Evidencia experimental de la abundancia de bacterias del suelo como el principal iniciador del efecto de preparación de la rizosfera

Se piensa que las comunidades microbianas del suelo son responsables del efecto de preparación de la rizósfera (RPE). Sin embargo, desde que las comunidades microbiales están compuestas de diversos componentes, se conoce muy poco acerca de cuál es el componente que tiene el rol principal en dicho efecto. En este estudio, se hicieron crecer soja y algodón en dos lugares a diferentes latitudes con diferentes condiciones de luz y temperatura in situ. Se cuantificó RPE usando un método natural de δC13 y se midió la abundancia, riqueza y composición de las comunidades de hongos y bacterias con métodos moleculares basados en el ADN. Entre todas las variables potenciales, incluyendo los tres índices de comunidades de hongos y bacterias anteriormente mencionados, e índices vegetales y físico-químicos del suelo, se mostró que la abundancia de bacterias explicó una gran proporción de la variación en RPE. Nuestro estudio identificó el mecanismo biológico que subyace este importante proceso ecológico.Soil microbial communities are thougth to be responsible for the rhizosphere priming effect (RPE). However, because soil microbial communities are comprised of diverse components, very little is known about which component plays the critical role. Here, soybean and cottonwood were grown at two latitudinal locations with different temperature and light conditions in-situ. We quantified RPE using a natural 13C method, and measured the abundance, richness and composition of bacteria and fungi communities with DNA-based molecular methods. Among all potential variables, including the three aforementioned indexes of bacteria and fungi communities and soil physiochemical and plant indexes, bacterial abundance was found to explain a large proportion of variation in RPE. Our study identified the biological mechanism underlying this important ecological process.Fil: Ma, Y.P.. Chinese Academy of Sciences. Institute of Applied Ecology; China. Chinese Academy of Agricultural Sciences. Institute of Environment and Sustainable Development in Agriculture. Key Laboratory of Dryland Agriculture;; China. University of Chinese Academy of Science; ChinaFil: Zhang, Z.J.. Chinese Academy of Sciences. Institute of Applied Ecology; China. Chinese Academy of Agricultural Sciences. Institute of Environment and Sustainable Development in Agriculture. Key Laboratory of Dryland Agriculture;; ChinaFil: Su, T.Q.. Chinese Academy of Sciences. Institute of Applied Ecology; ChinaFil: Busso, Carlos Alberto. Universidad Nacional del Sur. Departamento de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Johnston, E.R.. Georgia Institute of Technology. School of Civil and Environmental Engineering; Estados UnidosFil: Han, X.G.. Chinese Academy of Sciences. Institute of Applied Ecology; China. Chinese Academy of Sciences. Institute of Botany. State Key Laboratory of Vegetation and Environmental Change; ChinaFil: Zhang, X.M.. Chinese Academy of Agricultural Sciences. Institute of Environment and Sustainable Development in Agriculture. Key Laboratory of Dryland Agriculture;; Chin

Character extraction in web image for text recognition

Proceedings - International Conference on Pattern Recognition3042-3045PICR

A gradient vector flow-based method for video character segmentation

10.1109/ICDAR.2011.207Proceedings of the International Conference on Document Analysis and Recognition, ICDAR1024-102

Measuring health literacy in Asia: Validation of the HLS-EU-Q47 survey tool in six Asian countries

Background: Health literacy has been increasingly recognized as one of the most important social determinants for health. However, an appropriate and comprehensive assessment tool is not available in many Asian countries. This study validates a comprehensive health literacy survey tool European health literacy questionnaire (HLS-EU-Q47) for the general public in several Asian countries. Methods: A cross-sectional survey based on multistage random sampling in the target countries. A total of 10,024 participants aged ≥15 years were recruited during 2013e2014 in Indonesia, Kazakhstan, Malaysia, Myanmar, Taiwan, and Vietnam. The questionnaire was translated into local languages to measure general health literacy and its three domains. To evaluate the validity of the tool in these countries, data were analyzed by confirmatory factor analysis, internal consistency analysis, and regression analysis. Results: The questionnaire was shown to have good construct validity, satisfactory goodness-of-fit of the data to the hypothetical model in three health literacy domains, high internal consistency (Cronbach's alpha > 0.90), satisfactory item-scale convergent validity (item-scale correlation ≥0.40), and no floor/ ceiling effects in these countries. General health literacy index score was significantly associated with level of education (P from < 0.001 to 0.011) and perceived social status (P from < 0.001 to 0.016), with evidence of known-group validity. Conclusions: The HLS-EU-Q47 was a satisfactory and comprehensive health literacy survey tool for use in Asia

A cross-sectional survey of coronary plaque composition in individuals on non-statin lipid lowering drug therapies and undergoing coronary computed tomography angiography

Introduction: Non-statin therapy (NST)is used as second-line treatment when statin monotherapy is inadequate or poorly tolerated. Objective: To determine the association of NST with plaque composition, alone or in combination with statins, in patients undergoing coronary computed tomography angiography (coronary CTA). Methods: From the multicenter CONFIRM registry, we analyzed individuals who underwent coronary CTA with known lipid-lowering therapy status and without prior coronary artery disease at baseline. We created a propensity score for being on NST, followed by stepwise multivariate linear regression, adjusting for the propensity s\ueccore as well as risk factors, to determine the association between NST and the number of coronary artery segments with each plaque type (non-calcified (NCP), partially calcified (PCP)or calcified (CP))and segment stenosis score (SSS). Results: Of the 27,125 subjects in CONFIRM, 4,945 met the inclusion criteria; 371 (7.5%)took NST. At baseline, patients on NST had more prevalent risk factors and were more likely to be on concomitant cardiac medications. After multivariate and propensity score adjustment, NST was not associated with plaque composition: NCP (0.07 increase, 95% CI: 120.05, 0.20; p = 0.26), PCP (0.10 increase, 95% CI: 120.10, 0.31; p = 0.33), CP (0.18 increase, 95% CI: 120.10, 0.46; p = 0.21)or SSS (0.45 increase, 95% CI: 120.02,0.93; p = 0.06). The absence of an effect of NST on plaque type was not modified by statin use (p for interaction &gt; 0.05 for all). Conclusion: In this cross-sectional study, non-statin therapy was not associated with differences in plaque composition as assessed by coronary CTA