Thomsonharrell9389

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020.Germline pathogenic variants in the BRCA1-associated protein-1 (BAP1) gene cause the BAP1 tumor predisposition syndrome (TPDS). BAP1 TPDS is associated with an increased risk of uveal and cutaneous melanoma, mesothelioma, renal cell carcinoma, and several other cancer subtypes. Here, we report a germline nonsense BAP1 variant (c.850G>T, p.Glu284Ter) in a patient with bladder cancer and a strong family history of malignancy. Concurrently, we identified a somatic frameshift BAP1 variant, and as expected, immunostaining validated the loss of BAP1 protein in patient-derived tumor specimens. Together, these data provide strong evidence of pathogenicity in this case. With the addition of bladder cancer to the tumor types reported with germline BAP1 mutations, our understanding of the BAP1 TPDS continues to evolve, and may affect future screening and surveillance guidelines. © The Author(s) 2020.Liver metastasis, characterized by the spread of tumors to the liver from other areas, represents a deadly disease with poor prognosis. Currently, there is no effective therapeutic strategies and/or agents to combat liver metastasis primarily due to the insufficient understanding of liver metastasis. To develop a promising strategy for targeting liver metastasis, understanding of a cell origin responsible for liver metastasis and how this cell can be pharmacologically eliminated are therefore crucial. Using diverse tumor models including p53 -/- genetic mouse model and syngeneic tumor models, we identified primordial germ cell (PGC)-like tumor cells, which are enriched in earliest liver micro-metastasis (up to 99%), as a cell origin of liver metastasis. PGC-like tumor cells formed earliest micro-metastasis in liver and gradually differentiated into non-PGC-like tumor cells to constitute late macro-metastasis in the course of tumor metastasis. The liver metastasis-initiating cells (PGC-like tumor cells) displabiting BMP pathways serves a promising strategy for targeting liver metastasis. © The Author(s) 2020.Body shape and composition are heterogeneous among humans with possible impact for health. Anthropometric methods and data are needed to better describe the diversity of the human body in human populations, its age dependence, and associations with health risk. We applied whole-body laser scanning to a cohort of 8499 women and men of age 40-80 years within the frame of the LIFE (Leipzig Research Center for Civilization Diseases) study aimed at discovering health risk in a middle European urban population. Body scanning delivers multidimensional anthropometric data, which were further processed by machine learning to stratify the participants into body types. We here applied this body typing concept to describe the diversity of body shapes in an aging population and its association with physical activity and selected health and lifestyle factors. We find that aging results in similar reshaping of female and male bodies despite the large diversity of body types observed in the study. Slim body shapes remain slim and partly tend to become even more lean and fragile, while obese body shapes remain obese. Female body shapes change more strongly than male ones. The incidence of the different body types changes with characteristic Life Course trajectories. Physical activity is inversely related to the body mass index and decreases with age, while self-reported incidence for myocardial infarction shows overall the inverse trend. We discuss health risks factors in the context of body shape and its relation to obesity. Body typing opens options for personalized anthropometry to better estimate health risk in epidemiological research and future clinical applications. CHIR-98014 nmr © The Author(s) 2020.The fitness landscape metaphor has been central in our way of thinking about adaptation. In this scenario, adaptive walks are idealized dynamics that mimic the uphill movement of an evolving population towards a fitness peak of the landscape. Recent works in experimental evolution have demonstrated that the constraints imposed by epistasis are responsible for reducing the number of accessible mutational pathways towards fitness peaks. Here, we exhaustively analyse the statistical properties of adaptive walks for two empirical fitness landscapes and theoretical NK landscapes. Some general conclusions can be drawn from our simulation study. Regardless of the dynamics, we observe that the shortest paths are more regularly used. Although the accessibility of a given fitness peak is reasonably correlated to the number of monotonic pathways towards it, the two quantities are not exactly proportional. A negative correlation between predictability and mean path divergence is established, and so the decrease of the number of effective mutational pathways ensures the convergence of the attraction basin of fitness peaks. On the other hand, other features are not conserved among fitness landscapes, such as the relationship between accessibility and predictability. © 2020 The Authors.[This corrects the article DOI 10.1098/rsos.191350.]. © 2020 The Authors.Phase microscopy allows stain-free imaging of transparent biological samples. One technique, using the transport of intensity equation (TIE), can be performed without dedicated hardware by simply processing pairs of images taken at known spacings within the sample. The resulting TIE images are quantitative phase maps of unstained biological samples. Therefore, spatially resolved optical path length (OPL) information can also be determined. Using low-cost, open-source hardware, we applied the TIE to living algal cells to measure their effect on OPL. We obtained OPL values that were repeatable within species and differed by distinct amounts depending on the species being measured. We suggest TIE imaging as a method of discrimination between different algal species and, potentially, non-biological materials, based on refractive index/OPL. Potential applications in biogeochemical modelling and climate sciences are suggested. © 2020 The Authors.