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Background The effect of alcohol on the outcome and fibrinolysis phenotype in trauma patients remains unclear. Hence, we performed this study to determine whether alcohol is a risk factor for mortality and fibrinolysis shutdown in trauma patients. Materials and methods A total of 686 patients who presented to our trauma center and underwent rotational thromboelastometry were included in the study. The primary outcome was in-hospital mortality. Logistic regression analysis was performed to determine whether alcohol was an independent risk factor for in-hospital mortality and fibrinolysis shutdown. Results The rate of in-hospital mortality was 13.8% and blood alcohol was detected in 27.7% of the patients among our study population. The patients in the alcohol-positive group had higher mortality rate, higher clotting time, and lower maximum lysis, more fibrinolysis shutdown, and hyperfibrinolysis than those in the alcohol-negative group. In logistic regression analysis, blood alcohol was independently associated with in-hospital mortality (odds ratio [OR] 2.578; 95% confidence interval [CI], 1.550–4.288) and fibrinolysis shutdown (OR 1.883 [95% CI, 1.286–2.758]). Within the fibrinolysis shutdown group, blood alcohol was an independent predictor of mortality (OR 2.168 [95% CI, 1.030–4.562]). Conclusions Alcohol is an independent risk factor for mortality and fibrinolysis shutdown in trauma patients. Further, alcohol is an independent risk factor for mortality among patients who experienced fibrinolysis shutdown.

As the size of networks increases, it is becoming important to analyze large-scale network data. A network clustering algorithm is useful for analysis of network data. Conventional network clustering algorithms in a single machine environment rather than a parallel machine environment are actively being researched. However, these algorithms cannot analyze large-scale network data because of memory size issues. As a solution, we propose a network clustering algorithm for large-scale network data analysis using Apache Spark by changing the paradigm of the conventional clustering algorithm to improve its efficiency in the Apache Spark environment. We also apply optimization approaches such as Bloom filter and shuffle selection to reduce memory usage and execution time. By evaluating our proposed algorithm based on an average normalized cut, we confirmed that the algorithm can analyze diverse large-scale network datasets such as biological, co-authorship, internet topology and social networks. Experimental results show that the proposed algorithm can develop more accurate clusters than comparative algorithms with less memory usage. Furthermore, we confirm the proposed optimization approaches and the scalability of the proposed algorithm. In addition, we validate that clusters found from the proposed algorithm can represent biologically meaningful functions.

Ultraviolet B (UVB; 290~320nm) irradiation-induced lipid peroxidation induces inflammatory responses that lead to skin wrinkle formation and epidermal thickening. Peroxisome proliferator-activated receptor (PPAR) α/γ dual agonists have the potential to be used as anti-wrinkle agents because they inhibit inflammatory response and lipid peroxidation. In this study, we evaluated the function of 2-bromo-4-(5-chloro-benzo[d]thiazol-2-yl) phenol (MHY 966), a novel synthetic PPAR α/γ dual agonist, and investigated its anti-inflammatory and anti-lipid peroxidation effects. The action of MHY 966 as a PPAR α/γ dual agonist was also determined in vitro by reporter gene assay. Additionally, 8-week-old melanin-possessing hairless mice 2 (HRM2) were exposed to 150 mJ/cm(2) UVB every other day for 17 days and MHY 966 was simultaneously pre-treated every day for 17 days to investigate the molecular mechanisms involved. MHY 966 was found to stimulate the transcriptional activities of both PPAR α and γ. In HRM2 mice, we found that the skins of mice exposed to UVB showed significantly increased pro-inflammatory mediator levels (NF-κB, iNOS, and COX-2) and increased lipid peroxidation, whereas MHY 966 co-treatment down-regulated these effects of UVB by activating PPAR α and γ. Thus, the present study shows that MHY 966 exhibits beneficial effects on inflammatory responses and lipid peroxidation by simultaneously activating PPAR α and γ. The major finding of this study is that MHY 966 demonstrates potential as an agent against wrinkle formation associated with chronic UVB exposure.