Novel genetically encoded fluorescent probes enable real-time detection of potassium in vitro and in vivo

Changes in intra-and extracellular potassium ion (K+) concentrations control many important cellular processes and related biological functions. However, our current understanding of the spatiotemporal patterns of physiological and pathological K+ changes is severely limited by the lack of practicable detection methods. We developed K+-sensitive genetically encoded, Forster resonance energy transfer-(FRET) based probes, called GEPIIs, which enable quantitative real-time imaging of K+ dynamics. GEPIIs as purified biosensors are suitable to directly and precisely quantify K+ levels in different body fluids and cell growth media. GEPIIs expressed in cells enable time-lapse and real-time recordings of global and local intracellular K+ signals. Hitherto unknown Ca2+-triggered, organelle-specific K+ changes were detected in pancreatic beta cells. Recombinant GEPIIs also enabled visualization of extracellular K+ fluctuations in vivo with 2-photon microscopy. Therefore, GEPIIs are relevant for diverse K+ assays and open new avenues for live-cell K+ imaging

Beveridge on idleness

Beveridge's wartime proposals to eliminate idleness relied on the precepts of Keynesian economics and substantial extensions in the powers of central government to regulate industry and labour. Using convention theory, this paper demonstrates how these stipulations proved politically untenable. With the disappearance of full employment in the 1980s, the labour market problems Beveridge encountered in his youth have re-emerged accompanied by old problems of working poverty. Established forms of labour market analysis are obsolescent and employment rights disappear. The paper suggests a more decentralized and variable analysis of relations between work and idleness may offer a way forward

Universal ventricular coordinates: A generic framework for describing position within the heart and transferring data

Being able to map a particular set of cardiac ventricles to a generic topologically equivalent representation has many applications, including facilitating comparison of different hearts, as well as mapping quantities and structures of interest between them. In this paper we describe Universal Ventricular Coordinates (UVC), which can be used to describe position within any biventricular heart. UVC comprise four unique coordinates that we have chosen to be intuitive, well defined, and relevant for physiological descriptions. We describe how to determine these coordinates for any volumetric mesh by illustrating how to properly assign boundary conditions and utilize solutions to Laplace's equation. Using UVC, we transferred scalar, vector, and tensor data between four unstructured ventricular meshes from three different species. Performing the mappings was very fast, on the order of a few minutes, since mesh nodes were searched in a KD tree. Distance errors in mapping mesh nodes back and forth between meshes were less than the size of an element. Analytically derived fiber directions were also mapped across meshes and compared, showing < 5 ° difference over most of the ventricles. The ability to transfer gradients was also demonstrated. Topologically variable structures, like papillary muscles, required further definition outside of the UVC framework. In conclusion, UVC can aid in transferring many types of data between different biventricular geometries

Automatically generated, anatomically accurate meshes for cardiac electrophysiology problems.

Significant advancements in imaging technology and the dramatic increase in computer power over the last few years broke the ground for the construction of anatomically realistic models of the heart at an unprecedented level of detail. To effectively make use of high-resolution imaging datasets for modeling purposes, the imaged objects have to be discretized. This procedure is trivial for structured grids. However, to develop generally applicable heart models, unstructured grids are much preferable. In this study, a novel image-based unstructured mesh generation technique is proposed. It uses the dual mesh of an octree applied directly to segmented 3-D image stacks. The method produces conformal, boundary-fitted, and hexahedra-dominant meshes. The algorithm operates fully automatically with no requirements for interactivity and generates accurate volume-preserving representations of arbitrarily complex geometries with smooth surfaces. The method is very well suited for cardiac electrophysiological simulations. In the myocardium, the algorithm minimizes variations in element size, whereas in the surrounding medium, the element size is grown larger with the distance to the myocardial surfaces to reduce the computational burden. The numerical feasibility of the approach is demonstrated by discretizing and solving the monodomain and bidomain equations on the generated grids for two preparations of high experimental relevance, a left ventricular wedge preparation, and a papillary muscle