Using cloud-based, open-source technology to evaluate, improve, and rapidly disseminate community-based intervention data.
Ontology highlight
ABSTRACT:
SUBMITTER: Mayfield CA
PROVIDER: S-EPMC7671634 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundMetagenomic next-generation sequencing (mNGS) has enabled the rapid, unbiased detection and identification of microbes without pathogen-specific reagents, culturing, or a priori knowledge of the microbial landscape. mNGS data analysis requires a series of computationally intensive processing steps to accurately determine the microbial composition of a sample. Existing mNGS data analysis tools typically require bioinformatics expertise and access to local server-class hardware resources. For many research laboratories, this presents an obstacle, especially in resource-limited environments.FindingsWe present IDseq, an open source cloud-based metagenomics pipeline and service for global pathogen detection and monitoring (https://idseq.net). The IDseq Portal accepts raw mNGS data, performs host and quality filtration steps, then executes an assembly-based alignment pipeline, which results in the assignment of reads and contigs to taxonomic categories. The taxonomic relative abundances are reported and visualized in an easy-to-use web application to facilitate data interpretation and hypothesis generation. Furthermore, IDseq supports environmental background model generation and automatic internal spike-in control recognition, providing statistics that are critical for data interpretation. IDseq was designed with the specific intent of detecting novel pathogens. Here, we benchmark novel virus detection capability using both synthetically evolved viral sequences and real-world samples, including IDseq analysis of a nasopharyngeal swab sample acquired and processed locally in Cambodia from a tourist from Wuhan, China, infected with the recently emergent SARS-CoV-2.ConclusionThe IDseq Portal reduces the barrier to entry for mNGS data analysis and enables bench scientists, clinicians, and bioinformaticians to gain insight from mNGS datasets for both known and novel pathogens.
| S-EPMC7566497 | biostudies-literature
Project description:BACKGROUND:Web-based interventions for smoking cessation available in Portuguese do not adhere to evidence-based treatment guidelines. Besides, all existing web-based interventions are built on proprietary platforms that developing countries often cannot afford. We aimed to describe the development of "Viva sem Tabaco", an open-source web-based intervention. RESULTS:The development of the intervention included the selection of content from evidence-based guidelines for smoking cessation, the design of the first layout, conduction of 2 focus groups to identify potential features, refinement of the layout based on focus groups and correction of content based on feedback provided by specialists on smoking cessation. At the end, we released the source-code and intervention on the Internet and translated it into Spanish and English. CONCLUSIONS:The intervention developed fills gaps in the information available in Portuguese and the lack of open-source interventions for smoking cessation. The open-source licensing format and its translation system may help researchers from different countries deploying evidence-based interventions for smoking cessation.
| S-EPMC4970282 | biostudies-literature
Project description:It is well established that most of the plastic pollution found in the oceans is transported via rivers. Unfortunately, the main processes contributing to plastic and debris displacement through riparian systems is still poorly understood. The Marine Litter Drifter project from the Arno River aims at using modern consumer software and hardware technologies to track the movements of real anthropogenic marine debris (AMD) from rivers. The innovative "Marine Litter Trackers" (MLT) were utilized as they are reliable, robust, self-powered and they present almost no maintenance costs. Furthermore, they can be built not only by those trained in the field but also by those with no specific expertise, including high school students, simply by following the instructions. Five dispersion experiments were successfully conducted from April 2021 to December 2021, using different types of trackers in different seasons and weather conditions. The maximum distance tracked was 2845 km for a period of 94 days. The activity at sea was integrated by use of Lagrangian numerical models that also assisted in planning the deployments and the recovery of drifters. The observed tracking data in turn were used for calibration and validation, recursively improving their quality. The dynamics of marine litter (ML) dispersion in the Tyrrhenian Sea is also discussed, along with the potential for open-source approaches including the "citizen science" perspective for both improving big data collection and educating/awareness-raising on AMD issues.
