In situ turning defects of exfoliated Ti3C2 MXene into Fenton-like catalytic active sites.

Controllable in situ formation of nanoclusters with discrete active sites is highly desirable in heterogeneous catalysis. Herein, a titanium oxide-based Fenton-like catalyst is constructed using exfoliated Ti3C2 MXene as a template. Theoretical calculations reveal that a redox reaction between the surface Ti-deficit vacancies of the exfoliated Ti3C2 MXene and H2O2 molecules facilitates the in situ conversion of surface defects into titanium oxide nanoclusters anchoring on amorphous carbon (TiOx@C). The presence of mixed-valence Tiδ+ (δ = 0, 2, 3, and 4) within TiOx@C is confirmed by X-ray photoelectron spectroscopy (XPS) and X-ray absorption fine structure (XAFS) characterizations. The abundant surface defects within TiOx@C effectively promote the generation of reactive oxygen species (ROS) leading to superior and stable Fenton-like catalytic degradation of atrazine, a typical agricultural herbicide. Such an in situ construction of Fenton-like catalysts through defect engineering also applies to other MXene family materials, such as V2C and Nb2C.

Multilayer Ti3 C2 -CNTs-Au Loaded with Cyclodextrin-MOF for Enhanced Selective Detection of Rutin.

In this work, multi-layer Ti3 C2 - carbon nanotubes - gold nanoparticles (Ti3 C2 -CNTs-Au) and cyclodextrin metal-organic framework - carbon nanotubes (CD-MOF-CNTs) have been prepared by in situ growth method and used to construct the ultra-sensitive rutin electrochemical sensor for the first time. Among them, the large number of metal active sites of Ti3 C2 , the high electron transfer efficiency of CNTS, and the good catalytic properties of AuNPs significantly enhance the electrochemical properties of the composite carbon nanomaterials. Interestingly, CD-MOF has a unique host-guest recognition and a large number of cavities, molecular gaps, and surface reactive groups, which gives the composite outstanding accumulation properties and selectivity for rutin. Under the optimized conditions, the constructed novel sensor has satisfactory detection performance for rutin in the range of 2 × 10-9 to 8 × 10-7  M with a limit of detection of 6.5 × 10-10  M. In addition, the sensor exhibits amazing anti-interference performance against rutin in some flavonoid compounds and can be used to test natural plant samples (buckwheat, Cymbopogon distans, and flos sophorae immaturus). This work has promising applications in the field of environmental and food analysis, and exploring new directions for the application of Mxene-based composites.

CProMG: controllable protein-oriented molecule generation with desired binding affinity and drug-like properties.

MOTIVATION: Deep learning-based molecule generation becomes a new paradigm of de novo molecule design since it enables fast and directional exploration in the vast chemical space. However, it is still an open issue to generate molecules, which bind to specific proteins with high-binding affinities while owning desired drug-like physicochemical properties. RESULTS: To address these issues, we elaborate a novel framework for controllable protein-oriented molecule generation, named CProMG, which contains a 3D protein embedding module, a dual-view protein encoder, a molecule embedding module, and a novel drug-like molecule decoder. Based on fusing the hierarchical views of proteins, it enhances the representation of protein binding pockets significantly by associating amino acid residues with their comprising atoms. Through jointly embedding molecule sequences, their drug-like properties, and binding affinities w.r.t. proteins, it autoregressively generates novel molecules having specific properties in a controllable manner by measuring the proximity of molecule tokens to protein residues and atoms. The comparison with state-of-the-art deep generative methods demonstrates the superiority of our CProMG. Furthermore, the progressive control of properties demonstrates the effectiveness of CProMG when controlling binding affinity and drug-like properties. After that, the ablation studies reveal how its crucial components contribute to the model respectively, including hierarchical protein views, Laplacian position encoding as well as property control. Last, a case study w.r.t. protein illustrates the novelty of CProMG and the ability to capture crucial interactions between protein pockets and molecules. It's anticipated that this work can boost de novo molecule design. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are freely available at https://github.com/lijianing0902/CProMG.

