CENTER OF PRESSURE AND JOINT TORQUE ESTIMATION FOR SINGLE LEG SLACKLINE BALANCING USING MODEL-BASED OPTIMIZATION

Being similar to tightrope walking, slacklining has become very popular among athletes and physiotherapists to practice and improve balancing capabilities. For flat ground static balance the center of pressure is often used to quantify how stable a subject is. In this work we present a method to reconstruct the center of pressure and the joint torques from pure motion capture data for motions that don’t allow for force plate measurements. We demonstrate the application to a subject balancing on a slackline. We create a subject-specific 3D-model and perform a least-squares fit to the recorded reference motion by formulation and solution of an optimal control problem. From the resulting forces we can reconstruct the center of pressure dynamics and quantify how stable the subject is on a slackline. The joint torques allow for further insight into the balancing strategies applied

An fMRI study

Background Maternal sensitive behavior depends on recognizing one’s own child’s affective states. The present study investigated distinct and overlapping neural responses of mothers to sad and happy facial expressions of their own child (in comparison to facial expressions of an unfamiliar child). Methods We used functional MRI to measure dissociable and overlapping activation patterns in 27 healthy mothers in response to happy, neutral and sad facial expressions of their own school-aged child and a gender- and age- matched unfamiliar child. To investigate differential activation to sad compared to happy faces of one’s own child, we used interaction contrasts. During the scan, mothers had to indicate the affect of the presented face. After scanning, they were asked to rate the perceived emotional arousal and valence levels for each face using a 7-point Likert-scale (adapted SAM version). Results While viewing their own child’s sad faces, mothers showed activation in the amygdala and anterior cingulate cortex whereas happy facial expressions of the own child elicited activation in the hippocampus. Conjoint activation in response to one’s own child happy and sad expressions was found in the insula and the superior temporal gyrus. Conclusions Maternal brain activations differed depending on the child’s affective state. Sad faces of the own child activated areas commonly associated with a threat detection network, whereas happy faces activated reward related brain areas. Overlapping activation was found in empathy related networks. These distinct neural activation patterns might facilitate sensitive maternal behavior

Efecto de la recuperación nutricia en la concentración sérica de lipoperoxidos en niños con desnutrición proteínico-energética primaria grave.

Objective. The purpose is to show lipid peroxide’s serum concentration trend during a four-week nutritional recovery period in children with primary and severe protein energy malnutrition (PEM). Methods. In a clinical intervention 12 primarily and severely malnourished children (three to 48 months of age) were included. Dependent variable: Serum lipid peroxide (LPO) concentration (nmol/mL). Independent variables: non lactose starting infant formula (200 kcal/kg/d and proteins 4 g/kg/d). Age, sex, nutritional recovery, weight/age, length/age and weight/length indices calculated and expressed as Z scores were included. For statistical analysis a repeated measure ANOVA model was applied. A non-parametric Mann Whitney U-Test was used to compare groups. Null hypothesis was rejected with a p value 0.05. Results. Throughout the study the LPO concentration was higher in subjects with PEM than in the control group (p< 0.001). There was a decrease in the LPO concentration (nmol/mL) between basal vs. two weeks (12.9 vs. 7.3, p = 0.06) and basal vs. four weeks (12.9 vs. 8.16, p = 0.08). Conclusion. LPO concentrations were significantly higher in children with severe PEM at the beginning and end of the four-week nutritional recovery period. This finding was probably associated with increased metabolism of the cellular tissue and/or the high consumption of energy and nutrients compared to a control group. The null hypothesis of basal-end differences in LPO serum concentrations could not be rejected due to the great variability in serum lipoperoxides in these children with severe primary proteinenergy malnutrition

Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events

The crystal structure of an ‘All Locked’ nucleic acid duplex

‘Locked nucleic acids’ (LNAs) are known to introduce enhanced bio- and thermostability into natural nucleic acids rendering them powerful tools for diagnostic and therapeutic applications. We present the 1.9 Å X-ray structure of an ‘all LNA’ duplex containing exclusively modified β-d-2′-O-4′C-methylene ribofuranose nucleotides. The helix illustrates a new type of nucleic acid geometry that contributes to the understanding of the enhanced thermostability of LNA duplexes. A notable decrease of several local and overall helical parameters like twist, roll and propeller twist influence the structure of the LNA helix and result in a widening of the major groove, a decrease in helical winding and an enlarged helical pitch. A detailed structural comparison to the previously solved RNA crystal structure with the corresponding base pair sequence underlines the differences in conformation. The surrounding water network of the RNA and the LNA helix shows a similar hydration pattern

Results from a Large, Multinational Sample Using the Childhood Trauma Questionnaire

