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The Palaeocene-Eocene Thermal Maximum (ca. 56 million years ago) offers a primary analogue for future global warming and carbon cycle recovery. Yet, where and how massive carbon emissions were mitigated during this climate warming event remains largely unknown. Here we show that organic carbon burial in the vast epicontinental seaways that extended over Eurasia provided a major carbon sink during the Palaeocene-Eocene Thermal Maximum. We coupled new and existing stratigraphic analyses to a detailed paleogeographic framework and using spatiotemporal interpolation calculated ca. 720–1300 Gt organic carbon excess burial, focused in the eastern parts of the Eurasian epicontinental seaways. A much larger amount (2160–3900 Gt C, and when accounting for the increase in inundated shelf area 7400–10300 Gt C) could have been sequestered in similar environments globally. With the disappearance of most epicontinental seas since the Oligocene-Miocene, an effective negative carbon cycle feedback also disappeared making the modern carbon cycle critically dependent on the slower silicate weathering feedback.
The use of automated tools to reconstruct lipid metabolic pathways is not warranted in plants. Here, the authors construct Plant Lipid Module for Arabidopsis rosette using constraint-based modeling, demonstrate its integration in other plant metabolic models, and use it to dissect the genetic architecture of lipid metabolism.
Lipids play fundamental roles in regulating agronomically important traits. Advances in plant lipid metabolism have until recently largely been based on reductionist approaches, although modulation of its components can have system-wide effects. However, existing models of plant lipid metabolism provide lumped representations, hindering detailed study of component modulation. Here, we present the Plant Lipid Module (PLM) which provides a mechanistic description of lipid metabolism in the Arabidopsis thaliana rosette. We demonstrate that the PLM can be readily integrated in models of A. thaliana Col-0 metabolism, yielding accurate predictions (83%) of single lethal knock-outs and 75% concordance between measured transcript and predicted flux changes under extended darkness. Genome-wide associations with fluxes obtained by integrating the PLM in diel condition- and accession-specific models identify up to 65 candidate genes modulating A. thaliana lipid metabolism. Using mutant lines, we validate up to 40% of the candidates, paving the way for identification of metabolic gene function based on models capturing natural variability in metabolism.
An earthquake swarm affected the Bransfield Strait, Antarctica, a unique rift basin in transition from intra-arc rifting to ocean spreading. The swarm, counting similar to 85,000 volcano-tectonic earthquakes since August 2020, is located close to the Orca submarine volcano, previously considered inactive. Simultaneously, geodetic data reported up to similar to 11 cm north-westward displacement over King George Island. We use a broad variety of geophysical data and methods to reveal the complex migration of seismicity, accompanying the intrusion of 0.26-0.56 km(3) of magma. Strike-slip earthquakes mark the intrusion at depth, while shallower normal faulting the similar to 20 km long lateral growth of a dike. Seismicity abruptly decreased after a Mw 6.0 earthquake, suggesting the magmatic dike lost pressure with the slipping of a large fault. A seafloor eruption is likely, but not confirmed by sea surface temperature anomalies. The unrest documents episodic magmatic intrusion in the Bransfield Strait, providing unique insights into active continental rifting.
The prevalence of obesity in the pediatric population has become a major public health issue. Indeed, the dramatic increase of this epidemic causes multiple and harmful consequences, Physical activity, particularly physical exercise, remains to be the cornerstone of interventions against childhood obesity. Given the conflicting findings with reference to the relevant literature addressing the effects of exercise on adiposity and physical fitness outcomes in obese children and adolescents, the effect of duration-matched concurrent training (CT) [50% resistance (RT) and 50% high-intensity-interval-training (HIIT)] on body composition and physical fitness in obese youth remains to be elucidated. Thus, the purpose of this study was to examine the effects of 9-weeks of CT compared to RT or HIIT alone, on body composition and selected physical fitness components in healthy sedentary obese youth. Out of 73 participants, only 37; [14 males and 23 females; age 13.4 +/- 0.9 years; body-mass-index (BMI): 31.2 +/- 4.8 kg center dot m-2] were eligible and randomized into three groups: HIIT (n = 12): 3-4 setsx12 runs at 80-110% peak velocity, with 10-s passive recovery between bouts; RT (n = 12): 6 exercises; 3-4 sets x 10 repetition maximum (RM) and CT (n = 13): 50% serial completion of RT and HIIT. CT promoted significant greater gains compared to HIIT and RT on body composition (p < 0.01, d = large), 6-min-walking test distance (6 MWT-distance) and on 6 MWT-VO2max (p < 0.03, d = large). In addition, CT showed substantially greater improvements than HIIT in the medicine ball throw test (20.2 vs. 13.6%, p < 0.04, d = large). On the other hand, RT exhibited significantly greater gains in relative hand grip strength (p < 0.03, d = large) and CMJ (p < 0.01, d = large) than HIIT and CT. CT promoted greater benefits for fat, body mass loss and cardiorespiratory fitness than HIIT or RT modalities. This study provides important information for practitioners and therapists on the application of effective exercise regimes with obese youth to induce significant and beneficial body composition changes. The applied CT program and the respective programming parameters in terms of exercise intensity and volume can be used by practitioners as an effective exercise treatment to fight the pandemic overweight and obesity in youth.
Background
Teleost fishes comprise more than half of the vertebrate species. Within teleosts, most phylogenies consider the split between Osteoglossomorpha and Euteleosteomorpha/Otomorpha as basal, preceded only by the derivation of the most primitive group of teleosts, the Elopomorpha. While Osteoglossomorpha are generally species poor, the taxon contains the African weakly electric fish (Mormyroidei), which have radiated into numerous species. Within the mormyrids, the genus Campylomormyrus is mostly endemic to the Congo Basin. Campylomormyrus serves as a model to understand mechanisms of adaptive radiation and ecological speciation, especially with regard to its highly diverse species-specific electric organ discharges (EOD). Currently, there are few well-annotated genomes available for electric fish in general and mormyrids in particular. Our study aims at producing a high-quality genome assembly and to use this to examine genome evolution in relation to other teleosts. This will facilitate further understanding of the evolution of the osteoglossomorpha fish in general and of electric fish in particular.
Results
A high-quality weakly electric fish (C. compressirostris) genome was produced from a single individual with a genome size of 862 Mb, consisting of 1,497 contigs with an N50 of 1,399 kb and a GC-content of 43.69%. Gene predictions identified 34,492 protein-coding genes, which is a higher number than in the two other available Osteoglossomorpha genomes of Paramormyrops kingsleyae and Scleropages formosus. A Computational Analysis of gene Family Evolution (CAFE5) comparing 33 teleost fish genomes suggests an overall faster gene family turnover rate in Osteoglossomorpha than in Otomorpha and Euteleosteomorpha. Moreover, the ratios of expanded/contracted gene family numbers in Osteoglossomorpha are significantly higher than in the other two taxa, except for species that had undergone an additional genome duplication (Cyprinus carpio and Oncorhynchus mykiss). As potassium channel proteins are hypothesized to play a key role in EOD diversity among species, we put a special focus on them, and manually curated 16 Kv1 genes. We identified a tandem duplication in the KCNA7a gene in the genome of C. compressirostris.
Conclusions
We present the fourth genome of an electric fish and the third well-annotated genome for Osteoglossomorpha, enabling us to compare gene family evolution among major teleost lineages. Osteoglossomorpha appear to exhibit rapid gene family evolution, with more gene family expansions than contractions. The curated Kv1 gene family showed seven gene clusters, which is more than in other analyzed fish genomes outside Osteoglossomorpha. The KCNA7a, encoding for a potassium channel central for EOD production and modulation, is tandemly duplicated which may related to the diverse EOD observed among Campylomormyrus species.
