Environmental perturbations influence telomere dynamics in long-lived birds in their natural habitat

Telomeres are regarded as markers of biological or cellular ageing because they shorten with the degree of stress exposure. Accordingly, telomere lengths should show different rates of change when animals are faced with different intensities of environmental challenges. However, a relationship between telomere length and the environment has not yet been tested within a natural setting. Here, we report longitudinal telomere dynamics in free-living, black-tailed gulls (Larus crassirostris) through the recapture of birds of a known age over 2–5 consecutive years. The rate of change in telomere lengths differed with respect to year but not sex or age. The years when gulls showed stable telomere lengths or increases in telomere lengths (from 2009 to 2010) and decreases in telomere lengths (from 2010 to 2011) were characterized by El Niño and the Great Japan Earthquake, respectively. Both events are suspected to have had long-lasting effects on food availability and/or weather conditions. Thus, our findings that telomere dynamics in long-lived birds are influenced by dramatic changes in environmental conditions highlight the importance of environmental fluctuations in affecting stress and lifespan.     

汶川地震转运与震区住院患者回顾性对比分析

目的:探讨汶川地震转运与震区住院伤病员的特点和疾病谱.方法:采用“军卫一号“医院信息系统,收集整理三所军队医院收治汶川地震伤病员的诊疗信息.对比转运与震区住院伤病员的入院时间、基本情况和诊疗信息的差异.结果:震后第2日震区住院伤病员入院人数最多,为394人;前4日占震后10日内入院人数的80.6％.全部住院伤病员男性730人,占56.5％,女性562人,占43.5％;汉族占95％,羌族、藏族及其他民族占5％;已婚占76.4％;手术率为36.5％;住院天数的中位数为12天;治愈好转率为96.5％,病死率为1％.转运与震区住院伤病员的性别、年龄组、民族、手术与否和治疗结果构成差异具有统计学意义(P＜0.05);震区住院伤病员组的住院天数中位数低于转运住院伤病员组(P＜0.00l).按照出院第一诊断,损伤或中毒住院伤病员占81.5％;其他疾病前五位为消化系统疾病、呼吸系统疾病、肌肉骨骼和结缔组织疾病、循环系统疾病、症状和体征.结论:地震等灾害后应尽早(灾后3-5天)转运伤病员.震区一线医院和接收转运伤病员医院应科学、合理设置床位、安排陪护人员、招募志愿者.地震第一阶段医疗救援完成后,救援重点应转向内科和慢性疾病,并提前做好应医疗准备.     

Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines

Background

Recent advances in genome technologies and the subsequent collection of genomic information at various molecular resolutions hold promise to accelerate the discovery of new therapeutic targets. A critical step in achieving these goals is to develop efficient clinical prediction models that integrate these diverse sources of high-throughput data. This step is challenging due to the presence of high-dimensionality and complex interactions in the data. For predicting relevant clinical outcomes, we propose a flexible statistical machine learning approach that acknowledges and models the interaction between platform-specific measurements through nonlinear kernel machines and borrows information within and between platforms through a hierarchical Bayesian framework. Our model has parameters with direct interpretations in terms of the effects of platforms and data interactions within and across platforms. The parameter estimation algorithm in our model uses a computationally efficient variational Bayes approach that scales well to large high-throughput datasets.

Results

We apply our methods of integrating gene/mRNA expression and microRNA profiles for predicting patient survival times to The Cancer Genome Atlas (TCGA) based glioblastoma multiforme (GBM) dataset. In terms of prediction accuracy, we show that our non-linear and interaction-based integrative methods perform better than linear alternatives and non-integrative methods that do not account for interactions between the platforms. We also find several prognostic mRNAs and microRNAs that are related to tumor invasion and are known to drive tumor metastasis and severe inflammatory response in GBM. In addition, our analysis reveals several interesting mRNA and microRNA interactions that have known implications in the etiology of GBM.

Conclusions

Our approach gains its flexibility and power by modeling the non-linear interaction structures between and within the platforms. Our framework is a useful tool for biomedical researchers, since clinical prediction using multi-platform genomic information is an important step towards personalized treatment of many cancers. We have a freely available software at: http://odin.mdacc.tmc.edu/~vbaladan.