| S-EPMC9863889 | biostudies-literature
Project description:The increasing public availability of personal complete genome sequencing data has ushered in an era of democratized genomics. However, read mapping and variant calling software is constantly improving and individuals with personal genomic data may prefer to customize and update their variant calls. Here, we describe STORMSeq (Scalable Tools for Open-Source Read Mapping), a graphical interface cloud computing solution that does not require a parallel computing environment or extensive technical experience. This customizable and modular system performs read mapping, read cleaning, and variant calling and annotation. At present, STORMSeq costs approximately $2 and 5-10 hours to process a full exome sequence and $30 and 3-8 days to process a whole genome sequence. We provide this open-access and open-source resource as a user-friendly interface in Amazon EC2.
| S-EPMC3893165 | biostudies-literature
Project description:A key aspect of neuroscience research is the development of powerful, general-purpose data analyses that process large datasets. Unfortunately, modern data analyses have a hidden dependence upon complex computing infrastructure (e.g., software and hardware), which acts as an unaddressed deterrent to analysis users. Although existing analyses are increasingly shared as open-source software, the infrastructure and knowledge needed to deploy these analyses efficiently still pose significant barriers to use. In this work, we develop Neuroscience Cloud Analysis As a Service (NeuroCAAS): a fully automated open-source analysis platform offering automatic infrastructure reproducibility for any data analysis. We show how NeuroCAAS supports the design of simpler, more powerful data analyses and that many popular data analysis tools offered through NeuroCAAS outperform counterparts on typical infrastructure. Pairing rigorous infrastructure management with cloud resources, NeuroCAAS dramatically accelerates the dissemination and use of new data analyses for neuroscientific discovery.
| S-EPMC9464703 | biostudies-literature
Project description:Valid, direct observation of medical student competency in clinical settings remains challenging and limits the opportunity to promote performance-based student advancement. The rationale for direct observation is to ascertain that students have acquired the core clinical competencies needed to care for patients. Too often student observation results in highly variable evaluations which are skewed by factors other than the student's actual performance. Among the barriers to effective direct observation and assessment include the lack of effective tools and strategies for assuring that transparent standards are used for judging clinical competency in authentic clinical settings. We developed a web-based content management system under the name, Just in Time Medicine (JIT), to address many of these issues. The goals of JIT were fourfold: First, to create a self-service interface allowing faculty with average computing skills to author customizable content and criterion-based assessment tools displayable on internet enabled devices, including mobile devices; second, to create an assessment and feedback tool capable of capturing learner progress related to hundreds of clinical skills; third, to enable easy access and utilization of these tools by faculty for learner assessment in authentic clinical settings as a means of just in time faculty development; fourth, to create a permanent record of the trainees' observed skills useful for both learner and program evaluation. From July 2010 through October 2012, we implemented a JIT enabled clinical evaluation exercise (CEX) among 367 third year internal medicine students. Observers (attending physicians and residents) performed CEX assessments using JIT to guide and document their observations, record their time observing and providing feedback to the students, and their overall satisfaction. Inter-rater reliability and validity were assessed with 17 observers who viewed six videotaped student-patient encounters and by measuring the correlation between student CEX scores and their scores on subsequent standardized-patient OSCE exams. A total of 3567 CEXs were completed by 516 observers. The average number of evaluations per student was 9.7 (±1.8 SD) and the average number of CEXs completed per observer was 6.9 (±15.8 SD). Observers spent less than 10 min on 43-50% of the CEXs and 68.6% on feedback sessions. A majority of observers (92%) reported satisfaction with the CEX. Inter-rater reliability was measured at 0.69 among all observers viewing the videotapes and these ratings adequately discriminated competent from non-competent performance. The measured CEX grades correlated with subsequent student performance on an end-of-year OSCE. We conclude that the use of JIT is feasible in capturing discrete clinical performance data with a high degree of user satisfaction. Our embedded checklists had adequate inter-rater reliability and concurrent and predictive validity.
| S-EPMC3792179 | biostudies-literature
Project description:We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic indicators. Interactions between individuals are modelled in groups of various sizes and properties, such as households, schools and workplaces, and other social activities using social mixing matrices. June provides a suite of flexible parametrizations that describe infectious diseases, how they are transmitted and affect contaminated individuals. In this paper, we apply June to the specific case of modelling the spread of COVID-19 in England. We discuss the quality of initial model outputs which reproduce reported hospital admission and mortality statistics at national and regional levels as well as by age strata.
