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Background
This cluster-randomised monocentric controlled trial focuses on improving the uptake symptoms of mental health care in adolescents with chronic medical conditions who have been identified by screening to have depression or anxiety. The study aims to determine the efficacy of motivational interviewing (MI) delivered by trained physicians to increase 12- to 20-year-old adolescents’ utilisation of psychological health care for symptoms of anxiety or depression.
Methods/design
In this single-centre approach, n = 1,000 adolescents will be screened (using PHQ-9 and GAD-7), and adolescents with results indicative of anxiety or depressive symptoms (n = 162) will be advised to seek psychological health care in clusters from treating physicians in specialised outpatient departments. Participants who screen positive will receive either two sessions of MI or treatment as usual (TAU; regarded as the typical daily clinical practice), which is focused on recommending them to seek psychological health care for further evaluation. MI efficacy will be compared to the current TAU as the control condition. The primary outcome is the utilisation rate of psychological health care after counselling by an MI-trained physician vs. an untrained physician. Additionally, reasons for not claiming psychological support and changes in disease-related parameters will be evaluated in a 6-month follow-up session.
Discussion
This trial will evaluate the feasibility of MI as a way to improve the utilisation of mental health-care services by adolescents who need further support other than that provided by standard care for chronic diseases. Physicians offering MI to adolescents may serve as a model for optimising health-care management in daily clinical practice, which may improve adolescents’ long-term well-being by improving adherence to medical treatment and preventing negative lifelong consequences into adulthood.
During sentence reading, low spatial frequency information afforded by spaces between words is the primary factor for eye guidance in spaced writing systems, whereas saccade generation for unspaced writing systems is less clear and under debate. In the present study, we investigated whether word-boundary information, provided by alternating colors (consistent or inconsistent with word-boundary information) influences saccade-target selection in Chinese. In Experiment 1, as compared to a baseline (i.e., uniform color) condition, word segmentation with alternating color shifted fixation location towards the center of words. In contrast, incorrect word segmentation shifted fixation location towards the beginning of words. In Experiment 2, we used a gaze-contingent paradigm to restrict the color manipulation only to the upcoming parafoveal words and replicated the results, including fixation location effects, as observed in Experiment 1. These results indicate that Chinese readers are capable of making use of parafoveal word-boundary knowledge for saccade generation, even if such information is unfamiliar to them. The present study provides novel support for the hypothesis that word segmentation is involved in the decision about where to fixate next during Chinese reading.
Word recognition in sentence reading is influenced by information from both preview and context. Recently, semantic preview effect (SPE) was observed being modulated by the constraint of context, indicating that context might accelerate the processing of semantically related preview words. Besides, SPE was found to depend on preview time, which suggests that SPE may change with different processing stages of preview words. Therefore, it raises the question of whether preview time-dependent SPE would be modulated by contextual constraint. In this study, we not only investigated the impact of contextual constraint on SPE in Chinese reading but also examined its dependency on preview time. The preview word and the target word were identical, semantically related or unrelated to the target word. The results showed a significant three-way interaction: The SPE depended on contextual constraint and preview time. In separate analyses for low and high contextual constraint of target words, the SPE significantly decreased with an increase in preview duration when the target word was of low constraint in the sentence. The effect was numerically in the same direction but weaker and statistically nonsignificant when the target word was highly constrained in the sentence. The results indicate that word processing in sentences is a dynamic process of integrating information from both preview (bottom-up) and context (top-down).
Leaf senescence is an essential developmental process that involves diverse metabolic changes associated with degradation of macromolecules allowing nutrient recycling and remobilization. In contrast to the significant progress in transcriptomic analysis of leaf senescence, metabolomics analyses have been relatively limited. A broad overview of metabolic changes during leaf senescence including the interactions between various metabolic pathways is required to gain a better understanding of the leaf senescence allowing to link transcriptomics with metabolomics and physiology. In this chapter, we describe how to obtain comprehensive metabolite profiles and how to dissect metabolic shifts during leaf senescence in the model plant Arabidopsis thaliana. Unlike nucleic acid analysis for transcriptomics, a comprehensive metabolite profile can only be achieved by combining a suite of analytic tools. Here, information is provided for measurements of the contents of chlorophyll, soluble proteins, and starch by spectrophotometric methods, ions by ion chromatography, thiols and amino acids by HPLC, primary metabolites by GC/TOF-MS, and secondary metabolites and lipophilic metabolites by LC/ESI-MS. These metabolite profiles provide a rich catalogue of metabolic changes during leaf senescence, which is a helpful database and blueprint to be correlated to future studies such as transcriptome and proteome analyses, forward and reverse genetic studies, or stress-induced senescence studies.
