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Background
Millions of people in Germany suffer from chronic pain, in which course and intensity are multifactorial. Besides physical injuries, certain psychosocial risk factors are involved in the disease process. The national health care guidelines for the diagnosis and treatment of non-specific low back pain recommend the screening of psychosocial risk factors as early as possible, to be able to adapt the therapy to patient needs (e.g., unimodal or multimodal). However, such a procedure has been difficult to implement in practice and has not yet been integrated into the rehabilitation care structures across the country.
Methods
The aim of this study is to implement an individualized therapy and aftercare program within the rehabilitation offer of the German Pension Insurance in the area of orthopedics and to examine its success and sustainability in comparison to the previous standard aftercare program.
The study is a multicenter randomized controlled trial including 1204 patients from six orthopedic rehabilitation clinics. A 2:1 allocation ratio to intervention (individualized and home-based rehabilitation aftercare) versus the control group (regular outpatient rehabilitation aftercare) is set. Upon admission to the rehabilitation clinic, participants in the intervention group will be screened according to their psychosocial risk profile. They could then receive either unimodal or multimodal, together with an individualized training program. The program is instructed in the clinic (approximately 3 weeks) and will continue independently at home afterwards for 3 months. The success of the program is examined by means of a total of four surveys. The co-primary outcomes are the Characteristic Pain Intensity and Disability Score assessed by the German version of the Chronic Pain Grade questionnaire (CPG).
Discussion
An improvement in terms of pain, work ability, patient compliance, and acceptance in our intervention program compared to the standard aftercare is expected. The study contributes to provide individualized care also to patients living far away from clinical centers.
Trial registration
DRKS, DRKS00020373. Registered on 15 April 2020
This study investigates the relationship between teacher quality and teachers’ engagement in professional development (PD) activities using data on 229 German secondary school mathematics teachers. We assessed different aspects of teacher quality (e.g. professional knowledge, instructional quality) using a variety of measures, including standardised tests of teachers’ content knowledge, to determine what characteristics are associated with high participation in PD. The results show that teachers with higher scores for teacher quality variables take part in more content-focused PD than teachers with lower scores for these variables. This suggests that teacher learning may be subject to a Matthew effect, whereby more proficient teachers benefit more from PD than less proficient teachers.
Soziale Medien sind ein wesentlicher Bestandteil des Alltags von Schüler*innen und gleichzeitig zunehmend wichtig in Wirtschaft, Politik und Wissenschaft. Am Beispiel von Twitter zeigt dieser Beitrag, dass soziale Medien im Unterricht auch für die Beantwortung geographischer Fragestellungen verwendet werden können. Hierfür eignen sich Twitter-Daten aufgrund ihrer Georeferenzierung und weiterer interessanter Inhalte besonders. Der Beitrag gibt einen Überblick über die Verwendung von Twitter für sozialwissenschaftliche und humangeographische Fragestellungen und reflektiert die Nutzung von Twitter im Unterricht. Für die Unterrichtspraxis werden Beispiele zu den Themen Braunkohle, Flutereignisse und Raumwahrnehmungen sowie Anleitungen zur Auswertung, Anwendung und Reflexion von Twitter-Analysen vorgestellt.
The increasing development of antibiotic resistance in bacteria has been a major problem for years, both in human and veterinary medicine. Prophylactic measures, such as the use of vaccines, are of great importance in reducing the use of antibiotics in livestock. These vaccines are mainly produced based on formaldehyde inactivation. However, the latter damages the recognition elements of the bacterial proteins and thus could reduce the immune response in the animal. An alternative inactivation method developed in this work is based on gentle photodynamic inactivation using carbon nanodots (CNDs) at excitation wavelengths λex > 290 nm. The photodynamic inactivation was characterized on the nonvirulent laboratory strain Escherichia coli K12 using synthesized CNDs. For a gentle inactivation, the CNDs must be absorbed into the cytoplasm of the E. coli cell. Thus, the inactivation through photoinduced formation of reactive oxygen species only takes place inside the bacterium, which means that the outer membrane is neither damaged nor altered. The loading of the CNDs into E. coli was examined using fluorescence microscopy. Complete loading of the bacterial cells could be achieved in less than 10 min. These studies revealed a reversible uptake process allowing the recovery and reuse of the CNDs after irradiation and before the administration of the vaccine. The success of photodynamic inactivation was verified by viability assays on agar. In a homemade flow photoreactor, the fastest successful irradiation of the bacteria could be carried out in 34 s. Therefore, the photodynamic inactivation based on CNDs is very effective. The membrane integrity of the bacteria after irradiation was verified by slide agglutination and atomic force microscopy. The method developed for the laboratory strain E. coli K12 could then be successfully applied to the important avian pathogens Bordetella avium and Ornithobacterium rhinotracheale to aid the development of novel vaccines.
