Impact of meteorological variation on hospital visits of patients with tree pollen allergy

<p>Abstract</p> <p>Background</p> <p>Climate change could affect allergic diseases, especially due to pollen. However, there has been no epidemiologic study to demonstrate the relationship between meteorological factors, pollen, and allergic patients. We aimed to investigate the association between meteorological variations and hospital visits of patients with tree pollen allergy.</p> <p>Methods</p> <p>The study subjects were adult patients who received skin prick tests between April and July from 1999 to 2008. We reviewed the medical records for the test results of 4,715 patients. Patients with tree pollen allergy were defined as those sensitized to more than 1 of 12 tree pollen allergens. We used monthly means of airborne tree pollen counts and meteorological factors: maximum/average/minimum temperature, relative humidity, and precipitation. We analyzed the correlations between meteorological variations, tree pollen counts, and the patient numbers. Multivariable logistic regression analyses were used to investigate the associations between meteorological factors and hospital visits of patients.</p> <p>Results</p> <p>The minimum temperature in March was significantly and positively correlated with tree pollen counts in March/April and patient numbers from April through July. Pollen counts in March/April were also correlated with patient numbers from April through July. After adjusting for confounders, including air pollutants, there was a positive association between the minimum temperature in March and hospital visits of patients with tree pollen allergy from April to July(odds ratio, 1.14; 95% CI 1.03 to 1.25).</p> <p>Conclusions</p> <p>Higher temperatures could increase tree pollen counts, affecting the symptoms of patients with tree pollen allergy, thereby increasing the number of patients visiting hospitals.</p

Inhibition of IL-10 Production by Maternal Antibodies against Group B Streptococcus GAPDH Confers Immunity to Offspring by Favoring Neutrophil Recruitment

Group B Streptococcus (GBS) is the leading cause of neonatal pneumonia, septicemia, and meningitis. We have previously shown that in adult mice GBS glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is an extracellular virulence factor that induces production of the immunosuppressive cytokine interleukin-10 (IL-10) by the host early upon bacterial infection. Here, we investigate whether immunity to neonatal GBS infection could be achieved through maternal vaccination against bacterial GAPDH. Female BALB/c mice were immunized with rGAPDH and the progeny was infected with a lethal inoculum of GBS strains. Neonatal mice born from mothers immunized with rGAPDH were protected against infection with GBS strains, including the ST-17 highly virulent clone. A similar protective effect was observed in newborns passively immunized with anti-rGAPDH IgG antibodies, or F(ab')2 fragments, indicating that protection achieved with rGAPDH vaccination is independent of opsonophagocytic killing of bacteria. Protection against lethal GBS infection through rGAPDH maternal vaccination was due to neutralization of IL-10 production soon after infection. Consequently, IL-10 deficient (IL-10−/−) mice pups were as resistant to GBS infection as pups born from vaccinated mothers. We observed that protection was correlated with increased neutrophil trafficking to infected organs. Thus, anti-rGAPDH or anti-IL-10R treatment of mice pups before GBS infection resulted in increased neutrophil numbers and lower bacterial load in infected organs, as compared to newborn mice treated with the respective control antibodies. We showed that mothers immunized with rGAPDH produce neutralizing antibodies that are sufficient to decrease IL-10 production and induce neutrophil recruitment into infected tissues in newborn mice. These results uncover a novel mechanism for GBS virulence in a neonatal host that could be neutralized by vaccination or immunotherapy. As GBS GAPDH is a structurally conserved enzyme that is metabolically essential for bacterial growth in media containing glucose as the sole carbon source (i.e., the blood), this protein constitutes a powerful candidate for the development of a human vaccine against this pathogen

Visualization and Curve-Parameter Estimation Strategies for Efficient Exploration of Phenotype Microarray Kinetics

The Phenotype MicroArray (OmniLog® PM) system is able to simultaneously capture a large number of phenotypes by recording an organism's respiration over time on distinct substrates. This technique targets the object of natural selection itself, the phenotype, whereas previously addressed '-omics' techniques merely study components that finally contribute to it. The recording of respiration over time, however, adds a longitudinal dimension to the data. To optimally exploit this information, it must be extracted from the shapes of the recorded curves and displayed in analogy to conventional growth curves.The free software environment R was explored for both visualizing and fitting of PM respiration curves. Approaches using either a model fit (and commonly applied growth models) or a smoothing spline were evaluated. Their reliability in inferring curve parameters and confidence intervals was compared to the native OmniLog® PM analysis software. We consider the post-processing of the estimated parameters, the optimal classification of curve shapes and the detection of significant differences between them, as well as practically relevant questions such as detecting the impact of cultivation times and the minimum required number of experimental repeats.We provide a comprehensive framework for data visualization and parameter estimation according to user choices. A flexible graphical representation strategy for displaying the results is proposed, including 95% confidence intervals for the estimated parameters. The spline approach is less prone to irregular curve shapes than fitting any of the considered models or using the native PM software for calculating both point estimates and confidence intervals. These can serve as a starting point for the automated post-processing of PM data, providing much more information than the strict dichotomization into positive and negative reactions. Our results form the basis for a freely available R package for the analysis of PM data

A large-scale chloroplast phylogeny of the Lamiaceae sheds new light on its subfamilial classification

Lamiaceae, the sixth largest angiosperm family, contains more than 7000 species distributed all over the world. However, although considerable progress has been made in the last two decades, its phylogenetic backbone has never been well resolved. In the present study, a large-scale phylogenetic reconstruction of Lamiaceae using chloroplast sequences was carried out with the most comprehensive sampling of the family to date (288 species in 191 genera, representing approximately 78% of the genera of Lamiaceae). Twelve strongly supported primary clades were inferred, which form the phylogenetic backbone of Lamiaceae. Six of the primary clades correspond to the current recognized subfamilies Ajugoideae, Lamioideae, Nepetoideae, Prostantheroideae, Scutellarioideae, and Symphorematoideae, and one corresponds to a portion of Viticoideae. The other five clades comprise: 1) Acrymia and Cymaria; 2) Hymenopyramis, Petraeovitex, Peronema, and Garrettia; 3) Premna, Gmelina, and Cornutia; 4) Callicarpa; and 5) Tectona. Based on these results, three new subfamilies—Cymarioideae, Peronematoideae, and Premnoideae—are described, and the compositions of other subfamilies are updated based on new findings from the last decade. Furthermore, our analyses revealed five strongly supported, more inclusive clades that contain subfamilies, and we give them phylogenetically defined, unranked names: Cymalamiina, Scutelamiina, Perolamiina, Viticisymphorina, and Calliprostantherina