Search

This paper advances the self-attention mechanism in the standard transformer network specific to the modeling of the protein sequences. We introduce a novel context-window based scaled self-attention mechanism for processing protein sequences that is based on the notion of (i) local context and (ii) large contextual pattern. Both notions are essential to building a good representation for protein sequences. The proposed context-window based scaled self-attention mechanism is further used to build the multi context-window based scaled (MCWS) transformer network for the protein function prediction task at the protein sub-sequence level. Overall, the proposed MCWS transformer network produced improved predictive performances, outperforming existing state-of-the-art approaches by substantial margins. With respect to the standard transformer network, the proposed network produced improvements in F1-score of +2.30% and +2.08% on the biological process (BP) and molecular function (MF) datasets, respectively. The corresponding improvements over the state-of-the-art ProtVecGen-Plus+ProtVecGen-Ensemble approach are +3.38% (BP) and +2.86% (MF). Equally important, robust performances were obtained across protein sequences of different lengths.

During the COVID-19 pandemic, a number of data visualizations were created to inform the public about the rapidly evolving crisis. Data dashboards, a form of information dissemination used during the pandemic, have facilitated this process by visualizing statistics regarding the number of COVID-19 cases over time. Prior work on COVID-19 visualizations has primarily focused on the design and evaluation of specific visualization systems from technology-centered perspectives. However, little is known about what occurs behind the scenes during the visualization creation processes, given the complex sociotechnical contexts in which they are embedded. Yet, such ecological knowledge is necessary to help characterize the nuances and trajectories of visualization design practices in the wild, as well as generate insights into how creators come to understand and approach visualization design on their own terms and for their own situated purposes. In this research, we conducted a qualitative interview study among dashboard creators from federal agencies, state health departments, mainstream news media outlets, and other organizations that created (often widely-used) COVID-19 dashboards to answer the following questions: how did visualization creators engage in COVID-19 dashboard design, and what tensions, conflicts, and challenges arose during this process? Our findings detail the trajectory of design practices-from creation to expansion, maintenance, and termination-that are shaped by the complex interplay between design goals, tools and technologies, labor, emerging crisis contexts, and public engagement. We particularly examined the tensions between designers and the general public involved in these processes. These conflicts, which often materialized due to a divergence between public demands and standing policies, centered around the type and amount of information to be visualized, how public perceptions shape and are shaped by visualization design, and the strategies utilized to deal with (potential) misinterpretations and misuse of visualizations. Our findings and lessons learned shed light on new ways of thinking in visualization design, focusing on the bundled activities that are invariably involved in human and nonhuman participation throughout the entire trajectory of design practice.

Many clinical decision support systems (CDSS) have shown good performance in the research context, but only a few have been brought into routine care. Analysis of success or failure factors in the design of CDSS may support translation from development to routine care by guiding CDSS design and development along these factors. In this work, we propose a schema to describe CDSS designs in a consistent way. We focus on design criteria with the aim to investigate the observed translation gap in CDSS. Existing description models on different aspects relevant for CDSS are combined to a comprehensive schema that allows description and comparison of CDSS without limitation to the domain or architecture.

Aims: To investigate the applicability of deep learning image assessment software VeriSee DR to different color fundus cameras for the screening of diabetic retinopathy (DR)., Methods: Color fundus images of diabetes patients taken with three different nonmydriatic fundus cameras, including 477 Topcon TRC-NW400, 459 Topcon TRC-NW8 series, and 471 Kowa nonmyd 8 series that were judged as "gradable" by one ophthalmologist were enrolled for validation. VeriSee DR was then used for the diagnosis of referable DR according to the International Clinical Diabetic Retinopathy Disease Severity Scale. Gradability, sensitivity, and specificity were calculated for each camera model., Results: All images (100%) from the three camera models were gradable for VeriSee DR. The sensitivity for diagnosing referable DR in the TRC-NW400, TRC-NW8, and non-myd 8 series was 89.3%, 94.6%, and 95.7%, respectively, while the specificity was 94.2%, 90.4%, and 89.3%, respectively. Neither the sensitivity nor the specificity differed significantly between these camera models and the original camera model used for VeriSee DR development ( p = 0.40, p = 0.065, respectively)., Conclusions: VeriSee DR was applicable to a variety of color fundus cameras with 100% agreement with ophthalmologists in terms of gradability and good sensitivity and specificity for the diagnosis of referable DR., Competing Interests: Acer Inc. and National Taiwan University own the intellectual property of VeriSee DR. Y-T Hsieh received speaker's fees from Acer Inc., (Copyright © 2022 Meng-Ju Tsai et al.)

Population pharmacokinetic (PK) modeling is a widely used approach to analyze PK data obtained from groups of individuals, in both industry and academic research. The approach can also be used to analyze pharmacodynamic (PD) data and pooled PK/PD data. There are 2 main families of population PK methods: parametric and nonparametric. The objectives of this article are to present an overview of nonparametric methods used in population pharmacokinetic modeling and to explain their specific characteristics to inform scientists and clinicians about their potential value for data analysis, simulation, dosage design, and therapeutic drug monitoring (TDM). Nonparametric methods have several interesting characteristics for population PK analysis, including computation of exact likelihoods, the ability to accommodate parameter probability distributions of any shape (eg, non-Gaussian), and to detect subpopulations and outliers. Nonparametric population methods are also highly relevant for model-based TDM and design of individualized drug dosage regimens. Several algorithms have been developed to estimate model parameter values within an individual and compute that individual's dosage to achieve target drug exposure with maximum precision and accuracy. Nonparametric modeling methods for both population and individual PK analysis are available under user-friendly packages., (© 2020, The American College of Clinical Pharmacology.)

