Efficient Synthesis of Cyanohydrin Esters: P(NMe2)3 Mediated Direct Deoxygenation of Acyl Cyanides with Carboxylic Acids.

An efficient synthesis of cyanohydrin esters via a P(NMe2)3 mediated direct deoxygenation process has been exploited, circumventing the release or transformation of the CN─ anion during the reaction. This approach possesses a broad scope and acts as a powerful supplement for the construction of diverse cyanohydrin esters. It offers advantages such as mild conditions, straightforward operations, and excellent scalability, affirming the feasibility and versatility of this approach and highlighting its potential in practical synthesis.

Infrared Bilateral Polarity Ship Detection in Complex Maritime Scenarios.

In complex maritime scenarios where the grayscale polarity of ships is unknown, existing infrared ship detection methods may struggle to accurately detect ships among significant interference. To address this issue, this paper first proposes an infrared image smoothing method composed of Grayscale Morphological Reconstruction (GMR) and a Relative Total Variation (RTV). Additionally, a detection method considering the grayscale uniformity of ships and integrating shape and spatiotemporal features is established for detecting bright and dark ships in complex maritime scenarios. Initially, the input infrared images undergo opening (closing)-based GMR to preserve dark (bright) blobs with the opposite suppressed, followed by smoothing the image with the relative total variation model to reduce clutter and enhance the contrast of the ship. Subsequently, Maximally Stable Extremal Regions (MSER) are extracted from the smoothed image as candidate targets, and the results from the bright and dark channels are merged. Shape features are then utilized to eliminate clutter interference, yielding single-frame detection results. Finally, leveraging the stability of ships and the fluctuation of clutter, true targets are preserved through a multi-frame matching strategy. Experimental results demonstrate that the proposed method outperforms ITDBE, MRMF, and TFMSER in seven image sequences, achieving accurate and effective detection of both bright and dark polarity ship targets.

Combining blood pressure variability and heart rate variability to analyze the autonomic nervous function of rotenone induced Parkinson's rat model.

BACKGROUND: Parkinson's patients have significant autonomic dysfunction, early detect the disorder is a major challenge. To assess the autonomic function in the rat model of rotenone induced Parkinson's disease (PD), Blood pressure and ECG signal acquisition are very important. NEW METHOD: We used telemetry to record the electrocardiogram and blood pressure signals from awake rats, with linear and nonlinear analysis techniques calculate the heart rate variability (HRV) and blood pressure variability (BPV). we applied nonlinear analysis methods like sample entropy and detrended fluctuation analysis to analyze blood pressure signals. Particularly, this is the first attempt to apply nonlinear analysis to the blood pressure evaluate in rotenone induced PD model rat. RESULTS: HRV in the time and frequency domains indicated sympathetic-parasympathetic imbalance in PD model rats. Linear BPV analysis didn't reflect changes in vascular function and blood pressure regulation in PD model rats. Nonlinear analysis revealed differences in BPV, with lower sample entropy results and increased detrended fluctuation analysis results in the PD group rats. COMPARISON WITH EXISTING METHODS AND CONCLUSIONS: our experiments demonstrate the ability to evaluate autonomic dysfunction in models of Parkinson's disease by combining the analysis of BPV with HRV, consistent with autonomic impairment in PD patients. Nonlinear analysis by blood pressure signal may help in early detection of the PD. It indicates that the fluctuation of blood pressure in the rats in the rotenone model group tends to be regular and predictable, contributes to understand the PD pathophysiological mechanisms and to find strategies for early diagnosis.

Localization Performance Analysis and Algorithm Design of Reconfigurable Intelligent Surface-Assisted D2D Systems.

The research on high-precision and all-scenario localization using the millimeter-wave (mmWave) band is of great urgency. Due to the characteristics of mmWave, blockages make the localization task more complex. This paper proposes a cooperative localization system among user equipment (UEs) assisted by reconfigurable intelligent surfaces (RISs), which considers device-to-device (D2D) communication. RISs are used as anchor points, and position estimation is achieved through signal exchanges between UEs. Firstly, we establish a localization model based on this system and derive the UEs' positioning error bound (PEB) as a performance metric. Then, a UE-RIS joint beamforming design is proposed to optimize channel state information (CSI) with the objective of achieving the minimum PEB. Finally, simulation analysis demonstrates the advantages of the proposed scheme over RIS-assisted base station positioning, achieving centimeter-level accuracy with a 10 dBm lower transmission power.