Recently, there has been an upsurge of activity in image-based non-photorealistic rendering (NPR), and in particular portrait image stylisation, due to the advent of neural style transfer (NST). However, the state of performance evaluation in this field is poor, especially compared to the norms in the computer vision and machine learning communities. Unfortunately, the task of evaluating image stylisation is thus far not well defined, since it involves subjective, perceptual, and aesthetic aspects. To make progress towards a solution, this paper proposes a new structured, three-level, benchmark dataset for the evaluation of stylised portrait images. Rigorous criteria were used for its construction, and its consistency was validated by user studies. Moreover, a new methodology has been developed for evaluating portrait stylisation algorithms, which makes use of the different benchmark levels as well as annotations provided by user studies regarding the characteristics of the faces. We perform evaluation for a wide variety of image stylisation methods (both portrait-specific and general purpose, and also both traditional NPR approaches and NST) using the new benchmark dataset.
Oxygen (O-2) availability in soils is vital for plant growth and productivity. The transport and consumption of O-2 in the root zone is closely linked to soil moisture content, the spatial distribution of roots, as well as structure and heterogeneity of the surrounding soil. In this study, we measure three-dimensional root system architecture and the spatiotemporal dynamics of soil moisture (& theta;) and O-2 concentrations in the root zone of maize (Zea mays) via non-invasive imaging, and then construct and parameterize a reactive transport model based on the experimental data. The combination of three non-invasive imaging methods allowed for a direct comparison of simulation results with observations at high spatial and temporal resolution. In three different modeling scenarios, we investigated how the results obtained for different levels of conceptual complexity in the model were able to match measured & theta; and O-2 concentration patterns. We found that the modeling scenario that considers heterogeneous soil structure and spatial variability of hydraulic parameters (permeability, porosity, and van Genuchten & alpha; and n), better reproduced the measured & theta; and O-2 patterns relative to a simple model with a homogenous soil domain. The results from our combined imaging and modeling analysis reveal that experimental O-2 and water dynamics can be reproduced quantitatively in a reactive transport model, and that O-2 and water dynamics are best characterized when conditions unique to the specific system beyond the distribution of roots, such as soil structure and its effect on water saturation and macroscopic gas transport pathways, are considered.
Solid organ transplant (SOT) recipients receive therapeutic immunosuppression that compromises their immune response to infections and vaccines. For this reason, SOT patients have a high risk of developing severe coronavirus disease 2019 (COVID-19) and an increased risk of death from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. Moreover, the efficiency of immunotherapies and vaccines is reduced due to the constant immunosuppression in this patient group. Here, we propose adoptive transfer of SARS-CoV-2-specific T cells made resistant to a common immunosuppressant, tacrolimus, for optimized performance in the immunosuppressed patient. Using a ribonucleoprotein approach of CRISPR-Cas9 technology, we have generated tacrolimus-resistant SARS-CoV-2-specific T cell products from convalescent donors and demonstrate their specificity and function through characterizations at the single-cell level, including flow cytometry, single-cell RNA (scRNA) Cellular Indexing of Transcriptomes and Epitopes (CITE), and T cell receptor (TCR) sequencing analyses. Based on the promising results, we aim for clinical validation of this approach in transplant recipients. Additionally, we propose a combinatory approach with tacrolimus, to prevent an overshooting immune response manifested as bystander T cell activation in the setting of severe COVID-19 immunopathology, and tacrolimus-resistant SARS-CoV-2-specific T cell products, allowing for efficient clearance of viral infection. Our strategy has the potential to prevent severe COVID-19 courses in SOT or autoimmunity settings and to prevent immunopathology while providing viral clearance in severe non-transplant COVID-19 cases.
Background and aims: Accurate and user-friendly assessment tools quantifying alcohol consumption are a prerequisite to effective prevention and treatment programmes, including Screening and Brief Intervention. Digital tools offer new potential in this field. We developed the ‘Animated Alcohol Assessment Tool’ (AAA-Tool), a mobile app providing an interactive version of the World Health Organization's Alcohol Use Disorders Identification Test (AUDIT) that facilitates the description of individual alcohol consumption via culturally informed animation features. This pilot study evaluated the Russia-specific version of the Animated Alcohol Assessment Tool with regard to (1) its usability and acceptability in a primary healthcare setting, (2) the plausibility of its alcohol consumption assessment results and (3) the adequacy of its Russia-specific vessel and beverage selection. Methods: Convenience samples of 55 patients (47% female) and 15 healthcare practitioners (80% female) in 2 Russian primary healthcare facilities self-administered the Animated Alcohol Assessment Tool and rated their experience on the Mobile Application Rating Scale – User Version. Usage data was automatically collected during app usage, and additional feedback on regional content was elicited in semi-structured interviews. Results: On average, patients completed the Animated Alcohol Assessment Tool in 6:38 min (SD = 2.49, range = 3.00–17.16). User satisfaction was good, with all subscale Mobile Application Rating Scale – User Version scores averaging >3 out of 5 points. A majority of patients (53%) and practitioners (93%) would recommend the tool to ‘many people’ or ‘everyone’. Assessed alcohol consumption was plausible, with a low number (14%) of logically impossible entries. Most patients reported the Animated Alcohol Assessment Tool to reflect all vessels (78%) and all beverages (71%) they typically used. Conclusion: High acceptability ratings by patients and healthcare practitioners, acceptable completion time, plausible alcohol usage assessment results and perceived adequacy of region-specific content underline the Animated Alcohol Assessment Tool's potential to provide a novel approach to alcohol assessment in primary healthcare. After its validation, the Animated Alcohol Assessment Tool might contribute to reducing alcohol-related harm by facilitating Screening and Brief Intervention implementation in Russia and beyond.
Simulating the space weather in the AU Mic system: stellar winds and extreme coronal mass ejections
(2022)
Two close-in planets have been recently found around the M-dwarf flare star AU Microscopii (AU Mic). These Neptune-sized planets (AU Mic b and c) seem to be located very close to the so-called "evaporation valley" in the exoplanet population, making this system an important target for studying atmospheric loss on exoplanets. This process, while mainly driven by high-energy stellar radiation, will be strongly mediated by the space environment surrounding the planets. Here we present an investigation of this last area, performing 3D numerical modeling of the quiescent stellar wind from AU Mic, as well as time-dependent simulations describing the evolution of a highly energetic coronal mass ejection (CME) event in this system. Observational constraints on the stellar magnetic field and properties of the eruption are incorporated in our models. We carry out qualitative and quantitative characterizations of the stellar wind, the emerging CMEs, as well as the expected steady and transient conditions along the orbit of both exoplanets. Our results predict extreme space weather for AU Mic and its planets. This includes sub-Alfvenic regions for the large majority of the exoplanet orbits, very high dynamic and magnetic pressure values in quiescence (varying within 10(2)-10(5) times the dynamic pressure experienced by Earth), and an even harsher environment during the passage of any escaping CME associated with the frequent flaring observed in AU Mic. These space weather conditions alone pose an immense challenge for the survival of exoplanetary atmospheres (if any) in this system.
Introduction
Attempts to improve cognitive abilities via transcranial direct current stimulation (tDCS) have led to ambiguous results, likely due to the method's susceptibility to methodological and inter-individual factors. Conventional tDCS, i.e., using an active electrode over brain areas associated with the targeted cognitive function and a supposedly passive reference, neglects stimulation effects on entire neural networks.
Methods
We investigated the advantage of frontoparietal network stimulation (right prefrontal anode, left posterior parietal cathode) against conventional and sham tDCS in modulating working memory (WM) capacity dependent transfer effects of a single-session distractor inhibition (DIIN) training. Since previous results did not clarify whether electrode montage drives this individual transfer, we here compared conventional to frontoparietal and sham tDCS and reanalyzed data of 124 young, healthy participants in a more robust way using linear mixed effect modeling.
Results
The interaction of electrode montage and WM capacity resulted in systematic differences in transfer effects. While higher performance gains were observed with increasing WM capacity in the frontoparietal stimulation group, low WM capacity individuals benefited more in the sham condition. The conventional stimulation group showed subtle performance gains independent of WM capacity.
Discussion
Our results confirm our previous findings of WM capacity dependent transfer effects on WM by a single-session DIIN training combined with tDCS and additionally highlight the pivotal role of the specific electrode montage. WM capacity dependent differences in frontoparietal network recruitment, especially regarding the parietal involvement, are assumed to underlie this observation.