Population pharmacokinetic (popPK) approaches have spread widely throughout clinical pharmacology research, and every clinician should have some understanding of them. After a general introduction on the fundamentals and fields of application of these approaches, this review focuses on parametric popPK methods to provide the clinicians with the conceptual tools to interpret appropriately the results of parametric popPK analyses and to understand their clinical utility. The emphasis is put on the clinical questions that popPK methods are best suited to address. The basic principles of the methodology are introduced first, and then the main algorithms and reference software programs used in such analyses are presented. The description of data analysis and clinical applications of the parametric popPK approach (ie, use in simulations and therapeutic drug monitoring) are illustrated with the example of the antiretroviral drug efavirenz., (© 2020, The American College of Clinical Pharmacology.)

Population pharmacokinetics consists of analyzing pharmacokinetic (PK) data collected in groups of individuals. Population PK is widely used to guide drug development and to inform dose adjustment via therapeutic drug monitoring and model-informed precision dosing. There are 2 main types of population PK methods: parametric (P) and nonparametric (NP). The characteristics of P and NP population methods have been previously reviewed. The aim of this article is to answer some frequently asked questions that are often raised by scholars, clinicians, and researchers about P and NP population PK methods. The strengths and limitations of both approaches are explained, and the characteristics of the main software programs are presented. We also review the results of studies that compared the results of both approaches in the analysis of real data. This opinion article may be informative for potential users of population methods in PK and guide them in the selection and use of those tools. It also provides insights on future research in this area., (© 2021, The American College of Clinical Pharmacology.)

Competing Interests: The authors have declared that no competing interests exist.

An increasing number of recent studies have suggested that doubly robust estimators with cross-fitting should be used when estimating causal effects with machine learning methods. However, not all existing programs that implement doubly robust estimators support machine learning methods and cross-fitting, or provide estimates on multiplicative scales. To address these needs, we developed AIPW, a software package implementing augmented inverse probability weighting (AIPW) estimation of average causal effects in R (R Foundation for Statistical Computing, Vienna, Austria). Key features of the AIPW package include cross-fitting and flexible covariate adjustment for observational studies and randomized controlled trials (RCTs). In this paper, we use a simulated RCT to illustrate implementation of the AIPW estimator. We also perform a simulation study to evaluate the performance of the AIPW package compared with other doubly robust implementations, including CausalGAM, npcausal, tmle, and tmle3. Our simulation showed that the AIPW package yields performance comparable to that of other programs. Furthermore, we also found that cross-fitting substantively decreases the bias and improves the confidence interval coverage for doubly robust estimators fitted with machine learning algorithms. Our findings suggest that the AIPW package can be a useful tool for estimating average causal effects with machine learning methods in RCTs and observational studies., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Paraquat is responsible for an extremely high case-fatality rate poisoning. Mortality prediction remains a major issue since evidence to support benefits of routinely used treatments is lacking. We aimed to develop an easy-to-use prediction flowchart not requiring the ingestion time, for which accuracy is frequently questionable, and to evaluate the effectiveness of routinely used pharmacological therapies on mortality. We designed a two-centre cohort study including consecutive paraquat-poisoned adults with confirmed diagnosis based on serum/urine paraquat measurement. We built a flowchart using a multivariate analysis of death predictors and analysed the outcome according to the administered therapies. Overall, 256 patients were enrolled. Mortality rate was 75%. Independent death predictors on admission were serum creatinine (odds ratio [OR], 5.07; 95% confidence interval [CI], 1.97-13.05) and serum paraquat concentration (OR, 2.26; CI, 1.66-3.09). The area-under-the flowchart curve was 0.91. Overall sensitivity and specificity were 81.5% and 94.8%, respectively. More survivors than non-survivors of severe poisoning received methylprednisolone (P = 0.04). While not significantly differing in severity, methylprednisolone-treated patients had better survival (P = 0.04). To conclude, we defined an efficient flowchart to predict mortality in paraquat poisoning at presentation, even if ingestion time is undetermined. Methylprednisolone seems effective to improve the outcome, especially in the most severe cases., (© 2021 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society). Published by John Wiley & Sons Ltd.)

The clinical and societal measurement of human sleep has increased exponentially in recent years. However, unlike other fields of medical analysis that have become highly automated, basic and clinical sleep research still relies on human visual scoring. Such human-based evaluations are time-consuming, tedious, and can be prone to subjective bias. Here, we describe a novel algorithm trained and validated on +30,000 hr of polysomnographic sleep recordings across heterogeneous populations around the world. This tool offers high sleep-staging accuracy that matches human scoring accuracy and interscorer agreement no matter the population kind. The software is designed to be especially easy to use, computationally low-demanding, open source, and free. Our hope is that this software facilitates the broad adoption of an industry-standard automated sleep staging software package., Competing Interests: RV, MW No competing interests declared, (© 2021, Vallat and Walker.)

