Validation of the TracmorD Triaxial Accelerometer to Assess Physical Activity in Preschool Children

Objectives: To assess validity evidence of Tracmor_D to determine energy used for physical activity in 3‐4‐year‐old children. Design and Methods: Participants were randomly selected from GECKO Drenthe cohort (n = 30, age 3.4 ± 0.3 years). Total energy expenditure (TEE) was measured using the doubly labeled water method. Sleeping metabolic rate (SMR) was measured by indirect calorimetry (Deltatrac). TEE and SMR were used to calculate physical activity level (PAL) and activity energy expenditure (AEE). Physical activity was monitored using a DirectLife triaxial accelerometer, Tracmor_D with activity counts per minute (ACM) and activity counts per day (ACD) as outcome measures. Results: The best predictor for PAL was ACM with gender and weight, the best predictor for AEE was ACM alone (backward regression, R² = 0.50, P = 0.010 and R² = 0.31, P = 0.011, respectively). With ACD, the prediction model for PAL included ACD, height, gender, and sleep duration (R² = 0.48, P = 0.033), the prediction model for AEE included ACD, gender and sleep duration (R² = 0.39, P = 0.042). The accelerometer was worn for 5 days, but 3 days did not give a different estimated PAL. Conclusion: Tracmor_D provides moderate‐to‐strong validity evidence that supports its use to evaluate energy used for physical activity in 3‐4‐year‐old children.     

Feed-forward neural network model for hunger and satiety related VAS score prediction

Background

An artificial neural network approach was chosen to model the outcome of the complex signaling pathways in the gastro-intestinal tract and other peripheral organs that eventually produce the satiety feeling in the brain upon feeding.

Methods

A multilayer feed-forward neural network was trained with sets of experimental data relating concentration-time courses of plasma satiety hormones to Visual Analog Scales (VAS) scores. The network successfully predicted VAS responses from sets of satiety hormone data obtained in experiments using different food compositions.

Results

The correlation coefficients for the predicted VAS responses for test sets having i) a full set of three satiety hormones, ii) a set of only two satiety hormones, and iii) a set of only one satiety hormone were 0.96, 0.96, and 0.89, respectively. The predicted VAS responses discriminated the satiety effects of high satiating food types from less satiating food types both in orally fed and ileal infused forms.

Conclusions

From this application of artificial neural networks, one may conclude that neural network models are very suitable to describe situations where behavior is complex and incompletely understood. However, training data sets that fit the experimental conditions need to be available.

     

Automated Entire Thrombus Density Measurements for Robust and Comprehensive Thrombus Characterization in Patients with Acute Ischemic Stroke

Background and Purpose

In acute ischemic stroke (AIS) management, CT-based thrombus density has been associated with treatment success. However, currently used thrombus measurements are prone to inter-observer variability and oversimplify the heterogeneous thrombus composition. Our aim was first to introduce an automated method to assess the entire thrombus density and then to compare the measured entire thrombus density with respect to current standard manual measurements.

Materials and Method

In 135 AIS patients, the density distribution of the entire thrombus was determined. Density distributions were described using medians, interquartile ranges (IQR), kurtosis, and skewedness. Differences between the median of entire thrombus measurements and commonly applied manual measurements using 3 regions of interest were determined using linear regression.

Results

Density distributions varied considerably with medians ranging from 20.0 to 62.8 HU and IQRs ranging from 9.3 to 55.8 HU. The average median of the thrombus density distributions (43.5 ± 10.2 HU) was lower than the manual assessment (49.6 ± 8.0 HU) (p<0.05). The difference between manual measurements and median density of entire thrombus decreased with increasing density (r = 0.64; p<0.05), revealing relatively higher manual measurements for low density thrombi such that manual density measurement tend overestimates the real thrombus density.

Conclusions

Automatic measurements of the full thrombus expose a wide variety of thrombi density distribution, which is not grasped with currently used manual measurement. Furthermore, discrimination of low and high density thrombi is improved with the automated method.     

Measuring 3D Hand and Finger Kinematics—A Comparison between Inertial Sensing and an Opto-Electronic Marker System

Objective analysis of hand and finger kinematics is important to increase understanding of hand function and to quantify motor symptoms for clinical diagnosis. The aim of this paper is to compare a new 3D measurement system containing multiple miniature inertial sensors (PowerGlove) with an opto-electronic marker system during specific finger tasks in three healthy subjects. Various finger movements tasks were performed: flexion, fast flexion, tapping, hand open/closing, ab/adduction and circular pointing. 3D joint angles of the index finger joints and position of the thumb and index were compared between systems. Median root mean square differences of the main joint angles of interest ranged between 3.3 and 8.4deg. Largest differences were found in fast and circular pointing tasks, mainly in range of motion. Smallest differences for all 3D joint angles were observed in the flexion tasks. For fast finger tapping, the thumb/index amplitude showed a median difference of 15.8mm. Differences could be explained by skin movement artifacts caused by relative marker movements of the marker system, particularly during fast tasks; large movement accelerations and angular velocities which exceeded the range of the inertial sensors; and by differences in segment calibrations between systems. The PowerGlove is a system that can be of value to measure 3D hand and finger kinematics and positions in an ambulatory setting. The reported differences need to be taken into account when applying the system in studies understanding the hand function and quantifying hand motor symptoms in clinical practice.     