Childhood maltreatment has diverse, lifelong impact on morbidity and mortality. The Childhood Trauma Questionnaire (CTQ) is one of the most commonly used scales to assess and quantify these experiences and their impact. Curiously, despite very widespread use of the CTQ, scores on its Minimization-Denial (MD) subscale—originally designed to assess a positive response bias—are rarely reported. Hence, little is known about this measure. If response biases are either common or consequential, current practices of ignoring the MD scale deserve revision. Therewith, we designed a study to investigate 3 aspects of minimization, as defined by the CTQ’s MD scale: 1) its prevalence; 2) its latent structure; and finally 3) whether minimization moderates the CTQ’s discriminative validity in terms of distinguishing between psychiatric patients and community volunteers. Archival, item-level CTQ data from 24 multinational samples were combined for a total of 19,652 participants. Analyses indicated: 1) minimization is common; 2) minimization functions as a continuous construct; and 3) high MD scores attenuate the ability of the CTQ to distinguish between psychiatric patients and community volunteers. Overall, results suggest that a minimizing response bias—as detected by the MD subscale—has a small but significant moderating effect on the CTQ’s discriminative validity. Results also may suggest that some prior analyses of maltreatment rates or the effects of early maltreatment that have used the CTQ may have underestimated its incidence and impact. We caution researchers and clinicians about the widespread practice of using the CTQ without the MD or collecting MD data but failing to assess and control for its effects on outcomes or dependent variables

Reviews and syntheses:Remotely sensed optical time series for monitoring vegetation productivity

International audienceAbstract. Vegetation productivity is a critical indicator of global ecosystem health and is impacted by human activities and climate change. A wide range of optical sensing platforms, from ground-based to airborne and satellite, provide spatially continuous information on terrestrial vegetation status and functioning. As optical Earth observation (EO) data are usually routinely acquired, vegetation can be monitored repeatedly over time; reflecting seasonal vegetation patterns and trends in vegetation productivity metrics. Such metrics include e.g., gross primary productivity, net primary productivity, biomass or yield. To summarize current knowledge, in this paper, we systematically reviewed time series (TS) literature for assessing state-of-the-art vegetation productivity monitoring approaches for different ecosystems based on optical remote sensing (RS) data. As the integration of solar-induced fluorescence (SIF) data in vegetation productivity processing chains has emerged as a promising source, we also include this relatively recent sensor modality. We define three methodological categories to derive productivity metrics from remotely sensed TS of vegetation indices or quantitative traits: (i) trend analysis and anomaly detection, (ii) land surface phenology, and (iii) integration and assimilation of TS-derived metrics into statistical and process-based dynamic vegetation models (DVM). Although the majority of used TS data streams originate from data acquired from satellite platforms, TS data from aircraft and unoccupied aerial vehicles have found their way into productivity monitoring studies. To facilitate processing, we provide a list of common toolboxes for inferring productivity metrics and information from TS data. We further discuss validation strategies of the RS-data derived productivity metrics: (1) using in situ measured data, such as yield, (2) sensor networks of distinct sensors, including spectroradiometers, flux towers, or phenological cameras, and (3) inter-comparison of different productivity products or modelled estimates. Finally, we address current challenges and propose a conceptual framework for productivity metrics derivation, including fully-integrated DVMs and radiative transfer models here labelled as "Digital Twin". This novel framework meets the requirements of multiple ecosystems and enables both an improved understanding of vegetation temporal dynamics in response to climate and environmental drivers and also enhances the accuracy of vegetation productivity monitoring

Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity

Vegetation productivity is a critical indicator of global ecosystem health and is impacted by human activities and climate change. A wide range of optical sensing platforms, from ground-based to airborne and satellite, provide spatially continuous information on terrestrial vegetation status and functioning. As optical Earth observation (EO) data are usually routinely acquired, vegetation can be monitored repeatedly over time, reflecting seasonal vegetation patterns and trends in vegetation productivity metrics. Such metrics include gross primary productivity, net primary productivity, biomass, or yield. To summarize current knowledge, in this paper we systematically reviewed time series (TS) literature for assessing state-of-the-art vegetation productivity monitoring approaches for different ecosystems based on optical remote sensing (RS) data. As the integration of solar-induced fluorescence (SIF) data in vegetation productivity processing chains has emerged as a promising source, we also include this relatively recent sensor modality. We define three methodological categories to derive productivity metrics from remotely sensed TS of vegetation indices or quantitative traits: (i) trend analysis and anomaly detection, (ii) land surface phenology, and (iii) integration and assimilation of TS-derived metrics into statistical and process-based dynamic vegetation models (DVMs). Although the majority of used TS data streams originate from data acquired from satellite platforms, TS data from aircraft and unoccupied aerial vehicles have found their way into productivity monitoring studies. To facilitate processing, we provide a list of common toolboxes for inferring productivity metrics and information from TS data. We further discuss validation strategies of the RS data derived productivity metrics: (1) using in situ measured data, such as yield; (2) sensor networks of distinct sensors, including spectroradiometers, flux towers, or phenological cameras; and (3) inter-comparison of different productivity metrics. Finally, we address current challenges and propose a conceptual framework for productivity metrics derivation, including fully integrated DVMs and radiative transfer models here labelled as “Digital Twin”. This novel framework meets the requirements of multiple ecosystems and enables both an improved understanding of vegetation temporal dynamics in response to climate and environmental drivers and enhances the accuracy of vegetation productivity monitoring