“Chunking” spoken language
(2021)
In this introductory paper to the special issue on “Weak cesuras in talk-in-interaction”, we aim to guide the reader into current work on the “chunking” of naturally occurring talk. It is conducted in the methodological frameworks of Conversation Analysis and Interactional Linguistics – two approaches that consider the interactional aspect of humans talking with each other to be a crucial starting point for its analysis. In doing so, we will (1) lay out the background of this special issue (what is problematic about “chunking” talk-in-interaction, the characteristics of the methodological approach chosen by the contributors, the cesura model), (2) highlight what can be gained from such a revised understanding of “chunking” in talk-in-interaction by referring to previous work with this model as well as the findings of the contributions to this special issue, and (3) indicate further directions such work could take starting from papers in this special issue. We hope to induce a fruitful exchange on the phenomena discussed, across methodological divides.
Computation of the instantaneous phase and amplitude via the Hilbert Transform is a powerful tool of data analysis. This approach finds many applications in various science and engineering branches but is not proper for causal estimation because it requires knowledge of the signal’s past and future. However, several problems require real-time estimation of phase and amplitude; an illustrative example is phase-locked or amplitude-dependent stimulation in neuroscience. In this paper, we discuss and compare three causal algorithms that do not rely on the Hilbert Transform but exploit well-known physical phenomena, the synchronization and the resonance. After testing the algorithms on a synthetic data set, we illustrate their performance computing phase and amplitude for the accelerometer tremor measurements and a Parkinsonian patient’s beta-band brain activity.
We study the probability density function (PDF) of the first-reaction times between a diffusive ligand and a membrane-bound, immobile imperfect target region in a restricted 'onion-shell' geometry bounded by two nested membranes of arbitrary shapes. For such a setting, encountered in diverse molecular signal transduction pathways or in the narrow escape problem with additional steric constraints, we derive an exact spectral form of the PDF, as well as present its approximate form calculated by help of the so-called self-consistent approximation. For a particular case when the nested domains are concentric spheres, we get a fully explicit form of the approximated PDF, assess the accuracy of this approximation, and discuss various facets of the obtained distributions. Our results can be straightforwardly applied to describe the PDF of the terminal reaction event in multi-stage signal transduction processes.
Quantitative geomorphic research depends on accurate topographic data often collected via remote sensing. Lidar, and photogrammetric methods like structure-from-motion, provide the highest quality data for generating digital elevation models (DEMs). Unfortunately, these data are restricted to relatively small areas, and may be expensive or time-consuming to collect. Global and near-global DEMs with 1 arcsec (∼30 m) ground sampling from spaceborne radar and optical sensors offer an alternative gridded, continuous surface at the cost of resolution and accuracy. Accuracy is typically defined with respect to external datasets, often, but not always, in the form of point or profile measurements from sources like differential Global Navigation Satellite System (GNSS), spaceborne lidar (e.g., ICESat), and other geodetic measurements. Vertical point or profile accuracy metrics can miss the pixel-to-pixel variability (sometimes called DEM noise) that is unrelated to true topographic signal, but rather sensor-, orbital-, and/or processing-related artifacts. This is most concerning in selecting a DEM for geomorphic analysis, as this variability can affect derivatives of elevation (e.g., slope and curvature) and impact flow routing. We use (near) global DEMs at 1 arcsec resolution (SRTM, ASTER, ALOS, TanDEM-X, and the recently released Copernicus) and develop new internal accuracy metrics to assess inter-pixel variability without reference data. Our study area is in the arid, steep Central Andes, and is nearly vegetation-free, creating ideal conditions for remote sensing of the bare-earth surface. We use a novel hillshade-filtering approach to detrend long-wavelength topographic signals and accentuate short-wavelength variability. Fourier transformations of the spatial signal to the frequency domain allows us to quantify: 1) artifacts in the un-projected 1 arcsec DEMs at wavelengths greater than the Nyquist (twice the nominal resolution, so > 2 arcsec); and 2) the relative variance of adjacent pixels in DEMs resampled to 30-m resolution (UTM projected). We translate results into their impact on hillslope and channel slope calculations, and we highlight the quality of the five DEMs. We find that the Copernicus DEM, which is based on a carefully edited commercial version of the TanDEM-X, provides the highest quality landscape representation, and should become the preferred DEM for topographic analysis in areas without sufficient coverage of higher-quality local DEMs.
Background:
Research into the application of virtual reality technology in the health care sector has rapidly increased, resulting in a large body of research that is difficult to keep up with.
Objective:
We will provide an overview of the annual publication numbers in this field and the most productive and influential countries, journals, and authors, as well as the most used, most co-occurring, and most recent keywords.
