Multifocal Vasculopathy Due to Varicella-Zoster Virus (VZV): Serial Analysis of VZV DNA and Intrathecal Synthesis of VZV Antibody in Cerebrospinal Fluid

Recognition of multifocal vasculopathy due to varicella-zoster virus (VZV) is often problematic. We describe a human immunodeficiency virus—infected patient who had progressive central nervous system disease for >3 months. Both VZV DNA and antibody were detected in cerebrospinal fluid (CSF) specimens; serial polymerase chain reaction analyses confirmed the diagnosis and guided the duration of therapy. Reduced ratios of VZV antibody in serum to that in CSF were also demonstrate

Fixation of a double-coated titanium-hydroxyapatite focal knee resurfacing implant A 12-month study in sheep

SummaryObjectiveFocal cartilage lesions according to International Cartilage Repair Society (ICRS) grade 3–4 in the medial femoral condyle may progress to osteoarthritis. When treating such focal lesions with metallic implants a sound fixation to the underlying bone is mandatory. We developed a monobloc unipolar cobalt-chrome (Co-Cr) implant with a double coating; first a layer of commercially pure titanium (c.p.Ti) on top of which a layer of hydroxyapatite (HA) was applied. We hypothesised that such a double coating would provide long-lasting and adequate osseointegration.Design (materials and methods)Unilateral medial femoral condyles of 10 sheep were operated. The implants were inserted in the weight-bearing surface and immediate weight-bearing was allowed. Euthanasia was performed at 6 (three animals) or 12 months (six animals). Osseointegration was analysed with micro-computer tomography (CT), light microscopy and histomorphometric analyses using backscatter scanning electron microscopy (B-SEM) technique.ResultsAt 6 months one specimen out of three showed small osteolytic areas at the hat and at 12 months two specimens out of six showed small osteolytic areas at the hat, no osteolytical areas were seen around the peg at any time point. At both time points, a high total bone-to-implant contact was measured with a mean (95% confidence interval – CI) of 90.6 (79–102) at 6 months and 92.3 (89–95) at 12 months, respectively.ConclusionsA double coating (Ti + HA) of a focal knee resurfacing Co-Cr implant was presented in a sheep animal model. A firm and consistent bond to bone under weight-bearing conditions was shown up to 1 year

GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores

<p>Abstract</p> <p>Background</p> <p>Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits.</p> <p>Findings</p> <p>Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1) the interaction of SNPs within it in parallel, and 2) the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run.</p> <p>Conclusions</p> <p>GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from <url>http://www.cceb.upenn.edu/~mli/software/GENIE/</url>.</p

ML-based Real-Time Control at the Edge: An Approach Using hls4ml

This study focuses on implementing a real-time control system for a particle accelerator facility that performs high energy physics experiments. A critical operating parameter in this facility is beam loss, which is the fraction of particles deviating from the accelerated proton beam into a cascade of secondary particles. Accelerators employ a large number of sensors to monitor beam loss. The data from these sensors is monitored by human operators who predict the relative contribution of different sub-systems to the beam loss. Using this information, they engage control interventions. In this paper, we present a controller to track this phenomenon in real-time using edge-Machine Learning (ML) and support control with low latency and high accuracy. We implemented this system on an Intel Arria 10 SoC. Optimizations at the algorithm, high-level synthesis, and interface levels to improve latency and resource usage are presented. Our design implements a neural network, which can predict the main source of beam loss (between two possible causes) at speeds up to 575 frames per second (fps) (average latency of 1.74 ms). The practical deployed system is required to operate at 320 fps, with a 3ms latency requirement, which has been met by our design successfully

Mathematics and biology: a Kantian view on the history of pattern formation theory

Driesch’s statement, made around 1900, that the physics and chemistry of his day were unable to explain self-regulation during embryogenesis was correct and could be extended until the year 1972. The emergence of theories of self-organisation required progress in several areas including chemistry, physics, computing and cybernetics. Two parallel lines of development can be distinguished which both culminated in the early 1970s. Firstly, physicochemical theories of self-organisation arose from theoretical (Lotka 1910–1920) and experimental work (Bray 1920; Belousov 1951) on chemical oscillations. However, this research area gained broader acceptance only after thermodynamics was extended to systems far from equilibrium (1922–1967) and the mechanism of the prime example for a chemical oscillator, the Belousov–Zhabotinski reaction, was deciphered in the early 1970s. Secondly, biological theories of self-organisation were rooted in the intellectual environment of artificial intelligence and cybernetics. Turing wrote his The chemical basis of morphogenesis (1952) after working on the construction of one of the first electronic computers. Likewise, Gierer and Meinhardt’s theory of local activation and lateral inhibition (1972) was influenced by ideas from cybernetics. The Gierer–Meinhardt theory provided an explanation for the first time of both spontaneous formation of spatial order and of self-regulation that proved to be extremely successful in elucidating a wide range of patterning processes. With the advent of developmental genetics in the 1980s, detailed molecular and functional data became available for complex developmental processes, allowing a new generation of data-driven theoretical approaches. Three examples of such approaches will be discussed. The successes and limitations of mathematical pattern formation theory throughout its history suggest a picture of the organism, which has structural similarity to views of the organic world held by the philosopher Immanuel Kant at the end of the eighteenth century

Comparison of Strategies to Detect Epistasis from eQTL Data

Genome-wide association studies have been instrumental in identifying genetic variants associated with complex traits such as human disease or gene expression phenotypes. It has been proposed that extending existing analysis methods by considering interactions between pairs of loci may uncover additional genetic effects. However, the large number of possible two-marker tests presents significant computational and statistical challenges. Although several strategies to detect epistasis effects have been proposed and tested for specific phenotypes, so far there has been no systematic attempt to compare their performance using real data. We made use of thousands of gene expression traits from linkage and eQTL studies, to compare the performance of different strategies. We found that using information from marginal associations between markers and phenotypes to detect epistatic effects yielded a lower false discovery rate (FDR) than a strategy solely using biological annotation in yeast, whereas results from human data were inconclusive. For future studies whose aim is to discover epistatic effects, we recommend incorporating information about marginal associations between SNPs and phenotypes instead of relying solely on biological annotation. Improved methods to discover epistatic effects will result in a more complete understanding of complex genetic effects