Command-line software plays a critical role in biology research. However, processes for installing and executing software differ widely. The Common Workflow Language (CWL) is a community standard that addresses this problem. Using CWL, tool developers can formally describe a tool's inputs, outputs, and other execution details. CWL documents can include instructions for executing tools inside software containers. Accordingly, CWL tools are portable-they can be executed on diverse computers-including personal workstations, high-performance clusters, or the cloud. CWL also supports workflows, which describe dependencies among tools and using outputs from one tool as inputs to others. To date, CWL has been used primarily for batch processing of large datasets, especially in genomics. But it can also be used for analytical steps of a study. This article explains key concepts about CWL and software containers and provides examples for using CWL in biology research. CWL documents are text-based, so they can be created manually, without computer programming. However, ensuring that these documents conform to the CWL specification may prevent some users from adopting it. To address this gap, we created ToolJig, a Web application that enables researchers to create CWL documents interactively. ToolJig validates information provided by the user to ensure it is complete and valid. After creating a CWL tool or workflow, the user can create 'input-object' files, which store values for a particular invocation of a tool or workflow. In addition, ToolJig provides examples of how to execute the tool or workflow via a workflow engine. ToolJig and our examples are available at https://github.com/srp33/ToolJig., Competing Interests: SP, ZE, EA, JC, AB No competing interests declared, (© 2021, Piccolo et al.)

Mitochondria are dynamic organelles that differ significantly in their morphologies across cell types, reflecting specific cellular needs and stages in development. Despite the wide biological significance in disease and in health, delineating mitochondrial morphologies in complex systems remains challenging. Here, we present the Mitochondrial Cellular Phenotype (MitoCellPhe) tool developed for quantifying mitochondrial morphologies and demonstrate its utility in delineating differences in mitochondrial morphologies in a human fibroblast and human induced pluripotent stem cell (hiPSC) line. MitoCellPhe generates 24 parameters, allowing for a comprehensive analysis of mitochondrial structures and importantly allows for quantification to be performed on mitochondria in images containing single cells or clusters of cells. With this tool, we were able to validate previous findings that show networks of mitochondria in healthy fibroblast cell lines and a more fragmented morphology in hiPSCs. Using images generated from control and diseased fibroblasts and hiPSCs, we also demonstrate the efficacy of the toolset in delineating differences in morphologies between healthy and the diseased state in both stem cell (hiPSC) and differentiated fibroblast cells. Our results demonstrate that MitoCellPhe enables high-throughput, sensitive, detailed, and quantitative mitochondrial morphological assessment and thus enables better biological insights into mitochondrial dynamics in health and disease.

Background: Patients diagnosed with cancer who are due to commence radiotherapy, often, despite the provision of a considerable amount of information, report a range of unmet information needs about the treatment process. Factors such as inadequate provision of information, or the stressful situation of having to deal with information about unfamiliar things, may influence the patient's ability to comprehend the information. There is a need to further advance the format in which such information is presented. The composition of information should be tailored according to the patient's individual needs and style of learning., Method and Findings: The PD methodology is frequently used when a technology designed artefact is the desired result of the process. This research is descriptive of its kind and provides a transparent description of the co-design process used to develop an innovative digital information tool employing PD methodology where several stakeholders participated as co-designers. Involving different stakeholders in the process in line with recommended PD activities enabled us to develop a digital information tool that has the potential to be relevant and user-friendly for the ultimate consumer., Conclusions: Facilitating collaboration, structured PD activities can help researchers, healthcare professionals and patients to co-design patient information that meets the end users' needs. Furthermore, it can enhance the rigor of the process, ensure the relevance of the information, and finally have a potential to employ a positive effect on the reach of the related digital information tool., Competing Interests: The authors have declared that no competing interest exist.

Context.—: Tumor reporting constitutes a significant daily task of pathologists. An efficient tumor-reporting methodology is thus vitally important. The Web dynamic form (WbDF) method offers a multitude of advantages over the prevailing transcription-mediated reporting method based on static-text checklists. However, its adaptation has been severely hampered for 2 decades by its costly needs to maintain a complex back-end system and to change the system for frequent updates of reporting content., Objective.—: To overcome these 2 obstacles with a serverless Web platform that enables users to create, customize, use, and download WbDFs as synoptic templates for structured tumor reporting., Design.—: Deploy ReactJS as a Web platform. Create form components in JavaScript Object Notation files. Use JavaScript Object Notation files to make WbDFs on the Web platform. Use the WbDFs to generate final pathology reports., Results.—: Ordinary users (pathologists) can create/customize reporting templates as WbDFs on the Web platform. The WbDF can be used to make a pathology report and stored/shared like ordinary document files. There is no back-end system to change, nor a requirement for computer programming skills., Conclusions.—: This strategy eliminates the need for a complex back-end system and the associated cost when updating tumor-reporting standards, making it possible to adopt the WbDF method without the technological drawbacks associated with content updates. It also opens a new field of how the tumor-reporting system should be organized, updated, and implemented.

Real-time rendering of closed-loop visual environments is important for next-generation understanding of brain function and behaviour, but is often prohibitively difficult for non-experts to implement and is limited to few laboratories worldwide. We developed BonVision as an easy-to-use open-source software for the display of virtual or augmented reality, as well as standard visual stimuli. BonVision has been tested on humans and mice, and is capable of supporting new experimental designs in other animal models of vision. As the architecture is based on the open-source Bonsai graphical programming language, BonVision benefits from native integration with experimental hardware. BonVision therefore enables easy implementation of closed-loop experiments, including real-time interaction with deep neural networks, and communication with behavioural and physiological measurement and manipulation devices., Competing Interests: GL Gonçalo Lopes is affiliated with NeuroGEARS Ltd. The author has no financial interests to declare. KF, EH, CL, MM, TM, AP, FR, TW, SZ, SS, AS No competing interests declared, (© 2021, Lopes et al.)

