Comparison of the Prostate Imaging Reporting and Data System (PI-RADS) version 1 and 2 in a cohort of 245 patients with histopathological reference and long-term follow-up

Objective: To compare the performance of PI-RADSv2 with PI-RADSv1 in patients with elevated PSA before biopsy. Methods: 245 patients with elevated PSA underwent mpMRI before biopsy between May 2011 and December 2014 at 3.0 Tesla without endorectal coil. Patients underwent transrectal ultrasound-guided systematic 12-core biopsy followed by radical prostatectomy (N = 68), radiation therapy (N = 91) or clinical follow-up for at least two years (N = 86). All exams were scored on a per-patient basis according to PI-RADSv1 and PI-RADSv2. ClinsigPC was defined as Gleason score >= 7 (including 3+4 with prominent but not predominant Gleason 4 component), and/or tumour volume of >= 0.5cc, and/or tumour stage >= T3a. Results: In 144 patients (58.8%) a ClinsigPC was found within two years after mpMRI. The PI-RADSv1 and PI-RADSv2 overall assessment scores were significantly higher (P < 0.001) in patients with ClinsigPC as compared to patients without ClinsigPC. ROC analysis showed an area under the curve of 0.82 (CI 0.76-0.87) for PI-RADSv1 and 0.79 (CI 0.73-0.85) for PI-RADSv2 (P: NS). A threshold score of 3 exhibited sensitivities of 88.2% and 79.2% (P = 0.001) and specificities of 64.4% and 67.3% (P: NS) with PI-RADSv1 and PI-RADSv2, respectively. Conclusions: The mpMRI scoring systems PI-RADSv1 and PI-RADSv2 yield similar accuracy to detect ClinsigPC in patients with elevated PSA, although clinicians should be aware that when an overall assessment score of 3 is used as a threshold for a positive mpMRI, PI-RADSv2 has lower sensitivity than PI-RADSv1. Nevertheless, PI-RADSv2 is preferable over PI-RADSv1 because it has the advantage of providing well-defined instructions on how to determine the overall assessment category

HIV-1 Vpr N-terminal tagging affects alternative splicing of the viral genome

To facilitate studies on Vpr function in replicating HIV-1, we aimed to tag the protein in an infectious virus. First we showed that N-, but not C-terminal HA/FLAG tagging of Vpr protein preserves Vpr cytopathicity. Cloning the tags into proviral DNA however ablated viral production and replication. By construction of additional viral variants we could show this defect was not protein-but RNA-dependent and sequence specific, and characterized by oversplicing of the genomic RNA. Simulation of genomic RNA folding suggested that introduction of the tag sequence induced an alternative folding structure in a region enriched in splice sites and splicing regulatory sequences. In silico predictions identified the HA/His(6)-Vpr tagging in HIV-1 to affect mRNA folding less than HA/FLAG-Vpr tagging. In vitro infectivity and mRNA splice pattern improved but did not reach wild-type values. Thus, sequence-specific insertions may interfere with mRNA splicing, possibly due to altered RNA folding. Our results point to the complexity of viral RNA genome sequence interactions. This should be taken into consideration when designing viral manipulation strategies, for both research as for biological interventions

Unusual multisystemic involvement and a novel BAG3 mutation revealed by NGS screening in a large cohort of myofibrillar myopathies

Myofibrillar myopathies (MFM) are a group of phenotypically and genetically heterogeneous neuromuscular disorders, which are characterized by protein aggregations in muscle fibres and can be associated with multisystemic involvement.Methods We screened a large cohort of 38 index patients with MFM for mutations in the nine thus far known causative genes using Sanger and next generation sequencing (NGS). We studied the clinical and histopathological characteristics in 38 index patients and five additional relatives (n = 43) and particularly focused on the associated multisystemic symptoms.Results We identified 14 heterozygous mutations (diagnostic yield of 37%), among them the novel p.Pro209Gln mutation in the BAG3 gene, which was associated with onset in adulthood, a mild phenotype and an axonal sensorimotor polyneuropathy, in the absence of giant axons at the nerve biopsy. We revealed several novel clinical phenotypes and unusual multisystemic presentations with previously described mutations: hearing impairment with a FLNC mutation, dysphonia with a mutation in DES and the first patient with a FLNC mutation presenting respiratory insufficiency as the initial symptom. Moreover, we described for the first time respiratory insufficiency occurring in a patient with the p.Gly154Ser mutation in CRYAB. Interestingly, we detected a polyneuropathy in 28% of the MFM patients, including a BAG3 and a MYOT case, and hearing impairment in 13%, including one patient with a FLNC mutation and two with mutations in the DES gene. In four index patients with a mutation in one of the MFM genes, typical histological findings were only identified at the ultrastructural level (29%).Conclusions We conclude that extraskeletal symptoms frequently occur in MFM, particularly cardiac and respiratory involvement, polyneuropathy and/or deafness. BAG3 mutations should be considered even in cases with a mild phenotype or an adult onset. We identified a genetic defect in one of the known genes in less than half of the MFM patients, indicating that more causative genes are still to be found. Next generation sequencing techniques should be helpful in achieving this aim

