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.     

DBA/2J Genetic Background Exacerbates Spontaneous Lethal Seizures but Lessens Amyloid Deposition in a Mouse Model of Alzheimer’s Disease

Alzheimer’s disease (AD) is a leading cause of dementia in the elderly and is characterized by amyloid plaques, neurofibrillary tangles (NFTs) and neuronal dysfunction. Early onset AD (EOAD) is commonly caused by mutations in amyloid precursor protein (APP) or genes involved in the processing of APP including the presenilins (e.g. PSEN1 or PSEN2). In general, mouse models relevant to EOAD recapitulate amyloidosis, show only limited amounts of NFTs and neuronal cell dysfunction and low but significant levels of seizure susceptibility. To investigate the effect of genetic background on these phenotypes, we generated APP^swe and PSEN1^de9 transgenic mice on the seizure prone inbred strain background, DBA/2J. Previous studies show that the DBA/2J genetic background modifies plaque deposition in the presence of mutant APP but the impact of PSEN1^de9 has not been tested. Our study shows that DBA/2J.APP^swePSEN1^de9 mice are significantly more prone to premature lethality, likely to due to lethal seizures, compared to B6.APP^swePSEN1^de9 mice—70% of DBA/2J.APP^swePSEN1^de9 mice die between 2-3 months of age. Of the DBA/2J.APP^swePSEN1^de9 mice that survived to 6 months of age, plaque deposition was greatly reduced compared to age-matched B6.APP^swePSEN1^de9 mice. The reduction in plaque deposition appears to be independent of microglia numbers, reactive astrocytosis and complement C5 activity.     

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.     

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.     

Characterization of beta-adrenergic receptors in cultured human and bovine endothelial cells

We used radioligand binding methods to characterize beta-adrenergic receptors on endothelial cells cultured from adult human iliac vein (HIVE) and bovine fetal aorta (BFAE). For comparison, we also studied the well-characterized C6 glioma cell line (C6). Both human and bovine endothelial cells showed specific saturable binding of [125I]iodopindolol. There was no difference in the binding affinity (KD) of iodopindolol to membranes from the three cell types. However, the beta-receptor density (Bmax) was greater on HIVE cells and BFAE cells than on C6 cells. Displacement of ligand from HIVE and BFAE cells by zinterol or from BFAE cells by ICI 89,406 was consistent with binding to the beta 2-subtype. In contrast, displacement of ligand from C6 cells by zinterol or ICI 89,406 was consistent with binding to both beta 1- and beta 2-subtypes. Exposing BFAE cells in culture to 10 microM isoproterenol for 6 h resulted in a 55% decrease in Bmax without a change in KD. We conclude that 1) human and bovine endothelial cells in culture contain a substantial population of beta-adrenergic receptors, which are predominantly of the beta 2-subtype, and 2) endothelial beta-receptors exhibit downregulation by beta-agonists in culture.     

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.