Background
There is consistent evidence that the COVID-19 pandemic is associated with an increased psychosocial burden on children and adolescents and their parents. Relatively little is known about its particular impact on high-risk groups with chronic physical health conditions (CCs). Therefore, the primary aim of the study is to analyze the multiple impacts on health care and psychosocial well-being on these children and adolescents and their parents.
Methods
We will implement a two-stage approach. In the first step, parents and their underage children from three German patient registries for diabetes, obesity, and rheumatic diseases, are invited to fill out short questionnaires including questions about corona-specific stressors, the health care situation, and psychosocial well-being. In the next step, a more comprehensive, in-depth online survey is carried out in a smaller subsample.
Discussion
The study will provide insights into the multiple longer-term stressors during the COVID-19 pandemic in families with a child with a CC. The simultaneous consideration of medical and psycho-social endpoints will help to gain a deeper understanding of the complex interactions affecting family functioning, psychological well-being, and health care delivery.
Introduction General and particularly sport-specific testing is an integral aspect of performance optimization in artistic gymnastics. In artistic gymnastics, however, only non-specific field tests have been used to assess endurance performance (e.g., Multistage Shuttle Run Test; Cooper's Test).
Methods This study aimed to examine the validity of a new sport-specific endurance test in artistic gymnastics. Fourteen elite-level gymnasts (i.e., eight males and six females) participated in this study. The newly developed artistic gymnastics-specific endurance test (AGSET) was conducted on two different occasions seven days apart to determine its reliability. To assess the concurrent validity of AGSET, participants performed the multistage shuttle run test (MSRT). Maximum oxygen uptake (VO2max) and respiratory exchange ratio (RER) were directly assessed using a portable gas analyzer system during both protocols. Additionally, the total time maintained (TTM) during the AGSET, maximum heart rate (HRmax), maximal aerobic speed (MAS), and blood lactate concentration (BLa) during the two protocols were collected.
Results The main findings indicated that all variables derived from the AGSET (i.e., VO2max, MAS, HRmax, BLa, and RER) displayed very good relative (all intraclass correlation coefficients [ICC] > 0.90) and absolute (all typical errors of measurement [TEM] < 5%) reliability. Further, results showed that the ability of the AGSET to detect small changes in VO2max, MAS, BLa, and RER was good (smallest worthwhile change [SWC0.2] > TEM), except HRmax (SWC0.2 < TEM). Additionally, results showed a nearly perfect association between the VO2max values derived from the AGSET and MSRT (r = 0.985; coefficient of determination [R-2] = 97%) with no statistically significant differences (p>0.05). The mean (bias) +/- 95% limits of agreement between the two protocols were 0.28 +/- 0.55 mlminkg-1.
Discussion AGSET seems to present very good reliability and concurrent validity for assessing endurance performance in elite artistic gymnastics. In addition, the newly developed protocol presents a good ability to detect small changes in performance.
Background Anxiety and depressive disorders share common features of mood dysfunctions. This has stimulated interest in transdiagnostic dimensional research as proposed by the Research Domain Criteria (RDoC) approach by the National Institute of Mental Health (NIMH) aiming to improve the understanding of underlying disease mechanisms. The purpose of this study was to investigate the processing of RDoC domains in relation to disease severity in order to identify latent disorder-specific as well as transdiagnostic indicators of disease severity in patients with anxiety and depressive disorders.
Methods Within the German research network for mental disorders, 895 participants (n = 476 female, n = 602 anxiety disorder, n = 257 depressive disorder) were recruited for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) and included in this cross-sectional study. We performed incremental regression models to investigate the association of four RDoC domains on disease severity in patients with affective disorders: Positive (PVS) and Negative Valance System (NVS), Cognitive Systems (CS) and Social Processes (SP).
Results The results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: & beta; = -0.35; NVS: & beta; = 0.39; CS: & beta; = -0.12; SP: & beta; = -0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association.
Limitations The cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for.
Conclusion Our key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways.
Progressive habitat fragmentation threatens plant species with narrow habitat requirements. While local environmental conditions define population growth rates and recruitment success at the patch level, dispersal is critical for population viability at the landscape scale. Identifying the dynamics of plant meta-populations is often confounded by the uncertainty about soil-stored population compartments. We combined a landscape-scale assessment of an amphibious plant's population structure with measurements of dispersal complexity in time to track dispersal and putative shifts in functional connectivity. Using 13 microsatellite markers, we analyzed the genetic structure of extant Oenanthe aquatica populations and their soil seed banks in a kettle hole system to uncover hidden connectivity among populations in time and space. Considerable spatial genetic structure and isolation-by-distance suggest limited gene flow between sites. Spatial isolation and patch size showed minor effects on genetic diversity. Genetic similarity found among extant populations and their seed banks suggests increased local recruitment, despite some evidence of migration and recent colonization. Results indicate stepping-stone dispersal across adjacent populations. Among permanent and ephemeral demes the resulting meta-population demography could be determined by source-sink dynamics. Overall, these spatiotemporal connectivity patterns support mainland-island dynamics in our system, highlighting the importance of persistent seed banks as enduring sources of genetic diversity.
How to not induce SNAs
(2023)
People respond faster to smaller numbers in their left space and to larger numbers in their right space. Here we argue that movements in space contribute to the formation of spatial-numerical associations (SNAs). We studied the impact of continuous isometric forces along the horizontal or vertical cardinal axes on SNAs while participants performed random number production and arithmetic verification tasks. Our results suggest that such isometric directional force do not suffice to induce SNAs.
Background
Machine learning models promise to support diagnostic predictions, but may not perform well in new settings. Selecting the best model for a new setting without available data is challenging. We aimed to investigate the transportability by calibration and discrimination of prediction models for cognitive impairment in simulated external settings with different distributions of demographic and clinical characteristics.
Methods
We mapped and quantified relationships between variables associated with cognitive impairment using causal graphs, structural equation models, and data from the ADNI study. These estimates were then used to generate datasets and evaluate prediction models with different sets of predictors. We measured transportability to external settings under guided interventions on age, APOE & epsilon;4, and tau-protein, using performance differences between internal and external settings measured by calibration metrics and area under the receiver operating curve (AUC).
Results
Calibration differences indicated that models predicting with causes of the outcome were more transportable than those predicting with consequences. AUC differences indicated inconsistent trends of transportability between the different external settings. Models predicting with consequences tended to show higher AUC in the external settings compared to internal settings, while models predicting with parents or all variables showed similar AUC.
Conclusions
We demonstrated with a practical prediction task example that predicting with causes of the outcome results in better transportability compared to anti-causal predictions when considering calibration differences. We conclude that calibration performance is crucial when assessing model transportability to external settings.
BackgroundIn spring of 2020, the Sars-CoV-2 incidence rate increased rapidly in Germany and around the world. Throughout the next 2 years, schools were temporarily closed and social distancing measures were put in place to slow the spread of the Covid-19 virus. Did these social restrictions and temporary school lockdowns affect children's physical fitness? The EMOTIKON project annually tests the physical fitness of all third-graders in the Federal State of Brandenburg, Germany. The tests assess cardiorespiratory endurance (6-min-run test), coordination (star-run test), speed (20-m sprint test), lower (powerLOW, standing long jump test), and upper (powerUP, ball-push test) limbs muscle power, and static balance (one-legged stance test with eyes closed). A total of 125,893 children were tested in the falls from 2016 to 2022. Primary analyses focused on 98,510 keyage third-graders (i.e., school enrollment according to the legal key date, aged 8 to 9 years) from 515 schools. Secondary analyses included 27,383 older-than-keyage third-graders (i.e., OTK, delayed school enrollment or repetition of a grade, aged 9 to 10 years), who have been shown to exhibit lower physical fitness than expected for their age. Linear mixed models fitted pre-pandemic quadratic secular trends, and took into account differences between children and schools.ResultsThird-graders exhibited lower cardiorespiratory endurance, coordination, speed and powerUP in the Covid pandemic cohorts (2020-2022) compared to the pre-pandemic cohorts (2016-2019). Children's powerLOW and static balance were higher in the pandemic cohorts compared to the pre-pandemic cohorts. From 2020 to 2021, coordination, powerLOW and powerUP further declined. Evidence for some post-pandemic physical fitness catch-up was restricted to powerUP. Cohen's |ds| for comparisons of the pandemic cohorts 2020-2022 with pre-pandemic cohorts 2016-2019 ranged from 0.02 for powerLOW to 0.15 for coordination. Within the pandemic cohorts, keyage children exhibited developmental losses ranging from approximately 1 month for speed to 5 months for cardiorespiratory endurance. For powerLOW and static balance, the positive pandemic effects translate to developmental gains of 1 and 7 months, respectively. Pre-pandemic secular trends may account for some of the observed differences between pandemic and pre-pandemic cohorts, especially in powerLOW, powerUP and static balance. The pandemic further increased developmental delays of OTK children in cardiorespiratory endurance, powerUP and balance.ConclusionsThe Covid-19 pandemic was associated with declines in several physical fitness components in German third-graders. Pandemic effects are still visible in 2022. Health-related interventions should specifically target those physical fitness components that were negatively affected by the pandemic (cardiorespiratory endurance, coordination, speed).
