Sichuan University

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

Ethnic Groups Differences in the Prevalence of Sarcopenia Using the AWGS Criteria.

Abstract: To estimate the prevalence of sarcopenia in different ethnic groups and the association with cultural life styles in west China. A cross-sectional study. The communities in Yunnan, Guizhou, Sichuan, and Xinjiang provinces. 4500 participants aged 50 years or older in west China were enrolled in this study. Sarcopenia was defined according to the diagnostic algorithm of the Asia Working Group for Sarcopenia (AWGS). We measured gait speed, handgrip strength and muscle mass by using bioelectrical impedance analysis (BIA) for all eligible participants. Life-style information were collected by reviewers. Relationships between sarcopenia and ethnic groups were analyzed using univariate and multivariate analyses. We found 869 (19.31%) adults aged 50 years old or older were sarcopenia. The mean age is 62.4±8.3 years. The main ethnic groups enrolled in this study is Han, Tibetan, Qiang, Yi and Hui. The crude prevalence of sarcopenia is 22.3% in Han, 18.2% in Tibetan, 11.8% in Qiang, 34.7% in Yi and 26.7% in Hui. Compared to Han, after adjusting sex and age, Qiang has a lower prevalence of sarcopenia (odds ratio [OR]: 0.44, 95% CI 0.35–0.55), Yi has a higher prevalence of sarcopenia (OR: 1.78, 95% CI 1.29–2.43). While adding adjusting other potential cofounders, sarcopenia is still less prevalent in Qiang (OR: 0.44, 95% CI 0.34–0.57). The crude prevalence of sarcopenia is 22.3% in Han, 18.2% in Tibetan, 11.8% in Qiang, 34.7% in Yi and 26.7% in Hui. Sarcopenia was less prevalent in Qiang compared with Han. Further studies to determine related factors of sarcopenia among different ethnic groups are recommended.

Serum miR-21 and miR-92a as biomarkers in the diagnosis and prognosis of colorectal cancer.

Abstract: Previous studies from our laboratory identified a number of miRNAs that were aberrantly expressed in colorectal cancer (CRC) tissue. However, their diagnostic and prognostic value in serum has not been fully evaluated. In the present study, we measured the levels of five miRNAs (miR-21, miR-31, miR-92a, miR-18a, and miR-106a) in serum samples from 200 CRC patients, 50 advanced adenoma patients, and 80 healthy controls by real-time quantitative polymerase chain reaction (RT-PCR). In our study, the levels of miR-21 and miR-92a in patients with CRC and advanced adenoma were significantly higher than those in healthy controls (all P < 0.05). MiR-21 yielded an area under the receiver-operating characteristics (ROC) curve (AUC) of 0.802 and miR-92a yielded an AUC of 0.786 in discriminating CRCs from the controls. Additionally, miR-21 and miR-92a yielded an AUC of 0.709 and 0.701, respectively, in discriminating advanced adenomas from the controls. Combined ROC analyses using both miRNAs, revealed an elevated AUC of 0.847 in discriminating CRCs, and an AUC of 0.722 in discriminating advanced adenomas from the controls. In the multivariate Cox proportional hazards analysis, high miR-92a expression in CRC was independently associated with poor survival (P = 0.03; hazard ratio 4.36; 95 % confidence interval = 1.64–11.57). No significant difference was observed in the levels of miR-18a, miR-31, and miR-106a among CRC, advanced adenoma, and control samples. In summary, our data indicate that miR-21 and miR-92a serum levels have potential value for early detection of CRC. Furthermore, miR-92a has prognostic value in CRC patients.

A Self-Management Mechanism for Noncooperative Behaviors in Large-Scale Group Consensus Reaching Processes

Abstract: In large-scale group decision making (GDM), noncooperative behavior in the consensus reaching process (CRP) is not unusual. For example, some individuals might form a small alliance with the aim to refuse attempts to modify their preferences or even to move them against consensus to foster the alliance's own interests. In this paper, we propose a novel framework based on a self-management mechanism for noncooperative behaviors in large-scale CRPs (LCRPs). In the proposed consensus reaching framework, experts are classified into different subgroups using a clustering method, and experts provide their evaluation information, i.e., the multicriteria mutual evaluation matrices (MCMEMs), regarding the subgroups based on subgroups’ performance (e.g., professional skills, cooperation, and fairness). The subgroups’ weights are dynamically generated from the MCMEMs, which are in turn employed to update the individual experts’ weights. This self-management mechanism in the LCRP allows penalizing the weights of the experts with noncooperative behaviors. Detailed simulation experiments and comparison analysis are presented to verify the validity of the proposed framework for managing noncooperative behaviors in the LCRP.