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Background:
Digital therapeutic care apps provide a new effective and scalable approach for people with nonspecific low back pain (LBP). Digital therapeutic care apps are also driven by personalized decision-support interventions that support the user in self-managing LBP, and may induce prolonged behavior change to reduce the frequency and intensity of pain episodes. However, these therapeutic apps are associated with high attrition rates, and the initial prescription cost is higher than that of face-to-face physiotherapy. In Germany, digital therapeutic care apps are now being reimbursed by statutory health insurance; however, price targets and cost-driving factors for the formation of the reimbursement rate remain unexplored.
Objective:
The aim of this study was to evaluate the cost-effectiveness of a digital therapeutic care app compared to treatment as usual (TAU) in Germany. We further aimed to explore under which circumstances the reimbursement rate could be modified to consider value-based pricing.
Methods:
We developed a state-transition Markov model based on a best-practice analysis of prior LBP-related decision-analytic models, and evaluated the cost utility of a digital therapeutic care app compared to TAU in Germany. Based on a 3-year time horizon, we simulated the incremental cost and quality-adjusted life years (QALYs) for people with nonacute LBP from the societal perspective. In the deterministic sensitivity and scenario analyses, we focused on diverging attrition rates and app cost to assess our model's robustness and conditions for changing the reimbursement rate. All costs are reported in Euro (euro1=US $1.12).
Results:
Our base case results indicated that the digital therapeutic care strategy led to an incremental cost of euro121.59, but also generated 0.0221 additional QALYs compared to the TAU strategy, with an estimated incremental cost-effectiveness ratio (ICER) of euro5486 per QALY. The sensitivity analysis revealed that the reimbursement rate and the capability of digital therapeutic care to prevent reoccurring LBP episodes have a significant impact on the ICER. At the same time, the other parameters remained unaffected and thus supported the robustness of our model. In the scenario analysis, the different model time horizons and attrition rates strongly influenced the economic outcome. Reducing the cost of the app to euro99 per 3 months or decreasing the app's attrition rate resulted in digital therapeutic care being significantly less costly with more generated QALYs, and is thus considered to be the dominant strategy over TAU.
Conclusions:
The current reimbursement rate for a digital therapeutic care app in the statutory health insurance can be considered a cost-effective measure compared to TAU. The app's attrition rate and effect on the patient's prolonged behavior change essentially influence the settlement of an appropriate reimbursement rate. Future value-based pricing targets should focus on additional outcome parameters besides pain intensity and functional disability by including attrition rates and the app's long-term effect on quality of life.
The current paradigm of cosmic-ray (CR) origin states that the greater part of galactic CRs is produced by supernova remnants. The interaction of supernova ejecta with the interstellar medium after a supernova's explosions results in shocks responsible for CR acceleration via diffusive shock acceleration (DSA). We use particle-in-cell (PIC) simulations and a combined PIC-magnetohydrodynamic (PIC-MHD) technique to investigate whether DSA can occur in oblique high Mach number shocks. Using the PIC method, we follow the formation of the shock and determine the fraction of the particles that gets involved in DSA. With this result, we use PIC-MHD simulations to model the large-scale structure of the plasma and the magnetic field surrounding the shock and find out whether or not the reflected particles can generate upstream turbulence and trigger DSA. We find that the feasibility of this process in oblique shocks depends strongly on the Alfvenic Mach number, and the DSA process is more likely to be triggered at high Mach number shocks.
Diffraction enhanced imaging (DEI) is an advanced digital radiographic imaging technique employing the refraction of X-rays to contrast internal interfaces. This study aims to qualitatively and quantitatively evaluate images acquired using this technique and to assess how different fitting functions to the typical rocking curves (RCs) influence the quality of the images. RCs are obtained for every image pixel. This allows the separate determination of the absorption and the refraction properties of the material in a position-sensitive manner. Comparison of various types of fitting functions reveals that the Pseudo-Voigt (PsdV) function is best suited to fit typical RCs. A robust algorithm was developed in the Python programming language, which reliably extracts the physically meaningful information from each pixel of the image. We demonstrate the potential of the algorithm with two specimens: a silicone gel specimen that has well-defined interfaces, and an additively manufactured polycarbonate specimen.