Molecular-level carbon traits underlie the multidimensional fine root economics space.

Carbon influences the evolution and functioning of plants and their roots. Previous work examining a small number of commonly measured root traits has revealed a global multidimensionality of the resource economics traits in fine roots considering carbon as primary currency but without considering the diversity of carbon-related traits. To address this knowledge gap, we use data from 66 tree species from a tropical forest to illustrate that root economics space co-varies with a novel molecular-level traits space based on nuclear magnetic resonance. Thinner fine roots exhibit higher proportions of carbohydrates and lower diversity of molecular carbon than thicker roots. Mass-denser fine roots have more lignin and aromatic carbon compounds but less bioactive carbon compounds than lighter roots. Thus, the transition from thin to thick fine roots implies a shift in the root carbon economy from 'do-it-yourself' soil exploration to collaboration with mycorrhizal fungi, while the shift from light to dense fine roots emphasizes a shift from acquisitive to conservative root strategy. We reveal a previously undocumented role of molecular-level carbon traits that potentially undergird the multidimensional root economics space. This finding offers new molecular insight into the diversity of root form and function, which is fundamental to our understanding of plant evolution, species coexistence and adaptations to heterogeneous environments.

Spindle oscillations in communicating axons within a reconstituted hippocampal formation are strongest in CA3 without thalamus.

Spindle-shaped waves of oscillations emerge in EEG scalp recordings during human and rodent non-REM sleep. The association of these 10-16 Hz oscillations with events during prior wakefulness suggests a role in memory consolidation. Human and rodent depth electrodes in the brain record strong spindles throughout the cortex and hippocampus, with possible origins in the thalamus. However, the source and targets of the spindle oscillations from the hippocampus are unclear. Here, we employed an in vitro reconstruction of four subregions of the hippocampal formation with separate microfluidic tunnels for single axon communication between subregions assembled on top of a microelectrode array. We recorded spontaneous 400-1000 ms long spindle waves at 10-16 Hz in single axons passing between subregions as well as from individual neurons in those subregions. Spindles were nested within slow waves. The highest amplitudes and most frequent occurrence suggest origins in CA3 neurons that send feed-forward axons into CA1 and feedback axons into DG. Spindles had 50-70% slower conduction velocities than spikes and were not phase-locked to spikes suggesting that spindle mechanisms are independent of action potentials. Therefore, consolidation of declarative-cognitive memories in the hippocampus may be separate from the more easily accessible consolidation of memories related to thalamic motor function.

Prognostic factors associated with pulp status in patients with cracked teeth treated with occlusal veneer: A 6- through 24-month prospective clinical study.

BACKGROUND: The authors evaluated the prognostic factors associated with pulp status in patients with cracked teeth (CT) treated with occlusal veneer. METHODS: An analysis of 80 CT (71 patients) with 1 or more crack lines (CLs) and normal pulp vitality or reversible pulpitis was performed. All patients received occlusal veneer and their demographic and clinical data were recorded. Pulp status and clinical features were recorded at 1 week and posttreatment at 1, 2, 3, 6, 12, 18, and 24 months. RESULTS: Maxillary first molars were commonly involved (30 [38%]). The number of CLs on the finish line ranged from 1 through 7 and most had 3 CLs (24 [30%]). The number of CLs through preparation on the finish line ranged from 0 through 4, and 2 CLs (42 [53%]) were the most prevalent. During follow-up, 5 of 80 CT progressed to pulp disease, resulting in a success rate of 93.8%. Results of the Cox model and Kaplan-Meier analysis showed that probing depth greater than 6 mm, widening periodontal ligament of apical area, more than 4 CLs on finish line, and more than 2 CLs through preparation on the finish line were risk factors associated with pulp status (P < .05). CONCLUSIONS: Occlusal veneer can protect CT without preventive root canal therapy. PRACTICAL IMPLICATIONS: The success rate and risk factors of pulp disease in CT restored with occlusal veneer are reported.

Resistance risk assessment for benzovindiflupyr in Sclerotium rolfsii and transmission of resistance genes among population.

