21 research outputs found

    The Design and Optimization of a Compressive-Type Vector Sensor Utilizing a PMN-28PT Piezoelectric Single-Crystal

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    Underwater sensors that detect the distance and direction of acoustic sources are critical for surveillance monitoring and target detection in the water. Here, we propose an axial vector sensor that utilizes a small (~1 cm3) compressive-type piezoelectric accelerometer using piezoelectric single crystals. Initially, finite element analysis (FEA) was used to optimize the structure that comprised piezoelectric Pb(Mb1/3Nb2/3)O3-28%PbTiO3 single crystals on a tungsten seismic mass. The receiving voltage sensitivity (RVS) was enhanced through geometric optimization of the thickness and sensing area of the piezoelectric material and the seismic mass. The estimated maximum RVS of the optimized vector sensor was −212 dB. FEA simulations and practical measurements were used to verify the directivity of the vector sensor design, which exhibited a dipole pattern. The dipole beam pattern was used to obtain cardioid patterns using the simulated and measured results for comparison. The results clearly showed the feasibility of using the proposed piezoelectric single-crystal accelerometer for a compressive-type vector sensor. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.1

    An assessment of the methodological quality of published network meta-analyses: a systematic review

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    Objective To assess the methodological quality of published network meta-analysis. Design Systematic review. Methods We searched the medical literature for network meta-analyses of pharmaceuticals. We assessed general study characteristics, study transparency and reproducibility, methodological approach, and reporting of findings. We compared studies published in journals with lower impact factors with those published in journals with higher impact factors, studies published prior to January 1st, 2013 with those published after that date, and studies supported financially by industry with those supported by non-profit institutions or that received no support. Results The systematic literature search identified 854 citations. Three hundred and eighteen studies met our inclusion criteria. The number of network meta-analyses has grown rapidly, with 48% of studies published since January 2013. The majority of network meta-analyses were supported by a non-profit institution or received no support (68%). We found considerable inconsistencies among reviewed studies. Eighty percent reported search terms, 61% a network diagram, 65% sufficient data to replicate the analysis, and 90% the characteristics of included trials. Seventy percent performed a risk of bias assessment of included trials, 40% an assessment of model fit, and 56% a sensitivity analysis. Among studies with a closed loop, 69% examined the consistency of direct and indirect evidence. Sixty-four percent of studies presented the full matrix of head-to-head treatment comparisons. For Bayesian studies, 41% reported the probability that each treatment was best, 31% reported treatment ranking, and 16% included the model code or referenced publicly-available code. Network meta-analyses published in higher impact factors journals and those that did not receive industry support performed better across the assessment criteria. We found few differences between older and newer studies. Conclusions There is substantial variation in the network meta-analysis literature. Consensus among guidelines is needed improve the methodological quality, transparency, and consistency of study conduct and reporting

    Treatment Efficacy of Immune Checkpoint Inhibitors for Patients with Advanced or Metastatic Colorectal Cancer: A Systematic Review and Meta-Analysis

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    The treatment efficacy of immune checkpoint inhibitors (ICIs) in colorectal cancer (CRC) has been reported heterogeneously across clinical trials. We conducted a systematic review and meta-analysis to evaluate the efficacy of ICIs in patients with advanced/metastatic CRC. Ovid-Medline was searched to identify clinical trials providing the efficacy outcomes of overall response rate (ORR) or disease control rate (DCR). The pooled ORR and DCR were estimated across all studies and subgroups. Meta-regression was performed to find the influencing factors for treatment efficacy. A total of thirty studies (1870 patients) were eligible. The overall ORR and DCR were 20.1% and 58.5%, respectively, but these results were heterogeneous across studies. Multivariate meta-regression revealed that microsatellite phenotype (odds ratio of MSI-H/dMMR versus MSS/pMMR: 1.67, p < 0.001) and drug regimen (odds ratio of monotherapy versus combination therapy: 1.07, p = 0.019) were the source of heterogeneity and also significantly influenced factors for the efficacy of the treatment. Although the efficacy of ICIs as a first-line therapy was higher than that of ICIs as the second- or more-line therapy (ORR: 51.5% vs. 13.4%, DCR: 85% vs. 49.5%), multivariate regression showed that the line of therapy was not a significant factor for the treatment efficacy. Our study suggests that the microsatellite phenotype and drug regimen, rather than the line of treatment, are the primary factors influencing the treatment response among advanced/metastatic CRC patients treated with an ICI-based regimen