The cellular Potts model (CPM) is a powerful in silico method for simulating biological processes at tissue scale. Their inherently graphical nature makes CPMs very accessible in theory, but in practice, they are mostly implemented in specialised frameworks users need to master before they can run simulations. We here present Artistoo (Artificial Tissue Toolbox), a JavaScript library for building 'explorable' CPM simulations where viewers can change parameters interactively, exploring their effects in real time. Simulations run directly in the web browser and do not require third-party software, plugins, or back-end servers. The JavaScript implementation imposes no major performance loss compared to frameworks written in C++; Artistoo remains sufficiently fast for interactive, real-time simulations. Artistoo provides an opportunity to unlock CPM models for a broader audience: interactive simulations can be shared via a URL in a zero-install setting. We discuss applications in CPM research, science dissemination, open science, and education., Competing Interests: IW, JT No competing interests declared, (© 2021, Wortel and Textor.)

This paper describes the software design/development process leading to an improved computerized clinical/management solution-RSIPA (2016 version)-integrating care pathways (CPs) specifically designed to meet the needs of frail and disabled older adults in home care. The development methodology used Soft Systems Methodology (SSM) for the initial system design and participatory design (PD) to involve stakeholders and end users, along with AGILE SCRUM methodology to provide rapid iterations in adapting to new requests. Given scarce project resources, we opted to combine methodologies to efficiently deliver a fully functional system for three of the five CP clinical phases. The development methodology aggregated assessment-based data to identify risk factors and assist in needs prioritization leading to care plans and addressed in the current system. The new Quebec RSIPA solution incorporating CCPs is a promising example of technologies that support person-centered care, clinical and management processes, and proactive care in home-care settings.

Background: Following the provision of urgent care, screening for risks known to impact patient outcomes is an extension of safe emergency nursing care, in particular for falls, pressure injury and substance use. Screening is a process that primarily aims to identify people at increased risk for specific complications. This study aimed to describe and evaluate the implementation of a consolidated electronic checklist on the screening completion rates for falls, pressure injury and substance use in a regional health district., Methods: This pre-post study used emergency data from four Emergency Departments (EDs) in southern NSW, Australia between November 2016 and February 2019. Patient characteristics, triage category, discharge diagnosis, arrival date and time, screening completion date and time and treatment location were extracted. Descriptive statistics were used to describe the characteristics of the presentations. Z test with adjusted p-values using Bonferroni Correction method was used to compare the characteristics of the presentations and the rates of screening completion. The Theoretical Domains Framework was used to identify any deficits in the implementation., Results: There were 33,561 patients in the pre and 35,807 in the post group. There were no differences in patient characteristics between the two groups. The mean emergency department (ED) length of stay was unchanged (490.5min pre vs 489.9min post). The proportion of patients who had all three screens completed increased from 1.3% to 5.5% (p<0.001). Pressure injury risk screening increased from 46.6% (pre) to 53.1% (post) (p<0.001) as did substance use screening (1.7% vs 12.4%, p<0.001). Screening was strongly associated to which hospital the patient was admitted, their age and ED length of stay. Of the 51 mapped intervention functions, 20 (39%) were used in the implementation., Conclusions: The introduction of a consolidated electronic checklist for use by emergency nurses to complete fall, pressure injury and substance use screening resulted in an overall increase in risk screening. However screening rates remained poor. Implementation that considers the capability, opportunity and motivation of those that need to alter their behaviour would likely improve the overall compliance., (Crown Copyright © 2020. Published by Elsevier Ltd. All rights reserved.)

Mass spectrometry (MS)-based phosphoproteomics has revolutionized our ability to profile phosphorylation-based signaling in cells and tissues on a global scale. To infer the action of kinases and signaling pathways in phosphoproteomic experiments, we present PhosR, a set of tools and methodologies implemented in a suite of R packages facilitating comprehensive analysis of phosphoproteomic data. By applying PhosR to both published and new phosphoproteomic datasets, we demonstrate capabilities in data imputation and normalization by using a set of "stably phosphorylated sites" and in functional analysis for inferring active kinases and signaling pathways. In particular, we introduce a "signalome" construction method for identifying a collection of signaling modules to summarize and visualize the interaction of kinases and their collective actions on signal transduction. Together, our data and findings demonstrate the utility of PhosR in processing and generating biological knowledge from MS-based phosphoproteomic data., Competing Interests: Declaration of interests The authors declare no conflict of interest., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Fluorescence-detected linear dichroism microscopy allows observing various molecular processes in living cells, as well as obtaining quantitative information on orientation of fluorescent molecules associated with cellular features. Such information can provide insights into protein structure, aid in development of genetically encoded probes, and allow determinations of lipid membrane properties. However, quantitating and interpreting linear dichroism in biological systems has been laborious and unreliable. Here we present a set of open source ImageJ-based software tools that allow fast and easy linear dichroism visualization and quantitation, as well as extraction of quantitative information on molecular orientations, even in living systems. The tools were tested on model synthetic lipid vesicles and applied to a variety of biological systems, including observations of conformational changes during G-protein signaling in living cells, using fluorescent proteins. Our results show that our tools and model systems are applicable to a wide range of molecules and polarization-resolved microscopy techniques, and represent a significant step towards making polarization microscopy a mainstream tool of biological imaging.