Methods:
Based on a data set of 356 publications and 20,363 citations derived from Web of Science, we conducted a bibliometric analysis using BibExcel, HistCite, and VOSviewer.
Results:
The strongest growth in publications occurred in 2020, accounting for 29.49% of all publications so far. The most productive countries are the United States, the United Kingdom, and Spain; the most influential countries are the United States, Canada, and the United Kingdom. The most productive journals are the Journal of Medical Internet Research (JMIR), JMIR Serious Games, and the Games for Health Journal; the most influential journals are Patient Education and Counselling, Medical Education, and Quality of Life Research. The most productive authors are Riva, del Piccolo, and Schwebel; the most influential authors are Finset, del Piccolo, and Eide. The most frequently occurring keywords other than “virtual” and “reality” are “training,” “trial,” and “patients.” The most relevant research themes are communication, education, and novel treatments; the most recent research trends are fitness and exergames.
Conclusions:
The analysis shows that the field has left its infant state and its specialization is advancing, with a clear focus on patient usability.
Gamification als Motivator in der Sprachtherapie bei Menschen mit intellektueller Beeinträchtigung
(2021)
Infants show impressive speech decoding abilities and detect acoustic regularities that highlight the syntactic relations of a language, often coded via non-adjacent dependencies (NADs, e.g., is singing). It has been claimed that infants learn NADs implicitly and associatively through passive listening and that there is a shift from effortless associative learning to a more controlled learning of NADs after the age of 2 years, potentially driven by the maturation of the prefrontal cortex. To investigate if older children are able to learn NADs, Lammertink et al. (2019) recently developed a word-monitoring serial reaction time (SRT) task and could show that 6–11-year-old children learned the NADs, as their reaction times (RTs) increased then they were presented with violated NADs. In the current study we adapted their experimental paradigm and tested NAD learning in a younger group of 52 children between the age of 4–8 years in a remote, web-based, game-like setting (whack-a-mole). Children were exposed to Italian phrases containing NADs and had to monitor the occurrence of a target syllable, which was the second element of the NAD. After exposure, children did a “Stem Completion” task in which they were presented with the first element of the NAD and had to choose the second element of the NAD to complete the stimuli. Our findings show that, despite large variability in the data, children aged 4–8 years are sensitive to NADs; they show the expected differences in r RTs in the SRT task and could transfer the NAD-rule in the Stem Completion task. We discuss these results with respect to the development of NAD dependency learning in childhood and the practical impact and limitations of collecting these data in a web-based setting.
Comprior
(2021)
Background
Reproducible benchmarking is important for assessing the effectiveness of novel feature selection approaches applied on gene expression data, especially for prior knowledge approaches that incorporate biological information from online knowledge bases. However, no full-fledged benchmarking system exists that is extensible, provides built-in feature selection approaches, and a comprehensive result assessment encompassing classification performance, robustness, and biological relevance. Moreover, the particular needs of prior knowledge feature selection approaches, i.e. uniform access to knowledge bases, are not addressed. As a consequence, prior knowledge approaches are not evaluated amongst each other, leaving open questions regarding their effectiveness.
Results
We present the Comprior benchmark tool, which facilitates the rapid development and effortless benchmarking of feature selection approaches, with a special focus on prior knowledge approaches. Comprior is extensible by custom approaches, offers built-in standard feature selection approaches, enables uniform access to multiple knowledge bases, and provides a customizable evaluation infrastructure to compare multiple feature selection approaches regarding their classification performance, robustness, runtime, and biological relevance.
Conclusion
Comprior allows reproducible benchmarking especially of prior knowledge approaches, which facilitates their applicability and for the first time enables a comprehensive assessment of their effectiveness
Transitory starch plays a central role in the life cycle of plants. Many aspects of this important metabolism remain unknown; however, starch granules provide insight into this persistent metabolic process. Therefore, monitoring alterations in starch granules with high temporal resolution provides one significant avenue to improve understanding. Here, a previously established method that combines LCSM and safranin-O staining for in vivo imaging of transitory starch granules in leaves of Arabidopsis thaliana was employed to demonstrate, for the first time, the alterations in starch granule size and morphology that occur both throughout the day and during leaf aging. Several starch-related mutants were included, which revealed differences among the generated granules. In ptst2 and sex1-8, the starch granules in old leaves were much larger than those in young leaves; however, the typical flattened discoid morphology was maintained. In ss4 and dpe2/phs1/ss4, the morphology of starch granules in young leaves was altered, with a more rounded shape observed. With leaf development, the starch granules became spherical exclusively in dpe2/phs1/ss4. Thus, the presented data provide new insights to contribute to the understanding of starch granule morphogenesis.
Digitale Diagnostik
(2021)
Digitale Logopädie
(2021)