Metabolism is a key determinant of plant growth and modulates plant adaptive responses. Increased metabolic variation due to heterozygosity may be beneficial for highly homozygous plants if their progeny is to respond to sudden changes in the habitat. Here, we investigate the extent to which heterozygosity contributes to the variation in metabolism and size of hybrids of Arabidopsis thaliana whose parents are from a single growth habitat. We created full diallel crosses among seven parents, originating from Southern Germany, and analysed the inheritance patterns in primary and secondary metabolism as well as in rosette size in situ. In comparison to primary metabolites, compounds from secondary metabolism were more variable and showed more pronounced non-additive inheritance patterns which could be attributed to epistasis. In addition, we showed that glucosinolates, among other secondary metabolites, were positively correlated with a proxy for plant size. Therefore, our study demonstrates that heterozygosity in local A. thaliana population generates metabolic variation and may impact several tasks directly linked to metabolism.
The desiccation-tolerant plant Haberlea rhodopensis can withstand months of darkness without any visible senescence. Here, we investigated the molecular mechanisms of this adaptation to prolonged (30 d) darkness and subsequent return to light. H. rhodopensis plants remained green and viable throughout the dark treatment. Transcriptomic analysis revealed that darkness regulated several transcription factor (TF) genes. Stress-and autophagy-related TFs such as ERF8, HSFA2b, RD26, TGA1, and WRKY33 were up-regulated, while chloroplast-and flowering-related TFs such as ATH1, COL2, COL4, RL1, and PTAC7 were repressed. PHYTOCHROME INTERACTING FACTOR4, a negative regulator of photomorphogenesis and promoter of senescence, also was down-regulated. In response to darkness, most of the photosynthesis-and photorespiratory-related genes were strongly down-regulated, while genes related to autophagy were up-regulated. This occurred concomitant with the induction of SUCROSE NON-FERMENTING1-RELATED PROTEIN KINASES (SnRK1) signaling pathway genes, which regulate responses to stress-induced starvation and autophagy. Most of the genes associated with chlorophyll catabolism, which are induced by darkness in dark-senescing species, were either unregulated (PHEOPHORBIDE A OXYGENASE, PAO; RED CHLOROPHYLL CATABOLITE REDUCTASE, RCCR) or repressed (STAY GREEN-LIKE, PHEOPHYTINASE, and NON-YELLOW COLORING1). Metabolite profiling revealed increases in the levels of many amino acids in darkness, suggesting increased protein degradation. In darkness, levels of the chloroplastic lipids digalactosyldiacylglycerol, monogalactosyldiacylglycerol, phosphatidylglycerol, and sulfoquinovosyldiacylglycerol decreased, while those of storage triacylglycerols increased, suggesting degradation of chloroplast membrane lipids and their conversion to triacylglycerols for use as energy and carbon sources. Collectively, these data show a coordinated response to darkness, including repression of photosynthetic, photorespiratory, flowering, and chlorophyll catabolic genes, induction of autophagy and SnRK1 pathways, and metabolic reconfigurations that enable survival under prolonged darkness.
Leaf senescence is an essential physiological process in plants that supports the recycling of nitrogen and other nutrients to support the growth of developing organs, including young leaves, seeds, and fruits. Thus, the regulation of senescence is crucial for evolutionary success in wild populations and for increasing yield in crops. Here, we describe the influence of a NAC transcription factor, SlNAP2 (Solanum lycopersicum NAC-like, activated by Apetala3/Pistillata), that controls both leaf senescence and fruit yield in tomato (S. lycopersicum). SlNAP2 expression increases during age-dependent and dark-induced leaf senescence. We demonstrate that SlNAP2 activates SlSAG113 (S. lycopersicum SENESCENCE-ASSOCIATED GENE113), a homolog of Arabidopsis (Arabidopsis thaliana) SAG113, chlorophyll degradation genes such as SlSGR1 (S. lycopersicum senescence-inducible chloroplast stay-green protein 1) and SlPAO (S. lycopersicum pheide a oxygenase), and other downstream targets by directly binding to their promoters, thereby promoting leaf senescence. Furthermore, SlNAP2 directly controls the expression of genes important for abscisic acid (ABA) biosynthesis, S. lycopersicum 9-cis-epoxycarotenoid dioxygenase 1 (SlNCED1); transport, S. lycopersicum ABC transporter G family member 40 (SlABCG40); and degradation, S. lycopersicum ABA 8′-hydroxylase (SlCYP707A2), indicating that SlNAP2 has a complex role in establishing ABA homeostasis during leaf senescence. Inhibiting SlNAP2 expression in transgenic tomato plants impedes leaf senescence but enhances fruit yield and sugar content likely due to prolonged leaf photosynthesis in aging tomato plants. Our data indicate that SlNAP2 has a central role in controlling leaf senescence and fruit yield in tomato.
Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of local structures and roads. We employed neutron transport simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that roads introduce a substantial bias in the CRNS estimation of field soil moisture compared to off-road scenarios. However, this effect becomes insignificant at distances beyond a few meters from the road. Neutron measurements on the road could overestimate the field value by up to 40 % depending on road material, width, and the surrounding field water content. The bias could be largely removed with an analytical correction function that accounts for these parameters. Additionally, an empirical approach is proposed that can be used without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between road-effect corrected measurements and field soil moisture observations. However, if knowledge about the road characteristics is missing, measurements on the road could substantially reduce the accuracy of this method. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture. Plain Language Summary Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of roads. We employed physics simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that the presence of roads biased the CRNS estimation of field soil moisture compared to nonroad scenarios. Neutron measurements could overestimate the field value by up to 40 % depending on road material, width, surrounding field water content, and distance from the road. We proposed a correction function that successfully removed this bias and works even without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between corrected measurements and other field soil moisture observations. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture.
Cosmic-ray neutron sensing (CRNS) is a promising proximal soil sensing technique to estimate soil moisture at intermediate scale and high temporal resolution. However, the signal shows complex and non-unique response to all hydrogen pools near the land surface, providing some challenges for soil moisture estimation in practical applications. Aims of the study were 1) to assess the uncertainty of CRNS as a stand-alone approach to estimate volumetric soil moisture in cropped field 2) to identify the causes of this uncertainty 3) and possible improvements. Two experimental sites in Germany were equipped with a CRNS probe and point-scale soil moisture network. Additional monitoring activities were conducted during the crop growing season to characterize the soil-plant systems. This data is used to identify and quantify the different sources of uncertainty (factors). An uncertainty analysis, based on Monte Carlo approach, is applied to propagate these uncertainties to CRNS soil moisture estimations. In addition, a sensitivity analysis based on the Sobol’ method is performed to identify the most important factors explaining this uncertainty. Results show that CRNS soil moisture compares well to the soil moisture network when these point-scale values are weighted to account for the spatial sensitivity of the signal and other sources of hydrogen (lattice water and organic carbon) are added to the water content. However, the performance decreases when CRNS is considered as a stand-alone method to retrieve the actual (non-weighted) volumetric soil moisture. The support volume (penetration depth and radius) shows also a considerable uncertainty, especially in relatively dry soil moisture conditions. Four of the seven factors analyzed (the vertical soil moisture profile, bulk density, incoming neutron correction and the calibrated parameter N0) were found to play an important role. Among the possible improvements identified, a simple correction factor based on vertical point-scale soil moisture profiles shows to be a promising approach to account for the sensitivity of the CRNS signal to the upper soil layers.
Leaf senescence is a key process in plants that culminates in the degradation of cellular constituents and massive reprogramming of metabolism for the recovery of nutrients from aged leaves for their reuse in newly developing sinks. We used molecular-biological and metabolomics approaches to identify NAC transcription factor (TF) RD26 as an important regulator of metabolic reprogramming in Arabidopsis thaliana. RD26 directly activates CHLOROPLAST VESICULATION (CV), encoding a protein crucial for chloroplast protein degradation, concomitant with an enhanced protein loss in RD26 over-expressors during senescence, but a reduced decline of protein in rd26 knockout mutants. RD26 also directly activates LKR/SDH involved in lysine catabolism, and PES1 important for phytol degradation. Metabolic profiling revealed reduced c-aminobutyric acid (GABA) in RD26 overexpressors, accompanied by the induction of respective catabolic genes. Degradation of lysine, phytol and GABA is instrumental for maintaining mitochondrial respiration in carbon-limiting conditions during senescence. RD26 also supports the degradation of starch and the accumulation of mono-and disaccharides during senescence by directly enhancing the expression of AMY1, SFP1 and SWEET15 involved in carbohydrate metabolism and transport. Collectively, during senescence RD26 acts by controlling the expression of genes across the entire spectrum of the cellular degradation hierarchy.