Objective: Replacing face-to-face lessons by remote teaching due to COVID-19 led to a markedly reduced interaction between students and lecturers. In our opinion, one of the main reasons for this is the raise hand function of the respective web conference systems, which (independent of the system used) results in an unobtrusive signal that can easily be missed by the lecturer. Given the necessary focus on one's own presentation, questions can therefore only be perceived with a considerable time delay and can only be integrated into the lessons to a limited extent. Thus, the idea arose to display question requests of the auditorium by a clear visual signal in PowerPoint® itself. Methodology: With Visual Basic for Applications (VBA), Microsoft PowerPoint ® holds an integrated programming language that extends its functionality. Accordingly, VBA was used to program a routine running in the background of the presentation, which periodically retrieves the contents of a web-based "signal file" in a cycle of a few seconds. The content of this signal file, in turn, can be modified by the students by calling up an URL (i.e. from any Internet-capable device) - this results in a (customizable) visual signal in PowerPoint® that is temporarily visible and does not further interfere with the presentation. Conclusion: With the concept presented here, a raise hand function was realized in PowerPoint®, which manifests itself as a clear visual signal independent of the web conferencing system used. This enables the lecturers to respond instantly to questions from the audience during live transmission of lectures., Competing Interests: The author declares that he has no competing interests., (Copyright © 2021 Volf.)

Laboratory automation now commonly allows high-throughput sample preparation, culturing, and acquisition of microscopy images, but quantitative image analysis is often still a painstaking and subjective process. This is a problem especially significant for work on programmed morphogenesis, where the spatial organization of cells and cell types is of paramount importance. To address the challenges of quantitative analysis for such experiments, we have developed TASBE Image Analytics, a software pipeline for automatically segmenting collections of cells using the fluorescence channels of microscopy images. With TASBE Image Analytics, collections of cells can be grouped into spatially disjoint segments, the movement or development of these segments tracked over time, and rich statistical data output in a standardized format for analysis. Processing is readily configurable, rapid, and produces results that closely match hand annotation by humans for all but the smallest and dimmest segments. TASBE Image Analytics can thus provide the analysis necessary to complete the design-build-test-learn cycle for high-throughput experiments in programmed morphogenesis, as validated by our application of this pipeline to process experiments on shape formation with engineered CHO and HEK293 cells.

Cell-fate determination is a function of cell-intrinsic and -extrinsic signaling cues. Understanding the design principles governing fate control in multicellular systems remains difficult to understand and analyze. To address the current challenges of spatial analysis of potential signaling events, we have developed a pipeline for assessment of the neighboring cells at defined areas in the vicinity of target cells using a newly defined concept of Neighborhood Impact Factor. We have used our pipeline to interrogate cellular decision-making in a genetically derived multi-lineage liver organoid from induced pluripotent stem cells. We examined endothelial versus hepatocyte fate determination for cells with similar expression level of an engineered driver gene circuit. Our analysis suggests that the relative level of gene expression to the neighbor population can control the final fate choice in our engineered liver multicellular system.

Mobile technologies are becoming ubiquitous in the world, changing the way we communicate and provide patient care and services. Some of the most compelling benefits of mobile technologies are in the areas of disease prevention, health management, and care delivery. For all the advances that are occurring in mobile health, its full potential for older adults is only starting to emerge. Yet, existing mobile health applications have design flaws that may limit usability by older adults. The aim of this paper is to review barriers and identify knowledge gaps where more research is needed to improve the accessibility of mobile health use in aging populations. The same observations might apply to those who are not elderly, including individuals suffering from severe mental or medical illnesses.

Background: COVID-19 has officially been declared as a pandemic, and the spread of the virus is placing sustained demands on public health systems. There are speculations that the COVID-19 mortality differences between regions are due to the disparities in the availability of medical resources. Therefore, the selection of patients for diagnosis and treatment is essential in this situation. Military personnel are especially at risk for infectious diseases; thus, patient selection with an evidence-based prognostic model is critical for them., Objective: This study aims to assess the usability of a novel platform used in the military hospitals in Korea to gather data and deploy patient selection solutions for COVID-19., Methods: The platform's structure was developed to provide users with prediction results and to use the data to enhance the prediction models. Two applications were developed: a patient's application and a physician's application. The primary outcome was requiring an oxygen supplement. The outcome prediction model was developed with patients from four centers. A Cox proportional hazards model was developed. The outcome of the model for the patient's application was the length of time from the date of hospitalization to the date of the first oxygen supplement use. The demographic characteristics, past history, patient symptoms, social history, and body temperature were considered as risk factors. A usability study with the Post-Study System Usability Questionnaire (PSSUQ) was conducted on the physician's application on 50 physicians., Results: The patient's application and physician's application were deployed on the web for wider availability. A total of 246 patients from four centers were used to develop the outcome prediction model. A small percentage (n=18, 7.32%) of the patients needed professional care. The variables included in the developed prediction model were age; body temperature; predisease physical status; history of cardiovascular disease; hypertension; visit to a region with an outbreak; and symptoms of chills, feverishness, dyspnea, and lethargy. The overall C statistic was 0.963 (95% CI 0.936-0.99), and the time-dependent area under the receiver operating characteristic curve ranged from 0.976 at day 3 to 0.979 at day 9. The usability of the physician's application was good, with an overall average of the responses to the PSSUQ being 2.2 (SD 1.1)., Conclusions: The platform introduced in this study enables evidence-based patient selection in an effortless and timely manner, which is critical in the military. With a well-designed user experience and an accurate prediction model, this platform may help save lives and contain the spread of the novel virus, COVID-19., (©JoonNyung Heo, Ji Ae Park, Deokjae Han, Hyung-Jun Kim, Daeun Ahn, Beomman Ha, Woong Seog, Yu Rang Park. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 04.11.2020.)