Cortical Thickness,Surface Area and Subcortical Volume Differentially Contribute to Cognitive Heterogeneity in Parkinson’s Disease

Parkinson’s disease (PD) is often associated with cognitive deficits, although their severity varies considerably between patients. Recently, we used voxel-based morphometry (VBM) to show that individual differences in gray matter (GM) volume relate to cognitive heterogeneity in PD. VBM does, however, not differentiate between cortical thickness (CTh) and surface area (SA), which might be independently affected in PD. We therefore re-analyzed our cohort using the surface-based method FreeSurfer, and investigated (i) CTh, SA, and (sub)cortical GM volume differences between 93 PD patients and 45 matched controls, and (ii) the relation between these structural measures and cognitive performance on six neuropsychological tasks within the PD group. We found cortical thinning in PD patients in the left pericalcarine gyrus, extending to cuneus, precuneus and lingual areas and left inferior parietal cortex, bilateral rostral middle frontal cortex, and right cuneus, and increased cortical surface area in the left pars triangularis. Within the PD group, we found negative correlations between (i) CTh of occipital areas and performance on a verbal memory task, (ii) SA and volume of the frontal cortex and visuospatial memory performance, and, (iii) volume of the right thalamus and scores on two verbal fluency tasks. Our primary findings illustrate that i) CTh and SA are differentially affected in PD, and ii) VBM and FreeSurfer yield non-overlapping results in an identical dataset. We argue that this discrepancy is due to technical differences and the subtlety of the PD-related structural changes.     

The nature of plant adaptations to salinity stress has trophic consequences

In different ecosystems herbivores highly prefer particular plant species. This is often explained in a stoichiometric framework of nutrient‐based plant adaptations to herbivory. We hypothesize that such super‐palatability can also arise as an evolutionary by‐product of osmoregulatory adaptations of plants to stressful environmental conditions, as salinity, drought and cold. Here, we investigate in a coastal salt marsh why some plant species are highly preferred by migratory brent geese Branta bernicla bernicla in spring while others are avoided. This salt marsh is an important spring staging site for the geese. Sufficient energy storage in a short period is critical to enable their northward migration to Siberia and subsequent reproduction. We test if geese prefer plants that balance their internal osmotic potential with the saline environment through energy‐rich soluble sugars over plant species that use (compartmentalized) salts for this. We find that plant nitrogen and acid detergent fiber content, classic predictors of herbivore preferences, poorly explain which plants the geese prefer. Instead, plant species that are highly preferred by the geese adapt to salinity by high soluble sugar concentrations while avoided species do this by high plant salt concentrations. Thus, the type of osmoregulatory adaptation to stress displayed by different plant species is a good predictor for the food preference of geese on this salt marsh. We suggest that variation in other types of osmoregulation‐based stress adaptations, as plant cold adaptations in tundras and plant drought adaptations in savannas, have similar important consequences for trophic interactions.     

Effect of experimental gingivitis induction and erythritol on the salivary metabolome and functional biochemistry of systemically healthy young adults

Introduction

Understanding the changes occurring in the oral ecosystem during development of gingivitis could help improve prevention and treatment strategies for oral health. Erythritol is a non-caloric polyol proposed to have beneficial effects on oral health.

Objectives

To examine the effect of experimental gingivitis and the effect of erythritol on the salivary metabolome and salivary functional biochemistry.

Methods

In a two-week experimental gingivitis challenge intervention study, non-targeted, mass spectrometry-based metabolomic profiling was performed on saliva samples from 61 healthy adults, collected at five time-points. The effect of erythritol was studied in a randomized, controlled trial setting. Fourteen salivary biochemistry variables were measured with antibody- or enzymatic activity-based assays.

Results

Bacterial amino acid catabolites (cadaverine, N-acetylcadaverine, and α-hydroxyisovalerate) and end-products of bacterial alkali-producing pathways (N-α-acetylornithine and γ-aminobutyrate) increased significantly during the experimental gingivitis. Significant changes were found in a set of 13 salivary metabolite ratios composed of host cell membrane lipids involved in cell signaling, host responses to bacteria, and defense against free radicals. An increase in mevalonate was also observed. There were no significant effects of erythritol. No significant changes were found in functional salivary biochemistry.

Conclusions

The findings underline a dynamic interaction between the host and the oral microbial biofilm during an experimental induction of gingivitis.

     

Proteomic Profiling of Mouse Helper T Cell Differentiation

Helper T cell differentiation is a key process in the regulation of adaptive immune responses. Here, mouse Th1 and Th2 cells are profiled using high‐throughput proteomics to increase the understanding of the molecular biology of Th differentiation to support the design of prophylactic and therapeutic intervention strategies for (infectious) diseases. Protein profiling of Th1/Th2 differentiated cells results in the quantification of almost 6000 proteins of which 41 are differentially expressed at FDR < 0.1, and 19 at the FDR < 0.05 level, respectively. Differential protein expression analysis identifies a number of the expected canonical Th differentiation markers, and gene set analysis using the REACTOME database and a hypergeometric test (FDR < 0.05) confirms that helper T cell pathways are the top sets that are differentially expressed. Additionally, by network analysis, many differentially expressed proteins are associated with the Th1 and Th2 pathways. Data are available via PRIDE database with identifier PXD004532.     

Single introductions of soil biota and plants generate long‐term legacies in soil and plant community assembly

Recent demonstrations of the role of plant–soil biota interactions have challenged the conventional view that vegetation changes are mainly driven by changing abiotic conditions. However, while this concept has been validated under natural conditions, our understanding of the long‐term consequences of plant–soil interactions for above‐belowground community assembly is restricted to mathematical and conceptual model projections. Here, we demonstrate experimentally that one‐time additions of soil biota and plant seeds alter soil‐borne nematode and plant community composition in semi‐natural grassland for 20 years. Over time, aboveground and belowground community composition became increasingly correlated, suggesting an increasing connectedness of soil biota and plants. We conclude that the initial composition of not only plant communities, but also soil communities has a long‐lasting impact on the trajectory of community assembly.