Outcomes and complications of fibular head resection

The fibular head is often used as donor graft material for reconstruction of defects of the distal radius. However little is known on the safety of such a procedure. This report describes the long-term donor-site morbidity following the procedure. Fourteen patients who underwent simple or marginal resections of the proximal fibula between 1990 and 2007 were reviewed. Subjective donor-site morbidity, knee and ankle range of motion and instability, presence of sensory or motor function loss, gait and fibular regeneration were assessed. The mean age at surgery was 25 years; six were male, eight were female and the mean follow-up was 11 years. Abnormal clinical findings were present in 10 patients (71.4 %): nine patients (64.3 %) had Grade 2 varus laxity at the knee confirmed by stress radiographs; one had sensory loss in the distribution of the superficial peroneal nerve. Patients with varus laxity had significantly higher mean age at surgery than those without varus laxity (p = 0.001). None had deformity at the knee or ankle. The range of joint movements was normal. All had a normal tibiotalar angle and none had proximal migration of the fibula. One patient demonstrated near-complete regeneration of the fibula. Donor-site morbidity following simple and marginal resection of the proximal fibula is acceptable. Older patients had a higher risk of demonstrable varus laxity at the knee but proximal fibula resection in children appears to be safe

A Grid Computing Based Power System Monitoring Tool Using Gridgain

With the advancement of civilization, Power Sector is undergoing drastic upheavals. With the ever increasing demand and dependence on electric power, protection of power system against failures remains a major challenge, particularly against cascading failures that lead to blackouts. There is a great demand for power systems protection that is scattered all around the globe. Effective monitoring of the power system parameters is a prerequisite in providing effective control and protection schemas. This paper advocates the use of grid computing in power system monitoring which discusses the suitability of grid computing to address the requirements of distinguished power system protection. Albeit, the Supervisory Control And Data Acquisition (SCADA) system is presently implied for monitoring power systems; yet it has its limitations. This paper proposes to use Grid Computing as an aid to the existing SCADA based power system monitoring & control framework and demonstrates is applicability by means of a grid based real-time power system monitoring system. The afore mentioned system has been deployed in desktop computers with GridGain 2.0 as middleware has been employed to set up the grid environment, all relevant details of the design framework has been shown

Regional conductivity structure of Cascadia : preliminary results form 3D inversion of USArray transportable array magnetotelluric data

In conjunction with the USArray component of EarthScope, long period magnetotelluric (MT) data are being acquired in a series of arrays across the continental US. Initial deployments in 2006 and 2007 acquired data (10– 10,000 s) at 110 sites covering the US Pacific Northwest, distributed with the same nominal spacing as the USArray seismic transportable array (~75 km). The most striking and robust features revealed by initial three-dimensional inversion of this dataset are extensive areas of high conductivity in the lower crust beneath all of southeastern Oregon, and beneath the Cascade Mountains, contrasting with very resistive crust in Siletzia and the Columbia Embayment. Significant variations in upper mantle conductivity are also revealed by the inversions, with the most conductive mantle beneath the Washington backarc, and the most resistive corresponding to subducting oceanic mantle

Unifying Parsimonious Tree Reconciliation

Evolution is a process that is influenced by various environmental factors, e.g. the interactions between different species, genes, and biogeographical properties. Hence, it is interesting to study the combined evolutionary history of multiple species, their genes, and the environment they live in. A common approach to address this research problem is to describe each individual evolution as a phylogenetic tree and construct a tree reconciliation which is parsimonious with respect to a given event model. Unfortunately, most of the previous approaches are designed only either for host-parasite systems, for gene tree/species tree reconciliation, or biogeography. Hence, a method is desirable, which addresses the general problem of mapping phylogenetic trees and covering all varieties of coevolving systems, including e.g., predator-prey and symbiotic relationships. To overcome this gap, we introduce a generalized cophylogenetic event model considering the combinatorial complete set of local coevolutionary events. We give a dynamic programming based heuristic for solving the maximum parsimony reconciliation problem in time O(n^2), for two phylogenies each with at most n leaves. Furthermore, we present an exact branch-and-bound algorithm which uses the results from the dynamic programming heuristic for discarding partial reconciliations. The approach has been implemented as a Java application which is freely available from http://pacosy.informatik.uni-leipzig.de/coresym.Comment: Peer-reviewed and presented as part of the 13th Workshop on Algorithms in Bioinformatics (WABI2013

Relative Abundance of Transcripts (RATs):Identifying differential isoform abundance from RNA-seq [version 1; referees: 1 approved, 2 approved with reservations]

The biological importance of changes in RNA expression is reflected by the wide variety of tools available to characterise these changes from RNA-seq data. Several tools exist for detecting differential transcript isoform usage (DTU) from aligned or assembled RNA-seq data, but few exist for DTU detection from alignment-free RNA-seq quantifications. We present the RATs, an R package that identifies DTU transcriptome-wide directly from transcript abundance estimates. RATs is unique in applying bootstrapping to estimate the reliability of detected DTU events and shows good performance at all replication levels (median false positive fraction < 0.05). We compare RATs to two existing DTU tools, DRIM-Seq & SUPPA2, using two publicly available simulated RNA-seq datasets and a published human RNA-seq dataset, in which 248 genes have been previously identified as displaying significant DTU. RATs with default threshold values on the simulated Human data has a sensitivity of 0.55, a Matthews correlation coefficient of 0.71 and a false discovery rate (FDR) of 0.04, outperforming both other tools. Applying the same thresholds for SUPPA2 results in a higher sensitivity (0.61) but poorer FDR performance (0.33). RATs and DRIM-seq use different methods for measuring DTU effect-sizes complicating the comparison of results between these tools, however, for a likelihood-ratio threshold of 30, DRIM-Seq has similar FDR performance to RATs (0.06), but worse sensitivity (0.47). These differences persist for the simulated drosophila dataset. On the published human RNA-seq dataset the greatest agreement between the tools tested is 53%, observed between RATs and SUPPA2. The bootstrapping quality filter in RATs is responsible for removing the majority of DTU events called by SUPPA2 that are not reported by RATs. All methods, including the previously published qRT-PCR of three of the 248 detected DTU events, were found to be sensitive to annotation differences between Ensembl v60 and v87

