Citations

SummaryPolymorphonuclear (PMN) leucocytes participate in acute inflammatory pathologies such as acute respiratory distress syndrome (ARDS) following traumatic injury and shock, which also activates the coagulation system systemically. Trauma can prime the PMN nicotinamide adenine dinucleotide phosphate (NADPH) oxidase complex for an enhanced respiratory burst, but the relative role of various priming agents in this process remains incompletely understood. We therefore set out to identify mediators of PMN priming during coagulation and trauma-shock and determine whether PMN reactive oxygen species (ROS) generated in this manner could influence organ injury and coagulation. Initial experiments demonstrated that PMN are primed for predominantly extracellular ROS production by products of coagulation, which was abrogated by CD88/C5a receptor(C5aR) inhibition. The importance of this was highlighted further by demonstrating that known PMN priming agents result in fractionally different amounts of extracellular versus intracellular ROS release depending on the agent used. Plasma from trauma patients in haemodynamic shock (n = 10) also primed PMN for extracellular ROS in a C5a-dependent manner, which correlated with both complement alternative pathway activation and thrombin generation. Furthermore, PMN primed by preincubation with products of blood coagulation directly caused loss of endothelial barrier function in vitro that was abrogated by C5aR blockade or NADPH oxidase inhibition. Finally, we show in a murine model of trauma-shock that p47phox knock-out (KO) mice with PMN incapable of generating ROS were protected from inflammatory end-organ injury and activated protein C-mediated coagulopathy. In summary, we demonstrate that trauma-shock and coagulation primes PMN for predominantly extracellular ROS production in a C5a-dependent manner that contributes to endothelial barrier loss and organ injury, and potentially enhances traumatic coagulopathy.

Abstract Background Treatment of non‐small‐cell lung cancer (NSCLC) has been rapidly advancing over the last decade. Academic centers are considered equipped with better expertise. NSCLC outcome trends in novel therapeutic era and impact of initial treatment at academic centers have not been reported. Methods The National Cancer Database (NCDB) was used to identify NSCLC incident cases from 2004 to 2013. Overall survival (OS) was plotted by year of diagnosis and type of initial treatment center, accounting for several factors available in NCDB. Results A total of 1 150 722 NSCLC patients were included and separated by initial treatment center type (academic: 31.5%; nonacademic: 68.5%). Median follow‐up and OS for all patients were 11.8 months (range: 0‐133.6 months) and 13.1 months (95% CI: 13.08‐13.17), respectively. Median OS improved significantly for those diagnosed in 2010‐2013 (14.8 months [95% CI: 14.7‐14.9]) as compared to 2004‐2009 (12.4 months [95% CI: 12.3‐12.5]) ( P < 0.001). Treatment at academic centers was associated with improved OS (multivariate HR for OS = 0.929 [95% CI: 0.92‐0.94], P < 0.0010). Four‐year OS for academic and nonacademic cohorts was 28.5%% and 22.1%, respectively ( P < 0.001), and the difference was more pronounced in stage I to III NSCLC. Conclusion In this largest analysis, thus far, NSCLC survival has improved over time, and type of initial treatment center significantly influences survival. Identifying and removing barriers to obtaining initial treatment of NSCLC at academic medical centers could improve OS.

AbstractMotivationThe use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP–SNP interactions.ResultsWe tested two candidate approaches: the ‘Five-Full’ and ‘AA9int’ method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP–SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP–SNP interactions in large-scale studies.Availability and implementationThe ‘AA9int’ and ‘parAA9int’ functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/.Supplementary informationSupplementary data are available at Bioinformatics online.