BACKGROUND: Sclerotium rolfsii is a destructive soil-borne fungal pathogen which is distributed worldwide. In previous study, the succinate dehydrogenase inhibitor (SDHI) fungicide benzovindiflupyr has been identified for its great antifungal activity against Sclerotium rolfsii. This study is aimed to investigate the resistance risk and mechanism of benzovindiflupyr in Sclerotium rolfsii. RESULTS: Eight stable benzovindiflupyr-resistant isolates were generated by fungicide adaptation. Although the obtained eight resistant isolates have a stronger pathogenicity than the parental sensitive isolate, they have a fitness penalty in the mycelial growth and sclerotia formation compared to the parental isolate. A positive cross-resistance existed in the resistant isolates between benzovindiflupyr and thifluzamide, carboxin, boscalid and isopyrazam. Three-point mutations, including SdhBN180D, SdhCQ68E and SdhDH103Y, were identified in the benzovindiflupyr-resistant isolates. However, molecular docking analysis indicated that only SdhDH103Y could influence the sensitivity of Sclerotium rolfsii to benzovindiflupyr. After mycelial co-incubation of resistant isolates and the sensitive isolate, resistance genes may be transmitted to the sensitive isolate. The in vivo efficacy of benzovindiflupyr and thifluzamide against benzovindiflupyr-resistant isolates was a little lower than that against the sensitive isolate but with no significant difference. CONCLUSION: The results suggested a low to medium resistance risk of Sclerotium rolfsii to benzovindiflupyr. However, once resistance occurs, it is possible to spread in the population of Sclerotium rolfsii. This study is helpful to understanding the risk and mechanism of resistance to benzovindiflupyr in multinucleate pathogens such as Sclerotium rolfsii. © 2024 Society of Chemical Industry.

Association between thyroid autoimmunity and bone mineral density in patients with type 2 diabetes mellitus: a cross-sectional study.

PURPOSE: The purpose of this study was to analyze the relationship between thyroid autoimmunity and bone mineral density (BMD) in patients with type 2 diabetes mellitus (T2DM), and to further explore the influence of thyroid autoimmunity on diabetic osteoporosis. METHODS: A total of 601 T2DM patients were included and divided into two groups according to thyroid autoantibodies, namely thyroid autoimmunity positive group (TPOAb+ or TGAb + ) and thyroid autoimmunity negative group (TPOAb- and TGAb-). Clinical data were collected and BMD was determined by dual-energy X-ray absorptiometry (DXA). SPSS26.0 software was used to data analysis. Model regression was used to analyze the influencing factors of BMD, and ROC curve was used to analyze the optimal cut-off point of thyroid peroxidase antibody (TPOAb) for screening osteoporosis. RESULTS: TPOAb and thyroglobulin antibody (TGAb) were negatively correlated with BMD and T-score (LS, FN and WB) (P < 0.01), and TGAb was negatively correlated with 25(OH)D (P < 0.05). Multiple linear regression analysis showed that TPOAb was an independent influence factor on LS, FN and WB BMD. ROC curve analysis showed that the optimal threshold of TPOAb for predicting osteoporosis was 12.35. CONCLUSIONS: In T2DM patients, TPOAb and TGAb levels are negatively correlated with LS, FN and WB BMD, and TPOAb is an independent influencing factor for diabetic osteoporosis, and TPOAb has a certain predictive value for the occurrence and development of diabetic osteoporosis clinically.

P(NMe2)3-Mediated Regioselective N-Alkylation of 2-Pyridones via Direct Deoxygenation of α-Keto Esters.

A practical and regioselective direct N-alkylation of 2-pyridones is enabled by use of α-keto esters in the P(NMe2)3-mediated deoxygenation process. The reaction proceeds under mild conditions to produce N-alkylated 2-pyridones with high selectivity and generality, and the protocol is shown to be applicable for the scale-up synthesis, which makes it promising for practical applications.

Drugs targeting structural and nonstructural proteins of the chikungunya virus: A review.

Chikungunya virus (CHIKV) is a single positive-stranded RNA virus of the Togaviridae family and Alphavirus genus, with a typical lipid bilayer envelope structure, and is the causative agent of human chikungunya fever (CHIKF). The U.S. Food and Drug Administration has recently approved the first chikungunya vaccine, Ixchiq; however, vaccination rates are low, and CHIKF is prevalent owing to its periodic outbreaks. Thus, developing effective anti-CHIKV drugs in clinical settings is imperative. Viral proteins encoded by the CHIKV genome play vital roles in all stages of infection, and developing therapeutic agents that target these CHIKV proteins is an effective strategy to improve CHIKF treatment efficacy and reduce mortality rates. Therefore, in the present review article, we aimed to investigate the basic structure, function, and replication cycle of CHIKV and comprehensively outline the current status and future advancements in anti-CHIKV drug development, specifically targeting nonstructural (ns) proteins, including nsP1, nsP2, nsP3, and nsP4 and structural proteins such as capsid (C), E3, E2, 6K, and E1.

