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BACKGROUND Contrast-enhanced ultrasound (CEUS) with second-generation contrast agents performed 1-month after HCC treatment is almost as sensitive as contrast-enhanced computed tomography (CECT) in depicting the residual tumor. However, the efficacy of CEUS performed early after the procedure is still debated. AIM We evaluated the diagnostic accuracy of CEUS for the assessment of tumour response shortly after locoregional therapy in patients with unresectable HCC. METHODS Ninety-four patients with 104 HCC lesions who were scheduled to receive PEI, RFA, TACE or combined treatment were enrolled in this study. With CECT at 1-month as the reference standard, the diagnostic accuracy of CEUS performed 48-hours after the procedure was evaluated. Patients were followed-up to look for tumor or disease progression. RESULTS Based on CECT findings, 43/104 lesions were diagnosed as having residual viability after 1 month. CEUS performed 48-hours after treatment detected residual tumor in 34/43 nodules with treatment failure at CECT with a sensitivity, specificity, PPV, NPV and accuracy of 79.1%, 96.7%, 94.4%, 86.8% and 89% respectively. There was a high degree of concordance between CEUS and CECT (kappa coefficient=0.78). An hyperemic halo was detectable in 35 lesions without a statistically significant difference between concordant and discordant cases. In patients with uninodular disease responders according to 48 hours CEUS had a significantly longer mean overall survival and time to progression compared to non-responders. CONCLUSION CEUS performed 48 hours after treatment can be considered a reliable modality for the evaluation of the real extent of necrosis and has prognostic value in the assessment of hepatocellular carcinoma. © 2020 S. Karger AG, Basel.BACKGROUND Very little is known about receptor tyrosine kinase (RTK) expression on peripheral blood mononuclear cells (PBMC) in humans including renal cell carcinoma (RCC) patients. OBJECTIVES The primary objective of this study was to evaluate expression levels of major RTKs on PBMC and tumor-infiltrating lymphocytes (TIL) isolated from RCC patients. The secondary aim was to compare levels of RTK expression in RCC patients before surgery and on the 180th day after surgery (lymphocyte lifetime) and to compare them with the expression in healthy donors. In addition, we compared RTK and PD-L1 expression in TIL. METHODS Tumor and blood samples were obtained from 20 patients with primary RCC immediately after surgical resection. Blood samples were collected from 20 healthy donors. Tumors were harvested into RPMI 1640 medium (Gibco) and processed within 4 h. TIL isolation was performed using a modified protocol [Baldan et al. Br J Cancer. 2015;1121510-18]. Expression of RTKs was evaluated with NovoExpress Softwareefine a biological role of RTKs on different lymphocyte subsets and correlations between clinical outcomes and expression levels. © 2020 S. Karger AG, Basel.In recent years, much interest have been grabbed by materials with multi-purpose characteristics. As the performance of electrochemical energy device such as supercapacitors and photocatalytic activities depend strongly on the properties of materials. This study delineates the various parameters like morphology, energy bandgap, charge transfer resistance, different defect states, diffusion coefficient, functional groups adsorbed on the surface of material etc. to assess the performance of supercapacitor electrode and photocatalyic degradation efficiency of synthesised multi-dimensional ZnS nanostructures. Ethylenediamine mediated multi-dimensional ZnS nanostructures were grown by the Solvothermal route. 1D (one-dimensional), 2D (two-dimensional) and 3D(three-dimensional) morphologies were obtained by varying the ratio of de-ionised water(DI) and Ethylenediamine (EN) taken as 13,12 and 11 respectively. The EN molecules effectively cap most of the surfaces of the ZnS nanoparticles formed, preventing agglomeratis and Electrochemical Impedance Spectra(EIS), higher diffusion coefficient is obtained for 1D nanostructure material, hence higher specific capacitance and higher energy density of 159.12 F/g and 22.75 KWh/kg are found in this case. Only 9 % loss of specific capacitance is achieved after 1000 cycles, showing a relatively high cycling stability in 3-D nanostructures. The excellent super capacitive property can be attributed to the porous structure and high specific surface area. Thus, the synthesised multi-dimensional ZnS nanostructures are proved to be potential candidate for both photocatalytic and supercapacitor electrode performance. © 2020 IOP Publishing Ltd.OBJECTIVE Analysis of functional and structural brain networks have suggested that major depressive disorder (MDD) is associated with a disruption in brain networks. This paper aims to investigate the abnormalities of brain networks in MDD. APPROACH To this aim, we constructed weighted directed functional networks based on Electroencephalography (EEG) signals of 26 MDD patients and 23 normal (N) subjects. MRT68921 cell line The nodes of networks were 19 EEG electrodes, and the edges were phase transfer entropy (PTE) between each pair of electrodes. PTE is a model-free, phase-based effective connectivity measure that is relatively robust to noise and linear mixing. Since the correct instantaneous phase of a signal is computed for narrow frequency bands, the networks were analyzed in eight frequency sub-bands including delta, theta, alpha1, alpha2, beta1, beta2, beta3, and beta4. To assess the alteration in the topology of brain networks in MDD patients, graph theory metrics consist of global efficiency (GE), local efficiency (LE), node betweenness centrality (BC), node degree, and node strength were analyzed by statistical test and classification. Furthermore, directed differential connectivity graph (dDCG) for MDD and N group was studied. MAIN RESULTS These analyses revealed a higher node degree and strength in dDCG of MDD than normal. It was also found that MDD brain networks have a more randomized structure than the N group. Moreover, our result indicated the out-degree of networks classified MDD and N subjects with an accuracy of 92%; thus, it can be considered as a powerful feature for depression detection. SIGNIFICANCE Our analysis may provide new insights into developing biomarkers for depression detection based on brain networks. This study has the approval of the Iran University of Medical Sciences' ethics committee with 1397127 trial registration number. © 2020 IOP Publishing Ltd.
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