Taking into account the climatic conditions of the semiarid region of Brazil, with its intermittent rivers and long periods of water scarcity, a dense network of surface reservoirs (on average one dam every 5 km(2)) of very different sizes has been built. The impact of such a network on water and sediment dynamics constitutes a remarkable challenge for hydrologists. The main objective of this work is to present a novel way of simulating water and sediment fluxes through such high-density reservoir networks, which enables the assessment of water and sediment retention in those structures. The new reservoir modeling approach has been coupled with the fully process-oriented and semidistributed hydrological WASA-SED model, which was tailored for semiarid hydroclimatological characteristics. This integrated modeling system was applied to the 933-km(2) Bengue catchment, located in semiarid northeastern Brazil, which has a network of 114 reservoirs with a wide range of surface areas (from 0.003 to 350 ha). The small reservoirs were grouped into size classes according to their storage capacity and a cascade routing scheme was applied to describe the upstream-downstream position of the classes; the large reservoirs were handled explicitly in the reservoir modeling approach. According to the model results, the proposed approach is capable of representing the water and sediment fluxes though the entire reservoir network with reasonable accuracy. In addition, the model shows that the dynamics of water and sediment within the Bengue catchment are strongly impacted by the presence of multiple reservoirs, which are able to retain approximately 21% of the generated runoff and almost 42% of the sediment yield of the catchment for the simulation period, from 2000 to 2012. (C) 2018 American Society of Civil Engineers.
Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment
(2018)
Sensor-to-sensor variability is a source of error common to all geoscientific instruments that needs to be assessed before comparative and applied research can be performed with multiple sensors. Consistency among sensor systems is especially critical when subtle features of the surrounding terrain are to be identified. Cosmic-ray neutron sensors (CRNSs) are a recent technology used to monitor hectometre-scale environmental water storages, for which a rigorous comparison study of numerous co-located sensors has not yet been performed. In this work, nine stationary CRNS probes of type "CRS1000" were installed in relative proximity on a grass patch surrounded by trees, buildings, and sealed areas. While the dynamics of the neutron count rates were found to be similar, offsets of a few percent from the absolute average neutron count rates were found. Technical adjustments of the individual detection parameters brought all instruments into good agreement. Furthermore, we found a critical integration time of 6 h above which all sensors showed consistent dynamics in the data and their RMSE fell below 1% of gravimetric water content. The residual differences between the nine signals indicated local effects of the complex urban terrain on the scale of several metres. Mobile CRNS measurements and spatial simulations with the URANOS neutron transport code in the surrounding area (25 ha) have revealed substantial sub-footprint heterogeneity to which CRNS detectors are sensitive despite their large averaging volume. The sealed and constantly dry structures in the footprint furthermore damped the dynamics of the CRNS-derived soil moisture. We developed strategies to correct for the sealed-area effect based on theoretical insights about the spatial sensitivity of the sensor. This procedure not only led to reliable soil moisture estimation during dry-out periods, it further revealed a strong signal of intercepted water that emerged over the sealed surfaces during rain events. The presented arrangement offered a unique opportunity to demonstrate the CRNS performance in complex terrain, and the results indicated great potential for further applications in urban climate research.
Mold fungi on malting barley grains cause major economic loss in malting and brewery facilities. Possible proxies for their detection are volatile and semivolatile metabolites. Among those substances, characteristic marker compounds have to be identified for a confident detection of mold fungi in varying surroundings. The analytical determination is usually performed through passive sampling with solid phase microextraction, gas chromatographic separation, and detection by electron ionization mass spectrometry (EI-MS), which often does not allow a confident determination due to the absence of molecular ions. An alternative is GC-APCI-MS, generally, allowing the determination of protonated molecular ions. Commercial atmospheric pressure chemical ionization (APCI) sources are based on corona discharges, which are often unspecific due to the occurrence of several side reactions and produce complex product ion spectra. To overcome this issue, an APCI source based on soft X-radiation is used here. This source facilitates a more specific ionization by proton transfer reactions only. In the first part, the APCI source is characterized with representative volatile fungus metabolites. Depending on the proton affinity of the metabolites, the limits of detection are up to 2 orders of magnitude below those of EI-MS. In the second part, the volatile metabolites of the mold fungus species Aspergillus, Alternaria, Fusarium, and Penicillium are investigated. In total, 86 compounds were found with GC-EI/APCI-MS. The metabolites identified belong to the substance classes of alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, terpenes, and sesquiterpenes. In addition to substances unspecific for the individual fungus species, characteristic patterns of metabolites, allowing their confident discrimination, were found for each of the 4 fungus species. Sixty-seven of the 86 metabolites are detected by X-ray-based APCI-MS alone. The discrimination of the fungus species based on these metabolites alone was possible. Therefore, APCI-MS in combination with collision induced dissociation alone could be used as a supervision method for the detection of mold fungi.