Microbial changes and associated metabolic responses modify host plant adaptation in Stephanitis nashi.

Symbiotic microorganisms are essential for the physiological processes of herbivorous pests, including the pear lace bug Stephanitis nashi, which is known for causing extensive damage to garden plants and fruit trees due to its exceptional adaptability to diverse host plants. However, the specific functional effects of the microbiome on the adaptation of S. nashi to its host plants remains unclear. Here, we identified significant microbial changes in S. nashi on 2 different host plants, crabapple and cherry blossom, characterized by the differences in fungal diversity as well as bacterial and fungal community structures, with abundant correlations between bacteria or fungi. Consistent with the microbiome changes, S. nashi that fed on cherry blossom demonstrated decreased metabolites and downregulated key metabolic pathways, such as the arginine and mitogen-activated protein kinase signaling pathway, which were crucial for host plant adaptation. Furthermore, correlation analysis unveiled numerous correlations between differential microorganisms and differential metabolites, which were influenced by the interactions between bacteria or fungi. These differential bacteria, fungi, and associated metabolites may modify the key metabolic pathways in S. nashi, aiding its adaptation to different host plants. These results provide valuable insights into the alteration in microbiome and function of S. nashi adapted to different host plants, contributing to a better understanding of pest invasion and dispersal from a microbial perspective.

Association of serum trimethylamine N-oxide levels and bone mineral density in type 2 diabetes mellitus.

PURPOSE: The relationship between trimethylamine N-oxide (TMAO) and bone mineral density (BMD) in type 2 diabetes mellitus (T2DM) is unclear. We explore the relationship between TMAO levels and BMD in T2DM. METHODS: This is a cross-sectional study. 254 T2DM patients were enrolled and divided into three groups by TMAO tertiles, and the clinical data were collected. BMD was determined by dual-energy X-ray absorptiometry (DXA) and serum TMAO levels was determined by stable isotope dilution high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS). RESULTS: Patients in the highest tertile of TMAO levels (TMAO > 6.72 µmol/L) showed relatively low BMD and a higher number of fracture history, osteoporosis (OP) than those in the lower tertiles. Spearman correlation analysis showed that serum TMAO was negatively correlated with BMD of whole body (WB), lumbar spine (LS) and femoral neck (FN), while TMAO was positive correlated with osteoporotic fracture (p < 0.05). Logistic regression models showed that TMAO was an independent influencing factor of fracture history after adjusting for confounders in TMAO > 6.72 µmol/L group. CONCLUSIONS: There is a significant linear correlation between TMAO levels and BMD in T2DM patients. Especially in TMAO > 6.72 µmol/L group, TMAO was negatively correlated with WB, LS, and FN BMD, and was positive correlated with osteoporotic fracture in T2DM patients. The findings suggest that elevated TMAO levels are associated with OP and osteoporotic fracture in T2DM patients.

Fabrication of Au nanoclusters confined on hydroxy double salt-based intelligent biosensor for on-site monitoring of urease and its inhibitors.

Sensitive and convenient sensing of urease and its inhibitors is exceptionally urgent in clinical diagnosis and new drug development. In this study, the gold nanoclusters (AuNCs) and hydroxyl double salt (HDS) were composited by a simple confinement effect to prepare highly fluorescent AuNCs@HDS composites to monitor urease and its drug inhibitors. HDS was used as a matrix to confine AuNCs (AuNCs@HDS), facilitating the emission intensity of AuNCs. However, acidic conditions (low pH) can disrupt the structure of HDS to break the confinement effect, and quench the fluorescence of AuNCs. Therefore, a sensing platform for pH-related enzyme urease detection was constructed based on the sensitive response of AuNCs@HDS to pH. This sensing platform had a linear response range of 0.5-22.5 U/L and a low limit of detection (LOD) of 0.19 U/L for urease. Moreover, this sensing platform was also applied to monitor urease inhibitors and urease in human saliva samples. Additionally, a portable hydrogel kit combined with a smartphone was developed for urease detection to achieve portable, low-cost, instrument-free, and on-site monitoring of urease.

