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        Th2 cells infiltrating high-grade serous ovarian cancer: a feature that may account for the poor prognosis

        Hao Su,Yueqi Jin,Changyu Tao,Hua Yang,Ence Yang,Wei-Guang Zhang,Fengzhi Feng 대한부인종양학회 2023 Journal of Gynecologic Oncology Vol.34 No.4

        Objective: We aimed to investigate the differences of transcriptome profile between 2 groups of high-grade serous ovarian cancer (HGSOC) patients with distinct outcomes and identify potential biomarkers for recurrence. Methods: RNA sequencing was performed in 2 groups of HGSOC patients with similar demographic characteristics but exhibiting distinct progression-free survival (PFS). Transcriptome data of poor response (PR; PFS ≤6 months) and good response (GR; PFS ≥12 months) group were compared. We employed xCell to evaluate the abundance of 63 cells in tumor microenvironment. The predictive value of recurrence-related tumor infiltration cells was validated in cohort data from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) dataset. The weighted correlation network analysis was performed to identify the genes related to cell infiltration. Results: PR patients exhibited a distinct tumor infiltration immune cells-related transcriptional profile compared to GR patients, such as lower signatures of leukocyte differentiation, activation and chemotaxis. The fraction of T-helper 2 (Th2) cells infiltration was significantly higher in PR group than in GR group. High infiltration of Th2 was significantly associated with unfavorable prognosis in the GEO cohort (area under the curve=0.84 at 6 months recurrence) and TCGA cohort (p=0.008). Genes enriched to extracellular matrix organization and integrin binding were relevant to Th2 infiltration. Conclusion: Patients with HGSOC having shorter PFS exhibited a distinct gene signature that related to tumor-infiltrating immune cells. The level of Th2 infiltration could facilitate patient recurrence risk stratification and may be a promising biomarker for prognosis prediction and immune-related treatment.

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        Meta-Analysis of the Diagnostic Efficacy of the Luminex xTAG Respiratory Viral Panel FAST v2 Assay for Respiratory Viral Infections

        Xu-Guang Guo,Li-Min Xie,Xin Yin,Tian-Ao Xie,Jian-Wen Su,Qin Huang,Jing-Hao Zhang,Yin-Fei Huang 연세대학교의과대학 2022 Yonsei medical journal Vol.63 No.1

        Purpose: Acute respiratory viral infections pose significant morbidity and mortality, making it essential to diagnose respiratory viral infections rapidly. In this study, the diagnostic efficacy of the Luminex xTAG Respiratory Virus Panel (RVP) FAST v2 test was evaluated on respiratory viral infections. Materials and Methods: Information was retrieved from electronic databases, including Embase, Web of Science, PubMed, and Cochrane Library, for systematic review. Studies that fulfilled predefined inclusion criteria were included. After the extraction of information, statistical software was utilized for quality evaluation, data analysis, and assessment of publication bias. Results: Eighty groups in fourfold tables from nine articles were included to perform statistical analyses. Therein, the mean specificity and mean sensitivity of Luminex xTAG RVP FAST v2 test for the detection of respiratory viral infections were 0.99 (0.98–0.99) and 0.88 (0.87–0.90), respectively. Additionally, the negative and positive likelihood ratios were 0.14 (0.11–0.19) and 87.42 (61.88–123.50), respectively. Moreover, the diagnostic odds ratio and area under the curve of summary receiver operating characteristic were 714.80 and 0.9886, respectively. Conclusion: The Luminex xTAG RVP FAST v2 test could be a reliable and rapid diagnostic method for multiple respiratory viral infections.

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        Multi-stage Nonlinear Model Predictive Control with Online Scenario Update for Semi-batch Polymerization Processes

        Jing-Gao Sun,Xian-Feng Chen,Guang-Hao Su,Meng Wang,Hong-Guang Pan 제어·로봇·시스템학회 2022 International Journal of Control, Automation, and Vol.20 No.10

        In this paper, the problem of multi-stage nonlinear model predictive control with scenario update is investigated for semi-batch polymerization processes. The objective is to propose novel online scenario update schemes such that the more reasonable scenario tree can be generated. Firstly, based on the Orthogonal Configuration of Finite Elements (OCFE) method of direct radau configuration, the dynamic optimization problems are converted to Nonlinear Programing (NLP) problems such that the speed and accuracy of real-time optimization problem solving are effectively improved. Then, the scenario deviation is calculated based on model prediction information of each scenario and process measurement information. After that, calculate the bayesian probability weight of corresponding scenario is obtained. The online scenario reduction scheme uses the weight information update scenarios gradually reduce the scope of scenario tree representation. The online scenario weight update scheme uses the weight information as the basis for weight assignment of each scenario in the optimization problem. They use different methods to make the scenario tree modeling approach the real realization of uncertainty, and reduce the conservativeness compared with the traditional MSNMPC fixed scenario tree method. Through multiple batches numerical simulations of a semi-batch polymerization process, the advantages and effectiveness of the two proposed schemes are verified.

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