What Should We Learn From Early Hemodialysis Allocation About How We Should Be Using ECMO?

Early hemodialysis allocation deliberations should inform our current considerations of what constitutes reasonable uses of extracorporeal membrane oxygenation. Deliberative democracy can be used as a strategy to gather a plurality of views, consider criteria, and guide policy making

Finding the elusive balance between reducing fatigue and enhancing education: perspectives from American residents

Duty hour restrictions for residency training were implemented in the United States to improve residents' educational experience and quality of life, as well as to improve patient care and safety; however, these restrictions are by no means problem-free. In this paper, we discuss the positive and negative aspects of duty hour restrictions, briefly highlighting research on the impact of reduced duty hours and the experiences of American residents. We also consider whether certain specialties (e.g., Emergency Medicine, Radiology) may be more amenable than others (e.g., Surgery) to duty hour restrictions. We conclude that feedback from residents is a crucial element that must be considered in any future attempts to strike a balance between reducing fatigue and enhancing education

Classification of protein domain movements using Dynamic Contact Graphs

A new method for the classification of domain movements in proteins is described and applied to 1822 pairs of structures from the Protein Data Bank that represent a domain movement in two-domain proteins. The method is based on changes in contacts between residues from the two domains in moving from one conformation to the other. We argue that there are five types of elemental contact changes and that these relate to five model domain movements called: ‘‘free’’, ‘‘openclosed’’, ‘‘anchored’’, ‘‘sliding-twist’’, and ‘‘see-saw.’’ A directed graph is introduced called the ‘‘Dynamic Contact Graph’’ which represents the contact changes in a domain movement. In many cases a graph, or part of a graph, provides a clear visual metaphor for the movement it represents and is a motif that can be easily recognised. The Dynamic Contact Graphs are often comprised of disconnected subgraphs indicating independent regions which may play different roles in the domain movement. The Dynamic Contact Graph for each domain movement is decomposed into elemental Dynamic Contact Graphs, those that represent elemental contact changes, allowing us to count the number of instances of each type of elemental contact change in the domain movement. This naturally leads to sixteen classes into which the 1822 domain movements are classified

Pulmonic Papillary Fibroelastoma: Cause of Recurrent Pulmonary Emboli and Treatment

&lt;p&gt;Cardiac papillary fibroelastomas are rare, typically benign primary cardiac tumors.  The pulmonary valve is the least common site for valvular papillary fibroelastomas.  They commonly present with dyspnea on exertion and can show right ventricular outflow tract obstruction on echocardiography.  Embolic phenomena are one of the most serious consequences.  Treatment usually consists of surgical excision.  We report the first case of pulmonary emboli from pulmonary valve papillary fibroelastoma treated with anticoagulation.  This occurred in only the second case of pulmonary emboli from pulmonary papillary fibroelastoma reported in literature to date.&lt;/p&gt;</jats:p

Using transfer learning from prior reference knowledge to improve the clustering of single-cell RNA-Seq data.

Funder: Technische Universität Berlin (TU Berlin); doi: https://doi.org/10.13039/501100006764Funder: - German Federal Ministry for Education and Research through the Berlin Big Data Centre (01IS14013A), the Berlin Center for Machine Learning (01IS18037I) and the TraMeExCo project (01IS18056A). Partial funding by DFG is acknowledged (EXC 2046/1, project-ID: 390685689) - Institute for Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No.2017-0-01779)Funder: GlaxoSmithKline (GlaxoSmithKline plc.); doi: https://doi.org/10.13039/100004330Funder: Pfizer (Pfizer Inc.); doi: https://doi.org/10.13039/100004319In many research areas scientists are interested in clustering objects within small datasets while making use of prior knowledge from large reference datasets. We propose a method to apply the machine learning concept of transfer learning to unsupervised clustering problems and show its effectiveness in the field of single-cell RNA sequencing (scRNA-Seq). The goal of scRNA-Seq experiments is often the definition and cataloguing of cell types from the transcriptional output of individual cells. To improve the clustering of small disease- or tissue-specific datasets, for which the identification of rare cell types is often problematic, we propose a transfer learning method to utilize large and well-annotated reference datasets, such as those produced by the Human Cell Atlas. Our approach modifies the dataset of interest while incorporating key information from the larger reference dataset via Non-negative Matrix Factorization (NMF). The modified dataset is subsequently provided to a clustering algorithm. We empirically evaluate the benefits of our approach on simulated scRNA-Seq data as well as on publicly available datasets. Finally, we present results for the analysis of a recently published small dataset and find improved clustering when transferring knowledge from a large reference dataset. Implementations of the method are available at https://github.com/nicococo/scRNA

The “Goldilocks Zoneâ€? from a redox perspectiveâ€â€�Adaptive vs. deleterious responses to oxidative stress in striated muscle

Consequences of oxidative stress may be beneficial or detrimental in physiological systems. An organ system's position on the “hormetic curve� is governed by the source and temporality of reactive oxygen species (ROS) production, proximity of ROS to moieties most susceptible to damage, and the capacity of the endogenous cellular ROS scavenging mechanisms. Most importantly, the resilience of the tissue (the capacity to recover from damage) is a decisive factor, and this is reflected in the disparate response to ROS in cardiac and skeletal muscle. In myocytes, a high oxidative capacity invariably results in a significant ROS burden which in homeostasis, is rapidly neutralized by the robust antioxidant network. The up-regulation of key pathways in the antioxidant network is a central component of the hormetic response to ROS. Despite such adaptations, persistent oxidative stress over an extended time-frame (e.g., months to years) inevitably leads to cumulative damages, maladaptation and ultimately the pathogenesis of chronic diseases. Indeed, persistent oxidative stress in heart and skeletal muscle has been repeatedly demonstrated to have causal roles in the etiology of heart disease and insulin resistance, respectively. Deciphering the mechanisms that underlie the divergence between adaptive and maladaptive responses to oxidative stress remains an active area of research for basic scientists and clinicians alike, as this would undoubtedly lead to novel therapeutic approaches. Here, we provide an overview of major types of ROS in striated muscle and the divergent adaptations that occur in response to them. Emphasis is placed on highlighting newly uncovered areas of research on this topic, with particular focus on the mitochondria, and the diverging roles that ROS play in muscle health (e.g., exercise or preconditioning) and disease (e.g., cardiomyopathy, ischemia, metabolic syndrome)

SBML Level 3: an extensible format for the exchange and reuse of biological models

Abstract Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single‐cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution