Species occurrence.

<p>Presence and proportion and standard error (between brackets) of each species according to the dominant land cover at each spatial scale (intermediate and broad) of the 88 ponds surveyed and total number of ponds where the species was found. AGRIC—agricultural; EUC—eucalypt plantations; MONT—<i>montados</i>; NATFOR—native forests</p><p>Species occurrence.</p

Model averaged parameter estimates (β)(top-ranked models) for each of the anurans, odds ratio (OR) and respective 95% confidence intervals (IC_95%).

<p>Covariate importance between brackets. In bold are the covariates which confidence intervals do not overlap zero. Acronyms are explained in the text.</p><p>Model averaged parameter estimates (β)(top-ranked models) for each of the anurans, odds ratio (OR) and respective 95% confidence intervals (IC_95%).</p

Fitted values predicted by the top ranked model for the Caudata for each of the response variables with strong effect according to the odds ratio results.

<p>The dashed line are the confidence intervals at 95%.</p

Model averaged parameter estimates (β) (top-ranked models) for each of the Caudata, odds ratio (OR) and respective 95% confidence intervals (IC_95%).

<p>Covariate importance between brackets. In bold are the covariates which confidence intervals do not overlap zero. Acronyms are explained in the text.</p><p>Model averaged parameter estimates (β) (top-ranked models) for each of the Caudata, odds ratio (OR) and respective 95% confidence intervals (IC_95%).</p

Fitted values predicted by the top ranked model for the anurans for each of the response variables with strong effect according to the odds ratio results.

<p>The dashed line are the confidence intervals at 95%.</p

The location of the study area.

<p>Distribution of the 88 ponds surveyed monthly between February and June 2011 in central-east Portugal. There were three major study sites distributed in the region: Site A, with 67 ponds; Site B: 2 ponds; Site C: 19 ponds. Each site was divided into subsets (FC, SM, SRIN, CAT, CF. FR, MG, GAL), according to geographical, topographical or barrier features.</p

Project PANK: Rationale, study protocol and baseline results of a multidisciplinary school based intervention in children with cardiovascular and metabolic risk factors

<div><p>Abstract Aims: Cardiovascular disease risk factors occur more frequently in children with obesity. Project PANK is a multidisciplinary school-based intervention lasting 6 months to improve BMI z-score, waist circumference (WC), waist-to-height ratio (WHtR), blood pressure (BP), nutrition, physical activity (PA), sedentary behaviour (SB), cardiorespiratory fitness (CRF), glucose, cholesterol, and triglycerides (TG). Methods/DesignA total of 77 children (7-10 years) were recruited from an urban school. The protocol includes PA and SB individual meetings for children/parents; increasing school exercise; PA and SB lessons for children; A goal in the number of steps/day to accomplish in and after school. In nutrition, the protocol includes three individual meetings for children/parents and six lessons for children. ResultsPositive associations were found between the BMI Z-score, WC, and WHtR with TG; the BMI Z-score and WHtR with glucose; the light PA time and HDL-C; the vigorous and moderate-to-vigorous PA with CRF; the caloric intake and lipids with LDL-C, BMI z-score, WC, and WHtR. A negative association was found between CRF and TG. ConclusionBaseline results stress the importance of multidisciplinary school-based interventions. We hypothesized that PANK will improve blood variables, anthropometric measures, and BP, by changing food intake, enhancing PA and CRF, and decreasing SB.</p></div

Presentation_1_Assessment of math abilities before school entry: a tool development.ZIP

IntroductionThe years preceding school entry are pivotal for children to develop fundamental skills that bolster their learning in literacy and math in the following years. Skills like counting and subitizing stand as key predictors of future math abilities. Hence, the availability of universal screening tools is vital to promptly identify children who are lacking in these skills, allowing for tailored classroom practices to meet their needs. This study aimed to develop a mathematical screening tool and assess its psychometric properties.MethodsThe tool encompasses both group and individual tasks, to evaluate counting, cardinality, subitizing, quantity discrimination, addition, and subtraction. The tool was administered twice to 257 children, aged 5-6, in their final year of kindergarten in Portugal, at both the start and end of the school year.ResultsThe findings reveal that the tasks generally present a low level of difficulty, especially by the end of kindergarten. Factor analysis demonstrated an adequate structure, and all dimensions showed high internal consistency (>0.80). There was a medium-to-high intercorrelation among the various tasks. Correlations between task scores at the beginning and end of the school year were high. Furthermore, scores across all tasks correlated with math achievement in the first grade of primary education.DiscussionThese outcomes suggest that the tool is both valid and reliable, making it a useful resource for assessing and intervening in math skills during the critical years before school entry.</p

Dot blot validation of selected probes.

<p>Nine probes were evaluated with total DNA from a collection of BSX, consisting of 19 <i>Xeu</i>, five <i>Xv</i>, three <i>Xg</i> and two <i>Xp</i> strains. Probability values, obtained with a customized MATLAB algorithm for the automatic data analysis, are detailed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037836#pone-0037836-t003" target="_blank">Table 3</a>.</p

PCR validation.

<p>The selected primer-pairs were tested for efficiency using eight different <i>Xeu</i> strains. For each assay, three different annealing temperatures were tested: 57°C, 59°C and 61°C.</p