     

Trends and inequities in colorectal cancer screening participation in Ontario,Canada, 2005–2011

Background: Participation in screening tests for colorectal cancer (CRC) is generally low in Ontario, Canada. In addition, inequities in participation exist including lower participation among low-income individuals, males and individuals living in rural areas. In April 2008, Colon Cancer Check (CCC) program, the province-wide CRC screening program, was launched in Ontario. This study describes the trends and inequities in CRC screening participation three years before and three years after the CCC, and assesses the effect of the program on CRC screening participation, overall and among certain population groups. Methods: We used administrative data to identify cohorts of individuals eligible for CRC screening in fiscal years 2005–2011. We calculated the age-standardized percent of Fecal Occult Blood Test (FOBT) participation, large bowel endoscopy participation, and being ‘up-to-date’ with CRC screening tests. Results: From 2005 to 2011, FOBT participation increased from 7.6% to 14.8%, large bowel endoscopy participation from 3.4% to 5.7%, and ‘up-to-date’ with CRC screening from 27.2% to 41.3%. Before the launch of the CCC program, the quarterly increase in FOBT participation was 0.07% (p = 0.19), increased immediately after the launch (1.8%, p < 0.01), followed by a decline (?0.08%, p = 0.08), returning to its pre-program increase rate. We noted a significant decrease in FOBT participation every summer (?0.44%, p < 0.01). The CCC program had minimal effect on large bowel endoscopy participation. Before the launch of the CCC program, the quarterly increase in ‘up-to-date’ with CRC screening was 0.9% (p < 0.01), increased immediately after the launch (2.5%, p = 0.05), followed by a modest decline thereafter (?0.59%, p < 0.02). From 2005 to 2011, recent residents living in low-income neighborhoods were consistently and significantly less likely to have a FOBT and be ‘up-to-date’ with CRC screening than long-term residents living in high-income neighborhoods (2.9–4.5%; 14.7–17.3% respectively). Pre-CCC inequities in CRC participation persisted after the launch of the program. Conclusion: CRC testing was increasing in Ontario from 2005. An immediate increase in CRC testing, FOBT in particular, occurred after the launch of the CCC program, followed by a return to its pre-CCC increase rate thereafter. Future efforts are needed to improve screening participation and address inequities.     

Metabolite profiling of Neptunia oleracea and correlation with antioxidant and α-glucosidase inhibitory activities using 1H NMR-based metabolomics

Neptunia oleracea is a plant consumed as vegetable and used as a traditional herb to treat several ailments. This study evaluated metabolite variations among N. oleracea leaf and stem subjected to air drying (AD), freeze drying (FD) and oven drying (OD) using proton nuclear magnetic resonance (¹H NMR) based metabolomics. The correlation was also studied for the metabolite content with total phenolic content (TPC), DPPH free radical scavenging and α-glucosidase inhibitory activities. A total of 18 metabolites were identified from N. oleracea extracts, including 10 primary metabolites, 5 flavonoids and 3 phenolic acids using NMR. Ultra-high performance liquid chromatography tandem mass spectrometry analysis (UHPLC-MS/MS) confirmed the presence of the secondary metabolites and revealed the flavonoid derivatives present. All the identified phenolics are first reported from this plant. Multivariate data analysis (MVDA) showed strong correlation between the metabolites with the antioxidant and α-glucosidase inhibitory activities of FD N. oleracea leaves. The compounds suggested to be responsible for the high activity of FD leaves include vitexin-2-O-rhamnoside, catechin, caffeic acid, gallic acid and derivatives of quercetin, kaempferol and myricetin. This study demonstrates that FD N. oleracea leaves are a potential natural source for antioxidant and α-glucosidase inhibitors.     

Data gaps in anthropogenically driven local‐scale species richness change studies across the Earth's terrestrial biomes

There have been numerous attempts to synthesize the results of local‐scale biodiversity change studies, yet several geographic data gaps exist. These data gaps have hindered ecologist's ability to make strong conclusions about how local‐scale species richness is changing around the globe. Research on four of the major drivers of global change is unevenly distributed across the Earth's biomes. Here, we use a dataset of 638 anthropogenically driven species richness change studies to identify where data gaps exist across the Earth's terrestrial biomes based on land area, future change in drivers, and the impact of drivers on biodiversity, and make recommendations for where future studies should focus their efforts. Across all drivers of change, the temperate broadleaf and mixed forests and the tropical moist broadleaf forests are the best studied. The biome–driver combinations we have identified as most critical in terms of where local‐scale species richness change studies are lacking include the following: land‐use change studies in tropical and temperate coniferous forests, species invasion and nutrient addition studies in the boreal forest, and warming studies in the boreal forest and tropics. Gaining more information on the local‐scale effects of the specific human drivers of change in these biomes will allow for better predictions of how human activity impacts species richness around the globe.