Circ_0082878 contributes to prostate cancer progression via the miR-455-3p/WTAP axis.

Circ_0082878 has been found to be strongly expressed in prostate cancer (PCa). However, its roles and potential mechanism in PCa have not been investigated. This study aims to clarify it. RNase R digestion method was adopted for verifying the circular structure of circ_0082878. RT-qPCR assay is aimed to detect the expressions of circ_0082878, miR-455-3p and WTAP in PCa tissues and cells. For identifying cell proliferation, migration and invasion abilities, CCK-8 and transwell assay were used. To show the correlation between miR-455-3p and WTAP or circ_0082878, the luciferase reporter gene, RNA RIP and RNA pull-down experiments were employed. We employed western blot to detect protein level of WTAP. In addition, the impact of circ_0082878 on PCa cells in vivo was also studied. It was found that circ_0082878 and WTAP were highly expressed in PCa tissues and cells, whereas miR-455-3p was lowly expressed. Inhibition of circ_0082878 restrained the growth of PCa in vitro and in vivo. Regarding mechanism, miR-455-3p was the target of circ_0082878, and WTAP was the target of miR-455-3p. Circ_0082878 could downregulate the level of miR-455-3p, and inhibiting of miR-455-3p expression could partially eliminate the inhibitory impact of low expression of circ_0082878 on the proliferation and migration of PCa cells. Additionally, over-expression of miR-455-3p resulted in the reduced level of WTAP, and WTAP over-expression counteracted the tumor suppressive impact of miR-455-3p in PCa cells. Moreover, the obtained findings indicated that circ_0082878 may exert tumor-promoting activity in PCa via sponging miR-455-3p and then upregulating WTAP. This indicates that the circ_0082878/miR-455-3p/WTAP axis can probably become the possible therapeutic target for PCa.

Ultra-sensitive electrochemical sensor based on in situ grown ultrafine HKUST-1 nanoparticles @ graphite nanosheets and core-shell structured MoO3-polypyrrole nanowires for the detection of rutin in orange juice.

Rutin extracted from natural plants has important medical value, so developing accurate and sensitive quantitative detection methods is one of the most important tasks. In this work, HKUST-1@GN/MoO3-Ppy NWs were utilized to develop a high-performance rutin electrochemical sensor in virtue of its high conductivity and electrocatalytic activity. The morphology, crystal structure, and chemical element composition of the fabricated sensor composites were characterized by SEM, TEM, XPS, and XRD. Electrochemical techniques including EIS, CV, and DPV were used to investigate the electrocatalytic properties of the prepared materials. The electrochemical test conditions were optimized to achieve efficient detection of rutin. The 2-electron 2-proton mechanism, consisting of several rapid and sequential phases, is postulated to occur during rutin oxidation. The results show that HKUST-1@GN/MoO3-Ppy NWs have the characteristics of large specific surface area, excellent conductivity, and outstanding electrocatalytic ability. There is a significant linear relationship between rutin concentration and the oxidation peak current of DPV. The linear range is 0.50-2000 nM, and the limit of detection is 0.27 nM (S/N = 3). In addition, the prepared electrode has been confirmed to be useful for rutin analysis in orange juice.

Regional Pulmonary Ventilation Assessment Method and System Based on Impedance Sensing Information from the Pentapulmonary Lobes.