Production of 30 National Summary briefs : Deliverable 2.5

This document (ENERGISE D2.5) provides an overview of national energy and supply dynamics across 30 European countries. The Deliverable encompasses reviews of the current state of the art and existing trends in national energy policies, energy systems and energy campaigns in each of the 30 countries. To enhance accessibility and engagement with the material, the information gathered is presented in 30 independent National Briefs

Bridging the Gap between Field Experiments and Machine Learning: The EC H2020 B-GOOD Project as a Case Study towards Automated Predictive Health Monitoring of Honey Bee Colonies.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies' exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony's health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project's data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping

2020 Update of the quality indicators for acute myocardial infarction : a position paper of the Association for Acute Cardiovascular Care : the study group for quality indicators from the ACVC and the NSTE-ACS guideline group

Aims Quality indicators (QIs) are tools to improve the delivery of evidence-base medicine. In 2017, the European Society of Cardiology (ESC) Association for Acute Cardiovascular Care (ACVC) developed a set of QIs for acute myocardial infarction (AMI), which have been evaluated at national and international levels and across different populations. However, an update of these QIs is needed in light of the accumulated experience and the changes in the supporting evidence. Methods and results The ESC methodology for the QI development was used to update the 2017 ACVC QIs. We identified key domains of AMI care, conducted a literature review, developed a list of candidate QIs, and used a modified Delphi method to select the final set of indicators. The same seven domains of AMI care identified by the 2017 Study Group were retained for this update. For each domain, main and secondary QIs were developed reflecting the essential and complementary aspects of care, respectively. Overall, 26 QIs are proposed in this document, compared to 20 in the 2017 set. New QIs are proposed in this document (e.g. the centre use of high-sensitivity troponin), some were retained or modified (e.g. the in-hospital risk assessment), and others were retired in accordance with the changes in evidence [e.g. the proportion of patients with non-ST segment elevation myocardial infarction (NSTEMI) treated with fondaparinux] and the feasibility assessments (e.g. the proportion of patients with NSTEMI whom risk assessment is performed using the GRACE and CRUSADE risk scores). Conclusion Updated QIs for the management of AMI were developed according to contemporary knowledge and accumulated experience. These QIs may be applied to evaluate and improve the quality of AMI care

Twist exome capture allows for lower average sequence coverage in clinical exome sequencing

Background Exome and genome sequencing are the predominant techniques in the diagnosis and research of genetic disorders. Sufficient, uniform and reproducible/consistent sequence coverage is a main determinant for the sensitivity to detect single-nucleotide (SNVs) and copy number variants (CNVs). Here we compared the ability to obtain comprehensive exome coverage for recent exome capture kits and genome sequencing techniques. Results We compared three different widely used enrichment kits (Agilent SureSelect Human All Exon V5, Agilent SureSelect Human All Exon V7 and Twist Bioscience) as well as short-read and long-read WGS. We show that the Twist exome capture significantly improves complete coverage and coverage uniformity across coding regions compared to other exome capture kits. Twist performance is comparable to that of both short- and long-read whole genome sequencing. Additionally, we show that even at a reduced average coverage of 70× there is only minimal loss in sensitivity for SNV and CNV detection. Conclusion We conclude that exome sequencing with Twist represents a significant improvement and could be performed at lower sequence coverage compared to other exome capture techniques