One of the main purposes of detrital thermochronology is to provide constraints on the regional-scale exhumation rate and its spatial variability in actively eroding mountain ranges. Procedures that use cooling age distributions coupled with hypsometry and thermal models have been developed in order to extract quantitative estimates of erosion rate and its spatial distribution, assuming steady state between tectonic uplift and erosion. This hypothesis precludes the use of these procedures to assess the likely transient response of mountain belts to changes in tectonic or climatic forcing. Other methods are based on an a priori knowledge of the in situ distribution of ages to interpret the detrital age distributions. In this paper, we describe a simple method that, using the observed detrital mineral age distributions collected along a river, allows us to extract information about the relative distribution of erosion rates in an eroding catchment without relying on a steady-state assumption, the value of thermal parameters or an a priori knowledge of in situ age distributions. The model is based on a relatively low number of parameters describing lithological variability among the various sub-catchments and their sizes and only uses the raw ages. The method we propose is tested against synthetic age distributions to demonstrate its accuracy and the optimum conditions for it use. In order to illustrate the method, we invert age distributions collected along the main trunk of the Tsangpo-Siang-Brahmaputra river system in the eastern Himalaya. From the inversion of the cooling age distributions we predict present-day erosion rates of the catchments along the Tsangpo-Siang-Brahmaputra river system, as well as some of its tributaries. We show that detrital age distributions contain dual information about present-day erosion rate, i. e., from the predicted distribution of surface ages within each catchment and from the relative contribution of any given catchment to the river distribution. The method additionally allows comparing modern erosion rates to long-term exhumation rates. We provide a simple implementation of the method in Python code within a Jupyter Notebook that includes the data used in this paper for illustration purposes.
Achieving the highest power conversion efficiencies in bulk heterojunction organic solar cells requires a morphology that delivers electron and hole percolation pathways for optimized transport, plus sufficient donor:acceptor contact area for near unity charge transfer state formation. This is a significant structural challenge, particularly in semiconducting polymer:fullerene systems. This balancing act in the model high efficiency PTB7:PC70BM blend is studied by tuning the donor:acceptor ratio, with a view to understanding the recombination loss mechanisms above and below the fullerene transport percolation threshold. The internal quantum efficiency is found to be strongly correlated to the slower carrier mobility in agreement with other recent studies. Furthermore, second-order recombination losses dominate the shape of the current density-voltage curve in efficient blend combinations, where the fullerene phase is percolated. However, below the charge transport percolation threshold, there is an electric-field dependence of first-order losses, which includes electric-field-dependent photogeneration. In the intermediate regime, the fill factor appears to be limited by both first- and second-order losses. These findings provide additional basic understanding of the interplay between the bulk heterojunction morphology and the order of recombination in organic solar cells. They also shed light on the limitations of widely used transport models below the percolation threshold.
Engineering the interface between the perovskite absorber and the charge-transporting layers has become an important method for improving the charge extraction and open-circuit voltage (V-OC) of hybrid perovskite solar cells. Conjugated polymers are particularly suited to form the hole-transporting layer, but their hydrophobicity renders it difficult to solution-process the perovskite absorber on top. Herein, oxygen plasma treatment is introduced as a simple means to change the surface energy and work function of hydrophobic polymer interlayers for use as p-contacts in perovskite solar cells. We find that upon oxygen plasma treatment, the hydrophobic surfaces of different prototypical p-type polymers became sufficiently hydrophilic to enable subsequent perovskite junction processing. In addition, the oxygen plasma treatment also increased the ionization potential of the polymer such that it became closer to the valance band energy of the perovskite. It was also found that the oxygen plasma treatment could increase the electrical conductivity of the p-type polymers, facilitating more efficient charge extraction. On the basis of this concept, inverted MAPbI(3) perovskite devices with different oxygen plasma-treated polymers such as P3HT, P3OT, polyTPD, or PTAA were fabricated with power conversion efficiencies of up to 19%.
