Osteosarcopenia, an Asymmetrical Overlap of Two Connected Syndromes: Data from the OsteoSys Study

Osteoporosis and sarcopenia are two chronic conditions, which widely affect older people and share common risk factors. We investigated the prevalence of low bone mineral density (BMD) and sarcopenia, including the overlap of both conditions (osteosarcopenia) in 572 older hospitalized patients (mean age 75.1 ± 10.8 years, 78% women) with known or suspected osteoporosis in this prospective observational multicenter study. Sarcopenia was assessed according to the revised defini tion of the European Working Group on Sarcopenia in Older People (EWGSOP2). Low BMD was defined according to the World Health Organization (WHO) recommendations as a T-score < −1.0. Osteosarcopenia was diagnosed when both low BMD and sarcopenia were present. Low BMD was prevalent in 76% and the prevalence of sarcopenia was 9%, with 90% of the sarcopenic patients showing the overlap of osteosarcopenia (8% of the entire population). Conversely, only few patients with low BMD demonstrated sarcopenia (11%). Osteosarcopenic patients were older and frailer and had lower BMI, fat, and muscle mass, handgrip strength, and T-score compared to nonosteosar copenic patients. We conclude that osteosarcopenia is extremely common in sarcopenic subjects. Considering the increased risk of falls in patients with sarcopenia, they should always be evaluated for osteoporosis

Building in China - Study trip of the faculty of Civil Engineering of the HTWG Konstanz 2008

Im März 2008 führte die Fakultät Bauingenieurwesen der HTWG Konstanz eine studentische Exkursion nach China durch. Auf dem Programm standen interessante Baustellen Shanghai, Nanjing, Zhenjiang und Beijing sowie der Besuch von Hochschulen. Der Exkursionsbericht beschreibt die besuchten Bauvorhaben und gibt persönliche Eindrücke der Exkursionsteilnehmer wieder.In March 2008 the faculty of civil engineering of the University of Applied Sciences Konstanz, Germany, conducted a study trip for students of civil engineering to China. Construction sites and universities in Shanghai, Nanjing, Zhenjiang and Beijing have been visited. The report describes the places seen and reflects the personal impressions of the participants

varlociraptor/varlociraptor: v8.4.2

&lt;h2&gt;&lt;a href="https://github.com/varlociraptor/varlociraptor/compare/v8.4.1...v8.4.2"&gt;8.4.2&lt;/a&gt; (2023-11-09)&lt;/h2&gt; &lt;h3&gt;Bug Fixes&lt;/h3&gt; &lt;ul&gt; &lt;li&gt;out of bounds error in estimation of third allele probability (&lt;a href="https://github.com/varlociraptor/varlociraptor/issues/403"&gt;#403&lt;/a&gt;) (&lt;a href="https://github.com/varlociraptor/varlociraptor/commit/37eafa402865a9aa84d818233dc24dfeb301270a"&gt;37eafa4&lt;/a&gt;)&lt;/li&gt; &lt;/ul&gt

SLAMF7 and IL-6R define distinct cytotoxic versus helper memory CD8+ T cells

The prevailing ‘division of labor’ concept in cellular immunity is that CD8+ T cells primarily utilize cytotoxic functions to kill target cells, while CD4+ T cells exert helper/inducer functions. Multiple subsets of CD4+ memory T cells have been characterized by distinct chemokine receptor expression. Here, we demonstrate that analogous CD8+ memory T-cell subsets exist, characterized by identical chemokine receptor expression signatures and controlled by similar generic programs. Among them, Tc2, Tc17 and Tc22 cells, in contrast to Tc1 and Tc17 + 1 cells, express IL-6R but not SLAMF7, completely lack cytotoxicity and instead display helper functions including CD40L expression. CD8+ helper T cells exhibit a unique TCR repertoire, express genes related to skin resident memory T cells (TRM) and are altered in the inflammatory skin disease psoriasis. Our findings reveal that the conventional view of CD4+ and CD8+ T cell capabilities and functions in human health and disease needs to be revised

Sustainable data analysis with Snakemake

Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results

Osteosarcopenia, an asymmetrical overlap of two connected syndromes

Osteoporosis and sarcopenia are two chronic conditions, which widely affect older people and share common risk factors. We investigated the prevalence of low bone mineral density (BMD) and sarcopenia, including the overlap of both conditions (osteosarcopenia) in 572 older hospitalized patients (mean age 75.1 $\pm$ 10.8 years, 78% women) with known or suspected osteoporosis in this prospective observational multicenter study. Sarcopenia was assessed according to the revised definition of the European Working Group on Sarcopenia in Older People (EWGSOP2). Low BMD was defined according to the World Health Organization (WHO) recommendations as a T-score < −1.0. Osteosarcopenia was diagnosed when both low BMD and sarcopenia were present. Low BMD was prevalent in 76% and the prevalence of sarcopenia was 9%, with 90% of the sarcopenic patients showing the overlap of osteosarcopenia (8% of the entire population). Conversely, only few patients with low BMD demonstrated sarcopenia (11%). Osteosarcopenic patients were older and frailer and had lower BMI, fat, and muscle mass, handgrip strength, and T-score compared to nonosteosarcopenic patients. We conclude that osteosarcopenia is extremely common in sarcopenic subjects. Considering the increased risk of falls in patients with sarcopenia, they should always be evaluated for osteoporosis

12 Grand Challenges in Single-Cell Data Science

Laehnemann D, Köster J, Szczurek E, et al. 12 Grand Challenges in Single-Cell Data Science. PeerJ. 2019.The recent upswing of microfluidics and combinatorial indexing strategies, further enhanced by very low sequencing costs, have turned single cell sequencing into an empowering technology; analyzing thousands—or even millions—of cells per experimental run is becoming a routine assignment in laboratories worldwide. As a consequence, we are witnessing a data revolution in single cell biology. Although some issues are similar in spirit to those experienced in bulk sequencing, many of the emerging data science problems are unique to single cell analysis; together, they give rise to the new realm of 'Single-Cell Data Science'. Here, we outline twelve challenges that will be central in bringing this new field forward. For each challenge, the current state of the art in terms of prior work is reviewed, and open problems are formulated, with an emphasis on the research goals that motivate them. This compendium is meant to serve as a guideline for established researchers, newcomers and students alike, highlighting interesting and rewarding problems in 'Single-Cell Data Science' for the coming years.</jats:p

Eleven grand challenges in single-cell data science

The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands—or even millions—of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.Medicine, Faculty ofScience, Faculty ofOther UBCNon UBCPathology and Laboratory Medicine, Department ofStatistics, Department ofReviewedFacult