Regional lung ventilation assessment is a critical tool for the early detection of lung diseases and postoperative evaluation. Biosensor-based impedance measurements, known for their non-invasive nature, among other benefits, have garnered significant attention compared to traditional detection methods that utilize pressure sensors. However, solely utilizing overall thoracic impedance fails to accurately capture changes in regional lung air volume. This study introduces an assessment method for lung ventilation that utilizes impedance data from the five lobes, develops a nonlinear model correlating regional impedance with lung air volume, and formulates an approach to identify regional ventilation obstructions based on impedance variations in affected areas. The electrode configuration for the five lung lobes was established through numerical simulations, revealing a power-function nonlinear relationship between regional impedance and air volume changes. An analysis of 389 pulmonary function tests refined the equations for calculating pulmonary function parameters, taking into account individual differences. Validation tests on 30 cases indicated maximum relative errors of 0.82% for FVC and 0.98% for FEV1, all within the 95% confidence intervals. The index for assessing regional ventilation impairment was corroborated by CT scans in 50 critical care cases, with 10 validation trials showing agreement with CT lesion localization results.

Characterization and Potential Action Mode Divergences of Homologous ACO1 Genes during the Organ Development and Ripening Process between Non-Climacteric Grape and Climacteric Peach.

Ethylene is one crucial phytohormone modulating plants' organ development and ripening process, especially in fruits, but its action modes and discrepancies in non-climacteric grape and climacteric peach in these processes remain elusive. This work is focused on the action mode divergences of ethylene during the modulation of the organ development and ripening process in climacteric/non-climacteric plants. We characterized the key enzyme genes in the ethylene synthesis pathway, VvACO1 and PpACO1, and uncovered that their sequence structures are highly conserved, although their promoters exhibit important divergences in the numbers and types of the cis-elements responsive to hormones, implying various responses to hormone signals. Subsequently, we found the two have similar expression modes in vegetative organ development but inverse patterns in reproductive ones, especially in fruits. Then, VvACO1 and PpACO1 were further validated in promoting fruit ripening functions through their transient over-expression/RNAi-expression in tomatoes, of which the former possesses a weaker role than the latter in the fruit ripening process. Our findings illuminated the divergence in the action patterns and function traits of the key VvACO1/PpACO1 genes in the tissue development of climacteric/non-climacteric plants, and they have implications for further gaining insight into the interaction mechanism of ethylene signaling during the modulation of the organ development and ripening process in climacteric/non-climacteric plants.

MLGL-MP: a Multi-Label Graph Learning framework enhanced by pathway interdependence for Metabolic Pathway prediction.

MOTIVATION: During lead compound optimization, it is crucial to identify pathways where a drug-like compound is metabolized. Recently, machine learning-based methods have achieved inspiring progress to predict potential metabolic pathways for drug-like compounds. However, they neglect the knowledge that metabolic pathways are dependent on each other. Moreover, they are inadequate to elucidate why compounds participate in specific pathways. RESULTS: To address these issues, we propose a novel Multi-Label Graph Learning framework of Metabolic Pathway prediction boosted by pathway interdependence, called MLGL-MP, which contains a compound encoder, a pathway encoder and a multi-label predictor. The compound encoder learns compound embedding representations by graph neural networks. After constructing a pathway dependence graph by re-trained word embeddings and pathway co-occurrences, the pathway encoder learns pathway embeddings by graph convolutional networks. Moreover, after adapting the compound embedding space into the pathway embedding space, the multi-label predictor measures the proximity of two spaces to discriminate which pathways a compound participates in. The comparison with state-of-the-art methods on KEGG pathways demonstrates the superiority of our MLGL-MP. Also, the ablation studies reveal how its three components contribute to the model, including the pathway dependence, the adapter between compound embeddings and pathway embeddings, as well as the pre-training strategy. Furthermore, a case study illustrates the interpretability of MLGL-MP by indicating crucial substructures in a compound, which are significantly associated with the attending metabolic pathways. It is anticipated that this work can boost metabolic pathway predictions in drug discovery. AVAILABILITY AND IMPLEMENTATION: The code and data underlying this article are freely available at https://github.com/dubingxue/MLGL-MP.

A calmodulin-like protein (CML10) interacts with cytosolic enzymes GSTU8 and FBA6 to regulate cold tolerance.