In vivo endothelialization of polymer-based cardiovascular implant materials is a promising strategy to reduce the risk of platelet adherence and the subsequent thrombus formation and implant failure. However, endothelial cells from elderly patients are likely to exhibit a senescent phenotype that may counteract endothelialization. The senescence status of cells should therefore be investigated prior to implantation of devices designed to be integrated in the blood vessel wall. Here, human umbilical vein endothelial cells (HUVEC) were cultivated up to passage (P) 4, 10 and 26/27 to determine the population doubling time and the senescence status by four different methods. Determination of the senescence-associated beta-galactosidase activity (SA-beta-Gal) was carried out by colorimetric staining and microscopy (i), as well as by photometric quantification (ii), and the expression of senescence-associated nuclear proteins p16 and p21 as well as the proliferation marker Ki67 was assessed by immunostaining (iii), and by flow cytometry (iv). The population doubling time of P27-cells was remarkably greater (103 +/- 65 h) compared to P4-cells (24 +/- 3 h) and P10-cell (37 +/- 15 h). Among the four different methods tested, the photometric SA-beta-Gal activity assay and the flow cytometric determination of p16 and Ki67 were most effective in discriminating P27-cells from P4- and P10-cells. These methods combined with functional endothelial cell analyses might aid predictions on the performance of implant endothelialization in vivo.
Objective: Despite increasing research on psychotherapy preferences, the preferences of psychotherapy trainees are largely unknown. Moreover, differences in preferences between trainees and their patients could (a) hinder symptom improvement and therapy success for patients and (b) represent significant obstacles in the early career and development of future therapists. Method: We compared the preferences of n = 466 psychotherapy trainees to those of n = 969 laypersons using the Cooper-Norcross Inventory of Preferences. Moreover, we compared preferences between trainees in cognitive-behavioural therapy (CBT) and psychodynamic trainees. Results: We found significant differences between both samples in 13 of 18 items, and three of four subscales. Psychotherapy trainees preferred less therapist directiveness (d = 0.58), more emotional intensity (d = 0.74), as well as more focused challenge (d = 0.35) than laypeople. CBT trainees preferred more therapist directiveness (d = 2.00), less emotional intensity (d = 0.51), more present orientation (d = 0.76) and more focused challenge (d = 0.33) than trainees in psychodynamic/psychoanalytic therapy. Conclusion: Overall, the results underline the importance of implementing preference assessment and discussion during psychotherapy training. Moreover, therapists of different orientations seem to cover a large range of preferences for patients, in order to choose the right fit.
Manganese (Mn) as well as iron (Fe) are essential trace elements (TE) important for the maintenance of physiological functions including fetal development. However, in the case of Mn, evidence suggests that excess levels of intrauterine Mn are associated with adverse pregnancy outcomes. Although Mn is known to cross the placenta, the fundamentals of Mn transfer kinetics and mechanisms are largely unknown. Moreover, exposure to combinations of TEs should be considered in mechanistic transfer studies, in particular for TEs expected to share similar transfer pathways. Here, we performed a mechanistic in vitro study on the placental transfer of Mn across a BeWo b30 trophoblast layer. Our data revealed distinct differences in the placental transfer of Mn and Fe. While placental permeability to Fe showed a clear inverse dose-dependency, Mn transfer was largely independent of the applied doses. Concurrent exposure of Mn and Fe revealed transfer interactions of Fe and Mn, indicating that they share common transfer mechanisms. In general, mRNA and protein expression of discussed transporters like DMT1, TfR, or FPN were only marginally altered in BeWo cells despite the different exposure scenarios highlighting that Mn transfer across the trophoblast layer likely involves a combination of active and passive transport processes.
