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Caenorhabditis elegans (C. elegans) is gaining recognition and importance as an organismic model for toxicity testing in line with the 3Rs principle (replace, reduce, refine). In this study, we explored the use of C. elegans to examine the toxicities of alkylating sulphur mustard analogues, specifically the monofunctional agent 2-chloroethyl-ethyl sulphide (CEES) and the bifunctional, crosslinking agent mechlorethamine (HN2). We exposed wild-type worms at different life cycle stages (from larvae L1 to adulthood day 10) to CEES or HN2 and scored their viability 24 h later. The susceptibility of C. elegans to CEES and HN2 paralleled that of human cells, with HN2 exhibiting higher toxicity than CEES, reflected in LC50 values in the high µM to low mM range. Importantly, the effects were dependent on the worms’ developmental stage as well as organismic age: the highest susceptibility was observed in L1, whereas the lowest was observed in L4 worms. In adult worms, susceptibility to alkylating agents increased with advanced age, especially to HN2. To examine reproductive effects, L4 worms were exposed to CEES and HN2, and both the offspring and the percentage of unhatched eggs were assessed. Moreover, germline apoptosis was assessed by using ced-1p::GFP (MD701) worms. In contrast to concentrations that elicited low toxicities to L4 worms, CEES and HN2 were highly toxic to germline cells, manifesting as increased germline apoptosis as well as reduced offspring number and percentage of eggs hatched. Again, HN2 exhibited stronger effects than CEES. Compound specificity was also evident in toxicities to dopaminergic neurons–HN2 exposure affected expression of dopamine transporter DAT-1 (strain BY200) at lower concentrations than CEES, suggesting a higher neurotoxic effect. Mechanistically, nicotinamide adenine dinucleotide (NAD+) has been linked to mustard agent toxicities. Therefore, the NAD+-dependent system was investigated in the response to CEES and HN2 treatment. Overall NAD+ levels in worm extracts were revealed to be largely resistant to mustard exposure except for high concentrations, which lowered the NAD+ levels in L4 worms 24 h post-treatment. Interestingly, however, mutant worms lacking components of NAD+-dependent pathways involved in genome maintenance, namely pme-2, parg-2, and sirt-2.1 showed a higher and compound-specific susceptibility, indicating an active role of NAD+ in genotoxic stress response. In conclusion, the present results demonstrate that C. elegans represents an attractive model to study the toxicology of alkylating agents, which supports its use in mechanistic as well as intervention studies with major strength in the possibility to analyze toxicities at different life cycle stages.
Introduction Climbing is an increasingly popular activity and imposes specific physiological demands on the human body, which results in unique injury presentations. Of particular concern are overuse injuries (non-traumatic injuries). These injuries tend to present in the upper body and might be preventable with adequate knowledge of risk factors which could inform about injury prevention strategies. Research in this area has recently emerged but has yet to be synthesized comprehensively. Therefore, the aim of this study was to conduct a systematic review of the potential risk factors and injury prevention strategies for overuse injuries in adult climbers.
Methods This systematic review was conducted in accordance with the PRISMA guidelines. Databases were searched systematically, and articles were deemed eligible based upon specific criteria. Research included was original and peer-reviewed, involving climbers, and published in English, German or Czech. Outcomes included overuse injury, and at least one or more variable indicating potential risk factors or injury prevention strategies. The methodological quality of the included studies was assessed with the Downs and Black Quality Index. Data were extracted from included studies and reported descriptively for population, climbing sport type, study design, injury definition and incidence/prevalence, risk factors, and injury prevention strategies.
Results Out of 1,183 records, a total of 34 studies were included in the final analysis. Higher climbing intensity, bouldering, reduced grip/finger strength, use of a “crimp” grip, and previous injury were associated with an increased risk of overuse injury. Additionally, a strength training intervention prevented shoulder and elbow injuries. BMI/body weight, warm up/cool downs, stretching, taping and hydration were not associated with risk of overuse injury. The evidence for the risk factors of training volume, age/years of climbing experience, and sex was conflicting.
Discussion This review presents several risk factors which appear to increase the risk of overuse injury in climbers. Strength and conditioning, load management, and climbing technique could be targeted in injury prevention programs, to enhance the health and wellbeing of climbing athletes. Further research is required to investigate the conflicting findings reported across included studies, and to investigate the effectiveness of injury prevention programs.
Systematic Review Registrationhttps://www.crd.york.ac.uk/, PROSPERO (CRD42023404031).
