Sichuan University

About: Sichuan University is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Population & Catalysis. The organization has 107623 authors who have published 102844 publications receiving 1612131 citations. The organization is also known as: Sìchuān Dàxué.

The Coronavirus Disease 2019 (COVID-19) Pandemic.

Abstract: The present study provides an overview of the coronavirus disease 2019 (COVID-19) outbreak which has rapidly extended globally within a short period. COVID-19 is a highly infectious respiratory disease caused by a new coronavirus known as SARS-CoV-2 (severe acute respiratory syndrome-coronavirus-2). SARS-CoV-2 is different from usual coronaviruses responsible for mild sickness such as common cold among human beings. It is crucial to understand the impact and outcome of this pandemic. We therefore overview the changes in the curves of COVID-19 confirmed cases and fatality rate in China and outside of China from 31st of December 2019 to 25th of March 2020. We also aimed to assess the temporal developments and death rate of COVID-19 in China and worldwide. More than 414,179 confirmed cases of COVID-19 have been reported in 197 countries, including 81,848 cases in China and 332,331 outside of China. Furthermore, 18,440 infected patients died from COVID-19 infection; 3,287 cases were from China and 15,153 fatalities were reported worldwide. Among the worldwide infected cases, 113,802 patients have been recovered and discharged from different hospitals. Effective prevention and control measures should be taken to control the disease. The presented Chinese model (protocol) of disease prevention and control could be utilized in order to curb the pandemic situation.

IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems

Abstract: Inverted generational distance (IGD) has been widely considered as a reliable performance indicator to concurrently quantify the convergence and diversity of multiobjective and many-objective evolutionary algorithms. In this paper, an IGD indicator-based evolutionary algorithm for solving many-objective optimization problems (MaOPs) has been proposed. Specifically, the IGD indicator is employed in each generation to select the solutions with favorable convergence and diversity. In addition, a computationally efficient dominance comparison method is designed to assign the rank values of solutions along with three newly proposed proximity distance assignments. Based on these two designs, the solutions are selected from a global view by linear assignment mechanism to concern the convergence and diversity simultaneously. In order to facilitate the accuracy of the sampled reference points for the calculation of IGD indicator, we also propose an efficient decomposition-based nadir point estimation method for constructing the Utopian Pareto front (PF) which is regarded as the best approximate PF for real-world MaOPs at the early stage of the evolution. To evaluate the performance, a series of experiments is performed on the proposed algorithm against a group of selected state-of-the-art many-objective optimization algorithms over optimization problems with 8-, 15-, and 20-objective. Experimental results measured by the chosen performance metrics indicate that the proposed algorithm is very competitive in addressing MaOPs.

Siltuximab for multicentric Castleman's disease: A randomised, double-blind, placebo-controlled trial

Abstract: Summary Background Multicentric Castleman's disease is a rare lymphoproliferative disorder driven by dysregulated production of interleukin 6. No randomised trials have been done to establish the best treatment for the disease. We assessed the safety and efficacy of siltuximab—a chimeric monoclonal antibody against interleukin 6—in HIV-negative patients with multicentric Castleman's disease. Methods We did this randomised, double-blind, placebo-controlled study at 38 hospitals in 19 countries worldwide. We enrolled HIV-negative and human herpesvirus-8-seronegative patients with symptomatic multicentric Castleman's disease. Treatment allocation was randomised with a computer-generated list, with block size six, and stratification by baseline corticosteroid use. Patients and investigators were masked to treatment allocation. Patients were randomly assigned (2:1) to siltuximab (11 mg/kg intravenous infusion every 3 weeks) or placebo; all patients also received best supportive care. Patients continued treatment until treatment failure. The primary endpoint was durable tumour and symptomatic response for at least 18 weeks for the intention-to-treat population. Enrolment has been completed. The study is registered with ClinicalTrials.gov, number NCT01024036. Findings We screened 140 patients, 79 of whom were randomly assigned to siltuximab (n=53) or placebo (n=26). Durable tumour and symptomatic responses occurred in 18 (34%) of 53 patients in the siltuximab group and none of 26 in the placebo group (difference 34·0%, 95% CI 11·1–54·8, p=0·0012). The incidence of grade 3 or more adverse events (25 [47%] vs 14 [54%]) and serious adverse events (12 [23%] vs five [19%]) was similar in each group despite longer median treatment duration with siltuximab than with placebo (375 days [range 1–1031] vs 152 days [23–666]). The most common grade 3 or higher were fatigue (five vs one), night sweats (four vs one), and anaemia (one vs three). Three (6%) of 53 patients had serious adverse events judged reasonably related to siltuximab (lower respiratory tract infection, anaphylactic reaction, sepsis). Interpretation Siltuximab plus best supportive care was superior to best supportive care alone for patients with symptomatic multicentric Castleman's disease and well tolerated with prolonged exposure. Siltuximab is an important new treatment option for this disease. Funding Janssen Research & Development.

Deep Supervised Cross-Modal Retrieval

Abstract: Cross-modal retrieval aims to enable flexible retrieval across different modalities. The core of cross-modal retrieval is how to measure the content similarity between different types of data. In this paper, we present a novel cross-modal retrieval method, called Deep Supervised Cross-modal Retrieval (DSCMR). It aims to find a common representation space, in which the samples from different modalities can be compared directly. Specifically, DSCMR minimises the discrimination loss in both the label space and the common representation space to supervise the model learning discriminative features. Furthermore, it simultaneously minimises the modality invariance loss and uses a weight sharing strategy to eliminate the cross-modal discrepancy of multimedia data in the common representation space to learn modality-invariant features. Comprehensive experimental results on four widely-used benchmark datasets demonstrate that the proposed method is effective in cross-modal learning and significantly outperforms the state-of-the-art cross-modal retrieval methods.

The effect of corticosteroids on mortality of patients with influenza pneumonia: a systematic review and meta-analysis

Abstract: The effect of corticosteroids on clinical outcomes in patients with influenza pneumonia remains controversial. We aimed to further evaluate the influence of corticosteroids on mortality in adult patients with influenza pneumonia by comparing corticosteroid-treated and placebo-treated patients. The PubMed, Embase, Medline, Cochrane Central Register of Controlled Trials (CENTRAL), and Information Sciences Institute (ISI) Web of Science databases were searched for all controlled studies that compared the effects of corticosteroids and placebo in adult patients with influenza pneumonia. The primary outcome was mortality, and the secondary outcomes were mechanical ventilation (MV) days, length of stay in the intensive care unit (ICU LOS), and the rate of secondary infection. Ten trials involving 6548 patients were pooled in our final analysis. Significant heterogeneity was found in all outcome measures except for ICU LOS (I2 = 38%, P = 0.21). Compared with placebo, corticosteroids were associated with higher mortality (risk ratio [RR] 1.75, 95% confidence interval [CI] 1.30 ~ 2.36, Z = 3.71, P = 0.0002), longer ICU LOS (mean difference [MD] 2.14, 95% CI 1.17 ~ 3.10, Z = 4.35, P < 0.0001), and a higher rate of secondary infection (RR 1.98, 95% CI 1.04 ~ 3.78, Z = 2.08, P = 0.04) but not MV days (MD 0.81, 95% CI − 1.23 ~ 2.84, Z = 0.78, P = 0.44) in patients with influenza pneumonia. In patients with influenza pneumonia, corticosteroid use is associated with higher mortality. PROSPERO (ID: CRD42018112384 ).