Development of an Accelerometer-Linked Online Intervention System to Promote Physical Activity in Adolescents

Most adolescents do not achieve the recommended levels of moderate-to-vigorous physical activity (MVPA), placing them at increased risk for a diverse array of chronic diseases in adulthood. There is a great need for scalable and effective interventions that can increase MVPA in adolescents. Here we report the results of a measurement validation study and a preliminary proof-of-concept experiment testing the impact of Zamzee, an accelerometer-linked online intervention system that combines proximal performance feedback and incentive motivation features to promote MVPA. In a calibration study that parametrically varied levels of physical activity in 31 12-14 year-old children, the Zamzee activity meter was shown to provide a valid measure of MVPA (sensitivity in detecting MVPA = 85.9%, specificity = 97.5%, and r = .94 correspondence with the benchmark RT3 accelerometer system; all p < .0001). In a subsequent randomized controlled multi-site experiment involving 182 middle school-aged children assessed for MVPA over 6 wks, intent-to-treat analyses found that those who received access to the Zamzee intervention had average MVPA levels 54% greater than those of a passive control group (p < 0.0001) and 68% greater than those of an active control group that received access to a commercially available active videogame (p < .0001). Zamzee’s effects on MVPA did not diminish significantly over the course of the 6-wk study period, and were statistically significant in both females and males, and in normal- vs. high-BMI subgroups. These results provide promising initial indications that combining the Zamzee activity meter with online proximal performance feedback and incentive motivation features can positively impact MVPA levels in adolescents.     

A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform.     

Population regulation and demography in a harvested freshwater crayfish from Madagascar

Despite advances in statistical techniques for investigating population dynamics based on mark–recapture data, the majority of our understanding about demography and regulation comes from relatively few taxa. Most proposed generalisations about the association between demography and variation in population size are based on data from vertebrates, there are few sufficiently detailed invertebrate studies to examine whether these generalisations are widely supported. The population biology of freshwater invertebrates is especially poorly known. We present a large-scale mark–recapture study of an endemic freshwater crayfish from Madagascar ( Astacoides granulimanus ). Variation in density, caused by difference in fishing pressure due to local taboos, allowed us to investigate density-dependent regulation. We found evidence of density dependence in fecundity operating through the proportion of reproductive females by size but no significant evidence of density dependence in growth. Using a prospective analysis based on the elasticities from a size-structured matrix model, we found that both recruitment rates and survival rates of large individuals were strongly associated with deterministic population growth – a result that differs from generalisations drawn from vertebrate studies. A central assumption in mark–recapture studies is that handling does not affect mortality. By treating the number of times an individual was captured as an individual covariate, easily done using the freeware program MARK, we were able to test for, and take account of, handling-induced mortality. Our results show interesting similarities, and important differences, to generalisations based on vertebrate studies and emphasise the importance of population studies on poorly known taxa.     

Assessing Greater Sage-Grouse Selection of Brood-Rearing Habitat Using Remotely-Sensed Imagery: Can Readily Available High-Resolution Imagery Be Used to Identify Brood-Rearing Habitat Across a Broad Landscape?

Greater sage-grouse populations have decreased steadily since European settlement in western North America. Reduced availability of brood-rearing habitat has been identified as a limiting factor for many populations. We used radio-telemetry to acquire locations of sage-grouse broods from 1998 to 2012 in Strawberry Valley, Utah. Using these locations and remotely-sensed NAIP (National Agricultural Imagery Program) imagery, we 1) determined which characteristics of brood-rearing habitat could be used in widely available, high resolution imagery 2) assessed the spatial extent at which sage-grouse selected brood-rearing habitat, and 3) created a predictive habitat model to identify areas of preferred brood-rearing habitat. We used AIC model selection to evaluate support for a list of variables derived from remotely-sensed imagery. We examined the relationship of these explanatory variables at three spatial extents (45, 200, and 795 meter radii). Our top model included 10 variables (percent shrub, percent grass, percent tree, percent paved road, percent riparian, meters of sage/tree edge, meters of riparian/tree edge, distance to tree, distance to transmission lines, and distance to permanent structures). Variables from each spatial extent were represented in our top model with the majority being associated with the larger (795 meter) spatial extent. When applied to our study area, our top model predicted 75% of naïve brood locations suggesting reasonable success using this method and widely available NAIP imagery. We encourage application of our methodology to other sage-grouse populations and species of conservation concern.     

Can zoosporic true fungi grow or survive in extreme or stressful environments?

Zoosporic true fungi are thought to be ubiquitous in many ecosystems, especially in cool, moist soils and freshwater habitats which are rich in organic matter. However, some of the habitats where these fungi are found may periodically experience extreme conditions, such as soils in extremely dry, hot and cold climates, acidic and alkaline soils, polluted rivers, anaerobic soil and water, saline soil and water, periglacial soils, oligotrophic soils, tree canopies and hydrothermal vents. It is clear that many ecotypes of zoosporic true fungi have indeed adapted to extreme or stressful environmental conditions. This conclusion is supported by studies in both the field and in the laboratory. Therefore, in our opinion, at least some true zoosporic fungi can be considered to be extremophiles.     

Improving acclimatization through the photoautotrophic culture of coconut (Cocos nucifera) seedlings: an in vitro system for the efficient exchange of germplasm

An in vitro photoautotrophic step based on the supply of CO₂-enriched air (1,600 μmol mol^?1) during the light phase and ambient air (350 μmol mol^?1 CO₂) during the dark phase has been used to promote the ex vitro establishment of coconut (Cocos nucifera L.) seedlings. The introduction of this step into a previously developed in vitro protocol was found to improve the quality of the seedlings (as assessed by fresh weight increase, physical stature, leaf area and thickness, stomatal density, and chlorophyll a content, and primary and secondary root production), the proportion of seedlings successfully transferred to soil (improvement from 40% to 100%) and achieved in a shorter time (reduction from 10 to 6 mo). Best results using this photoautotrophic growth step were obtained when a low medium concentration of sucrose (43.8 mM or lower) was used, when it was applied to seedlings that had already reached 4 or 5 mo of age in the in vitro culture step, and when seedlings were cultured in the photoautotrophic system for 2 mo or more before transfer to soil. Our improved protocol is more efficient and it reduces the cost per plant for the international exchange of coconut germplasm.