Metabolic engineering of microalgae offers a promising solution for sustainable biofuel production, and rational design of engineering strategies can be improved by employing metabolic models that integrate enzyme turnover numbers. However, the coverage of turnover numbers for Chlamydomonas reinhardtii, a model eukaryotic microalga accessible to metabolic engineering, is 17-fold smaller compared to the heterotrophic cell factory Saccharomyces cerevisiae. Here we generate quantitative protein abundance data of Chlamydomonas covering 2337 to 3708 proteins in various growth conditions to estimate in vivo maximum apparent turnover numbers. Using constrained-based modeling we provide proxies for in vivo turnover numbers of 568 reactions, representing a 10-fold increase over the in vitro data for Chlamydomonas. Integration of the in vivo estimates instead of in vitro values in a metabolic model of Chlamydomonas improved the accuracy of enzyme usage predictions. Our results help in extending the knowledge on uncharacterized enzymes and improve biotechnological applications of Chlamydomonas.
Spatial and temporal variation in perceived predation risk is an important determinant of movement and foraging activity of animals. Foraging in this landscape of fear, individuals need to decide where and when to move, and what resources to choose. Foraging theory predicts the outcome of these decisions based on energetic trade-offs, but complex interactions between perceived predation risk and preferences of foragers for certain functional traits of their resources are rarely considered. Here, we studied the interactive effects of perceived predation risk on food trait preferences and foraging behavior in bank voles (Myodes glareolus) in experimental landscapes. Individuals (n = 19) were subjected for periods of 24 h to two extreme, risk-uniform landscapes (either risky or safe), containing 25 discrete food patches, filled with seeds of four plant species in even amounts. Seeds varied in functional traits: size, nutrients, and shape. We evaluated whether and how risk modifies forager preference for functional traits. We also investigated whether perceived risk and distance from shelter affected giving-up density (GUD), time in patches, and number of patch visits. In safe landscapes, individuals increased time spent in patches, lowered GUD and visited distant patches more often compared to risky landscapes. Individuals preferred bigger seeds independent of risk, but in the safe treatment they preferred fat-rich over carb-rich seeds. Thus, higher densities of resource levels remained in risky landscapes, while in safe landscapes resource density was lower and less diverse due to selective foraging. Our results suggest that the interaction of perceived risk and dietary preference adds an additional layer to the cascading effects of a landscape of fear which affects biodiversity at resource level.
The detection of communities in graph datasets provides insight about a graph's underlying structure and is an important tool for various domains such as social sciences, marketing, traffic forecast, and drug discovery. While most existing algorithms provide fast approaches for community detection, their results usually contain strictly separated communities. However, most datasets would semantically allow for or even require overlapping communities that can only be determined at much higher computational cost. We build on an efficient algorithm, FOX, that detects such overlapping communities. FOX measures the closeness of a node to a community by approximating the count of triangles which that node forms with that community. We propose LAZYFOX, a multi-threaded adaptation of the FOX algorithm, which provides even faster detection without an impact on community quality. This allows for the analyses of significantly larger and more complex datasets. LAZYFOX enables overlapping community detection on complex graph datasets with millions of nodes and billions of edges in days instead of weeks. As part of this work, LAZYFOX's implementation was published and is available as a tool under an MIT licence at https://github.com/TimGarrels/LazyFox.
Protein-protein-interactions play an important role in many cellular functions. Quantitative non-invasive techniques are applied in living cells to evaluate such interactions, thereby providing a broader understanding of complex biological processes. Fluorescence fluctuation spectroscopy describes a group of quantitative microscopy approaches for the characterization of molecular interactions at single cell resolution. Through the obtained molecular brightness, it is possible to determine the oligomeric state of proteins. This is usually achieved by fusing fluorescent proteins (FPs) to the protein of interest. Recently, the number of novel green FPs has increased, with consequent improvements to the quality of fluctuation-based measurements. The photophysical behavior of FPs is influenced by multiple factors (including photobleaching, protonation-induced "blinking" and long-lived dark states). Assessing these factors is critical for selecting the appropriate fluorescent tag for live cell imaging applications. In this work, we focus on novel green FPs that are extensively used in live cell imaging. A systematic performance comparison of several green FPs in living cells under different pH conditions using Number & Brightness (N & B) analysis and scanning fluorescence correlation spectroscopy was performed. Our results show that the new FP Gamillus exhibits higher brightness at the cost of lower photostability and fluorescence probability (pf), especially at lower pH. mGreenLantern, on the other hand, thanks to a very high pf, is best suited for multimerization quantification at neutral pH. At lower pH, mEGFP remains apparently the best choice for multimerization investigation. These guidelines provide the information needed to plan quantitative fluorescence microscopy involving these FPs, both for general imaging or for protein-protein-interactions quantification via fluorescence fluctuation-based methods.
When two initially thermal many-body systems start to interact strongly, their transient states quickly become non-Gibbsian, even if the systems eventually equilibrate. To see beyond this apparent lack of structure during the transient regime, we use a refined notion of thermality, which we call g-local. A system is g-locally thermal if the states of all its small subsystems are marginals of global thermal states. We numerically demonstrate for two harmonic lattices that whenever the total system equilibrates in the long run, each lattice remains g-locally thermal at all times, including the transient regime. This is true even when the lattices have long-range interactions within them. In all cases, we find that the equilibrium is described by the generalized Gibbs ensemble, with three-dimensional lattices requiring special treatment due to their extended set of conserved charges. We compare our findings with the well-known two-temperature model. While its standard form is not valid beyond weak coupling, we show that at strong coupling it can be partially salvaged by adopting the concept of a g-local temperature.
Psychology and nutritional science research has highlighted the impact of negative emotions and cognitive load on calorie consumption behaviour using subjective questionnaires. Isolated studies in other domains objectively assess cognitive load without considering its effects on eating behaviour. This study aims to explore the potential for developing an integrated eating behaviour assistant system that incorporates cognitive load factors. Two experimental sessions were conducted using custom-developed experimentation software to induce different stimuli. During these sessions, we collected 30 h of physiological, food consumption, and affective states questionnaires data to automatically detect cognitive load and analyse its effect on food choice. Utilising grid search optimisation and leave-one-subject-out cross-validation, a support vector machine model achieved a mean classification accuracy of 85.12% for the two cognitive load tasks using eight relevant features. Statistical analysis was performed on calorie consumption and questionnaire data. Furthermore, 75% of the subjects with higher negative affect significantly increased consumption of specific foods after high-cognitive-load tasks. These findings offer insights into the intricate relationship between cognitive load, affective states, and food choice, paving the way for an eating behaviour assistant system to manage food choices during cognitive load. Future research should enhance system capabilities and explore real-world applications.
In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer. The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements.
