AF/AFL). However, there is still insufficient evidence to determine the varying effects of different hypoglycemic drugs (HDs) on the incidence of new-onset AF/AFL in diabetic patients. To address this gap, we conducted a network meta-analysis to investigate whether various HDs have different effects on the risk of new-onset AF/AFL compared with insulin. Method: We conducted a comprehensive search in PubMed, EMBASE, Cochrane Library, and Web of Science to identify all clinical trials investigating the association between various HDs or insulin and incident AF/AFL up until April 1, 2024. Bayesian random-effects model was used for network meta-analysis, and the results were expressed as relative risk (RR) and 95% confidence interval (CI). Result: After searching 2070 articles, a total of 12 studies (2,349,683 patients) were included in the network meta-analysis. The treatment regimen comprised insulin and 8 HDs hypoglycemic drugs, which are sodium-dependent glucose transporters 2 inhibitor (SGLT2i), glucagon-like peptide 1 receptor agonist (GLP-1RA), dipeptidyl peptidase 4 inhibitors (DPP4i), metformin (Met), sulfonylureas (SU), non-sulfonylureas (nSU), thiazolidinedione (TZD) and α-glycosidase inhibitors (AGI). The use of SGLT2i [RR 0.23, 95%CI (0.11, 0.49)], GLP-1RA [RR 0.28, 95%CI (0.13, 0.57)], and DPP4i [RR 0.34, 95%CI (0.17, 0.67)] demonstrated significant efficacy in reducing the incidence of new-onset AF/AFL when compared to insulin. When HDs were compared in pairs, SGLT2i is more effective than Met [RR 0.35, 95% CI (0.19, 0.62)], SU (RR 0.27, 95% CI (0.14, 0.51)], nSU [RR 0.28, 95% CI (0.08, 0.95)], TZD [RR 0.34, 95% CI (0.17, 0.7)], GLP-1RA is more effective Met [RR 0.42, 95% CI (0.25, 0.71)], SU (RR 0.33, 95% CI (0.18, 0.6)], TZD [RR 0.41, 95% CI (0.21, 0.82)], while Met[RR 1.98, 95% CI (1.23, 3.23)], SU [RR 2.54, 95% CI (1.46, 4.43)], TZD [RR 2.01, 95% CI (1.05, 3.79)] was not as effective as DPP4i. Conclusion: SGLT-2i, GLP-1RA, and DPP4i showed a superior efficacy in reducing the risk of new-onset AF/AFL compared to insulin therapy.

Communication is an effective mechanism for coordinating the behaviors of multiple agents, broadening their views of the environment, and to support their collaborations. In the field of multi-agent deep reinforcement learning (MADRL), agents can improve the overall learning performance and achieve their objectives by communication. Agents can communicate various types of messages, either to all agents or to specific agent groups, or conditioned on specific constraints. With the growing body of research work in MADRL with communication (Comm-MADRL), there is a lack of a systematic and structural approach to distinguish and classify existing Comm-MADRL approaches. In this paper, we survey recent works in the Comm-MADRL field and consider various aspects of communication that can play a role in designing and developing multi-agent reinforcement learning systems. With these aspects in mind, we propose 9 dimensions along which Comm-MADRL approaches can be analyzed, developed, and compared. By projecting existing works into the multi-dimensional space, we discover interesting trends. We also propose some novel directions for designing future Comm-MADRL systems through exploring possible combinations of the dimensions.

Severe burns threaten patient lives due to pain, inflammation, bacterial infection, and scarring. Most burn dressings that are commonly used perform a single function and are not well suited for the management of deep burns. Therefore, a multifunctional antimicrobial peptide‐ and stem cell‐loaded macroporous hydrogel that can fight bacterial infection and regulate wound healing progression by temporally regulating cytokine production by internal stem cells is developed. The macroporous skeletal hydrogel is manufactured via the cryogenic gelation of hyaluronic acid (cryogel). Based on the oxidative polymerization reaction of dopamine, the antimicrobial peptide DP7 is immobilized on the surface of the cryogel (DA7CG). Placental mesenchymal stem cells (PMSCs) are then packaged inside the macroporous hydrogel (DA7CG@C). According to the results of in vitro and in vivo experiments, during the inflammatory phase, DP7 inhibits infection and modulates inflammation; during the proliferative phase, DA7CG@C accelerates the regeneration of skin, blood vessels, and hair follicles via internal stem cells; and during the remodeling phase, DA7CG@C contributes to extracellular matrix remodeling due to the ability of DP7 to regulate the paracrine secretion of PMSCs, synergistically promoting scar‐free healing. DA7CG@C can participate in all phases of wound healing; therefore, it is a promising dressing for burn treatment. Antibacterial peptide and stem cell loaded hydrogels possessantibacterial properties and promote wound healing; and so, are bifunctional. This study reports a cryogel wound dressing that regulates inflammatory reactions and growth factor expression. This cryogel wound dressing can participate in all the stages of wound healing and regulate wound healing progress.