HSRA: Hadoop-based spliced read aligner for RNA sequencing data

[Abstract] Nowadays, the analysis of transcriptome sequencing (RNA-seq) data has become the standard method for quantifying the levels of gene expression. In RNA-seq experiments, the mapping of short reads to a reference genome or transcriptome is considered a crucial step that remains as one of the most time-consuming. With the steady development of Next Generation Sequencing (NGS) technologies, unprecedented amounts of genomic data introduce significant challenges in terms of storage, processing and downstream analysis. As cost and throughput continue to improve, there is a growing need for new software solutions that minimize the impact of increasing data volume on RNA read alignment. In this work we introduce HSRA, a Big Data tool that takes advantage of the MapReduce programming model to extend the multithreading capabilities of a state-of-the-art spliced read aligner for RNA-seq data (HISAT2) to distributed memory systems such as multi-core clusters or cloud platforms. HSRA has been built upon the Hadoop MapReduce framework and supports both single- and paired-end reads from FASTQ/FASTA datasets, providing output alignments in SAM format. The design of HSRA has been carefully optimized to avoid the main limitations and major causes of inefficiency found in previous Big Data mapping tools, which cannot fully exploit the raw performance of the underlying aligner. On a 16-node multi-core cluster, HSRA is on average 2.3 times faster than previous Hadoop-based tools. Source code in Java as well as a user’s guide are publicly available for download at http://hsra.dec.udc.es.Ministerio de Economía, Industria y Competitividad; TIN2016-75845-PXunta de Galicia; ED431G/0

Simultaneous Optimization of Both Node and Edge Conservation in Network Alignment via WAVE

Network alignment can be used to transfer functional knowledge between conserved regions of different networks. Typically, existing methods use a node cost function (NCF) to compute similarity between nodes in different networks and an alignment strategy (AS) to find high-scoring alignments with respect to the total NCF over all aligned nodes (or node conservation). But, they then evaluate quality of their alignments via some other measure that is different than the node conservation measure used to guide the alignment construction process. Typically, one measures the amount of conserved edges, but only after alignments are produced. Hence, a recent attempt aimed to directly maximize the amount of conserved edges while constructing alignments, which improved alignment accuracy. Here, we aim to directly maximize both node and edge conservation during alignment construction to further improve alignment accuracy. For this, we design a novel measure of edge conservation that (unlike existing measures that treat each conserved edge the same) weighs each conserved edge so that edges with highly NCF-similar end nodes are favored. As a result, we introduce a novel AS, Weighted Alignment VotEr (WAVE), which can optimize any measures of node and edge conservation, and which can be used with any NCF or combination of multiple NCFs. Using WAVE on top of established state-of-the-art NCFs leads to superior alignments compared to the existing methods that optimize only node conservation or only edge conservation or that treat each conserved edge the same. And while we evaluate WAVE in the computational biology domain, it is easily applicable in any domain.Comment: 12 pages, 4 figure

High fatigue scores in patients with idiopathic inflammatory myopathies: a multigroup comparative study from the COVAD e-survey

Idiopathic inflammatory myopathies (IIMs) confer a significant risk of disability and poor quality of life, though fatigue, an important contributing factor, remains under-reported in these individuals. We aimed to compare and analyze differences in visual analog scale (VAS) scores (0–10&nbsp;cm) for fatigue (VAS-F) in patients with IIMs, non-IIM systemic autoimmune diseases (SAIDs), and healthy controls (HCs). We performed a cross-sectional analysis of the data from the COVID-19 Vaccination in Autoimmune Diseases (COVAD) international patient self-reported e-survey. The COVAD survey was circulated from December 2020 to August 2021, and details including demographics, COVID-19 history, vaccination details, SAID details, global health, and functional status were collected from adult patients having received at least one COVID-19 vaccine dose. Fatigue experienced 1 week prior to survey completion was assessed using a single-item 10&nbsp;cm VAS. Determinants of fatigue were analyzed in regression models. Six thousand nine hundred and eighty-eight respondents (mean age 43.8&nbsp;years, 72% female; 55% White) were included in the analysis. The overall VAS-F score was 3 (IQR 1–6). Patients with IIMs had similar fatigue scores (5, IQR 3–7) to non-IIM SAIDs [5 (IQR 2–7)], but higher compared to HCs (2, IQR 1–5; P &lt; 0.001), regardless of disease activity. In adjusted analysis, higher VAS-F scores were seen in females (reference female; coefficient −0.17; 95%CI −0.21 to −13; P &lt; 0.001) and Caucasians (reference Caucasians; coefficient −0.22; 95%CI −0.30 to −0.14; P &lt; 0.001 for Asians and coefficient −0.08; 95%CI −0.13 to 0.30; P = 0.003 for Hispanics) in our cohort. Our study found that patients with IIMs exhibit considerable fatigue, similar to other SAIDs and higher than healthy individuals. Women and Caucasians experience greater fatigue scores, allowing identification of stratified groups for optimized multidisciplinary care and&nbsp;improve&nbsp;outcomes such as&nbsp;quality of life