The promoter of ZmMRP-1, a maize transfer cell-specific transcriptional activator, is induced at solute exchange surfaces and responds to transport demands

Transfer cells have specializations that facilitate the transport of solutes across plant exchange surfaces. ZmMRP-1 is a maize (Zea mays) endosperm transfer cell-specific transcriptional activator that plays a central role in the regulatory pathways controlling transfer cell differentiation and function. The present work investigates the signals controlling the expression of ZmMRP-1 through the production of transgenic lines of maize, Arabidopsis, tobacco and barley containing ZmMRP-1promoter:GUS reporter constructs. The GUS signal predominantly appeared in regions of active transport between source and sink tissues, including nematode-induced feeding structures and at sites of vascular connection between developing organs and the main plant vasculature. In those cases, promoter induction was associated with the initial developmental stages of transport structures. Significantly, transfer cells also differentiated in these regions suggesting that, independent of species, location or morphological features, transfer cells might differentiate in a similar way under the influence of conserved induction signals. In planta and yeast experiments showed that the promoter activity is modulated by carbohydrates, glucose being the most effective inducer

Evaluation of biases present in the cohort multiple randomised controlled trial design: a simulation study

Background The cohort multiple randomised controlled trial (cmRCT) design provides an opportunity to incorporate the benefits of randomisation within clinical practice; thus reducing costs, integrating electronic healthcare records, and improving external validity. This study aims to address a key concern of the cmRCT design: refusal to treatment is only present in the intervention arm, and this may lead to bias and reduce statistical power. Methods We used simulation studies to assess the effect of this refusal, both random and related to event risk, on bias of the effect estimator and statistical power. A series of simulations were undertaken that represent a cmRCT trial with time-to-event endpoint. Intention-to-treat (ITT), per protocol (PP), and instrumental variable (IV) analysis methods, two stage predictor substitution and two stage residual inclusion, were compared for various refusal scenarios. Results We found the IV methods provide a less biased estimator for the causal effect when refusal is present in the intervention arm, with the two stage residual inclusion method performing best with regards to minimum bias and sufficient power. We demonstrate that sample sizes should be adapted based on expected and actual refusal rates in order to be sufficiently powered for IV analysis. Conclusion We recommend running both an IV and ITT analyses in an individually randomised cmRCT as it is expected that the effect size of interest, or the effect we would observe in clinical practice, would lie somewhere between that estimated with ITT and IV analyses. The optimum (in terms of bias and power) instrumental variable method was the two stage residual inclusion method. We recommend using adaptive power calculations, updating them as refusal rates are collected in the trial recruitment phase in order to be sufficiently powered for IV analysis

Pilot evaluation of a walking school bus program in a low-income, urban community

<p>Abstract</p> <p>Background</p> <p>To evaluate the impact of a walking school bus (WSB) program on student transport in a low-income, urban neighborhood.</p> <p>Methods</p> <p>The design was a controlled, quasi-experimental trial with consecutive cross-sectional assessments. The setting was three urban, socioeconomically disadvantaged, public elementary schools (1 intervention vs. 2 controls) in Seattle, Washington, USA. Participants were ethnically diverse students in kindergarten-5^thgrade (aged 5–11 years). The intervention was a WSB program consisting of a part-time WSB coordinator and parent volunteers. Students' method of transportation to school was assessed by a classroom survey at baseline and one-year follow-up. The Pearson Chi-squared test compared students transported to school at the intervention versus control schools at each time point. Due to multiple testing, we calculated adjusted p-values using the Ryan-Holm stepdown Bonferroni procedure. McNemar's test was used to examine the change from baseline to 12-month follow-up for walking versus all other forms of school transport at the intervention or control schools.</p> <p>Results</p> <p>At baseline, the proportions of students (n = 653) walking to the intervention (20% +/- 2%) or control schools (15% +/- 2%) did not differ (<it>p </it>= 0.39). At 12-month follow up, higher proportions of students (n = 643, <it>p </it>= 0.001)) walked to the intervention (25% +/- 2%) versus the control schools (7% +/- 1%). No significant changes were noted in the proportion of students riding in a car or taking the school bus at baseline or 12-month follow up (all <it>p </it>> 0.05). Comparing baseline to 12-month follow up, the numbers of students who walked to the intervention school increased while the numbers of students who used the other forms of transport did not change (<it>p </it>< 0.0001). In contrast, the numbers of students who walked to the control schools decreased while the numbers of students who used the other forms of transport did not change (<it>p </it>< 0.0001).</p> <p>Conclusion</p> <p>A WSB program is a promising intervention among urban, low-income elementary school students that may promote favorable changes toward active transport to school.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov NCT00402701</p

