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Abstract Background Experimental mice are often single-housed either for an individual analysis (feeding behavior, imaging, calorimetry) or as a stress paradigm (social isolation) in translational biomedical research. Reports of the influence of single housing in rodents are conflicting and may depend on age and duration of isolation. Sex is often not included as a factor. In this study we investigated the effects of 4-week single housing in male and female mice on behavior, body weight, and serum corticosterone levels. Results Behavioral tests showed no effect on anhedonia and stress coping, anxiety and motor exploration. Social avoidance occurred in both males and females. Regarding physiological effects, single housing did not induce changes in serum corticosterone levels, but reduced body weight gain. Conclusions While some mouse studies of chronic social isolation reported depression-related disturbances, our data suggest that single housing might be not necessarily be too stressful. This is important for animal welfare regulations and experiments in life science research.

Abstract Low-carbohydrates diets are increasingly used to treat obesity and metabolic disorders. A very low-carbohydrate, ketogenic diet is hard to follow and, due to the very high fat content, linked to severe side effects, like hyperlipidemia and atherogenesis. Therefore, a less restrictive, unsaturated fat-based low-carbohydrate diet appears as a promising alternative. Since neither sex differences, nor their effect on specific metabolic hormones and adipose tissue compartments have been investigated thoroughly in these diets, we aimed to analyze their dynamics and metabolic factors in mice. We found a significant sexual dimorphism with decreased body weight and subcutaneous fat only in males on ketogenic diet, while diminished insulin, elevated ghrelin and FGF-21 were present with a differential time course in both sexes. The non-ketogenic moderate low-carbohydrate diet increased body weight and perigonadal fat in females, but induced leptin elevation in males. Both diets enhanced transiently TNFɑ only in males and had no impact on behavior. Altogether, these results reveal complex sex-dependent effect of dietary interventions, indicating unexpectedly females as more prone to unfavorable metabolic effects of low-carbohydrate diets.

Abstract The placenta is crucial to fetal well-being and it plays a significant role in the pathogenesis of hypertensive pregnancy disorders. Moreover, a timely diagnosis of placenta previa may save lives. Ultrasound is the primary imaging modality in pregnancy, but high-quality imaging depends on the access to equipment and staff, which is not possible in all settings. Convolutional neural networks may help standardize the acquisition of images for fetal diagnostics. Our aim was to develop a deep learning based model for classification and segmentation of the placenta in ultrasound images. We trained a model based on manual annotations of 7,500 ultrasound images to identify and segment the placenta. The model's performance was compared to annotations made by 25 clinicians (experts, trainees, midwives). The overall image classification accuracy was 81%. The average intersection over union score (IoU) reached 0.78. The model’s accuracy was lower than experts’ and trainees’, but it outperformed all clinicians at delineating the placenta, IoU = 0.75 vs 0.69, 0.66, 0.59. The model was cross validated on 100 2nd trimester images from Barcelona, yielding an accuracy of 76%, IoU 0.68. In conclusion, we developed a model for automatic classification and segmentation of the placenta with consistent performance across different patient populations. It may be used for automated detection of placenta previa and enable future deep learning research in placental dysfunction.

Abstract The second law of thermodynamics leaves no doubt that life on planet Earth and its inherent substantial decrease in entropy is fundamentally based on mechanisms converting environmental free energy into the spatial and temporal order of metabolic processes. This argument holds for present life as much as it does for its very beginnings some 4 billion years ago. In this contribution, we try to strip down free energy conversion in extant life (known as “bioenergetics” to the biologists) to its basic principles with the aim to potentially retrodict the nature of the pre‐biotic precursor which drove life into existence. We demonstrate that these basic principles are deeply rooted in aqueous electrochemistry and strongly rely on inorganic redox compounds. The question of life's emergence, generally considered to fall into the realm of organic chemistry, should therefore rather be recognized as an electrochemical problem and its ultimate elucidation will need to strongly implicate the community of electrochemical scientists.

Although mobile genetic elements, or transposons, have played an important role in genome evolution, excess activity of mobile elements can have detrimental consequences. Already, the enhanced expression of transposons-derived nucleic acids can trigger autoimmune reactions that may result in severe autoinflammatory disorders. Thus, cells contain several layers of protective measures to restrict transposons and to sense the enhanced activity of these “intragenomic pathogens”. This review focuses on our current understanding of immunogenic patterns derived from the most active elements in humans, the retrotransposons long interspersed element (LINE)-1 and Alu. We describe the role of known pattern recognition receptors in nucleic acid sensing of LINE-1 and Alu and the possible consequences for autoimmune diseases.