The phase equilibriums of the ternary system KCl-(NH2)2CO-H2O at 303.15 K, 323.15 K, 333.15 K, and 343.15 K were studied using the isothermal dissolution equilibrium method, in which the composition of equilibrium solid phase was determined by Schreinemaker’s wet residue method and X-ray diffraction (XRD) method. It was found that the ternary system is a simple cosaturated system, without the formation of neither double salt nor solid solution. Wilson and NRTL models were employed to correlate in the solubility data of the system at experimental temperatures. The maximum values of RAD and RMSD of the Wilson model were 2.18 × 10−2 and 0.83 and those of the NRTL model were 1.69 × 10−2 and 0.40, respectively. The two models were utilized to forecast solubility data at various temperatures, and the obtained outcomes were in line with the literature data. Based on the experimental solubility data at 343.15 K, the cooling crystallization process of the system was monitored online by focused beam reflectance measurement (FBRM) and particle video microscope (PVM). The crystal products were characterized by XRD, scanning electron microscope (SEM), and energy dispersive spectrometry (EDS). The results showed that the precipitation of (NH2)2CO occurred during the crystallization process, and this was followed by KCl. KCl was formed on the surface of (NH2)2CO crystal. The crystal was a simple mixture containing KCl and (NH2)2CO.

Previous studies demonstrated that hydantoin ibuprofen conjugates had effective anti-inflammatory and antitussive activities. In this study, we evaluated their analgesic and gastric ulcerogenic activities. Our results showed that these compounds retained analgesic activity from ibuprofen, more important, could suppress gastric ulceration. Furthermore, by analyzing the metabolites of the compounds in rat plasma using LC-MS/MS, we found that the compounds were hydrolyzed to hydantoin and ibuprofen, and then followed by ibuprofen conjugation to glucuronic acid.

The incidence and outcomes of disseminated intravascular coagulation (DIC) are incompletely defined. Therefore, we aimed to evaluate the trends in incidence and outcomes of critically ill patients with DIC.

1-Methylhydantion is a compound, which was isolated from Oviductus Ranae for the first time. In our study, we found that it showed good antitussive and anti-inflammatory activity. It is also the first report which illustrates the antitussive activity of hydantion derivative. A series of hydantion derivatives were synthesized and evaluated for their anti-inflammatory and antitussive activity in vivo. The pharmacological tests showed that compounds 7a, 7c and 7d have good anti-inflammatory and antitussive activity compared to Ibuprofen and codeine. Compound 7a in particular showed two-fold stronger anti-inflammatory activity than Ibuprofen.

To ensure the highest quality of Oviductus Ranaeproducts for consumers, an accurate, efficient, scientific and comprehensive evaluation method for assessing the quality of Oviductus Ranaewas proposed in this paper. The fingerprint of Oviductus Ranaehas been established based on the method of high performance liquid chromatography (HPLC). Oviductus Ranaefrom different habitats were analyzed by hierarchical cluster analysis (HCA). The HPLC profiles of fourteen batches of Oviductus Ranaeshowed 33 well-resolved common peaks in each chromatogram. Five of these were assigned to 1-methyl hydantoin, 7-ketocholesterol, 4-cholesten-3-one, cholesterol and stigmasterol. Contents of these five main effective components were determined in the meantime. Based on the HPLC profiles of all the samples, the reference HPLC fingerprint and similarity values were calculated by statistical software (SPSS 19.0). It was found that similarity value of all Oviductus Ranaesamples were more than 0.85 and Oviductus Ranaefrom same habitats had similarity to some degree. In conclusion, the proposed method had good specificity, repeatability, stability and precision, which can provide a reference for the quality evaluation and identification of the medicine origin of Oviductus Ranae. Quantitation of effective components revealed that contents of five effective constituents in Oviductus Ranaeobtained from Ji Lin province were the highest, followed by Hei Longjiang province and Liaoning province. The results of HCA showed that samples classified into one group were associated with their habitats. HPLC fingerprint combined with quantitation of main effective compounds and data analysis techniques can be an efficient and useful method for monitoring the quality of Oviductus Ranae.