Perovskite solar cells (PSCs) are currently one of the most promising photovoltaic technologies for highly efficient and cost-effective solar energy production. In only a few years, an unprecedented progression of preparation procedures and material compositions delivered lab-scale devices that have now reached record power conversion efficiencies (PCEs) higher than 20%, competing with most established solar cell materials such as silicon, CIGS, and CdTe. However, despite a large number of researchers currently involved in this topic, only a few groups in the world can reproduce >20% efficiencies on a regular n-i-p architecture. In this work, we present detailed protocols for preparing PSCs in regular (n-i-p) and inverted (p-i-n) architectures with >= 20% PCE. We aim to provide a comprehensive, reproducible description of our device fabrication , protocols. We encourage the practice of reporting detailed and transparent protocols that can be more easily reproduced by other laboratories. A better reporting standard may, in turn, accelerate the development of perovskite solar cells and related research fields.
The performance of perovskite solar cells is predominantly limited by non-radiative recombination, either through trap-assisted recombination in the absorber layer or via minority carrier recombination at the perovskite/transport layer interfaces. Here, we use transient and absolute photoluminescence imaging to visualize all non-radiative recombination pathways in planar pintype perovskite solar cells with undoped organic charge transport layers. We find significant quasi-Fermi-level splitting losses (135 meV) in the perovskite bulk, whereas interfacial recombination results in an additional free energy loss of 80 meV at each individual interface, which limits the open-circuit voltage (V-oc) of the complete cell to similar to 1.12 V. Inserting ultrathin interlayers between the perovskite and transport layers leads to a substantial reduction of these interfacial losses at both the p and n contacts. Using this knowledge and approach, we demonstrate reproducible dopant-free 1 cm(2) perovskite solar cells surpassing 20% efficiency (19.83% certified) with stabilized power output, a high V-oc (1.17 V) and record fill factor (>81%).
Background: Core-specific sensorimotor exercises are proven to enhance neuromuscular activity of the trunk, improve athletic performance and prevent back pain. However, the dose-response relationship and, therefore, the dose required to improve trunk function is still under debate. The purpose of the present trial will be to compare four different intervention strategies of sensorimotor exercises that will result in improved trunk function.
Methods/design: A single-blind, four-armed, randomized controlled trial with a 3-week (home-based) intervention phase and two measurement days pre and post intervention (M1/M2) is designed. Experimental procedures on both measurement days will include evaluation of maximum isokinetic and isometric trunk strength (extension/flexion, rotation) including perturbations, as well as neuromuscular trunk activity while performing strength testing. The primary outcome is trunk strength (peak torque). Neuromuscular activity (amplitude, latencies as a response to perturbation) serves as secondary outcome. The control group will perform a standardized exercise program of four sensorimotor exercises (three sets of 10 repetitions) in each of six training sessions (30 min duration) over 3 weeks. The intervention groups’ programs differ in the number of exercises, sets per exercise and, therefore, overall training amount (group I: six sessions, three exercises, two sets; group II: six sessions, two exercises, two sets; group III: six sessions, one exercise, three sets). The intervention programs of groups I, II and III include additional perturbations for all exercises to increase both the difficulty and the efficacy of the exercises performed. Statistical analysis will be performed after examining the underlying assumptions for parametric and non-parametric testing.
Discussion: The results of the study will be clinically relevant, not only for researchers but also for (sports) therapists, physicians, coaches, athletes and the general population who have the aim of improving trunk function.
Long-distance race car drivers are classified as athletes. The sport is physically and mentally demanding, requiring long hours of practice. Therefore, optimal dietary intake is essential for health and performance of the athlete. The aim of the study was to evaluate dietary intake and to compare the data with dietary recommendations for athletes and for the general adult population according to the German Nutrition Society (DGE). A 24-h dietary recall during a competition preparation phase was obtained from 16 male race car drivers (28.3 ± 6.1 years, body mass index (BMI) of 22.9 ± 2.3 kg/m2). The mean intake of energy, nutrients, water and alcohol was recorded. The mean energy, vitamin B2, vitamin E, folate, fiber, calcium, water and alcohol intake were 2124 ± 814 kcal/day, 1.3 ± 0.5 mg/day, 12.5 ± 9.5 mg/day, 231.0 ± 90.9 ug/day, 21.4 ± 9.4 g/day, 1104 ± 764 mg/day, 3309 ± 1522 mL/day and 0.8 ± 2.5 mL/day respectively. Our study indicated that many of the nutrients studied, including energy and carbohydrate, were below the recommended dietary intake for both athletes and the DGE.