| S-EPMC8261230 | biostudies-literature
Project description:Rivers worldwide are now acting as major transport pathways for plastic pollution and discharge large quantities of waste into the ocean. Previous oceanographic modelling and current drifter data have been used to predict the movement and accumulation of plastic pollution in the marine environment, but our understanding of the transport and fate through riparian systems is still largely unknown. Here we undertook a proof of concept study by applying open source tracking technology (both GPS (Global Positing System) cellular networks and satellite technology), which have been successfully used in many animal movement studies, to track the movements of individual plastic litter items (500 ml PET (polyethylene terephthalate) drinks bottles) through the Ganges River system (known as the Ganga in India and the Padma and Meghna in Bangladesh, hereafter known as the Ganges) and the Bay of Bengal. Deployed tags were successfully tracked through the Ganges river system and into the Bay of Bengal marine system. The "bottle tags" were designed and built (e.g. shape, size, buoyancy) to replicate true movement patterns of a plastic bottle. The maximum distance tracked to date is 2845 km over a period of 94 days. We discuss lessons learnt from the development of these plastic litter tags, and outline how the potential widespread use of this open source technology has the ability to significantly increase understanding of the location of accumulation areas and the timing of large inputs of plastic pollution into the aquatic system. Furthermore, "bottle tags" may act as a powerful tool for stimulating social behaviour change, informing science-based policy, and as valuable educational outreach tools for public awareness.
| S-EPMC7710111 | biostudies-literature
Project description:The utilization of technology has allowed for several advances in aphasia rehabilitation for individuals with acquired brain injury. Thirty-one previous studies that provide technology-based language or language and cognitive rehabilitation are examined in terms of the domains addressed, the types of treatments that were provided, details about the methods and the results, including which types of outcomes are reported. From this, we address questions about how different aspects of the delivery of treatment can influence rehabilitation outcomes, such as whether the treatment was standardized or tailored, whether the participants were prescribed homework or not, and whether intensity was varied. Results differed by these aspects of treatment delivery but ultimately the studies demonstrated consistent improvement on various outcome measures. With these aspects of technology-based treatment in mind, the ultimate goal of personalized rehabilitation is discussed.
| S-EPMC5532441 | biostudies-other
Project description:Wireless potentiostats capable of cyclic voltammetry and amperometry that connect to the Internet are emerging as key attributes of future point-of-care devices. This work presents an "integrated microfluidic electrochemical detector" (iMED) three-electrode multi-potentiostat designed around operational amplifiers connected to a powerful WiFi-based microcontroller as a promising alternative to more expensive and complex strategies reported in the literature. The iMED is integrated with a microfluidic system developed to be controlled by the same microcontroller. The iMED is programmed wirelessly over a standard WiFi network and all electrochemical data is uploaded to an open-source cloud-based server. A wired desktop computer is not necessary for operation or program uploading. This method of integrated microfluidic automation is simple, uses common and inexpensive materials, and is compatible with commercial sample injectors. An integrated biosensor platform contains four screen-printed carbon arrays inside 4 separate microfluidic detection chambers with Pt counter and pseudo Ag/AgCl reference electrodes in situ. The iMED is benchmarked with K3[Fe(CN)6] against a commercial potentiostat and then as a glucose biosensor using glucose-oxidising films of [Os(2,2'-bipyridine)2(polyvinylimidazole)10Cl] prepared on screen-printed electrodes with multi walled carbon nanotubes, poly(ethylene glycol) diglycidyl ether and flavin adenine dinucleotide-dependent glucose dehydrogenase. Potential application of this cost-effective wireless potentiostat approach to modern bioelectronics and point-of-care diagnosis is demonstrated by production of glucose oxidation currents, under pseudo-physiological conditions, using mediating films with lower redox potentials.
| S-EPMC7213535 | biostudies-literature