Correlation Between Insulin Resistance and Urinary Incontinence in Female Patients with Type 2 Diabetes Mellitus.

INTRODUCTION AND HYPOTHESIS: Patients with type 2 diabetes mellitus (T2DM) are at a high risk of developing urinary incontinence; however, its pathogenesis is unclear. The purpose of this study is to explore the relationship between insulin resistance and urinary incontinence and its severity in female patients with T2DM. METHODS: A total of 366 women with T2DM aged ≥18 years were enrolled in this study. Insulin resistance was evaluated by the homeostasis model insulin resistance (HOMA-IR) index and urinary incontinence was assessed by the International Consultation on Incontinence Questionnaire Short Form (ICIQ-SF). All subjects were divided into four groups according to HOMA-IR quartiles. Logistic regression analysis was performed to investigate the relationship between insulin resistance and urinary incontinence and its severity. RESULTS: Among the 366 patients, 186 (50.8%) had urinary incontinence. The prevalence of urinary incontinence increased significantly with HOMA-IR quartiles (p < 0.001). Adjusted logistic regression analysis showed that compared with HOMA-IR ≤ 1.76, 2.81 ≤ HOMA-IR ≤ 4.27 was associated with a significantly increased risk of moderate incontinence (OR = 2.197, 95% CI 1.031-4.683, p = 0.041), and HOMA-IR ≥ 4.28 was associated with a significantly increased risk of severe incontinence (OR = 5.699, 95% CI 1.685-19.276, p = 0.005). Binary logistic regression analysis showed that HOMA-IR was the independent risk factor for urinary incontinence (p < 0.001). CONCLUSIONS: Higher levels of insulin resistance are associated with urinary incontinence and its severity in female patients with type 2 diabetes mellitus.

Theoretical Study of the Reactive Mechanisms of Li-Doped Ni-Based Oxygen Carrier during Chemical Looping Combustion.

Ni-based oxygen carriers (OCs) are considered promising materials in the chemical looping combustion (CLC) process. However, the reactivity of Ni-based OCs still offers the potential for further enhancement. In this work, the Li doping method has been employed for the modification of Ni-based OCs. The reactivity and microreaction mechanisms of different concentrations of Li-doped Ni-based OCs with CO in CLC are clarified using density functional theory (DFT) simulation. The structures, energy, and density of states are obtained through computational investigation of the reaction path in elementary reactions. The results show that (1) the adsorption energies of CO molecules on NiO surfaces with 4, 8, and 12% Li doping concentrations are -0.53, -0.48, and -0.54 eV, respectively, demonstrating an enhanced reactivity compared to that of pure NiO (-0.41 eV); (2) the calculation of the transition state indicates that the most favorable pathway for CO oxidation takes place on the surface of NiO with an 8% Li doping concentration, exhibiting the lowest energy barrier of 0.51 eV; and (3) the oxygen vacancy formation energies on the surface of NiO are 3.05, 2.30, and 2.10 eV for 4, 8, and 12% doping concentrations, respectively. Additionally, the decrease in oxygen vacancy formation energies exhibits a gradual decline with an increasing Li doping concentration. By comprehensive analysis, 8% is considered to be the optimal doping concentration of NiO for chemical looping combustion.

Stable and Highly Efficient Photocatalysis with Two-Dimensional Organic-Inorganic Hybrid Perovskites.

Two-dimensional organic-inorganic hybrid perovskites (OIHPs) have excellent photoelectric properties, such as high charge mobility and a high optical absorption coefficient, which have attracted enormous attention in the field of optoelectronic devices and photochemistry. However, the stability of 2D OIHPs in solution is deficient. In particular, the lack of stability in polar solutions hinders their application in photochemistry. In this work, (iso-BA)2PbI4 was used as a model to explore the three possibilities of the stable existence of a 2D perovskite in aqueous solution. And two of these systems that stabilize the presence of (iso-BA)2PbI4 were further investigated through electrochemical testing. Moreover, (iso-BA)2PbI4 2D hybrid perovskites exhibited an outstanding degradation rate. The chiral perovskite (R/S-MBA)2PbI4 is able to degrade a 30 mg/L methyl orange solution completely within 5 min, making it one of the fastest catalysts for this particular organic reaction. Further, based on the electron spin resonance test, a degradation mechanism by the halide perovskite was proposed. Based on the great catalytic performance as well as good reusability and stability, (R/S-MBA)2PbI4 perovskites are expected to be a new generation of catalysts, making a great impact on the application of asymmetrically catalyzed photoreactions.