This review discusses picosecond ultrasonics experiments using ultrashort hard x-ray probe pulses to extract the transient strain response of laser-excited nanoscopic structures from Bragg-peak shifts. This method provides direct, layer-specific, and quantitative information on the picosecond strain response for structures down to few-nm thickness. We model the transient strain using the elastic wave equation and express the driving stress using Gruneisen parameters stating that the laser-induced stress is proportional to energy density changes in the microscopic subsystems of the solid, i.e., electrons, phonons and spins. The laser-driven strain response can thus serve as an ultrafast proxy for local energy-density and temperature changes, but we emphasize the importance of the nanoscale morphology for an accurate interpretation due to the Poisson effect. The presented experimental use cases encompass ultrathin and opaque metal-heterostructures, continuous and granular nanolayers as well as negative thermal expansion materials, that each pose a challenge to established all-optical techniques.
Physical fitness of primary school children differs depending on their timing of school enrollment
(2023)
Previous research has shown that children who were enrolled to school according to the legal key date (i.e., keyage children, between eight and nine years in third grade) exhibited a linear physical fitness development in the ninth year of life. In contrast, children who were enrolled with a delay (i.e., older-than-keyage children [OTK], between nine and ten years in third grade) exhibited a lower physical fitness compared to what would be expected for their age. In these studies, cross-sectional age differences within third grade and timing of school enrollment were confounded. The present study investigated the longitudinal development of keyage and OTK children from third to fifth grade. This design also afforded a comparison of the two groups at the same average chronological age, that is a dissociation of the effects of timing of school enrollment and age. We tested six physical fitness components: cardiorespiratory endurance, coordination, speed, power of lower and upper limbs, and static balance. 1502 children (i.e., 1206 keyage and 296 OTK children) from 35 schools were tested in third, fourth, and fifth grade. Except for cardiorespiratory endurance, both groups developed from third to fourth and from fourth to fifth grade and keyage children outperformed OTK children at the average ages of 9.5 or 10.5 years. For cardiorespiratory endurance, there was no significant gain from fourth to fifth grade and keyage and OTK children did not differ significantly at 10.5 years of age. One reason for a delayed school enrollment could be that a child is (or is perceived as) biologically younger than their chronological age at the school entry examination, implying a negative correlation between chronological and biological age for OTK children. Indeed, a simple reflection of chronological age brought the developmental rate of the chronologically youngest OTK children in line with the developmental rate observed for keyage children, but did not eliminate all differences. The mapping of chronological and biological age of OTK children and other possible reasons for lower physical fitness of OTK children remain a task for future research.
The unmixed debris of Gaia-Sausage/Enceladus in the form of a pair of halo stellar overdensities
(2022)
In the first billion years after its formation, the galaxy underwent several mergers with dwarf satellites of various masses. The debris of Gaia-Sausage/Enceladus (GSE), the galaxy responsible for the last significant merger of the Milky Way, dominates the inner halo and has been suggested to be the progenitor of both the Hercules-Aquila Cloud (HAC) and Virgo Overdensity (VOD). We combine SEGUE, APOGEE, Gaia, and StarHorse distances to characterize the chemodynamical properties and verify the link between HAC, VOD, and GSE. We find that the orbital eccentricity distributions of the stellar overdensities and GSE are comparable. We also find that they have similar, strongly peaked, metallicity distribution functions, reinforcing the hypothesis of common origin. Furthermore, we show that HAC and VOD are indistinguishable from the prototypical GSE population within all chemical-abundance spaces analyzed. All these evidences combined provide a clear demonstration that the GSE merger is the main progenitor of the stellar populations found within these halo overdensities.
All plant cells are encased in primary cell walls that determine plant morphology, but also protect the cells against the environment. Certain cells also produce a secondary wall that supports mechanically demanding processes, such as maintaining plant body stature and water transport inside plants. Both these walls are primarily composed of polysaccharides that are arranged in certain patterns to support cell functions. A key requisite for patterned cell walls is the arrangement of cortical microtubules that may direct the delivery of wall polymers and/or cell wall producing enzymes to certain plasma membrane locations. Microtubules also steer the synthesis of cellulose-the load-bearing structure in cell walls-at the plasma membrane. The organization and behaviour of the microtubule array are thus of fundamental importance to cell wall patterns. These aspects are controlled by the coordinated effort of small GTPases that probably coordinate a Turing's reaction-diffusion mechanism to drive microtubule patterns. Here, we give an overview on how wall patterns form in the water-transporting xylem vessels of plants. We discuss systems that have been used to dissect mechanisms that underpin the xylem wall patterns, emphasizing the VND6 and VND7 inducible systems, and outline challenges that lay ahead in this field.
Efficient Removal of Tetracycline and Bisphenol A from Water with a New Hybrid Clay/TiO2 Composite
(2023)
New TiO2 hybrid composites were prepared fromkaolinclay, predried and carbonized biomass, and titanium tetraisopropoxideand explored for tetracycline (TET) and bisphenol A (BPA) removalfrom water. Overall, the removal rate is 84% for TET and 51% for BPA.The maximum adsorption capacities (q (m))are 30 and 23 mg/g for TET and BPA, respectively. These capacitiesare far greater than those obtained for unmodified TiO2. Increasing the ionic strength of the solution does not change theadsorption capacity of the adsorbent. pH changes only slightly changeBPA adsorption, while a pH > 7 significantly reduces the adsorptionof TET on the material. The Brouers-Sotolongo fractal modelbest describes the kinetic data for both TET and BPA adsorption, predictingthat the adsorption process occurs via a complex mechanism involvingvarious forces of attraction. Temkin and Freundlich isotherms, whichbest fit the equilibrium adsorption data for TET and BPA, respectively,suggest that adsorption sites are heterogeneous in nature. Overall,the composite materials are much more effective for TET removal fromaqueous solution than for BPA. This phenomenon is assigned to a differencein the TET/adsorbent interactions vs the BPA/adsorbent interactions:the decisive factor appears to be favorable electrostatic interactionsfor TET yielding a more effective TET removal.
The active global SARS-CoV-2 pandemic caused more than 426 million cases and 5.8 million deaths worldwide. The development of completely new drugs for such a novel disease is a challenging, time intensive process. Despite researchers around the world working on this task, no effective treatments have been developed yet. This emphasizes the importance of drug repurposing, where treatments are found among existing drugs that are meant for different diseases. A common approach to this is based on knowledge graphs, that condense relationships between entities like drugs, diseases and genes. Graph neural networks (GNNs) can then be used for the task at hand by predicting links in such knowledge graphs. Expanding on state-of-the-art GNN research, Doshi et al. recently developed the Dr-COVID model. We further extend their work using additional output interpretation strategies. The best aggregation strategy derives a top-100 ranking of 8,070 candidate drugs, 32 of which are currently being tested in COVID-19-related clinical trials. Moreover, we present an alternative application for the model, the generation of additional candidates based on a given pre-selection of drug candidates using collaborative filtering. In addition, we improved the implementation of the Dr-COVID model by significantly shortening the inference and pre-processing time by exploiting data-parallelism. As drug repurposing is a task that requires high computation and memory resources, we further accelerate the post-processing phase using a new emerging hardware-we propose a new approach to leverage the use of high-capacity Non-Volatile Memory for aggregate drug ranking.
Understanding the origin of inefficient photocurrent generation in organic solar cells with low energy offset remains key to realizing high-performance donor-acceptor systems. Here, we probe the origin of field-dependent free-charge generation and photoluminescence in wnon-fullereneacceptor (NFA)-based organic solar cells using the polymer PM6 and the NFA Y5-a non-halogenated sibling to Y6, with a smaller energetic offset to PM6. By performing time-delayed collection field (TDCF) measurements on a variety of samples with different electron transport layers and active layer thickness, we show that the fill factor and photocurrent are limited by field-dependent free charge generation in the bulk of the blend. We also introduce a new method of TDCF called m-TDCF to prove the absence of artifacts from non-geminate recombination of photogenerated and dark charge carriers near the electrodes. We then correlate free charge generation with steady-state photoluminescence intensity and find perfect anticorrelation between these two properties. Through this, we conclude that photocurrent generation in this low-offset system is entirely controlled by the field-dependent dissociation of local excitons into charge-transfer states. (c) 2023 Author(s).