'Good Morning Fitfam': Top posts, hashtags and gender display on Instagram

Social networking sites are important platforms for visual self-presentation online. This article investigates how content producers present their gender identities on the social networking site, Instagram. We draw upon and develop Goffman’s analytic framework to understand the self-presentation techniques and styles users employ online. Conducting a visual content analysis of clean eating–related top posts, we examine how users deploy clean eating hashtags and how the architecture of Instagram constrains and enables certain identities around shared lifestyles and commercial interests. Our findings reveal the symbolic significance of hashtags for group membership and the degree to which gender identities on Instagram are configured around platform interfaces

Patterns and correlates of physical activity: a cross-sectional study in urban Chinese women

<p>Abstract</p> <p>Background</p> <p>Inactivity is a modifiable risk factor for many diseases. Rapid economic development in China has been associated with changes in lifestyle, including physical activity. The purpose of this study was to investigate the patterns and correlates of physical activity in middle-aged and elderly women from urban Shanghai.</p> <p>Methods</p> <p>Study population consisted of 74,942 Chinese women, 40–70 years of age, participating in the baseline survey of the Shanghai Women's Health Study (1997–2000), an ongoing population-based cohort study. A validated, interviewer-administered physical activity questionnaire was used to collect information about several physical activity domains (exercise/sports, walking and cycling for transportation, housework). Correlations between physical activity domains were evaluated by Spearman rank-correlation coefficients. Associations between physical activity and socio-demographic and lifestyle factors were evaluated by odds ratios derived from logistic regression.</p> <p>Results</p> <p>While more than a third of study participants engaged in regular exercise, this form of activity contributed only about 10% to daily non-occupational energy expenditure. About two-thirds of women met current recommendations for lifestyle activity. Age was positively associated with participation in exercise/sports and housework. Dietary energy intake was positively associated with all physical activity domains. High socioeconomic status, unemployment (including retirement), history of chronic disease, small household, non-smoking status, alcohol and tea consumption, and ginseng intake were all positively associated with exercise participation. High socioeconomic status and small household were inversely associated with non-exercise activities.</p> <p>Conclusion</p> <p>This study demonstrates that physical activity domains other than sports and exercise are important contributors to total energy expenditure in women. Correlates of physical activity are domain-specific. These findings provide important information for research on the health benefits of physical activity and have public health implications for designing interventions to promote participation in physical activity.</p

A qualitative study of older adults' responses to sitting-time questions: do we get the information we want?

In the last decade, there has been increasing interest in the health effects of sedentary behavior, which is often assessed using self-report sitting-time questions. The aim of this qualitative study was to document older adults' understanding of sitting-time questions from the International Physical Activity (PA) Questionnaire (IPAQ) and the PA Scale for the Elderly (PASE)

“Keeping Moving”: factors associated with sedentary behaviour among older people recruited to an exercise promotion trial in general practice

Background Sedentary behaviour is detrimental to health, even in those who achieve recommended levels of physical activity. Efforts to increase physical activity in older people so that they reach beneficial levels have been disappointing. Reducing sedentary behaviour may improve health and be less demanding of older people, but it is not clear how to achieve this. We explored the characteristics of sedentary older people enrolled into an exercise promotion trial to gain insights about those who were sedentary but wanted to increase activity. Method Participants in the ProAct65+ trial (2009–2013) were categorised as sedentary or not using a self-report questionnaire. Demographic data, health status, self-rated function and physical test performance were examined for each group. 1104 participants aged 65 & over were included in the secondary analysis of trial data from older people recruited via general practice. Results were analysed using logistic regression with stepwise backward elimination. Results Three hundred eighty seven (35 %) of the study sample were characterised as sedentary. The likelihood of being categorised as sedentary increased with an abnormal BMI (25 kg/m2) (Odds Ratio 1.740, CI 1.248–2.425), ever smoking (OR 1.420, CI 1.042–1.934) and with every additional medication prescribed (OR 1.069, CI 1.016–1.124). Participants reporting better self-rated physical health (SF-12) were less likely to be sedentary; (OR 0.961, 0.936–0.987). Participants’ sedentary behaviour was not associated with gender, age, income, education, falls, functional fitness, quality of life or number of co-morbidities. Conclusion Some sedentary older adults will respond positively to an invitation to join an exercise study. Those who did so in this study had poor self-rated health, abnormal BMI, a history of smoking, and multiple medication use, and are therefore likely to benefit from an exercise intervention

Estimates of adherence and error analysis of physical activity data collected via accelerometry in a large study of free-living adults