Calmodulin-like proteins (CMLs) are calcium (Ca2+) sensors involved in plant growth and development as well as adaptation to environmental stresses; however, their roles in plant responses to cold are not well understood. To reveal the role of MsCML10 from alfalfa (Medicago sativa) in regulating cold tolerance, we examined transgenic alfalfa and Medicago truncatula overexpressing MsCML10, MsCML10-RNAi alfalfa, and a M. truncatula cml10-1 mutant and identified MsCML10-interacting proteins. MsCML10 and MtCML10 transcripts were induced by cold treatment. Upregulation or downregulation of MsCML10 resulted in increased or decreased cold tolerance, respectively, while cml10-1 showed decreased cold tolerance that was complemented by expressing MsCML10, suggesting that MsCML10 regulates cold tolerance. MsCML10 interacted with glutathione S-transferase (MsGSTU8) and fructose 1,6-biphosphate aldolase (MsFBA6), and the interaction depended on the presence of Ca2+. The altered activities of Glutathione S-transferase and FBA and levels of ROS and sugars were associated with MsCML10 transcript levels. We propose that MsCML10 decodes the cold-induced Ca2+ signal and regulates cold tolerance through activating MsGSTU8 and MsFBA6, leading to improved maintenance of ROS homeostasis and increased accumulation of sugars for osmoregulation, respectively.

Pump-probe-alternating photothermal interferometry for two-component gas sensing.

We demonstrate a high-sensitivity acetylene/methane gas sensor based on hollow-core fiber photothermal interferometry (PTI) with a pump-probe-alternating technique. This technique utilizes two distributed-feedback lasers as pump and probe beams alternatively for two gas components to facilitate photothermal phase modulation and detection through time-division multiplexing. With a 2.5-cm-long hollow-core conjoint-tube fiber, noise-equivalent concentrations of 370 ppb and 130 ppb are demonstrated for methane and acetylene, respectively. Noise characteristics of the PTI system are analyzed and experimentally tested. The proposed technique eliminates the need for an additional laser in the traditional PTI setup, enabling the construction of a sensitive yet more cost-effective multi-gas component detection system.

Effects of acute normovolemic hemodilution on allogeneic blood transfusion & coagulation in orthognathic surgery: A randomized study.

BACKGROUND: Acute normovolemic hemodilution (ANH) is one of the important techniques predominantly used in cardiac, hepatic, and vascular surgery for decreasing allogeneic blood transfusion. However, the effect of ANH in orthognathic surgery has been rarely studied. Therefore, this study aims to assess the ANH-mediated reduction in the allogeneic red blood cell transfusion for orthognathic surgery patients. STUDY DESIGN AND METHODS: In this single-center study, 18-80 years old patients were recruited. Patients with hemoglobin ≥11 g/dL and normal coagulation function were randomly divided into ANH or standard treatment group. RESULTS: Ninety six patients underwent ANH, and 101 patients received standard treatment. No differences in demographic or major pre-operative characteristics were observed between the two groups. One patient in the ANH and three patients in the standard treatment group received allogeneic blood [3(2.97%) vs. 1(1.16%), control vs. ANH, p = .395]. Multivariate logistic regression analysis revealed that ANH treatment was not associated with transfusion of allogeneic blood (p = .763). After retransfusing autologous blood, PT and APTT in the ANH group significantly increased compared to standard treatment group (PT: -1.73 ± 1.09 vs. -2.15 ± 1.06, p = .035; APTT: -6.39 ± 5.76 vs. -8.16 ± 5.70, p = .031; control vs. ANH). No significant differences between the two groups were observed for changes in coagulation parameters at first postoperative day. However, platelet counts in the ANH group decreased compared to the standard group. No significant difference in major adverse outcomes was observed between the two groups. CONCLUSION: ANH did not reduce the incidence of allogeneic transfusion in patients undergoing orthognathic surgery.

Paclitaxel inhibits hepatocellular carcinoma tumorigenesis by regulating the circ_0005785/miR-640/GSK3ß.