Purpose: The present work aimed to delineate (i) a revised protocol according to recent methodological developments in evidence generation, to (ii) describe its interpretation, the assessment of the overall certainty of evidence and to (iii) outline an Evidence to Decision framework for deriving an evidence-based guideline on quantitative and qualitative aspects of dietary protein intake. Methods A methodological protocol to systematically investigate the association between dietary protein intake and several health outcomes and for deriving dietary protein intake recommendations for the primary prevention of various non-communicable diseases in the general adult population was developed. Results The developed methodological protocol relies on umbrella reviews including systematic reviews with or without meta-analyses. Systematic literature searches in three databases will be performed for each health-related outcome. The methodological quality of all selected systematic reviews will be evaluated using a modified version of AMSTAR 2, and the outcome-specific certainty of evidence for systematic reviews with or without meta-analysis will be assessed with NutriGrade. The general outline of the Evidence to Decision framework foresees that recommendations in the derived guideline will be given based on the overall certainty of evidence as well as on additional criteria such as sustainability. Conclusion The methodological protocol permits a systematic evaluation of published systematic reviews on dietary protein intake and its association with selected health-related outcomes. An Evidence to Decision framework will be the basis for the overall conclusions and the resulting recommendations for dietary protein intake.
The present study estimated diet-related greenhouse gas emissions (GHGE) and land use (LU) in a sample of adults, examined main dietary contributors of GHGE, and evaluated socio demographic, lifestyle, and wellbeing factors as potential determinants of high environmental impact. A cross-sectional design based on data collected from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (2010-2012) was used. Usual diet was assessed using food frequency questionnaires. Diet-related GHGE and LU were calculated using a European-average lifecycle analyses-food-item database (SHARP-ID). Information on potential determinants were collected using self-administered questionnaires. Men (n = 404) and women (n = 401) at an average age of 66.0 +/- 8.4 years were included. Dietary-related energy-adjusted GHGE in men was 6.6 +/- 0.9 and in women was 7.0 +/- 1.1 kg CO2 eq per 2000 kcal. LU in men was 7.8 +/- 1.2 and in women was 7.7 +/- 1.2 m(2)/year per 2000 kcal. Food groups contributing to most GHGE included dairy, meat and non-alcoholic beverages. Among women, being single, having a job, being a smoker and having higher BMI were characteristics associated with higher GHGE, whereas for men these included being married, longer sleeping duration and higher BMI. Further studies are warranted to provide insights into population-specific determinants of sustainable dietary choices.
Over the last few years, the vegan diet has become increasingly popular in Germany. It has been proposed that this diet is generally lower in fat, but less is known about the impact on fatty acid (FA) profiles. Therefore, the cross-sectional "Risks and Benefits of a Vegan Diet" (RBVD) study (n = 72) was used to investigate dietary FA intake as well as plasma phospholipid FA in vegans (n = 36) compared to omnivores (n = 36). Vegans had a significantly lower dietary intake of total fat (median 86 g/day, IQR 64-111) in comparison to omnivores (median 104 g/day, IQR 88-143, p = 0.004). Further, vegans had a lower intake of saturated fatty acids (SFA) (p < 0.0001) and monounsaturated fatty acids (MUFA) (p = 0.001) compared to omnivores. Vegans had a higher intake in total polyunsaturated fatty acids (PUFA), omega-3 and omega-6 PUFA compared to omnivores, but without statistical significance after Bonferroni correction. According to plasma phospholipid profiles, relatively lower proportions of SFA (p < 0.0001), total trans fatty acids (TFA) (p = 0.0004) and omega-3-FA (p < 0.0001), but higher proportions of omega-6-FA (p < 0.0001) were observed in vegans. With the exception of omega-3 PUFA, a vegan diet is associated with a more favorable dietary fat intake and more favorable plasma FA profiles and therefore may reduce cardiovascular risk.
Diet analysis of bats killed at wind turbines suggests large-scale losses of trophic interactions
(2022)
Agricultural practice has led to landscape simplification and biodiversity decline, yet recently, energy-producing infrastructures, such as wind turbines, have been added to these simplified agroecosystems, turning them into multi-functional energy-agroecosystems. Here, we studied the trophic interactions of bats killed at wind turbines using a DNA metabarcoding approach to shed light on how turbine-related bat fatalities may possibly affect local habitats. Specifically, we identified insect DNA in the stomachs of common noctule bats (Nyctalus noctula) killed by wind turbines in Germany to infer in which habitats these bats hunted. Common noctule bats consumed a wide variety of insects from different habitats, ranging from aquatic to terrestrial ecosystems (e.g., wetlands, farmland, forests, and grasslands). Agricultural and silvicultural pest insects made up about 20% of insect species consumed by the studied bats. Our study suggests that the potential damage of wind energy production goes beyond the loss of bats and the decline of bat populations. Bat fatalities at wind turbines may lead to the loss of trophic interactions and ecosystem services provided by bats, which may add to the functional simplification and impaired crop production, respectively, in multi-functional ecosystems.