<p>Abstract</p> <p>Background</p> <p>Activity monitors (AM) are small, electronic devices used to quantify the amount and intensity of physical activity (PA). Unfortunately, it has been demonstrated that data loss that occurs when AMs are not worn by subjects (removals during sleeping and waking hours) tend to result in biased estimates of PA and total energy expenditure (TEE). No study has reported the degree of data loss in a large study of adults, and/or the degree to which the estimates of PA and TEE are affected. Also, no study in adults has proposed a methodology to minimize the effects of AM removals.</p> <p>Methods</p> <p>Adherence estimates were generated from a pool of 524 women and men that wore AMs for 13 – 15 consecutive days. To simulate the effect of data loss due to AM removal, a reference dataset was first compiled from a subset consisting of 35 highly adherent subjects (24 HR; minimum of 20 hrs/day for seven consecutive days). AM removals were then simulated during sleep and between one and ten waking hours using this 24 HR dataset. Differences in the mean values for PA and TEE between the 24 HR reference dataset and the different simulations were compared using paired <it>t</it>-tests and/or coefficients of variation.</p> <p>Results</p> <p>The estimated average adherence of the pool of 524 subjects was 15.8 ± 3.4 hrs/day for approximately 11.7 ± 2.0 days. Simulated data loss due to AM removals during sleeping hours in the 24 HR database (n = 35), resulted in biased estimates of PA (p < 0.05), but not TEE. Losing as little as one hour of data from the 24 HR dataset during waking hours results in significant biases (p < 0.0001) and variability (coefficients of variation between 7 and 21%) in the estimates of PA. Inserting a constant value for sleep and imputing estimates for missing data during waking hours significantly improved the estimates of PA.</p> <p>Conclusion</p> <p>Although estimated adherence was good, measurements of PA can be improved by relatively simple imputation of missing AM data.</p

A calibration protocol for population-specific accelerometer cut-points in children

PurposeTo test a field-based protocol using intermittent activities representative of children\u27s physical activity behaviours, to generate behaviourally valid, population-specific accelerometer cut-points for sedentary behaviour, moderate, and vigorous physical activity.MethodsTwenty-eight children (46% boys) aged 10&ndash;11 years wore a hip-mounted uniaxial GT1M ActiGraph and engaged in 6 activities representative of children\u27s play. A validated direct observation protocol was used as the criterion measure of physical activity. Receiver Operating Characteristics (ROC) curve analyses were conducted with four semi-structured activities to determine the accelerometer cut-points. To examine classification differences, cut-points were cross-validated with free-play and DVD viewing activities.ResultsCut-points of &le;372, &gt;2160 and &gt;4806 counts&bull;min&minus;1 representing sedentary, moderate and vigorous intensity thresholds, respectively, provided the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of the activity). Cross-validation data demonstrated that these values yielded the best overall kappa scores (0.97; 0.71; 0.62), and a high classification agreement (98.6%; 89.0%; 87.2%), respectively. Specificity values of 96&ndash;97% showed that the developed cut-points accurately detected physical activity, and sensitivity values (89&ndash;99%) indicated that minutes of activity were seldom incorrectly classified as inactivity.ConclusionThe development of an inexpensive and replicable field-based protocol to generate behaviourally valid and population-specific accelerometer cut-points may improve the classification of physical activity levels in children, which could enhance subsequent intervention and observational studies.<br /

Adherence to 24-Hour Movement Guidelines for the Early Years and associations with social-cognitive development among Australian preschool children

Background: The new Australian 24-Hour Movement Guidelines for the Early Years recommend that, for preschoolers, a healthy 24-h includes: i) ≥180 min of physical activity, including ≥60 min of energetic play, ii) ≤1 h of sedentary screen time, and iii) 10–13 h of good quality sleep. Using an Australian sample, this study reports the proportion of preschool children meeting these guidelines and investigates associations with social-cognitive development. Methods: Data from 248 preschool children (mean age = 4.2 ± 0.6 years, 57% boys) participating in the PATH-ABC study were analyzed. Children completed direct assessments of physical activity (accelerometry) and social cognition (the Test of Emotional Comprehension (TEC) and Theory of Mind (ToM)). Parents reported on children’s screen time and sleep. Children were categorised as meeting/not meeting: i) individual guidelines, ii) combinations of two guidelines, or iii) all three guidelines. Associations were examined using linear regression adjusting for child age, sex, vocabulary, area level socio-economic status and childcare level clustering. Results: High proportions of children met the physical activity (93.1%) and sleep (88.7%) guidelines, whereas fewer met the screen time guideline (17.3%). Overall, 14.9% of children met all three guidelines. Children meeting the sleep guideline performed better on TEC than those who did not (mean difference [MD] = 1.41; 95% confidence interval (CI) = 0.36, 2.47). Children meeting the sleep and physical activity or sleep and screen time guidelines also performed better on TEC (MD = 1.36; 95% CI = 0.31, 2.41) and ToM (MD = 0.25; 95% CI = −0.002, 0.50; p = 0.05), respectively, than those who did not. Meeting all three guidelines was associated with better ToM performance (MD = 0.28; 95% CI = −0.002, 0.48, p = 0.05), while meeting a larger number of guidelines was associated with better TEC (3 or 2 vs. 1/none, p < 0.02) and ToM performance (3 vs. 2, p = 0.03). Conclusions: Strategies to promote adherence to the 24-Hour Movement Behaviour Guidelines for the Early Years among preschool children are warranted. Supporting preschool children to meet all guidelines or more guidelines, particularly the sleep and screen time guidelines, may be beneficial for their social-cognitive development