Paclitaxel (PTX) is an effective chemotherapeutic agent for cancer patients. It has been reported that circular RNA (circRNA) circ_0005785is involved in the progression of hepatocellular carcinoma (HCC). The purpose of this study is to explore the role and mechanism of circ_0005785 in the PTX resistance of HCC. Cell viability, proliferation, invasion, migration, apoptosis, and angiogenesis were detected using 3-(4, 5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2-H-tetrazolium bromide (MTT), colony formation, transwell, wound-healing, flow cytometry, and tube formation assay. Circ_0005785, microRNA-640 (miR-640), and Glycogen synthase kinase-3 beta (GSK3ß) levels were detected using real-time quantitative polymerase chain reaction. Protein levels of Proliferating cell nuclear antigen (PCNA), Bcl-2, and GSK3ß were measured using western blot assay. After being predicted using Circular RNA interactome or TargetScan, binding between miR-640 and circ_0005785 or GSK3ß was verified using dual-luciferase reporter and RNA Immunoprecipitation assay. PTX treatment could repress HCC cell viability, decrease circ_0005785 and GSK3ß expression, and increase the miR-640 level in HCC cell lines. Furthermore, circ_0005785 and GSK3ß were increased, and miR-640 was decreased in HCC tissues and cell lines. Moreover, circ_0005785 knockdown hindered proliferation, migration, invasion, angiogenesis, and boosted apoptosis in PTX-treated HCC cells in vitro. In addition, circ_0005785 silencing improved the PTX sensitivity of HCC in vivo. Mechanistically, circ_0005785 acted as a sponge of miR-640 to regulate GSK3ß expression. PTX restrained HCC tumorigenesis partly via regulating the circ_0005785/miR-640/GSK3ß axis, hinting at a promising therapeutic target for the HCC treatment.

Chemical and metabolic profiling of Codonopsis Radix extract with an integrated strategy using ultra-high-performance liquid chromatography coupled with mass spectrometry.

Codonopsis radix was commonly used as food materials or herbal medicines in many countries. However, the comprehensive analysis of chemical constituents, and in vivo xenobiotics of Codonopsis radix remain unclear. In the present study, an integrated strategy with feature-based molecular networking using ultra-high-performance liquid chromatography coupled with mass spectrometry was established to systematically screen the chemical constituents and the in vivo xenobiotics of Codonopsis radix. A step-by-step manner based on a composition database, visual structure classification, discriminant ions, and metabolite software prediction was proposed to overcome the complexities due to the similar structure of chemical constituents and metabolites of Codonopsis radix. As a result, 103 compounds were tentatively characterized, 20 of which were identified by reference standards. Besides, a total of 50 xenobiotics were detected in vivo, including 26 prototypes and 24 metabolites, while the metabolic features of the pyrrolidine alkaloids were elucidated for the first time. The metabolism reactions of pyrrolidine alkaloids and sesquiterpene lactones included oxidation, methylation, hydration, hydrogenation, demethylation, glucuronidation, and sulfation. This study provided a generally applicable approach to the comprehensive investigation of the chemical and metabolic profile of traditional Chinese medicine and offered reasonable guidelines for further screening of quality control indicators and pharmacodynamics mechanism of Codonopsis radix.

Soy Protein Isolate-Chitosan Nanoparticle-Stabilized Pickering Emulsions: Stability and In Vitro Digestion for DHA.

The purpose of the study was to investigate the stability and oral delivery of DHA-encapsulated Pickering emulsions stabilized by soy protein isolate-chitosan (SPI-CS) nanoparticles (SPI-CS Pickering emulsions) under various conditions and in the simulated gastrointestinal (GIT) model. The stability of DHA was characterized by the retention rate under storage, ionic strength, and thermal conditions. The oral delivery efficiency was characterized by the retention and release rate of DHA in the GIT model and cell viability and uptake in the Caco-2 model. The results showed that the content of DHA was above 90% in various conditions. The retention rate of DHA in Pickering emulsions containing various nanoparticle concentrations (1.5 and 3.5%) decreased to 80%, while passing through the mouth to the stomach, and DHA was released 26% in 1.5% Pickering emulsions, which was faster than that of 3.5% in the small intestine. After digestion, DHA Pickering emulsions proved to be nontoxic and effectively absorbed by cells. These findings helped to develop a novel delivery system for DHA.