In many countries, women are over-represented among low-wage employees, which is why a wage floor could benefit them particularly. Following this notion, we analyse the impact of the German minimum wage introduction in 2015 on the gender wage gap. Germany poses an interesting case study in this context, since it has a rather high gender wage gap and set the minimum wage at a relatively high level, affecting more than four million employees. Based on individual data from the Structure of Earnings Survey, containing information for over one million employees working in 60,000 firms, we use a difference-in-difference framework that exploits regional differences in the bite of the minimum wage. We find a significant negative effect of the minimum wage on the regional gender wage gap. Between 2014 and 2018, the gap at the 10th percentile of the wage distribution was reduced by 4.6 percentage points (or 32%) in regions that were strongly affected by the minimum wage compared to less affected regions. For the gap at the 25th percentile, the effect still amounted to 18%, while for the mean it was smaller (11%) and not particularly robust. We thus find that the minimum wage can indeed reduce gender wage disparities. While the effect is highest for the low-paid, it also reaches up into higher parts of the wage distribution.
Dictyostelium amoebae perform a semi-closed mitosis, in which the nuclear envelope is fenestrated at the insertion sites of the mitotic centrosomes and around the central spindle during karyokinesis. During late telophase the centrosome relocates to the cytoplasmic side of the nucleus, the central spindle disassembles and the nuclear fenestrae become closed. Our data indicate that Dictyostelium spastin (DdSpastin) is a microtubule-binding and severing type I membrane protein that plays a role in this process. Its mitotic localization is in agreement with a requirement for the removal of microtubules that would hinder closure of the fenestrae. Furthermore, DdSpastin interacts with the HeH/ LEM-family protein Src1 in BioID analyses as well as the inner nuclear membrane protein Sun1, and shows subcellular co-localizations with Src1, Sun1, the ESCRT component CHMP7 and the IST1-like protein filactin, suggesting that the principal pathway of mitotic nuclear envelope remodeling is conserved between animals and Dictyostelium amoebae.
Development of birthweight and length for gestational age and sex references in Yucatan, Mexico
(2022)
Objective To develop sex- and gestational age specific reference percentiles and curves for birth weight and length for Yucatec neonates using data from birth registers of infants born during 2015-2019. Material and methods Observational, descriptive, epidemiologic study in a 5-year period including every registered birth in the state of Yucatan, Mexico using birth registries. A total of 158 432 live, physically healthy singletons (76 442 females and 81 990 males) between 25 and 42 weeks of gestation were included in the analysis. We used the LMS method to construct smoothed reference centiles (3rd, 10th, 25th, 50th, 75th, 95th, and 97th) and curves for males and females separately. Results Mean maternal age was 26 (SD = 6.22) years. Fifty-two percent of births occurred by vaginal delivery, 37% were firstborn and similar proportions were second (33%) and third or more (30%) born. 5.5% of newborns included in the references corresponds to neonates born before 37 weeks of gestation (5.9% boys and 5.1% girls). In both sexes, the percentage of infants with a birthweight less than 2500 g was 6.7%. The birthweight at the 50th percentile for males and females at 40 weeks of gestation in this cohort was 3256 and 3167 g, respectively, and the corresponding values for birth length were 50.23 and 49.84 cm (mean differences between sexes: 89 g and 0.40 cm, respectively). Conclusion The reference percentile and curves developed in this study are useful for research purposes and can help health practitioners to assess the biological status of infants born in Yucatan.
Objective:
Current data regarding the roles of branched-chain amino acids (BCAA) in metabolic health are rather conflicting, as positive and negative effects have been attributed to their intake.
Methods:
To address this, individual effects of leucine and valine were elucidated in vivo (C57BL/6JRj mice) with a detailed phenotyping of these supplementations in high-fat (HF) diets and further characterization with in vitro approaches (C2C12 myocytes).