The plasma membrane of mammalian cells links transmembrane receptors, various structural components, and membrane-binding proteins to subcellular processes, allowing inter- and intracellular communication. Therefore, membrane-binding proteins, together with structural components such as actin filaments, modulate the cell membrane in their flexibility, stiffness, and curvature. Investigating membrane components and curvature in cells remains challenging due to the diffraction limit in light microscopy. Preparation of 5–15-nm-thin plasma membrane sheets and subsequent inspection by metal replica transmission electron microscopy (TEM) reveal detailed information about the cellular membrane topology, including the structure and curvature. However, electron microscopy cannot identify proteins associated with specific plasma membrane domains. Here, we describe a novel adaptation of correlative super-resolution light microscopy and platinum replica TEM (CLEM-PREM), allowing the analysis of plasma membrane sheets with respect to their structural details, curvature, and associated protein composition. We suggest a number of shortcuts and troubleshooting solutions to contemporary PREM protocols. Thus, implementation of super-resolution stimulated emission depletion (STED) microscopy offers significant reduction in sample preparation time and reduced technical challenges for imaging and analysis. Additionally, highly technical challenges associated with replica preparation and transfer on a TEM grid can be overcome by scanning electron microscopy (SEM) imaging. The combination of STED microscopy and platinum replica SEM or TEM provides the highest spatial resolution of plasma membrane proteins and their underlying membrane and is, therefore, a suitable method to study cellular events like endocytosis, membrane trafficking, or membrane tension adaptations.
Introduction Flux phenotypes from different organisms and growth conditions allow better understanding of differential metabolic networks functions. Fluxes of metabolic reactions represent the integrated outcome of transcription, translation, and post-translational modifications, and directly affect growth and fitness. However, fluxes of intracellular metabolic reactions cannot be directly measured, but are estimated via metabolic flux analysis (MFA) that integrates data on isotope labeling patterns of metabolites with metabolic models. While the application of metabolomics technologies in photosynthetic organisms have resulted in unprecedented data from 13CO2-labeling experiments, the bottleneck in flux estimation remains the application of isotopically nonstationary MFA (INST-MFA). INST-MFA entails fitting a (large) system of coupled ordinary differential equations, with metabolite pools and reaction fluxes as parameters. Here, we focus on the Calvin-Benson cycle (CBC) as a key pathway for carbon fixation in photosynthesizing organisms and ask if approaches other than classical INST-MFA can provide reliable estimation of fluxes for reactions comprising this pathway.
Methods First, we show that flux estimation with the labeling patterns of all CBC intermediates can be formulated as a single constrained regression problem, avoiding the need for repeated simulation of time-resolved labeling patterns.
Results We then compare the flux estimates of the simulation-free constrained regression approach with those obtained from the classical INST-MFA based on labeling patterns of metabolites from the microalgae Chlamydomonas reinhardtii, Chlorella sorokiniana and Chlorella ohadii under different growth conditions.
Discussion Our findings indicate that, in data-rich scenarios, simulation-free regression-based approaches provide a suitable alternative for flux estimation from classical INST-MFA since we observe a high qualitative agreement (rs=0.89) to predictions obtained from INCA, a state-of-the-art tool for INST-MFA.
The deficiency of a (bio)chemical reaction network can be conceptually interpreted as a measure of its ability to support exotic dynamical behavior and/or multistationarity. The classical definition of deficiency relates to the capacity of a network to permit variations of the complex formation rate vector at steady state, irrespective of the network kinetics. However, the deficiency is by definition completely insensitive to the fine details of the directionality of reactions as well as bounds on reaction fluxes. While the classical definition of deficiency can be readily applied in the analysis of unconstrained, weakly reversible networks, it only provides an upper bound in the cases where relevant constraints on reaction fluxes are imposed. Here we propose the concept of effective deficiency, which provides a more accurate assessment of the network’s capacity to permit steady state variations at the complex level for constrained networks of any reversibility patterns. The effective deficiency relies on the concept of nonstoichiometric balanced complexes, which we have already shown to be present in real-world biochemical networks operating under flux constraints. Our results demonstrate that the effective deficiency of real-world biochemical networks is smaller than the classical deficiency, indicating the effects of reaction directionality and flux bounds on the variation of the complex formation rate vector at steady state.
HARE
(2023)
Sensor-based human activity recognition is becoming ever more prevalent. The increasing importance of distinguishing human movements, particularly in healthcare, coincides with the advent of increasingly compact sensors. A complex sequence of individual steps currently characterizes the activity recognition pipeline. It involves separate data collection, preparation, and processing steps, resulting in a heterogeneous and fragmented process. To address these challenges, we present a comprehensive framework, HARE, which seamlessly integrates all necessary steps. HARE offers synchronized data collection and labeling, integrated pose estimation for data anonymization, a multimodal classification approach, and a novel method for determining optimal sensor placement to enhance classification results. Additionally, our framework incorporates real-time activity recognition with on-device model adaptation capabilities. To validate the effectiveness of our framework, we conducted extensive evaluations using diverse datasets, including our own collected dataset focusing on nursing activities. Our results show that HARE’s multimodal and on-device trained model outperforms conventional single-modal and offline variants. Furthermore, our vision-based approach for optimal sensor placement yields comparable results to the trained model. Our work advances the field of sensor-based human activity recognition by introducing a comprehensive framework that streamlines data collection and classification while offering a novel method for determining optimal sensor placement.
