Anatomical analysis of peach palm (Bactris gasipaes) leaves cultivated in vitro, ex vitro and in vivo

(Anatomical analysis of peach palm (Bactris gasipaes) leaves cultivated in vitro, ex vitro and in vivo). The present work characterized and compared the anatomical structures of the leaves of Bactris gasipaes (Arecaceae) plants grown under different cultivation conditions (in vitro, ex vitro and in vivo) with the goal of identifying the origins of the difficulties encountered in acclimatizing micro-plants. The Quant program was used to determine leaf tissue thicknesses and areas, and histochemical tests were performed on leaf sections and analyzed using light microscopy. Stomatal and trichome densities were determined using the epidermal impression method and by scanning electronic microscopy. Our results indicated that there were no discernible alterations of the anatomical characteristics of the leaves of micro-plants cultivated under differing conditions and that the thickening of the mesophyll and the vascular fibers indicated adaptive responses to ex vitro conditions. As such, the observed difficulties in acclimatizing peach palm micro-plants to ex vitro conditions cannot be attributed to plant anatomical characteristics acquired during in vitro cultivation.

Understanding the correlates of adolescents' dietary intake patterns. A multivariate analysis

We investigated dietary intake patterns (DIP) in adolescents (14-18 year-olds) and the association with demographic and socioeconomic characteristics and lifestyle variables. This school-based survey was carried out among high school students from the city of Maringa in the state of Parana (PR), Brazil (2007). The sample included 991 students (54.5% girls) from high schools. DIPs were investigated by the frequency of weekly consumption of each food group: vegetables, fruit, rice, beans, fried food, sweet food, milk, soda, meat, eggs, alcoholic drinks. Independent variables were: demographic and socioeconomic characteristics and lifestyle variables. DIPS were identified using principal component analysis with orthogonal rotation (varimax). Three components were extracted. Component 1 (fried foods, sweets and soft drinks) was positively associated with not having breakfast for girls and dinner for boys. Moreover, component 2 (consumption of fruit and vegetables) was positively associated with having breakfast at home for boys and number of meals for girls. Component 3 (beans, eggs and meat) was positively associated with having lunch, employment and sedentary behavior level for girls. However, it was negatively associated with having lunch and dinner for boys. Adolescents who have healthier eating patterns also had other healthier behaviors regardless of gender. However, factors associated with dietary patterns differ between boys and girls. (C) 2012 Elsevier Ltd. All rights reserved.

Relationship between ozone, meteorological conditions, gas exchange and leaf injury in Nicotiana tabacum Bel-W3 in a sub-tropical region

The city of Sao Paulo is located in a subtropical region whose climate exhibits few defined seasons as well as frequent oscillations in temperature and rainfall throughout the year. In addition to interfering with physiological processes, these peculiar climatic dynamics influence the formation of O-3 and its influx into leaves, causing species used as bioindicators in temperate climates to be ineffective here. This study evaluated gas exchange variations in CO2 and H2O and leaf injuries induced by O-3 in Nicotiana tabacum Bel-W3 in relation to oscillations in environmental conditions. Plants were exposed to an O-3-polluted environment for fifteen periods of fourteen days each throughout 2008. Gas exchange and O-3 were higher during the summer and winter but were highly variable in all seasons. Severe injuries occurred during the winter and spring, with significant variation in this parameter being observed throughout the year. An analysis of biotic and abiotic variables revealed complex relationships among them, with great importance of meteorological factors in plant responses. We conclude that under unstable climatic conditions, the relationship between O-3 flux and injury is weak, and the qualitative character of biomonitoring is further confirmed. (c) 2012 Elsevier Ltd. All rights reserved.

Effects of an adapted physical activity program on the physical condition of elderly women: an analysis of efficiency

Background: Specific research tools and designs can assist in identifying the efficiency of physical activity in elderly women. Objectives: To identify the effects of physical activity on the physical condition of older women. Method: A one-year-long physical activity program (123 sessions) was implemented for women aged 60 years or older. Four physical assessments were conducted, in which weight, height, BMI, blood pressure, heart rate, absences, grip strength, flexibility, VO2max, and static and dynamic balance were assessed. The statistical analyses included a repeated measures analysis, both inferential (analysis of variance - ANOVA) and effect size (Cohen's d coefficient), as well as identification of the participants' efficiency (Data Envelopment Analysis - DEA). Results: Despite the observation of differences that depended on the analysis used, the results were successful in the sense that they showed that physical activity adapted to older women can effectively change the decline in physical ability associated with aging, depending on the purpose of the study. The 60-65 yrs group was the most capable of converting physical activity into health benefits in both the short and long term. The >65 yrs group took less advantage of physical activity. Conclusions: Adherence to the program and actual time spent on each type of exercise are the factors that determine which population can benefit from physical activity programs. The DEA allows the assessment of the results related to time spent on physical activity in terms of health concerns. Article registered in Clinicaltrials.gov under number NCT01558401.