Ore precipitation in porphyry copper systems is generally characterized by metal zoning (Cu-Mo to Zn-Pb-Ag), which is suggested to be variably related to solubility decreases during fluid cooling, fluid-rock interactions, partitioning during fluid phase separation and mixing with external fluids. Here, we present new advances of a numerical process model by considering published constraints on the temperature- and salinity-dependent solubility of Cu, Pb and Zn in the ore fluid. We quantitatively investigate the roles of vapor-brine separation, halite saturation, initial metal contents, fluid mixing and remobilization as first-order controls of the physical hydrology on ore formation. The results show that the magmatic vapor and brine phases ascend with different residence times but as miscible fluid mixtures, with salinity increases generating metal-undersaturated bulk fluids. The release rates of magmatic fluids affect the location of the thermohaline fronts, leading to contrasting mechanisms for ore precipitation: higher rates result in halite saturation without significant metal zoning, lower rates produce zoned ore shells due to mixing with meteoric water. Varying metal contents can affect the order of the final metal precipitation sequence. Redissolution of precipitated metals results in zoned ore shell patterns in more peripheral locations and also decouples halite saturation from ore precipitation.
We present a Reduced Order Model (ROM) which exploits recent developments in Physics Informed Neural Networks (PINNs) for solving inverse problems for the Navier-Stokes equations (NSE). In the proposed approach, the presence of simulated data for the fluid dynamics fields is assumed. A POD-Galerkin ROM is then constructed by applying POD on the snapshots matrices of the fluid fields and performing a Galerkin projection of the NSE (or the modified equations in case of turbulence modeling) onto the POD reduced basis. A POD-Galerkin PINN ROM is then derived by introducing deep neural networks which approximate the reduced outputs with the input being time and/or parameters of the model. The neural networks incorporate the physical equations (the POD-Galerkin reduced equations) into their structure as part of the loss function. Using this approach, the reduced model is able to approximate unknown parameters such as physical constants or the boundary conditions. A demonstration of the applicability of the proposed ROM is illustrated by three cases which are the steady flow around a backward step, the flow around a circular cylinder and the unsteady turbulent flow around a surface mounted cubic obstacle.
The oil palm (Elaeis guineensis Jacq.) produces a large amount of oil from the fruit. However, increasing the oil production in this fruit is still challenging. A recent study has shown that starch metabolism is essential for oil synthesis in fruit-producing species. Therefore, the transcriptomic analysis by RNA-seq was performed to observe gene expression alteration related to starch metabolism genes throughout the maturity stages of oil palm fruit with different oil yields. Gene expression profiles were examined with three different oil yields group (low, medium, and high) at six fruit development phases (4, 8, 12, 16, 20, and 22 weeks after pollination). We successfully identified and analyzed differentially expressed genes in oil palm mesocarps during development. The results showed that the transcriptome profile for each developmental phase was unique. Sucrose flux to the mesocarp tissue, rapid starch turnover, and high glycolytic activity have been identified as critical factors for oil production in oil palms. For starch metabolism and the glycolytic pathway, we identified specific gene expressions of enzyme isoforms (isozymes) that correlated with oil production, which may determine the oil content. This study provides valuable information for creating new high-oil-yielding palm varieties via breeding programs or genome editing approaches.
Background
Self-regulation (SR) as the ability to regulate one's own physical state, emotions, cognitions, and behavior, is considered to play a pivotal role in the concurrent and subsequent mental and physical health of an individual. Although SR skills encompass numerous sub-facets, previous research has often focused on only one or a few of these sub-facets, and only rarely on adolescence. Therefore, little is known about the development of the sub-facets, their interplay, and their specific contributions to future developmental outcomes, particularly in adolescence. To fill these research gaps, this study aims to prospectively examine (1) the development of SR and (2) their influence on adolescent-specific developmental outcomes in a large community sample.
Methods/design
Based on previously collected data from the Potsdam Intrapersonal Developmental Risk (PIER) study with three measurement points, the present prospective, longitudinal study aims to add a fourth measurement point (PIERYOUTH). We aim to retain at least 1074 participants now between 16 and 23 years of the initially 1657 participants (6-11 years of age at the first measurement point in 2012/2013; 52.2% female). The study will continue to follow a multi-method (questionnaires, physiological assessments, performance-based computer tasks), multi-facet (assessing various domains of SR), and multi-rater (self-, parent-, and teacher-report) approach. In addition, a broad range of adolescent-specific developmental outcomes is considered. In doing so, we will cover the development of SR and relevant outcomes over the period of 10 years. In addition, we intend to conduct a fifth measurement point (given prolonged funding) to investigate development up to young adulthood.
Discussion
With its broad and multimethodological approach, PIERYOUTH aims to contribute to a deeper understanding of the development and role of various SR sub-facets from middle childhood to adolescence. The large sample size and low drop-out rates in the first three measurements points form a sound database for our present prospective research.Trial registration German Clinical Trials Register, registration number DRKS00030847.
Keeping cool on hot days
(2023)
Long-lived organisms are likely to respond to a rapidly changing climate with behavioral flexibility. Animals inhabiting the arid parts of southern Africa face a particularly rapid rise in temperature which in combination with food and water scarcity places substantial constraints on the ability of animals to tolerate heat. We investigated how three species of African antelope-springbok Antidorcas marsupialis, kudu Tragelaphus strepsiceros and eland T. oryx-differing in body size, habitat preference and movement ecology, change their activity in response to extreme heat in an arid savanna. Serving as a proxy for activity, dynamic body acceleration data recorded every five minutes were analyzed for seven to eight individuals per species for the three hottest months of the year. Activity responses to heat during the hottest time of day (the afternoons) were investigated and diel activity patterns were compared between hot and cool days. Springbok, which prefer open habitat, are highly mobile and the smallest of the species studied, showed the greatest decrease in activity with rising temperature. Furthermore, springbok showed reduced mean activity over the 24 h cycle on hot days compared to cool days. Large-bodied eland seemed less affected by afternoon heat than springbok. While eland also reduced diurnal activity on hot days compared to cool days, they compensated for this by increasing nocturnal activity, possibly because their predation risk is lower. Kudu, which are comparatively sedentary and typically occupy shady habitat, seemed least affected during the hottest time of day and showed no appreciable difference in diel activity patterns between hot and cool days. The interplay between habitat preference, body size, movement patterns, and other factors seems complex and even sub-lethal levels of heat stress have been shown to impact an animal's long-term survival and reproduction. Thus, differing heat tolerances among species could result in a shift in the composition of African herbivore communities as temperatures continue to rise, with significant implications for economically important wildlife-based land use and conservation.
Starch has been a convenient, economically important polymer with substantial applications in the food and processing industry. However, native starches present restricted applications, which hinder their industrial usage. Therefore, modification of starch is carried out to augment the positive characteristics and eliminate the limitations of the native starches. Modifications of starch can result in generating novel polymers with numerous functional and value-added properties that suit the needs of the industry. Here, we summarize the possible starch modifications in planta and outside the plant system (physical, chemical, and enzymatic) and their corresponding applications. In addition, this review will highlight the implications of each starch property adjustment.
Students enter school with a vast range of individual differences, resulting from the complex interplay between genetic dispositions and unequal environmental conditions. Schools thus face the challenge of organizing instruction and providing equal opportunities for students with diverse needs. Schools have traditionally managed student heterogeneity by sorting students both within and between schools according to their academic ability. However, empirical evidence suggests that such tracking approaches increase inequalities. In more recent years, driven largely by technological advances, there have been calls to embrace students' individual differences in the classroom and to personalize students' learning experiences. A central justification for personalized learning is its potential to improve educational equity. In this paper, we discuss whether and under which conditions personalized learning can indeed increase equity in K-12 education by bringing together empirical and theoretical insights from different fields, including the learning sciences, philosophy, psychology, and sociology. We distinguish between different conceptions of equity and argue that personalized learning is unlikely to result in "equality of outcomes" and, by definition, does not provide "equality of inputs". However, if implemented in a high-quality way, personalized learning is in line with "adequacy" notions of equity, which aim to equip all students with the basic competencies to participate in society as active members and to live meaningful lives.
Knowledge on the response of sediment export to recent climate change in glacierized areas in the European Alps is limited, primarily because long-term records of suspended sediment concentrations (SSCs) are scarce. Here we tested the estimation of sediment export of the past five decades using quantile regression forest (QRF), a nonparametric, multivariate regression based on random forest. The regression builds on short-term records of SSCs and long records of the most important hydroclimatic drivers (discharge, precipitation and air temperature - QPT). We trained independent models for two nested and partially glacier-covered catchments, Vent (98 km(2)) and Vernagt (11.4 km(2)), in the upper otztal in Tyrol, Austria (1891 to 3772 m a.s.l.), where available QPT records start in 1967 and 1975. To assess temporal extrapolation ability, we used two 2-year SSC datasets at gauge Vernagt, which are almost 20 years apart, for a validation. For Vent, we performed a five-fold cross-validation on the 15 years of SSC measurements. Further, we quantified the number of days where predictors exceeded the range represented in the training dataset, as the inability to extrapolate beyond this range is a known limitation of QRF. Finally, we compared QRF performance to sediment rating curves (SRCs). We analyzed the modeled sediment export time series, the predictors and glacier mass balance data for trends (Mann-Kendall test and Sen's slope estimator) and step-like changes (using the widely applied Pettitt test and a complementary Bayesian approach).Our validation at gauge Vernagt demonstrated that QRF performs well in estimating past daily sediment export (Nash-Sutcliffe efficiency (NSE) of 0.73) and satisfactorily for SSCs (NSE of 0.51), despite the small training dataset. The temporal extrapolation ability of QRF was superior to SRCs, especially in periods with high-SSC events, which demonstrated the ability of QRF to model threshold effects. Days with high SSCs tended to be underestimated, but the effect on annual yields was small. Days with predictor exceedances were rare, indicating a good representativity of the training dataset. Finally, the QRF reconstruction models outperformed SRCs by about 20 percent points of the explained variance.Significant positive trends in the reconstructed annual suspended sediment yields were found at both gauges, with distinct step-like increases around 1981. This was linked to increased glacier melt, which became apparent through step-like increases in discharge at both gauges as well as change points in mass balances of the two largest glaciers in the Vent catchment. We identified exceptionally high July temperatures in 1982 and 1983 as a likely cause. In contrast, we did not find coinciding change points in precipitation. Opposing trends at the two gauges after 1981 suggest different timings of "peak sediment". We conclude that, given large-enough training datasets, the presented QRF approach is a promising tool with the ability to deepen our understanding of the response of high-alpine areas to decadal climate change.
Background:
Contamination detection is a important step that should be carefully considered in early stages when designing and performing microbiome studies to avoid biased outcomes. Detecting and removing true contaminants is challenging, especially in low-biomass samples or in studies lacking proper controls. Interactive visualizations and analysis platforms are crucial to better guide this step, to help to identify and detect noisy patterns that could potentially be contamination. Additionally, external evidence, like aggregation of several contamination detection methods and the use of common contaminants reported in the literature, could help to discover and mitigate contamination.
Results:
We propose GRIMER, a tool that performs automated analyses and generates a portable and interactive dashboard integrating annotation, taxonomy, and metadata. It unifies several sources of evidence to help detect contamination. GRIMER is independent of quantification methods and directly analyzes contingency tables to create an interactive and offline report. Reports can be created in seconds and are accessible for nonspecialists, providing an intuitive set of charts to explore data distribution among observations and samples and its connections with external sources. Further, we compiled and used an extensive list of possible external contaminant taxa and common contaminants with 210 genera and 627 species reported in 22 published articles.
Conclusion:
GRIMER enables visual data exploration and analysis, supporting contamination detection in microbiome studies. The tool and data presented are open source and available at https://gitlab.com/dacs-hpi/grimer.
Background
The aggregation of a series of N-of-1 trials presents an innovative and efficient study design, as an alternative to traditional randomized clinical trials. Challenges for the statistical analysis arise when there is carry-over or complex dependencies of the treatment effect of interest.
Methods
In this study, we evaluate and compare methods for the analysis of aggregated N-of-1 trials in different scenarios with carry-over and complex dependencies of treatment effects on covariates. For this, we simulate data of a series of N-of-1 trials for Chronic Nonspecific Low Back Pain based on assumed causal relationships parameterized by directed acyclic graphs. In addition to existing statistical methods such as regression models, Bayesian Networks, and G-estimation, we introduce a carry-over adjusted parametric model (COAPM).
Results
The results show that all evaluated existing models have a good performance when there is no carry-over and no treatment dependence. When there is carry-over, COAPM yields unbiased and more efficient estimates while all other methods show some bias in the estimation. When there is known treatment dependence, all approaches that are capable to model it yield unbiased estimates. Finally, the efficiency of all methods decreases slightly when there are missing values, and the bias in the estimates can also increase.
Conclusions
This study presents a systematic evaluation of existing and novel approaches for the statistical analysis of a series of N-of-1 trials. We derive practical recommendations which methods may be best in which scenarios.
Graphene is well-knownfor its unique combination of electricaland mechanical properties. However, its vanishing band gap limitsthe use of graphene in microelectronics. Covalent functionalizationof graphene has been a common approach to address this critical issueand introduce a band gap. In this Article, we systematically analyzethe functionalization of single-layer graphene (SLG) and bilayer graphene(BLG) with methyl (CH3) using periodic density functionaltheory (DFT) at the PBE+D3 level of theory. We also include a comparisonof methylated single-layer and bilayer graphene, as well as a discussionof different methylation options (radicalic, cationic, and anionic).For SLG, methyl coverages ranging from 1/8 to 1/1, (i.e.,the fully methylated analogue of graphane) are considered. We findthat up to a coverage theta of 1/2, graphene readily accepts CH3, with neighbor CH3 groups preferring trans positions. Above theta = 1/2, the tendency to accept further CH3 weakens and the lattice constant increases. The band gapbehaves less regularly, but overall it increases with increasing methylcoverage. Thus, methylated graphene shows potential for developingband gap-tuned microelectronics devices and may offer further functionalizationoptions. To guide in the interpretation of methylation experiments,vibrational signatures of various species are characterized by normal-modeanalysis (NMA), their vibrational density of states (VDOS), and infrared(IR) spectra, the latter two are obtained from ab initio moleculardynamics (AIMD) in combination with a velocity-velocity autocorrelationfunction (VVAF) approach.
Genomic and epigenomic determinants of heat stress-induced transcriptional memory in Arabidopsis
(2023)
Background
Transcriptional regulation is a key aspect of environmental stress responses. Heat stress induces transcriptional memory, i.e., sustained induction or enhanced re-induction of transcription, that allows plants to respond more efficiently to a recurrent HS. In light of more frequent temperature extremes due to climate change, improving heat tolerance in crop plants is an important breeding goal. However, not all heat stress-inducible genes show transcriptional memory, and it is unclear what distinguishes memory from non-memory genes. To address this issue and understand the genome and epigenome architecture of transcriptional memory after heat stress, we identify the global target genes of two key memory heat shock transcription factors, HSFA2 and HSFA3, using time course ChIP-seq.
Results
HSFA2 and HSFA3 show near identical binding patterns. In vitro and in vivo binding strength is highly correlated, indicating the importance of DNA sequence elements. In particular, genes with transcriptional memory are strongly enriched for a tripartite heat shock element, and are hallmarked by several features: low expression levels in the absence of heat stress, accessible chromatin environment, and heat stress-induced enrichment of H3K4 trimethylation. These results are confirmed by an orthogonal transcriptomic data set using both de novo clustering and an established definition of memory genes.
Conclusions
Our findings provide an integrated view of HSF-dependent transcriptional memory and shed light on its sequence and chromatin determinants, enabling the prediction and engineering of genes with transcriptional memory behavior.