    The Design and Optimization of a Compressive-Type Vector Sensor Utilizing a PMN-28PT Piezoelectric Single-Crystal

    No full text
    Underwater sensors that detect the distance and direction of acoustic sources are critical for surveillance monitoring and target detection in the water. Here, we propose an axial vector sensor that utilizes a small (~1 cm3) compressive-type piezoelectric accelerometer using piezoelectric single crystals. Initially, finite element analysis (FEA) was used to optimize the structure that comprised piezoelectric Pb(Mb1/3Nb2/3)O3-28%PbTiO3 single crystals on a tungsten seismic mass. The receiving voltage sensitivity (RVS) was enhanced through geometric optimization of the thickness and sensing area of the piezoelectric material and the seismic mass. The estimated maximum RVS of the optimized vector sensor was −212 dB. FEA simulations and practical measurements were used to verify the directivity of the vector sensor design, which exhibited a dipole pattern. The dipole beam pattern was used to obtain cardioid patterns using the simulated and measured results for comparison. The results clearly showed the feasibility of using the proposed piezoelectric single-crystal accelerometer for a compressive-type vector sensor

    Method for clearance of contaminated buildings in Korea research reactor 1 and 2

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    The objective of this study was the establishment of clearance method that can ensure radiological safety and reasonably minimize radioactive waste when demolishing contaminated buildings at KRR-1&2. By reviewing Korean and international laws related to decommissioning, the method for clearance of contaminated buildings presented in this study is to first decontaminate the building and then conduct a radiological safety assessment, such as measuring residual radioactivity, to determine whether the radiation dose criteria for clearance are satisfied. The measurement results meet the radiation dose criteria, the contaminated buildings are regarded as clearance and can be converted into the general buildings. The demolition of the cleared buildings is carried out using conventional demolition methods. The waste generated during the demolition is classified as general construction waste and is disposed of according to relevant laws. The proposed method significantly optimized the number of samples analyzed and reduced the time and cost associated with the decommissioning. The established method will be applied to the ongoing decommissioning of contaminated buildings at KRR-1&2, and its application will be verified by regulatory bodies. The study suggests that this method could be used for the decommissioning of contaminated buildings at other Korean nuclear facilities in the future.© 2017 Elsevier Inc. All rights reserved

    CCR8 as a Therapeutic Novel Target: Omics-Integrated Comprehensive Analysis for Systematically Prioritizing Indications

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    Target identification is a crucial process in drug development, aiming to identify key proteins, genes, and signal pathways involved in disease progression and their relevance in potential therapeutic interventions. While C-C chemokine receptor 8 (CCR8) has been investigated as a candidate anti-cancer target, comprehensive multi-omics analyzes across various indications are limited. In this study, we conducted an extensive bioinformatics analysis integrating genomics, proteomics, and transcriptomics data to establish CCR8 as a promising anti-cancer drug target. Our approach encompassed data collection from diverse knowledge resources, gene function analysis, differential gene expression profiling, immune cell infiltration assessment, and strategic prioritization of target indications. Our findings revealed strong correlations between CCR8 and specific cancers, notably Breast Invasive Carcinoma (BRCA), Colon Adenocarcinoma (COAD), Head and Neck Squamous Cell Carcinoma (HNSC), Rectum adenocarcinoma (READ), Stomach adenocarcinoma (STAD), and Thyroid carcinoma (THCA). This research advances our understanding of CCR8 as a potential target for anti-cancer drug development, bridging the gap between molecular insights and creating opportunities for personalized treatment of solid tumors
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