Results:
Here, we demonstrate that under HF conditions, leucine mediates beneficial effects on adiposity and insulin sensitivity, in part due to increasing energy expenditure-likely contributing partially to the beneficial effects of a higher milk protein intake. On the other hand, valine feeding leads to a worsening of HF-induced health impairments, specifically reducing glucose tolerance/ insulin sensitivity. These negative effects are driven by an accumulation of the valine-derived metabolite 3-hydroxyisobutyrate (3HIB). Higher plasma 3-HIB levels increase basal skeletal muscle glucose uptake which drives glucotoxicity and impairs myocyte insulin signaling.
Conclusion:
These data demonstrate the detrimental role of valine in an HF context and elucidate additional targetable pathways in the etiology of BCAA-induced obesity and insulin resistance.
The increase in the performance of organic solar cells observed over the past few years has reinvigorated the search for a deeper understanding of the loss and extraction processes in this class of device. A detailed knowledge of the density of free charge carriers under different operating conditions and illumination intensities is a prerequisite to quantify the recombination and extraction dynamics. Differential charging techniques are a promising approach to experimentally obtain the charge carrier density under the aforementioned conditions. In particular, the combination of transient photovoltage and photocurrent as well as impedance and capacitance spectroscopy have been successfully used in past studies to determine the charge carrier density of organic solar cells. In this Tutorial, these experimental techniques will be discussed in detail, highlighting fundamental principles, practical considerations, necessary corrections, advantages, drawbacks, and ultimately their limitations. Relevant references introducing more advanced concepts will be provided as well. Therefore, the present Tutorial might act as an introduction and guideline aimed at new prospective users of these techniques as well as a point of reference for more experienced researchers. Published under an exclusive license by AIP Publishing.
The Caenorhabditis elegans (C. elegans) is a model organism that has been increasingly used in health and environmental toxicity assessments. The quantification of such elements in vivo can assist in studies that seek to relate the exposure concentration to possible biological effects.
Therefore, this study is the first to propose a method of quantitative analysis of 21 ions by ion chromatography (IC), which can be applied in different toxicity studies in C. elegans.
The developed method was validated for 12 anionic species (fluoride, acetate, chloride, nitrite, bromide, nitrate, sulfate, oxalate, molybdate, dichromate, phosphate, and perchlorate), and 9 cationic species (lithium, sodium, ammonium, thallium, potassium, magnesium, manganese, calcium, and barium).
The method did not present the presence of interfering species, with R2 varying between 0.9991 and 0.9999, with a linear range from 1 to 100 mu g L-1.
Limits of detection (LOD) and limits of quantification (LOQ) values ranged from 0.2319 mu g L-1 to 1.7160 mu g L-1 and 0.7028 mu g L-1 to 5.1999 mu g L-1, respectively.
The intraday and interday precision tests showed an Relative Standard Deviation (RSD) below 10.0 % and recovery ranging from 71.0 % to 118.0 % with a maximum RSD of 5.5 %.
The method was applied to real samples of C. elegans treated with 200 uM of thallium acetate solution, determining the uptake and bioaccumulated Tl+ content during acute exposure.
Meter-sized ground-based telescopes are frequently used today for the follow-up of extrasolar planet candidates. While the transit signal of a Jupiter-sized object can typically be detected to a high level of confidence with small telescope apertures as well, the shallow transit dips of planets with the size of Neptune and smaller are more challenging to reveal. We employ new observational data to illustrate the photometric follow-up capabilities of meter-sized telescopes for shallow exoplanet transits. We describe in detail the capability of distinguishing the photometric signal of an exoplanet transit from an underlying trend in the light curve. The transit depths of the six targets we observed, Kepler-94b, Kepler-63b, K2-100b, K2-138b, K2-138c, and K2-138e, range from 3.9 ppt down to 0.3 ppt. For five targets of this sample, we provide the first ground-based photometric follow-up. The timing of three targets is precisely known from previous observations, and the timing of the other three targets is uncertain and we aim to constrain it. We detect or rule out the transit features significantly in single observations for the targets that show transits of 1.3 ppt or deeper. The shallower transit depths of two targets of 0.6 and 0.8 ppt were detected tentatively in single light curves, and were detected significantly by repeated observations. Only for the target of the shallowest transit depth of 0.3 ppt were we unable to draw a significant conclusion despite combining five individual light curves. An injection-recovery test on our real data shows that we detect transits of 1.3 ppt depth significantly in single light curves if the transit is fully covered, including out-of-transit data toward both sides, in some cases down to 0.7 ppt depth. For Kepler-94b, Kepler-63b, and K2-100b, we were able to verify the ephemeris. In the case of K2-138c with a 0.6 ppt deep transit, we were able to refine it, and in the case of K2-138e, we ruled out the transit in the time interval of more than ±1.5 σ of its current literature ephemeris.