Multivariate analysis of fresh-cut carambola slices stored under different temperatures

Quality of fresh-cut carambola (Averrhoa carambola L) is related to many chemical and biochemical variables especially those involved with softening and browning, both influenced by storage temperature. To study these effects, a multivariate analysis was used to evaluate slices packaged in vacuum-sealed polyolefin bags, and stored at 2.5 degrees C, 5 degrees C and 10 degrees C, for up to 16 d. The quality of slices at each temperature was correlated with the duration of storage, O(2) and CO(2) concentration in the package, physical chemical constituents, and activity of enzymes involved in softening (PG) and browning (PPO) metabolism. Three quality groups were identified by hierarchical cluster analysis, and the classification of the components within each of these groups was obtained from a principal component analysis (PCA). The characterization of samples by PCA clearly distinguished acceptable and non-acceptable slices. According to PCA, acceptable slices presented higher ascorbic acid content, greater hue angles ((o)h) and final lightness (L-5) in the first principal component (PC1). On the other hand, non-acceptable slices presented higher total pectin content. PPO activity in the PC1. Non-acceptable slices also presented higher soluble pectin content, increased pectin solubilisation and higher CO(2) concentration in the second principal component (PC2) whereas acceptable slices showed lower total sugar content. The hierarchical cluster and PCA analyses were useful for discriminating the quality of slices stored at different temperatures. (C) 2011 Elsevier B.V. All rights reserved.

Composition and antioxidant activity of honey from Africanized and stingless bees in Alagoas (Brazil): a multivariate analysis

The purpose of this study was to evaluate the antioxidant activity of honey from different entomological sources which were harvested in the dry season of 2008-2009 from distinct mesoregions of the State of Alagoas in the North East of Brazil. Honey produced by five different species of bees, even from the same region and season, showed a statistically significant difference (p <0.05) in the content of phenols, flavonoids and antioxidants, with higher levels of these compounds found in honey produced by Plebeia spp. and A. mellifera. Honey from stingless bees was quite different from that of A. mellifera, especially from the Plebeia spp. A dendrogram of the five species of bees showed the formation of 3 groups, one being formed by Apis mellifera, one by the genus Melipona (M. subnitida, M. quadrifasciata and M. scutellaris) and another formed by Plebeia spp.

PXRF and multivariate statistics analysis of pre-colonial pottery from northeast of Brazil

Portable system of energy dispersive X-ray fluorescence was used to determine the elemental composition of 68 pottery fragments from Sambaqui do Bacanga, an archeological site in Sao Luis, Maranhao, Brazil. This site was occupied from 6600 BP until 900 BP. By determining the element chemical composition of those fragments, it was possible to verify the existence of engobe in 43 pottery fragments. Obtained from two-dimensional graphs and hierarchical cluster analysis performed in fragments of stratigraphies from surface and 113-cm level, and 10 to 20, 132 and 144-cm level, it was possible to group these fragments in five distinct groups, according to their stratigraphies. The results of data grouping (two-dimensional graphics) are in agreement with hierarchical cluster analysis by Ward method. Copyright (C) 2011 John Wiley & Sons, Ltd.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Development of an integrative cessation program for co-smokers of cigarettes and cannabis: demand analysis, program description, and acceptability

Abstract Background Tobacco and cannabis use are strongly interrelated, but current national and international cessation programs typically focus on one substance, and address the other substance either only marginally or not at all. This study aimed to identify the demand for, and describe the development and content of, the first integrative group cessation program for co-smokers of cigarettes and cannabis. Methods First, a preliminary study using expert interviews, user focus groups with (ex-)smokers, and an online survey was conducted to investigate the demand for, and potential content of, an integrative smoking cessation program (ISCP) for tobacco and cannabis co-smokers. This study revealed that both experts and co-smokers considered an ISCP to be useful but expected only modest levels of readiness for participation.Based on the findings of the preliminary study, an interdisciplinary expert team developed a course concept and a recruitment strategy. The developed group cessation program is based on current treatment techniques (such as motivational interviewing, cognitive behavioural therapy, and self-control training) and structured into six course sessions.The program was evaluated regarding its acceptability among participants and course instructors. Results Both the participants and course instructors evaluated the course positively. Participants and instructors especially appreciated the group discussions and the modules that were aimed at developing personal strategies that could be applied during simultaneous cessation of tobacco and cannabis, such as dealing with craving, withdrawal, and high-risk situations. Conclusions There is a clear demand for a double cessation program for co-users of cigarettes and cannabis, and the first group cessation program tailored for these users has been developed and evaluated for acceptability. In the near future, the feasibility of the program will be evaluated. Trial registration Current Controlled Trials ISRCTN15248397

Quantitative chemical profile and multivariate statistical analysis of alembic distilled sugarcane spirit fractions

