Display of probability densities for data from a continuous distribution

Based on cumulative distribution functions, Fourier series expansion and Kolmogorov tests, we present a simple method to display probability densities for data drawn from a continuous distribution. It is often more efficient than using histograms.Comment: 5 pages, 4 figures, presented at Computer Simulation Studies XXIV, Athens, GA, 201

Synonymous mutations in RNASEH2A create cryptic splice sites impairing RNase H2 enzyme function in Aicardi-Goutières syndrome

Aicardi-Goutières syndrome is an inflammatory disorder resulting from mutations in TREX1, RNASEH2A/2B/2C, SAMHD1, or ADAR1. Here, we provide molecular, biochemical, and cellular evidence for the pathogenicity of two synonymous variants in RNASEH2A. Firstly, the c.69G>A (p.Val23Val) mutation causes the formation of a splice donor site within exon 1, resulting in an out of frame deletion at the end of exon 1, leading to reduced RNase H2 protein levels. The second mutation, c.75C>T (p.Arg25Arg), also introduces a splice donor site within exon 1, and the internal deletion of 18 amino acids. The truncated protein still forms a heterotrimeric RNase H2 complex, but lacks catalytic activity. However, as a likely result of leaky splicing, a small amount of full-length active protein is apparently produced in an individual homozygous for this mutation. Recognition of the disease causing status of these variants allows for diagnostic testing in relevant families

Synonymous mutations in RNASEH2A create cryptic splice sites impairing RNase H2 enzyme function in Aicardi-Goutières syndrome.

Synonymous mutations in RNASEH2A create cryptic splice sites impairing RNase H2 enzyme function in Aicardi-Goutières syndrome

Animal models and animal-free innovations for cardiovascular research: current status and routes to be explored. Consensus document of the ESC working group on myocardial function and the ESC Working Group on Cellular Biology of the Heart

Cardiovascular diseases represent a major cause of morbidity and mortality, necessitating research to improve diagnostics, and to discover and test novel preventive and curative therapies. All of which warrant experimental models that recapitulate human disease. The translation of basic science results to clinical practice is a challenging task. In particular for complex conditions such as cardiovascular diseases, which often result from multiple risk factors and co-morbidities. This difficulty might lead some individuals to question the value of animal research, citing the translational 'valley of death', which largely reflects the fact that studies in rodents are difficult to translate to humans. This is also influenced by the fact that new, human-derived in vitro models can recapitulate aspects of disease processes. However, it would be a mistake to think that animal models cannot provide a vital step in the translational pathway as they do provide important pathophysiological insights into disease mechanisms particularly on a organ and systemic level. While stem cell-derived human models have the potential to become key in testing toxicity and effectiveness of new drugs, we need to be realistic, and carefully validate all new human-like disease models. In this position paper, we highlight recent advances in trying to reduce the number of animals for cardiovascular research ranging from stem cell-derived models to in situ modelling of heart properties, bioinformatic models based on large datasets, and improved current animal models, which show clinically relevant characteristics observed in patients with a cardiovascular disease. We aim to provide a guide to help researchers in their experimental design to translate bench findings to clinical routine taking the replacement, reduction and refinement (3R) as a guiding concept