Economic evaluation of digital therapeutic care apps for unsupervised treatment of low back pain
(2023)
Background:
Digital therapeutic care (DTC) programs are unsupervised app-based treatments that provide video exercises and educational material to patients with nonspecific low back pain during episodes of pain and functional disability. German statutory health insurance can reimburse DTC programs since 2019, but evidence on efficacy and reasonable pricing remains scarce. This paper presents a probabilistic sensitivity analysis (PSA) to evaluate the efficacy and cost-utility of a DTC app against treatment as usual (TAU) in Germany.
Objective:
The aim of this study was to perform a PSA in the form of a Monte Carlo simulation based on the deterministic base case analysis to account for model assumptions and parameter uncertainty. We also intend to explore to what extent the results in this probabilistic analysis differ from the results in the base case analysis and to what extent a shortage of outcome data concerning quality-of-life (QoL) metrics impacts the overall results.
Methods:
The PSA builds upon a state-transition Markov chain with a 4-week cycle length over a model time horizon of 3 years from a recently published deterministic cost-utility analysis. A Monte Carlo simulation with 10,000 iterations and a cohort size of 10,000 was employed to evaluate the cost-utility from a societal perspective. Quality-adjusted life years (QALYs) were derived from Veterans RAND 6-Dimension (VR-6D) and Short-Form 6-Dimension (SF-6D) single utility scores. Finally, we also simulated reducing the price for a 3-month app prescription to analyze at which price threshold DTC would result in being the dominant strategy over TAU in Germany.
Results:
The Monte Carlo simulation yielded on average a euro135.97 (a currency exchange rate of EUR euro1=US $1.069 is applicable) incremental cost and 0.004 incremental QALYs per person and year for the unsupervised DTC app strategy compared to in-person physiotherapy in Germany. The corresponding incremental cost-utility ratio (ICUR) amounts to an additional euro34,315.19 per additional QALY. DTC yielded more QALYs in 54.96% of the iterations. DTC dominates TAU in 24.04% of the iterations for QALYs. Reducing the app price in the simulation from currently euro239.96 to euro164.61 for a 3-month prescription could yield a negative ICUR and thus make DTC the dominant strategy, even though the estimated probability of DTC being more effective than TAU is only 54.96%.
Conclusions:
Decision-makers should be cautious when considering the reimbursement of DTC apps since no significant treatment effect was found, and the probability of cost-effectiveness remains below 60% even for an infinite willingness-to-pay threshold. More app-based studies involving the utilization of QoL outcome parameters are urgently needed to account for the low and limited precision of the available QoL input parameters, which are crucial to making profound recommendations concerning the cost-utility of novel apps.
Reliability of the active knee joint position sense test and influence of limb dominance and sex
(2023)
The output of a sensorimotor performance can be measured with the joint position sense (JPS) test. However, investigations of leg dominance, sex and quality measures on this test are limited. Therefore, these potential influencing factors as well as reliability and consistency measures were evaluated for angular reproduction performance and neuromuscular activity during the active knee JPS test in healthy participants. Twenty healthy participants (10 males; 10 females; age 29 +/- 8 years; height 165 +/- 39 cm; body mass 69 +/- 13 kg) performed a seated knee JPS test with a target angle of 50 degrees. Measurements were conducted in two sessions separated by two weeks and consisted of two blocks of continuous angular reproduction (three minutes each block). The difference between reproduced and target angle was identified as angular error measured by an electrogoniometer. During reproduction, the neuromuscular activity of the quadriceps muscle was assessed by surface electromyography. Neuromuscular activity was normalized to submaximal voluntary contraction (subMVC) and displayed per muscle and movement phase. Differences between leg dominance and sex were calculated using Friedman-test (alpha = 0.05). Reliability measures including intraclass correlation coefficient (ICC), Bland-Altman analysis (bias +/- limits of agreement (LoA)) and minimal detectable change (MDC) were analysed. No significant differences between leg dominance and sex were found in angular error and neuromuscular activity. Angular error demonstrated inter-session ICC scores of 0.424 with a bias of 2.4 degrees (+/- 2.4 degrees LoA) as well as MDC of 6.8 degrees and moderate intra-session ICC (0.723) with a bias of 1.4 degrees (+/- 1.65 degrees LoA) as well as MDC of 4.7 degrees. Neuromuscular activity for all muscles and movement phases illustrated inter-session ICC ranging from 0.432 to 0.809 with biases between - 2.5 and 13.6% subMVC and MDC from 13.4 to 63.9% subMVC. Intra-session ICC ranged from 0.705 to 0.987 with biases of - 7.7 to 2.4% subMVC and MDC of 2.7 to 46.5% subMVC. Leg dominance and sex seem not to influence angular reproduction performance and neuromuscular activity. Poor to excellent relative reliability paired with an acceptable consistency confirm findings of previous studies. Comparisons to pathological populations should be conducted with caution.
Poema
(2023)
POEMA ist ein komparatistisch angelegtes Jahrbuch, das sich der systematischen Erforschung von Lyrik und Gedicht widmet. Es richtet sich an Fachwissenschaftlerinnen und Fachwissenschaftler aller Philologien wie auch der mit anderen Kunstformen befassten Wissenschaften und der philosophischen Ästhetik. POEMA erscheint als Open-Access-Journal wie auch als Print-on-Demand-Fassung im Universitätsverlag Kiel | Kiel University Publishing. Die wissenschaftlichen Beiträge werden in einem double-blind Peer-Review-Verfahren begutachtet.
Quinoa (Chenopodium quinoa Willd.) is an herbaceous annual crop of the amaranth family (Amaranthaceae). It is increasingly cultivated for its nutritious grains, which are rich in protein and essential amino acids, lipids, and minerals. Quinoa exhibits a high tolerance towards various abiotic stresses including drought and salinity, which supports its agricultural cultivation under climate change conditions. The use of quinoa grains is compromised by anti-nutritional saponins, a terpenoid class of secondary metabolites deposited in the seed coat; their removal before consumption requires extensive washing, an economically and environmentally unfavorable process; or their accumulation can be reduced through breeding. In this study, we analyzed the seed metabolomes, including amino acids, fatty acids, and saponins, from 471 quinoa cultivars, including two related species, by liquid chromatography - mass spectrometry. Additionally, we determined a large number of agronomic traits including biomass, flowering time, and seed yield. The results revealed considerable diversity between genotypes and provide a knowledge base for future breeding or genome editing of quinoa.
The heat is on
(2023)
Climate conditions severely impact the activity and, consequently, the fitness of wildlife species across the globe. Wildlife can respond to new climatic conditions, but the pace of human-induced change limits opportunities for adaptation or migration. Thus, how these changes affect behavior, movement patterns, and activity levels remains unclear. In this study, we investigate how extreme weather conditions affect the activity of European hares (Lepus europaeus) during their peak reproduction period. When hares must additionally invest energy in mating, prevailing against competitors, or lactating, we investigated their sensitivities to rising temperatures, wind speed, and humidity. To quantify their activity, we used the overall dynamic body acceleration (ODBA) calculated from tri-axial acceleration measurements of 33 GPS-collared hares. Our analysis revealed that temperature, humidity, and wind speed are important in explaining changes in activity, with a strong response for high temperatures above 25 & DEG;C and the highest change in activity during temperature extremes of over 35 & DEG;C during their inactive period. Further, we found a non-linear relationship between temperature and activity and an interaction of activity changes between day and night. Activity increased at higher temperatures during the inactive period (day) and decreased during the active period (night). This decrease was strongest during hot tropical nights. At a stage of life when mammals such as hares must substantially invest in reproduction, the sensitivity of females to extreme temperatures was particularly pronounced. Similarly, both sexes increased their activity at high humidity levels during the day and low wind speeds, irrespective of the time of day, while the effect of humidity was stronger for males. Our findings highlight the importance of understanding the complex relationships between extreme weather conditions and mammal behavior, critical for conservation and management. With ongoing climate change, extreme weather events such as heat waves and heavy rainfall are predicted to occur more often and last longer. These events will directly impact the fitness of hares and other wildlife species and hence the population dynamics of already declining populations across Europe.