Lennard-Jones mixtures represent one of the popular systems for the study of glass-forming liquids.
Spatio/temporal heterogeneity and rare (activated) events are at the heart of the slow dynamics typical of these systems. Such slow dynamics is characterised by the development of a plateau in the mean-squared displacement (MSD) at intermediate times, accompanied by a non-Gaussianity in the displacement distribution identified by exponential tails.
As pointed out by some recent works, the non-Gaussianity persists at times beyond the MSD plateau, leading to a Brownian yet non-Gaussian regime and thus highlighting once again the relevance of rare events in such systems.
Single-particle motion of glass-forming liquids is usually interpreted as an alternation of rattling within the local cage and cage-escape motion and therefore can be described as a sequence of waiting times and jumps. In this work, by using a simple yet robust algorithm, we extract jumps and waiting times from single-particle trajectories obtained via molecular dynamics simulations.
We investigate the presence of correlations between waiting times and find negative correlations, which becomes more and more pronounced when lowering the temperature.
Detecting DNA of novel fungal pathogens using ResNets and a curated fungi-hosts data collection
(2022)
Background:
Emerging pathogens are a growing threat, but large data collections and approaches for predicting the risk associated with novel agents are limited to bacteria and viruses. Pathogenic fungi, which also pose a constant threat to public health, remain understudied.
Relevant data remain comparatively scarce and scattered among many different sources, hindering the development of sequencing-based detection workflows for novel fungal pathogens.
No prediction method working for agents across all three groups is available, even though the cause of an infection is often difficult to identify from symptoms alone.
Results:
We present a curated collection of fungal host range data, comprising records on human, animal and plant pathogens, as well as other plant-associated fungi, linked to publicly available genomes.
We show that it can be used to predict the pathogenic potential of novel fungal species directly from DNA sequences with either sequence homology or deep learning.
We develop learned, numerical representations of the collected genomes and visualize the landscape of fungal pathogenicity.
Finally, we train multi-class models predicting if next-generation sequencing reads originate from novel fungal, bacterial or viral threats.
Conclusions:
The neural networks trained using our data collection enable accurate detection of novel fungal pathogens.
A curated set of over 1400 genomes with host and pathogenicity metadata supports training of machine-learning models and sequence comparison, not limited to the pathogen detection task.
Only a fast and global transformation towards decarbonization and sustainability can keep the Earth in a civilization-friendly state. As hotspots for (green) innovation and experimentation, cities could play an important role in this transition. They are also known to profit from each other's ideas, with policy and technology innovations spreading to other cities. In this way, cities can be conceptualized as nodes in a globe-spanning learning network. The dynamics of this process are important for society's response to climate change and other challenges, but remain poorly understood on a macroscopic level. In this contribution, we develop an approach to identify whether network-based complex contagion effects are a feature of sustainability policy adoption by cities, based on dose-response contagion and surrogate data models. We apply this methodology to an exemplary data set, comprising empirical data on the spreading of a public transport innovation (Bus Rapid Transit Systems) and a global inter-city connection network based on scheduled flight routes. Although our approach is not able to identify detailed mechanisms, our results point towards a contagious spreading process, and cannot be explained by either the network structure or the increase in global adoption rate alone. Further research on the role of a city's abstract "global neighborhood" regarding its policy and innovation decisions is thus both needed and promising, and may connect with research on social tipping processes. The methodology is generic, and can be used to compare the predictive power for innovation spreading of different kinds of inter-city network connections, e.g. via transport links, trade, or co-membership in political networks.