Objectives: The isotope bone scan (IBS) is the gold-standard imaging modality for detecting skeletal metastases as part of prostate cancer staging. However, its clinical utility for assessing skeletal metastatic burden is limited due to the need for subjective interpretation. We designed and tested a novel custom software tool, the Metastatic Bone Scan Tool (MetsBST), aimed at improving interpretation of IBSs, and compared its performance with that of an established software programme., Methods: We used IBS images from 62 patients diagnosed with prostate cancer and suspected bone metastases to design and implement MetsBST in MATLAB by defining thresholds used to identify the texture and size of metastatic bone lesions. The results of MetsBST were compared with those of the commercially available automated Bone Scan Index (aBSI) with regression analysis., Results: There was strong agreement between the MetsBST and aBSI results ( R 2 = 0.9189). In a subregional analysis, MetsBST quantified the extent of metastatic disease in multiple bone sites in patients receiving multimodality therapy (radium-223 and external beam radiotherapy) to illustrate the differences in bone metastatic response to different treatments., Conclusion: The results of MetsBST and the commercial software aBSI were highly consistent. MetsBST introduces novel clinical utility by its ability to differentiate between the responses of different bone metastases to multimodality therapies., Advances in Knowledge: MetsBST reduces the variability in assessment of tumour burden caused by subjective interpretation. Therefore, it is a useful aid to physicians reporting nuclear medicine scans, and may improve decision-making in the treatment of metastatic prostate cancer.

Visual neuroprosthesis, that provide electrical stimulation along several sites of the human visual system, constitute a potential tool for vision restoration for the blind. Scientific and technological progress in the fields of neural engineering and artificial vision comes with new theories and tools that, along with the dawn of modern artificial intelligence, constitute a promising framework for the further development of neurotechnology. In the framework of the development of a Cortical Visual Neuroprosthesis for the blind (CORTIVIS), we are now facing the challenge of developing not only computationally powerful tools and flexible approaches that will allow us to provide some degree of functional vision to individuals who are profoundly blind. In this work, we propose a general neuroprosthesis framework composed of several task-oriented and visual encoding modules. We address the development and implementation of computational models of the firing rates of retinal ganglion cells and design a tool - Neurolight - that allows these models to be interfaced with intracortical microelectrodes in order to create electrical stimulation patterns that can evoke useful perceptions. In addition, the developed framework allows the deployment of a diverse array of state-of-the-art deep-learning techniques for task-oriented and general image pre-processing, such as semantic segmentation and object detection in our system's pipeline. To the best of our knowledge, this constitutes the first deep-learning-based system designed to directly interface with the visual brain through an intracortical microelectrode array. We implement the complete pipeline, from obtaining a video stream to developing and deploying task-oriented deep-learning models and predictive models of retinal ganglion cells' encoding of visual inputs under the control of a neurostimulation device able to send electrical train pulses to a microelectrode array implanted at the visual cortex.

High throughput sequencing of multiplexed PCR amplicons with Short Tandem Repeats (STRs) requires software solutions that sort the information and allow a comprehensive overview of the results without overwhelming the data analyst with details. Here, we present an updated version (2.0) of the STR analysis tool STRinNGS. It is freely available as a Docker image or zip file ready for downloading. STRinNGS predicts genotypes using criteria for read depth, noise, flanking region lengths, mismatches in the flanking regions, locus balance, and heterozygote balance. Warning flags highlight suspicious genotypes as well as suspicious sequences that are not identified as either noise or alleles in the result table used for the manual analysis. STRinNGS analyses both the STR and the flanking regions, and names the alleles according to the STRidER guidelines as well as an in-house nomenclature that also include variants in the flanking regions. Furthermore, STRinNGS generates files with analysed data in a format that may be uploaded directly to the STRidER database. We re-analysed 627 sample files from eight different MiSeq FGx runs with STRinNGS v2.0. The samples were previously typed with the ForenSeq™ Signature Prep Kit and analysed with STRinNGS v1.0 and the Universal Analysis Software. Apart from three poorly performing loci with large heterozygote imbalances (Penta E and D22S1045) or frequent single nucleotide errors (DYS461), only 58 genotype calls (0.2 %) had to be manually corrected and only 14 genotype calls were discordant with the previous analyses. The discordant calls were primarily caused by manual oversights and in every case, the STRinNGS v2.0 analysis was correct., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: The scope of methodological development and innovation in multi- and mixed methods design is endless and, at times, challenging. The latter is especially true with regards to the integration of data generated through different methods. About a decade ago, Professor Jo Moran-Ellis and her colleagues at the University of Sussex suggested a framework for analytical integration known as "following a thread." Despite an increased focus within health services research on different perspectives and approaches to successful data integration, the framework's usability and application have not yet been well described., Objectives: This systematic review aims to integrate and synthesise published accounts of the framework and its applications., Design and Data Sources: Seven electronic databases were utilised. Included were peer-reviewed scientific papers published in English from 2006 - 2018. The authors independently screened eligible publications by title and abstract., Results: Thirteen studies were included in our systematic review. One notable finding is that in almost half of the cases (n = 6), the framework had been applied as an analytical integration framework in single studies using multiple qualitative methods. Overall, the descriptions and accounts of the framework were sparse and lacked transparency. Accounts of the analytical integration framework could be said to fall within three overarching areas: (1) applications of the framework, (2) justifications for analytical integration, and (3) benefits and shortfalls of the framework., Conclusion: Data integration is often one of the major method steps in multi- and mixed methods designs. To further the future development of methodologically sound frameworks for analytical integration, it is essential that they are sufficiently described so as to ensure validation of the framework's usability and replicability. "Following a thread" appears to be an promising analytical integration framework, particularly in that it can be applied with the same datatypes as well as between different types of data., Competing Interests: Conflict of Interest The authors declare that they have no competing interests., (Copyright © 2020. Published by Elsevier Ltd.)

