A Prediction Rule to Identify Severe Cases among Adult Patients Hospitalized with Pandemic Influenza A (H1N1) 2009

The purpose of this study was to establish a prediction rule for severe illness in adult patients hospitalized with pandemic influenza A (H1N1) 2009. At the time of initial presentation, the baseline characteristics of those with severe illness (i.e., admission to intensive care unit, mechanical ventilation, or death) were compared to those of patients with non-severe illnesses. A total of 709 adults hospitalized with pandemic influenza A (H1N1) 2009 were included: 75 severe and 634 non-severe cases. The multivariate analysis demonstrated that altered mental status, hypoxia (PaO2/FiO2 ≤ 250), bilateral lung infiltration, and old age (≥ 65 yr) were independent risk factors for severe cases (all P < 0.001). The area under the ROC curve (0.834 [95% CI, 0.778-0.890]) of the number of risk factors were not significantly different with that of APACHE II score (0.840 [95% CI, 0.790-0.891]) (P = 0.496). The presence of ≥ 2 risk factors had a higher sensitivity, specificity, positive predictive value and negative predictive value than an APACHE II score of ≥ 13. As a prediction rule, the presence of ≥ 2 these risk factors is a powerful and easy-to-use predictor of the severity in adult patients hospitalized with pandemic influenza A (H1N1) 2009

Potential cellular and biochemical mechanisms of exercise and physical activity on the ageing process

Exercise in young adults has been consistently shown to improve various aspects of physiological and psychological health but we are now realising the potential benefits of exercise with advancing age. Specifically, exercise improves cardiovascular, musculoskeletal, and metabolic health through reductions in oxidative stress, chronic low-grade inflammation and modulating cellular processes within a variety of tissues. In this this chapter we will discuss the effects of acute and chronic exercise on these processes and conditions in an ageing population, and how physical activity affects our vasculature, skeletal muscle function, our immune system, and cardiometabolic risk in older adults

Glucosinolate Content in Brassica Genetic Resources and Their Distribution Pattern within and between Inner, Middle, and Outer Leaves

Glucosinolates (GSLs) are sulfur-containing secondary metabolites naturally occurring in Brassica species. The purpose of this study was to identify the GSLs, determine their content, and study their accumulation patterns within and between leaves of kimchi cabbage (Brassica rapa L.) cultivars. GSLs were analyzed using UPLC-MS/MS in negative electron-spray ionization (ESI&minus;) and multiple reaction monitoring (MRM) mode. The total GSL content determined in this study ranged from 621.15 to 42434.21 &mu;molkg&minus;1 DW. Aliphatic GSLs predominated, representing from 4.44% to 96.20% of the total GSL content among the entire samples. Glucobrassicanapin (GBN) contributed the greatest proportion while other GSLs such as glucoerucin (ERU) and glucotropaeolin (TRO) were found in relatively low concentrations. Principal component analysis (PCA) yielded three principal components (PCs) with eigenvalues &ge; 1, altogether representing 74.83% of the total variation across the entire dataset. Three kimchi cabbage (S/No. 20, 4, and 2), one leaf mustard (S/No. 26), and one turnip (S/No. 8) genetic resources were well distinguished from other samples. The GSL content varied significantly among the different positions (outer, middle, and inner) of the leaves and sections (top, middle, bottom, green/red, and white) within the leaves. In most of the samples, higher GSL content was observed in the proximal half and white sections and the middle layers of the leaves. GSLs are regarded as allelochemicals; hence, the data related to the patterns of GSLs within the leaf and between leaves at a different position could be useful to understand the defense mechanism of Brassica plants. The observed variability could be useful for breeders to develop Brassica cultivars with high GSL content or specific profiles of GSLs