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Porcine pasteurellosis is an infectious disease caused by Pasteurella multocida (P. multocida), which seriously endangers the healthy development of pig breeding industry. Early detection of disease transmission in animals is a crucial early warning for humans. Therefore, predicting risk areas for disease is essential for public health authorities to adopt preventive measures and control strategies against diseases. In this study, we developed a predictive model based on multi-criteria decision analysis (MCDA) and assessed risk areas for porcine pasteurellosis in the Chinese mainland. By using principal component analysis, the weights of seven spatial risk factors were determined. Fuzzy membership function was used to standardize all risk factors, and weight linear combination was used to create a risk map. The sensitivity of the risk map was analyzed by calculating the mean of absolute change rates of risk factors, as well as calculating an uncertainty map. The results showed that risk areas for porcine pasteurellosis were predicted to be locate in the south-central of the Chinese mainland, including Sichuan, Chongqing, Guangdong, and Guangxi. The maximum standard deviation of the uncertain map was less than 0.01and the ROC results showed that the prediction model has moderate predictive performance with the area under the curve (AUC) value of 0.80 (95% CI 0.75-0.84). Based on the above process, MCDA was combined with WebGIS technology to construct a system for predicting risk areas of porcine pasteurellosis. Risk factor data was directly linked to the developed model, providing decision support for disease prevention and control through monthly updates.

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Metal-organic frameworks (MOFs), recognized as advanced catalyst carriers due to their adjustable porous, diverse structure and highly exposed active sites, have earned increasing attention for their potential to address the longevity of catalytic centers. In this manuscript, we have devised and synthesized a multifunctional amino-pyridine benzoic acid (APBA) ligand to replace the modulator ligand of the MOF-808 and disperse the palladium catalytic centers atomically on the MOF-APBA. The resulting single-site catalytic system, Pd@MOF-APBA, demonstrates preeminent efficiency and stability, as evidenced by a high average turnover number (95000) and a low metal residue (4.8 ppm) in the Heck reaction. This catalyst has exhibited recyclability for multiple runs without significant loss of reactivity for gram-scale reactions. The catalyst's high activity and efficiency can be attributed to the suitable electrical properties and structures of the N, N'-bidentate ligand for the catalytic palladium ions, postponing their deactivations, including leaching and agglomeration.

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Cu(II) supramolecular assemblies [Cu2(tipe)2(H2O)2](NO3)4·2.5H2O (CuN4) and [Cu2Cl4(tipe)(CH3CN)]·H2O (CuN2Cl2) (tipe = 1,1,2,2-tetrakis(4-(imidazole-1-yl)phenyl)ethene) were synthesized and utilized for photocatalytic CO2 reduction. CuN4 exhibits CO production of up to 891 µmol gcat-1 with a selectivity of 79.9%, while CuN2Cl2 gives low CO production of 206 µmol gcat-1 but with a high selectivity of >99.9% in 5 h. The experimental and DFT calculation results indicate that the coordination environment and non-covalent interactions within the assemblies have a great impact on the photocatalytic CO2 reduction behavior. This work provides useful insights on Cu(II) assembly catalyzed CO2 photoreduction.

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Diagnostic methods for Helicobacter pylori infection include, but are not limited to, urea breath test, serum antibody test, fecal antigen test, and rapid urease test. However, these methods suffer drawbacks such as low accuracy, high false-positive rate, complex operations, invasiveness, etc. Therefore, there is a need to develop simple, rapid, and noninvasive detection methods for H. pylori diagnosis. In this study, we propose a novel technique for accurately detecting H. pylori infection through machine learning analysis of surface-enhanced Raman scattering (SERS) spectra of gastric fluid samples that were noninvasively collected from human stomachs via the string test. One hundred participants were recruited to collect gastric fluid samples noninvasively. Therefore, 12,000 SERS spectra (n = 120 spectra/participant) were generated for building machine learning models evaluated by standard metrics in model performance assessment. According to the results, the Light Gradient Boosting Machine algorithm exhibited the best prediction capacity and time efficiency (accuracy = 99.54% and time = 2.61 seconds). Moreover, the Light Gradient Boosting Machine model was blindly tested on 2,000 SERS spectra collected from 100 participants with unknown H. pylori infection status, achieving a prediction accuracy of 82.15% compared with qPCR results. This novel technique is simple and rapid in diagnosing H. pylori infection, potentially complementing current H. pylori diagnostic methods.

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INTRODUCTION AND IMPORTANCE: Primary Clear Cell subtype of Hepatocellular Carcinoma (PCHCC) is a rare kind of Hepatocellular Carcinoma (HCC). The coexistence of PCHCC, Intrahepatic Cholangiocarcinoma (ICC), and ordinary-type HCC(OHCC) in different parts of the liver is seldom reported in the literature. CASE PRESENTATION: A 66 years old man with three masses in his liver was admitted. Positron emission tomography-computed tomography suggested that 2 of the lesions were low-density and likely malignant, while the 3rd lesion was considered benign. Magnetic Resonance Imaging indicated all were malignant tumors. Minor hepatectomies were underwent respectively, and the pathology indicated the 3 tumors were PCHCC, ICC, and OHCC. Twelve months post operation, the patient was readmitted because of the recurrence of a 10.2 × 9.2 × 8.9 cm hepatic tumor. Transarterial chemoembolization and three courses of systemic chemotherapy were carried out, but the effectiveness was limited. The patient passed away 20 months after surgery. CLINICAL DISCUSSION: Surgical resection is the primary treatment of CHCC and minor hepatectomy should be considered especially when complicated with cirrhosis. Considering the poor prognosis and the high recurrence rate, sequential treatments like hepatectomy, targeted therapy, and TACE are recommended. CONCLUSION: PCHCC, ICC, and OHCC coexisted in a different part of one liver is particularly rare, comprehensive treatment with minor hepatectomy should be recommended, but the prognosis is poor.

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OBJECTIVE: To explore the correlation between hepatocellular carcinoma (HCC) gene variation profile and clinical characteristics in Han nationality with HBV infection in Sichuan province. METHODS: The clinical data and HCC tissues were obtained from the enrolled patients. Whole exome sequencing and bioinformatics analysis were performed on formalin-fixed and paraffin-embedded samples from HCC. Tumor mutational burden (TMB) was measured by an algorithm developed in-house. RESULTS: Sixteen high-frequency mutated genes with differential expressions were identified by WES. SMG1 gene variation could be positively correlated with satellite lesions. AMY2B and RGPD4 gene mutation seemed to have a greater chance of vascular invasion. The patients with TATDN1 variation have bigger diameters and greater chances of vascular and microvascular invasion (all P < 0.05). Univariate analysis indicated patients with gene TATDN1 variation had worse prognoses both in disease free survival (DFS) and overall survival (OS). In addition, the enrichment analysis showed many pathways, including the cell cycle pathway, viral oncogene pathway, MAPK pathway, PI3K-AKT pathway, etc., may be associated with HCC. CONCLUSION: This study explores the gene variation profile of HCC patients with HBV infection in Han nationality of Sichuan Province for the first time, which confirmed the existence of some high-frequency mutated genes and the possibility that the gene variations are involved in the tumorigenesis of HCC through multiple signal pathways. Also, patients with TATDN1 wild type showed a trend of better prognosis both in DFS and OS.

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