Background: African Americans breastfeed less than other groups, which has implications for health throughout the life course. Little is known about mobile health technologies to support breastfeeding., Research Aims: This study proceeded in two phases. The aim of Phase 1 was to identify ideal technological components and content of a mobile health intervention. The aim of Phase 2 was to determine the usability of a prototype, KULEA-NET, based on the Phase 1 findings., Methods: For this mixed-methods study, we used community-based participatory research methods and user-centered technology design methods. We used open coding in NVivo 11 to organize data from focus groups and in-depth interviews, then we analyzed the data. We then developed a prototype and tested the prototype's usability with the System Usability Scale. Fifty pregnant and postpartum African Americans from the District of Columbia participated., Results: Participants preferred an app with text messaging technology and identified areas for intervention: self-efficacy, parent-child attachment beliefs, social support, public breastfeeding and social desirability, and returning to work. Desired features included local resources, support person access, baby care logs, identification of public breastfeeding venues, and peer discussions. The System Usability Scale score was 73.8, which indicates above average usability., Conclusions: A mobile health technology like KULEA-NET can be used to meet the breastfeeding needs of African Americans, build social desirability, and complement traditional health care. The appeal of an African American-specific intervention is unclear. Responding to mixed feeding practices is challenging. KULEA-NET is a mobile breastfeeding intervention guided by the preferences of African American parents and offers promising usability metrics.

Objective: To develop an easy-to-use R package and web application that summarises baseline characteristics across different arms of a clinical trial or different exposures., Methods: Tables and figures are the efficient means of visualising, communicating and summarising data. It is common in comparative effectiveness research to provide a synopsis of characteristics and outcomes across the various treatment groups. The popularity of such a table has earned it a name and we simply call it the 'TableOne', as it is usually the first TableOne encounters looking at a published clinical trial. Such a table includes not only descriptive statistics for each group but also appropriate tests (p values and 95% CIs) for checking for differences across groups. We have developed an R package (called TableOne) (accessible through https://github.com/agapiospanos/TableOne) that quickly summarises and compares results across different groups. We have also extended it to an online web application that is easily handled by the researcher. All computations are done in R and plots are produced using the plotly library. We provide a detailed description on how to use the web application., Results: The application guides the user in a step by step format (wizard) and it is accessible through any browser in the following link (https://esm.uoi.gr/shiny/tableone/). Finally, appropriate interactive plots are provided for each variable., Conclusions: This easy-to-use web application will help researchers quickly and easily to visualise differences across treatment groups or different exposures., Competing Interests: Competing interests: No, there are no competing interests., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: We tested whether the level of endothelial dysfunction assessed by digital tonometry, and expressed as reactive hyperemia index (RHI), is related to occurrences of a discrepancy between fractional flow reserve (FFR) and the instantaneous wave free ratio (iFR) (ClinicalTrials.gov identifier: NCT03033810). Methods: We examined patients with coronary stenosis in the range of 40-70%, assessed by both FFR and iFR (system Philips-Volcano) for stable angina. We included consecutive patients with FFR and iFR in one native coronary artery, and who had had no previous intervention. Results: We included 138 patients. Out of those, 24 patients (17.4%) had a negative FFR (with an FFR value >0.8) and positive iFR (with a iFR value ≤0.89) - designated the FFRn/iFRp discrepancy group, and 22 patients (15.9%) had a positive FFR (≤0.8) and negative iFR (>0.89) - designated the FFRp/iFRn discrepancy. RHI was higher in the discrepancy groups compared the group without discrepancy (1.73 ± 0.79 vs. 1.48 ± 0.50, p  = 0.025). However, this finding was not confirmed in multivariant logistic regression analyses. Patients with any type of discrepancy differed from the agreement group by having a higher occurrence of diabetes mellitus [9 patients (21.4%) vs. 36 patients (39.6%), p  = 0.029], active smoking (23 patients or 54.8% vs. 26 patients or 28.6%, p  = 0.003) and lower use of calcium channel blockers (9 patients, 21.4%, vs. 43 patients, 46.7%, p  = 0.004). Conclusion: The presence of endothelial dysfunction can be associated with a discrepancy in FFR/iFR. However, RHI correlated with risk factors of atherosclerosis, not with FFR or iFR.