Advanced data post-processing method for rapid identification and classification of the major triterpenoids of Alismatis rhizoma by ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry.

INTRODUCTION: Alismatis rhizoma (AR), a distinguished diuretic traditional Chinese herbal medicine, is widely used for the treatment of diarrhea, edema, nephropathy, hyperlipidemia, and tumors in clinical settings. Most beneficial effects of AR are attributed to the major triterpenoids, whose contents are relatively high in AR. To date, only 25 triterpenoids in AR have been characterized by LC-MS because the low-mass diagnostic ions are hardly triggered in MS, impeding structural identification. Herein, we developed an advanced data post-processing method with abundant characteristic fragments (CFs) and neutral losses (NLs) for rapid identification and classification of the major triterpenoids in AR by UPLC-Q-TOF-MSE . OBJECTIVE: We aimed to establish a systematic method for rapid identification and classification of the major triterpenoids of AR. METHODS: UPLC-Q-TOF-MSE coupled with an advanced data post-processing method was established to characterize the major triterpenoids of AR. The abundant CFs and NLs of different types of triterpenoids were discovered and systematically summarized. The rapid identification and classification of the major triterpenoids of AR were realized by processing the data and comparing with information described in the literature. RESULTS: In this study, a total of 44 triterpenoids were identified from AR, including three potentially new compounds and 41 known ones, which were classified into six types. CONCLUSION: The newly established approach is suitable for the chemical profiling of the major triterpenoids in AR, which could provide useful information about chemical constituents and a basis for further exploration of its active ingredients in vivo.

Design and Optimization of Multi-Stage TMR Sensors for Power Equipment AC/DC Leakage Current Detection.

Tunnel magnetoresistance (TMR) can measure weak magnetic fields and has significant advantages for use in alternating current/direct current (AC/DC) leakage current sensors for power equipment; however, TMR current sensors are easily perturbed by external magnetic fields, and their measurement accuracy and measurement stability are limited in complex engineering application environments. To enhance the TMR sensor measurement performance, this paper proposes a new multi-stage TMR weak AC/DC sensor structure with high measurement sensitivity and anti-magnetic interference capability. The front-end magnetic measurement characteristics and interference immunity of the multi-stage TMR sensor are found to be closely related to the multi-stage ring size design via finite element simulation. The optimal size of the multipole magnetic ring is determined using an improved non-dominated ranking genetic algorithm (ACGWO-BP-NSGA-II) to derive the optimal sensor structure. Experimental results demonstrate that the newly designed multi-stage TMR current sensor has a measurement range of 60 mA, a fitting nonlinearity error of less than 1%, a measurement bandwidth of 0-80 kHz, a minimum AC measurement value of 85 µA and a minimum DC measurement value of 50 µA, as well as a strong external electromagnetic interference. The TMR sensor can effectively enhance measurement precision and stability in the presence of intense external electromagnetic interference.

Research on Field Source Characteristics of Leakage Current of Arrester Based on TMR Sensor.

The status of zinc oxide (ZnO) arresters is directly related to the safety of power grids. However, as the service life of ZnO arresters increases, their insulation performance may decrease due to factors such as operating voltage and humidity, which can be identified through the measurement of leakage current. Tunnel magnetoresistance (TMR) sensors with high sensitivity, good temperature stability, and small size are excellent for measuring leakage current. This paper constructs a simulation model of the arrester and investigates the deployment of the TMR current sensor and the size of the magnetic concentrating ring. The arrester's leakage current magnetic field distribution under different operating conditions is simulated. The simulation model can aid in optimizing the detection of leakage current in arresters using TMR current sensors, and the findings serve as a basis for monitoring the condition of arresters and improving the installation of current sensors. The TMR current sensor design offers potential advantages such as high accuracy, miniaturization, and ease of distributed application measurement, making it suitable for large-scale use. Finally, the validity of the simulations and conclusions is verified through experiments.