Several lines of research have demonstrated spatial-numerical associations in both adults and children, which are thought to be based on a spatial representation of numerical information in the form of a mental number line. The acquisition of increasingly precise mental number line representations is assumed to support arithmetic learning in children. It is further suggested that sensorimotor experiences shape the development of number concepts and arithmetic learning, and that mental arithmetic can be characterized as “motion along a path” and might constitute shifts in attention along the mental number line. The present study investigated whether movements in physical space influence mental arithmetic in primary school children, and whether the expected effect depends on concurrency of body movements and mental arithmetic. After turning their body towards the left or right, 48 children aged 8 to 10 years solved simple subtraction and addition problems. Meanwhile, they either walked or stood still and looked towards the respective direction. We report a congruency effect between body orientation and operation type, i.e., higher performance for the combinations leftward orientation and subtraction and rightward orientation and addition. We found no significant difference between walking and looking conditions. The present results suggest that mental arithmetic in children is influenced by preceding sensorimotor cues and not necessarily by concurrent body movements.
Any system at play in a data-driven project has a fundamental requirement: the ability to load data. The de-facto standard format to distribute and consume raw data is CSV. Yet, the plain text and flexible nature of this format make such files often difficult to parse and correctly load their content, requiring cumbersome data preparation steps. We propose a benchmark to assess the robustness of systems in loading data from non-standard CSV formats and with structural inconsistencies. First, we formalize a model to describe the issues that affect real-world files and use it to derive a systematic lpollutionz process to generate dialects for any given grammar. Our benchmark leverages the pollution framework for the csv format. To guide pollution, we have surveyed thousands of real-world, publicly available csv files, recording the problems we encountered. We demonstrate the applicability of our benchmark by testing and scoring 16 different systems: popular csv parsing frameworks, relational database tools, spreadsheet systems, and a data visualization tool.
Core-collapse supernova remnants are structures of the interstellar medium (ISM) left behind the explosive death of most massive stars ( ?40 M-?). Since they result in the expansion of the supernova shock wave into the gaseous environment shaped by the star's wind history, their morphology constitutes an insight into the past evolution of their progenitor star. Particularly, fast-mo ving massiv e stars can produce asymmetric core-collapse superno va remnants. We inv estigate the mixing of materials in core-collapse supernova remnants generated by a moving massive 35 M-? star, in a magnetized ISM. Stellar rotation and the wind magnetic field are time-dependently included into the models which follow the entire evolution of the stellar surroundings from the zero-age main-sequence to 80 kyr after the supernova explosion. It is found that very little main-sequence material is present in remnants from moving stars, that the Wolf-Rayet wind mixes very efficiently within the 10 kyr after the explosion, while the red supergiant material is still unmixed by 30 per cent within 50 kyr after the supernova. Our results indicate that the faster the stellar motion, the more complex the internal organization of the supernova remnant and the more ef fecti ve the mixing of ejecta therein. In contrast, the mixing of stellar wind material is only weakly affected by progenitor motion, if at all.
Many geophysical inverse problems are known to be ill-posed and, thus, requiring some kind of regularization in order to provide a unique and stable solution. A possible approach to overcome the inversion ill-posedness consists in constraining the position of the model interfaces. For a grid-based parameterization, such a structurally constrained inversion can be implemented by adopting the usual smooth regularization scheme in which the local weight of the regularization is reduced where an interface is expected. By doing so, sharp contrasts are promoted at interface locations while standard smoothness constraints keep affecting the other regions of the model. In this work, we present a structurally constrained approach and test it on the inversion of frequency-domain electromagnetic induction (FD-EMI) data using a regularization approach based on the Minimum Gradient Support stabilizer, which is capable to promote sharp transitions everywhere in the model, i.e., also in areas where no structural a prioriinformation is available. Using 1D and 2D synthetic data examples, we compare the proposed approach to a structurally constrained smooth inversion as well as to more standard (i.e., not structurally constrained) smooth and sharp inversions. Our results demonstrate that the proposed approach helps in finding a better and more reliable reconstruction of the subsurface electrical conductivity distribution, including its structural characteristics. Furthermore, we demonstrate that it allows to promote sharp parameter variations in areas where no structural information are available. Lastly, we apply our structurally constrained scheme to FD-EMI field data collected at a field site in Eastern Germany to image the thickness of peat deposits along two selected profiles. In this field example, we use collocated constant offset ground-penetrating radar (GPR) data to derive structural a priori information to constrain the inversion of the FD-EMI data. The results of this case study demonstrate the effectiveness and flexibility of the proposed approach.