As concentrações de 39 compostos orgânicos foram determinadas em três frações (cabeça, coração e cauda) obtidas da destilação em alambique do caldo de cana fermentado. Os resultados foram avaliados utilizando-se análise de variância (ANOVA), teste de Tukey, análise de componentes principais (PCA), agrupamento hierárquico (HCA) e análise discriminante linear (LDA). De acordo com PCA e HCA, os dados experimentais conduzem à formação de três agrupamentos. As frações de cabeça deram origem a um grupo mais definido. As frações coração e cauda apresentaram alguma sobreposição coerente com sua composição em ácidos. As habilidades preditivas de calibração e validação dos modelos gerados pela LDA para a classificação das três frações foram de 90,5 e 100%, respectivamente. Este modelo reconheceu como coração doze de treze cachaças comerciais (92,3%) com boas características sensoriais, apresentando potencial para a orientação do processo de cortes.

What drives the seasonality of photosynthesis across the Amazon basin? A cross-site analysis of eddy flux tower measurements from the Brasil flux network

We investigated the seasonal patterns of Amazonian forest photosynthetic activity, and the effects thereon of variations in climate and land-use, by integrating data from a network of ground-based eddy flux towers in Brazil established as part of the ‘Large-Scale Biosphere Atmosphere Experiment in Amazonia’ project. We found that degree of water limitation, as indicated by the seasonality of the ratio of sensible to latent heat flux (Bowen ratio) predicts seasonal patterns of photosynthesis. In equatorial Amazonian forests (5◦ N–5◦ S), water limitation is absent, and photosynthetic fluxes (or gross ecosystem productivity, GEP) exhibit high or increasing levels of photosynthetic activity as the dry season progresses, likely a consequence of allocation to growth of new leaves. In contrast, forests along the southern flank of the Amazon, pastures converted from forest, and mixed forest-grass savanna, exhibit dry-season declines in GEP, consistent with increasing degrees of water limitation. Although previous work showed tropical ecosystem evapotranspiration (ET) is driven by incoming radiation, GEP observations reported here surprisingly show no or negative relationships with photosynthetically active radiation (PAR). Instead, GEP fluxes largely followed the phenology of canopy photosynthetic capacity (Pc), with only deviations from this primary pattern driven by variations in PAR. Estimates of leaf flush at three

Multivariate spectroscopic methods for the analysis of solutions

In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. These spectroscopic methods consisting of spectroscopic analysis, a high level of automation and chemometric data evaluation can lead to analytical methods with a high analytical capacity, and for these methods, the term high-capacity analysis (HCA) is suggested. It is further shown how chemometric evaluation of the multivariate data in chromatographic analyses decreases the need for baseline separation. The thesis is based on six papers and the chemometric tools used are experimental design, principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC). The analytical techniques utilised are scanning ultraviolet-visible (UV-Vis) spectroscopy, diode array detection (DAD) used in non-column chromatographic diode array UV spectroscopy, high-performance liquid chromatography with diode array detection (HPLC-DAD) and fluorescence spectroscopy. The methods proposed are exemplified in the analysis of pharmaceutical solutions and serum proteins. In Paper I a method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of UV-Vis spectroscopy, orthogonal signal correction and multivariate calibration with PLS and SIMCA classification. Paper II proposes a new method for the rapid determination of pharmaceutical solutions by the use of non-column chromatographic diode array UV spectroscopy, i.e. a conventional HPLC-DAD system without any chromatographic column connected. In Paper III an investigation is made of the ability of a control sample, of known content and identity to diagnose and correct errors in multivariate predictions something that together with use of multivariate residuals can make it possible to use the same calibration model over time. In Paper IV a method is proposed for simultaneous determination of serum proteins with fluorescence spectroscopy and multivariate calibration. Paper V proposes a method for the determination of chromatographic peak purity by means of PCA of HPLC-DAD data. In Paper VI PARAFAC is applied for the decomposition of DAD data of some partially separated peaks into the pure chromatographic, spectral and concentration profiles.

A partial dependence factorial analysis to deal with selection bias in observational studis

This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

Multivariate analysis methods in the search for the Higgs boson produced in association with top pairs at the ATLAS experiment at LHC.

The Large Hadron Collider, located at the CERN laboratories in Geneva, is the largest particle accelerator in the world. One of the main research fields at LHC is the study of the Higgs boson, the latest particle discovered at the ATLAS and CMS experiments. Due to the small production cross section for the Higgs boson, only a substantial statistics can offer the chance to study this particle properties. In order to perform these searches it is desirable to avoid the contamination of the signal signature by the number and variety of the background processes produced in pp collisions at LHC. Much account assumes the study of multivariate methods which, compared to the standard cut-based analysis, can enhance the signal selection of a Higgs boson produced in association with a top quark pair through a dileptonic final state (ttH channel). The statistics collected up to 2012 is not sufficient to supply a significant number of ttH events; however, the methods applied in this thesis will provide a powerful tool for the increasing statistics that will be collected during the next LHC data taking.