Stable Loading of TiO2 Catalysts on the Surface of Metal Substrate for Enhanced Photocatalytic Toluene Oxidation.

To promote the practical application of TiO2 in photocatalytic toluene oxidation, the honeycomb aluminum plates were selected as the metal substrate for the loading of TiO2 powder. Surface-etching treatment was performed and titanium tetrachloride was selected as the binder to strengthen the loading stability. The loading stability and photocatalytic activity of the monolithic catalyst were further investigated, and the optimal surface treatment scheme (acid etching with 15.0 wt.% HNO3 solution for 15 min impregnation) was proposed. Therein, the optimal monolithic catalyst could achieve the loading efficiency of 42.4% and toluene degradation efficiencies of 76.2%. The mechanism for the stable loading of TiO2 was revealed by experiment and DFT calculation. The high surface roughness of metal substrate and the strong chemisorption between TiO2 and TiCl4 accounted for the high loading efficiency and photocatalytic activity. This work provides the pioneering exploration for the practical application of TiO2 catalysts loaded on the surface of metal substrate for VOCs removal, which is of significance for the large-scaled application of photocatalytic technology.

A Semantic-Enhancement-Based Social Network User-Alignment Algorithm.

User alignment can associate multiple social network accounts of the same user. It has important research implications. However, the same user has various behaviors and friends across different social networks. This will affect the accuracy of user alignment. In this paper, we aim to improve the accuracy of user alignment by reducing the semantic gap between the same user in different social networks. Therefore, we propose a semantically enhanced social network user alignment algorithm (SENUA). The algorithm performs user alignment based on user attributes, user-generated contents (UGCs), and user check-ins. The interference of local semantic noise can be reduced by mining the user's semantic features for these three factors. In addition, we improve the algorithm's adaptability to noise by multi-view graph-data augmentation. Too much similarity of non-aligned users can have a large negative impact on the user-alignment effect. Therefore, we optimize the embedding vectors based on multi-headed graph attention networks and multi-view contrastive learning. This can enhance the similar semantic features of the aligned users. Experimental results show that SENUA has an average improvement of 6.27% over the baseline method at hit-precision30. This shows that semantic enhancement can effectively improve user alignment.

Targets preliminary screening for the fresh natural drug molecule based on Cosine-correlation and similarity-comparison of local network.

BACKGROUND: Chinese herbal medicine is made up of hundreds of natural drug molecules and has played a major role in traditional Chinese medicine (TCM) for several thousand years. Therefore, it is of great significance to study the target of natural drug molecules for exploring the mechanism of treating diseases with TCM. However, it is very difficult to determine the targets of a fresh natural drug molecule due to the complexity of the interaction between drug molecules and targets. Compared with traditional biological experiments, the computational method has the advantages of less time and low cost for targets screening, but it remains many great challenges, especially for the molecules without social ties. METHODS: This study proposed a novel method based on the Cosine-correlation and Similarity-comparison of Local Network (CSLN) to perform the preliminary screening of targets for the fresh natural drug molecules and assign weights to them through a trained parameter. RESULTS: The performance of CSLN is superior to the popular drug-target-interaction (DTI) prediction model GRGMF on the gold standard data in the condition that is drug molecules are the objects for training and testing. Moreover, CSLN showed excellent ability in checking the targets screening performance for a fresh-natural-drug-molecule (scenario simulation) on the TCMSP (13 positive samples in top20), meanwhile, Western-Blot also further verified the accuracy of CSLN. CONCLUSIONS: In summary, the results suggest that CSLN can be used as an alternative strategy for screening targets of fresh natural drug molecules.