Browsing by Issue Date, starting with "2018-06-29"
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- EpiMass: a Clinical and Epidemiological Platform for Mass GatheringsPublication . Vieira, Miguel Felício; Silva, Mário Jorge Costa Gaspar da; Martins, Bruno Emanuel da GraçaThis work presents a clinical and epidemiological web platform designed for supporting the basic needs of a first aid post during Mass Gatherings (MGs), called EpiMass. The World Health Organization (WHO) defines an MG as a concentration of people which has the potential to strain the local emergency response mechanisms. EpiMass was built over a 3-tier architecture, based on the MEAN stack (MongoDB, Express, Angular, and Node.js), i.e., a state-of-the-art open-source framework for developing web applications. It enables clinical and epidemiology professionals to perform actions and gather information relevant for their roles. The platform offers integrated data visualization tools and an API which gives the ability to extract the data for analysis with other platforms. This allows for near fast real-time reporting with a preliminary analysis giving some statistics and visual clues over the data, as well as the possibility to do a more thorough analysis with external specialized software. An early prototype of the platform was implemented and tested during the 2018 Torres Vedras Carnival, where it has shown to be viable to collect data during MG events.
- Cystic Fibrosis Newborn Screening in Portugal: PAP Value in Populations with Stringent Rules for Genetic StudiesPublication . Marcão, Ana; Barreto, Celeste; Pereira, Luísa; Vaz, Luísa; Cavaco, José; Casimiro, Ana; Félix, Miguel; Silva, Teresa; Barbosa, Telma; Freitas, Cristina; Nunes, Sidónia; Felício, Verónica; Lopes, Lurdes; Amaral, Margarida; Vilarinho, LauraNewborn screening (NBS) for cystic fibrosis (CF) has been shown to be advantageous for children with CF, and has thus been included in most NBS programs using various algorithms. With this study, we intend to establish the most appropriate algorithm for CF-NBS in the Portuguese population, to determine the incidence, and to contribute to elucidating the genetic epidemiology of CF in Portugal. This was a nationwide three-year pilot study including 255,000 newborns (NB) that were also screened for congenital hypothyroidism (CH) and 24 other metabolic disorders included in the Portuguese screening program. Most samples were collected in local health centers spread all over the country, between the 3rd and 6th days of life. The algorithm tested includes immunoreactive trypsinogen (IRT) determination, pancreatitis associated protein (PAP) as a second tier, and genetic study for cases referred to specialized clinical centers. Thirty-four CF cases were confirmed positive, thus indicating an incidence of 1:7500 NB. The p.F508del mutation was found in 79% of the alleles. According to the results presented here, CF-NBS is recommended to be included in the Portuguese NBS panel with a small adjustment regarding the PAP cut-off, which we expect to contribute to the improvement of the CF-NBS performance. According to our results, this algorithm is a valuable alternative for CF-NBS in populations with stringent rules for genetic studies.
- INSaFLU: an automated open web-based bioinformatics suite "from-reads" for influenza whole-genome-sequencing-based surveillancePublication . Borges, Vítor; Pinheiro, Miguel; Pechirra, Pedro; Guiomar, Raquel; Gomes, João PauloBackground: A new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data. Results: We developed and implemented INSaFLU (“INSide the FLU”), which is the first influenza-oriented bioinformatics free web-based suite that deals with primary NGS data (reads) towards the automatic generation of the output data that are actually the core first-line “genetic requests” for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants’ annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform multi-step software intensive analyses in a user-friendly manner without previous advanced training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tuned data analysis. This platform additionally flags samples as “putative mixed infections” if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional “consensus-based” influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission. Conclusions: In summary, INSaFLU supplies public health laboratories and influenza researchers with an open “one size fits all” framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.