A Novel and Green Method for Preparing Highly Conductive PEDOT:PSS Films for Thermoelectric Energy Harvesting.

As a π-conjugated conductive polymer, poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) is recognized as a promising environmentally friendly thermoelectric material. However, its low conductivity has limited applications in the thermoelectric field. Although thermoelectric efficiency can be significantly enhanced through post-treatment doping, these processes often involve environmentally harmful organic solvents or reagents. In this study, a novel and environmentally benign method using purified water (including room temperature water and subsequent warm water) to treat PEDOT:PSS film has been developed, resulting in improved thermoelectric performance. The morphology data, chemical composition, molecular structure, and thermoelectric performance of the films before and after treatment were characterized and analyzed using a scanning electron microscope (SEM), Raman spectrum, XRD pattern, X-ray photoelectron spectroscopy (XPS), and a thin film thermoelectric measurement system. The results demonstrate that the water treatment effectively removes nonconductive PSS from PEDOT:PSS composites, significantly enhancing their conductivity. Treated films exhibit improved thermoelectric properties, particularly those treated only 15 times with room temperature water, achieving a high electrical conductivity of 62.91 S/cm, a Seebeck coefficient of 14.53 µV K-1, and an optimal power factor of 1.3282 µW·m-1·K-2. In addition, the subsequent warm water treatment can further enhance the thermoelectric properties of the film sample. The underlying mechanism of these improvements is also discussed.

Emerging Xene-Based Single-Atom Catalysts: Theory, Synthesis, and Catalytic Applications.

In recent years, the emergence of novel 2D monoelemental materials (Xenes), e.g., graphdiyne, borophene, phosphorene, antimonene, bismuthene, and stanene, has exhibited unprecedented potentials for their versatile applications as well as addressing new discoveries in fundamental science. Owing to their unique physicochemical, optical, and electronic properties, emerging Xenes have been regarded as promising candidates in the community of single-atom catalysts (SACs) as single-atom active sites or support matrixes for significant improvement in intrinsic activity and selectivity. In order to comprehensively understand the relationships between the structure and property of Xene-based SACs, this review represents a comprehensive summary from theoretical predictions to experimental investigations. Firstly, theoretical calculations regarding both the anchoring of Xene-based single-atom active sites on versatile support matrixes and doping/substituting heteroatoms at Xene-based support matrixes are briefly summarized. Secondly, controlled synthesis and precise characterization are presented for Xene-based SACs. Finally, current challenges and future opportunities for the development of Xene-based SACs are highlighted.

Multi feature fusion network for schizophrenia classification and abnormal brain network recognition.

Schizophrenia classification and abnormal brain network recognition have an important research significance. Researchers have proposed many classification methods based on machine learning and deep learning. However, fewer studies utilized the advantages of complementary information from multi feature to learn the best representation of schizophrenia. In this study, we proposed a multi-feature fusion network (MFFN) using functional network connectivity (FNC) and time courses (TC) to distinguish schizophrenia patients from healthy controls. DNN backbone was adopted to learn the feature map of functional network connectivity, C-RNNAM backbone was designed to learn the feature map of time courses, and Deep SHAP was applied to obtain the most discriminative brain networks. We proved the effectiveness of this proposed model using the combining two public datasets and evaluated this model quantitatively using the evaluation indexes. The results showed that the functional network connectivity generated by independent component analysis has advantage in schizophrenia classification by comparing static and dynamic functional connections. This method obtained the best classification accuracy (ACC=87.30%, SPE=89.28%, SEN=85.71%, F1 =88.23%, and AUC=0.9081), and it demonstrated the superiority of this proposed model by comparing state-of-the-art methods. Ablation experiment also demonstrated that multi feature fusion and attention module can improve classification accuracy. The most discriminative brain networks showed that default mode network and visual network of schizophrenia patients have aberrant connections in brain networks. In conclusion, this method can identify schizophrenia effectively and visualize the abnormal brain network, and it has important clinical application value.