Introduction: BRCA1 and BRCA2 are the two main genes causing hereditary breast and ovarian cancer (HBOC). However, thanks to the development of Next Generation Sequencing (NGS), other genes linked to this syndrome (CH...
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Introduction: BRCA1 and BRCA2 are the two main genes causing hereditary breast and ovarian cancer (HBOC). However, thanks to the development of Next Generation Sequencing (NGS), other genes linked to this syndrome (CHEK2, BRIP1, ATM and PALB2 among others) can be analysed. Material and methods: an analysis by multigene panel testing was performed in 138 index cases (ICs) from HBOC Spanish families with a previous non-informative result for BRCA1/2. The BRCA Hereditary Cancer MasterTM Plus kit, including 26 actionable and candidate genes related to HBOC was employed. Once classified, an algorithm was employed to prioritized those variants of unknown significance with a higher risk of having a deleterious effect. Moreover, a mRNA splicing assay was performed for the prioritized VUS c.3402+3A > C in ATM, located at intron 23. Results: A total of 82 variants were found: 70 VUS and 12 pathogenic or probably pathogenic variants. The diagnostic yield in actionable genes non-BRCA was 7.97% of the total tested ICs. Overall, 19 VUS were prioritized, which meant 27% of the 70 total VUS. RNA analysis of the variant 3402+3A > C confirmed a deleterious impact on splicing. Discussion: The implementation of a multigene panel in HBOC studied families improved the diagnostic yield, concordant with results obtained in previous publications. Due to the important number of VUS obtained in NGS, the application of a prioritization algorithm is needed in order to select those variants in which it is necessary to conduct further studies.
Discerning clinically relevant autism spectrum disorder (ASD) candidate variants from whole-exome sequencing (WES) data is complex, time-consuming, and labor-intensive. To this end, we developed AutScore, an integrati...
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Discerning clinically relevant autism spectrum disorder (ASD) candidate variants from whole-exome sequencing (WES) data is complex, time-consuming, and labor-intensive. To this end, we developed AutScore, an integrative prioritization algorithm of ASD candidate variants from WES data and assessed its performance to detect clinically relevant variants. We studied WES data from 581 ASD probands, and their parents registered in the Azrieli National Center database for Autism and Neurodevelopment Research. We focused on rare allele frequency (< 1%) and high-quality proband-specific variants affecting genes associated with ASD or other neurodevelopmental disorders (NDDs). We developed AutScore and AutScore.r and assigned each variant based on their pathogenicity, clinical relevance, gene-disease association, and inheritance patterns. Finally, we compared the performance of both AutScore versions with the rating of clinical experts and the NDD variant prioritization algorithm, AutoCaSc. Overall, 1161 rare variants distributed in 687 genes in 441 ASD probands were evaluated by AutScore with scores ranging from - 4 to 25, with a mean +/- SD of 5.89 +/- 4.18. AutScore.r cut-off of >= 0.335 performs better than AutoCaSc and AutScore in detecting clinically relevant ASD variants, with a detection accuracy rate of 85% and an overall diagnostic yield of 10.3%. Five variants with AutScore.r of >= 0.335 were distributed in five novel ASD candidate genes. AutScore.r is an effective automated ranking system for ASD candidate variants that could be implemented in ASD clinical genetics pipelines.
YouTube has become a great showcase for audiovisual products and a source of income for a number of creators. Several pioneers of internet animation migrated to this platform to provide greater visibility and economic...
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YouTube has become a great showcase for audiovisual products and a source of income for a number of creators. Several pioneers of internet animation migrated to this platform to provide greater visibility and economic security for their productions. A group of YouTubers, so-called 'Reply Girls', achieved rapid economic benefits by publishing content without any value, neither artistic nor communicative, but that deceived YouTube's remuneration system and prioritization algorithm. To fight this phenomenon, YouTube subsequently applied changes to its prioritization algorithm and monetization plans. In this article, the author examines more than 3,300 videos published by 25 animation channels between 2006 and 2018 with Digital Methods tools to analyse how the changes applied to the platform policies have influenced and shaped the evolution of animation production on the internet.
Desktop version websites are designed for viewing on desktops or laptops screens and are not optimized for mobile devices. With increased adoption of mobile technologies, businesses and governments, which already own ...
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ISBN:
(纸本)9781728114606
Desktop version websites are designed for viewing on desktops or laptops screens and are not optimized for mobile devices. With increased adoption of mobile technologies, businesses and governments, which already own a desktop version website but not a mobile version website are often required to invest heavily in a full web development life cycle to obtain a website optimized for mobile devices. Given that website development is complex, time consuming and costly, we propose a simplified approach in the form of a tool, which makes use of open source technologies to automatically convert existing desktop websites into mobile versions without the need to go through a complete website development life cycle. The proposed tool presented in this paper particularly targets, but is not limited to, Governments from developing countries with strict budget constraints.
Background: prioritization of waiting lists for elective surgery represents a major issue in public systems in view of the fact that patients often suffer from consequences of long waiting times. In addition, administ...
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Background: prioritization of waiting lists for elective surgery represents a major issue in public systems in view of the fact that patients often suffer from consequences of long waiting times. In addition, administrative and standardized data on waiting lists are generally lacking in Italy, where no detailed national reports are available. This is true although since 2002 the National Government has defined implicit Urgency-Related Groups (URGs) associated with Maximum Time Before Treatment (MTBT), similar to the Australian classification. The aim of this paper is to propose a model to manage waiting lists and prioritize admissions to elective surgery. Methods: In 2001, the Italian Ministry of Health funded the Surgical Waiting List Info System (SWALIS) project, with the aim of experimenting solutions for managing elective surgery waiting lists. The project was split into two phases. In the first project phase, ten surgical units in the largest hospital of the Liguria Region were involved in the design of a pre-admission process model. The model was embedded in a Web based software, adopting Italian URGs with minor modifications. The SWALIS pre-admission process was based on the following steps: 1) urgency assessment into URGs;2) correspondent assignment of a preset MTBT;3) real time prioritization of every referral on the list, according to urgency and waiting time. In the second project phase a prospective descriptive study was performed, when a single general surgery unit was selected as the deployment and test bed, managing all registrations from March 2004 to March 2007 (1809 ordinary and 597 day cases). From August 2005, once the SWALIS model had been modified, waiting lists were monitored and analyzed, measuring the impact of the model by a set of performance indexes (average waiting time, length of the waiting list) and Appropriate Performance Index (API). Results: The SWALIS pre-admission model was used for all registrations in the test period, fully cov
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