Background: FAIR (findability, accessibility, interoperability, and reusability) guiding principles seek the reuse of data and other digital research input, output, and objects (algorithms, tools, and workflows that led to that data) making them findable, accessible, interoperable, and reusable. GO FAIR - a bottom-up, stakeholder driven and self-governed initiative - defined a seven-step FAIRification process focusing on data, but also indicating the required work for metadata. This FAIRification process aims at addressing the translation of raw datasets into FAIR datasets in a general way, without considering specific requirements and challenges that may arise when dealing with some particular types of data., Objectives: This scientific contribution addresses the architecture design of an open technological solution built upon the FAIRification process proposed by "GO FAIR" which addresses the identified gaps that such process has when dealing with health datasets., Methods: A common FAIRification workflow was developed by applying restrictions on existing steps and introducing new steps for specific requirements of health data. These requirements have been elicited after analyzing the FAIRification workflow from different perspectives: technical barriers, ethical implications, and legal framework. This analysis identified gaps when applying the FAIRification process proposed by GO FAIR to health research data management in terms of data curation, validation, deidentification, versioning, and indexing., Results: A technological architecture based on the use of Health Level Seven International (HL7) FHIR (fast health care interoperability resources) resources is proposed to support the revised FAIRification workflow., Discussion: Research funding agencies all over the world increasingly demand the application of the FAIR guiding principles to health research output. Existing tools do not fully address the identified needs for health data management. Therefore, researchers may benefit in the coming years from a common framework that supports the proposed FAIRification workflow applied to health datasets., Conclusion: Routine health care datasets or data resulting from health research can be FAIRified, shared and reused within the health research community following the proposed FAIRification workflow and implementing technical architecture., Competing Interests: A.A.S. reports grants from EU H2020 Program, during the conduct of the study., (Georg Thieme Verlag KG Stuttgart · New York.)

To study the diversity of immune receptors and pathogens, multiplex PCR has become a central approach in research and diagnostics. However, insufficient primer design against highly diverse templates often prevents amplification and therefore limits the correct understanding of biological processes. Here, we present openPrimeR, an R-based tool for evaluating and designing multiplex PCR primers. openPrimeR provides a functional and intuitive interface and uses either a greedy algorithm or an integer linear program to compute the minimal set of primers that performs full target coverage. As proof of concept, we used openPrimeR to find optimal primer sets for the amplification of highly mutated immunoglobulins. Comprehensive analyses on specifically generated immunoglobulin variable gene segment libraries resulted in the composition of highly effective primer sets (oPR-IGHV, oPR-IGKV and oPR-IGLV) that demonstrated to be particularly suitable for the isolation of novel human antibodies., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Software systems are often developed in such a way that good practices in the object-oriented paradigm are not met, causing the occurrence of specific disharmonies which are sometimes called code smells. Design patterns catalogue best practices for developing object-oriented software systems. Although code smells and design patterns are widely divergent, there might be a co-occurrence relation between them. The objective of this paper is to empirically evaluate if the presence of design patterns is related to the presence of code smells at different granularity levels. We performed an empirical study using 20 design patterns and 13 code smells in ten small-size to medium-size, open source Java-based systems. We applied statistical analysis and association rules. Results confirm that classes participating in design patterns have less smell-proneness and smell frequency than classes not participating in design patterns. We also noticed that every design pattern category act in the same way in terms of smell-proneness in the subject systems. However, we observed, based on the association rules learning and the proposed validation technique, that some patterns may be associated with certain smells in some cases. For instance, Command patterns can co-occur with God Class, Blob and External Duplication smell., Competing Interests: NO authors have competing interests

Neonatal calf diarrhea (NCD) is a major problem to calf health worldwide, in terms of both morbidity and mortality. A five-point ordinal scale clinical assessment scoring (CAS) chart was utilized to assess calves suffering from NCD-related clinical abnormalities (acidosis and dehydration) on commercial farms. The objective of this research was to determine the predictive capability of this CAS chart against gold standard blood gas parameters, designed to assist farmers in the accurate assessment of the clinical consequences of NCD. A total of 443 diarrheic and non-diarrheic calves were enrolled in the study. The CAS chart rated a calf's health from no clinical signs to varying degrees of clinical severity on a 0 (clinically normal) to 4 (grave) scale, based on clinical indicators including calf demeanour, ear position, mobility, suckle reflex, desire-to-feed, and enophthalmos. Blood gas analysis was conducted for individual calves, consisting of pH, base excess, Na+, K+, Ca2+, Cl-, glucose, total hemoglobin, bicarbonate, anion gap, and strong ion difference. Statistical evaluation was performed by comparison of the CAS score with blood gas profiles using ordinal logistic regression and a non-parametric estimation of the Receiver Operating Characteristics (ROC). The ROC analysis indicated that the CAS chart had acceptable specificity (>95%) with low sensitivity (<60%) in differentiating clinically normal from acidotic/dehydrated cases. Assessment of individual severity classes indicated that the chart can predict and differentiate both clinically normal and advanced cases from the other severity classes (peak estimations >80%) but had reduced accuracy in differentiating mild and moderate cases (peak estimations >50%). The chart, as presented, provides a simple tool to differentiate clinically normal from calves suffering the consequences of diarrhea, but fails to accurately differentiate severity for NCD related acidosis and dehydration. Further efforts are required to enhance the sensitivity and differential diagnostic value of this type of chart., Competing Interests: The authors have declared that no competing interests exist

Normalization is crucial in RNA-seq data analyses. Due to the existence of excessive zeros and a large number of small measures, it is challenging to find reliable linear rescaling normalization parameters. We propose a Zipf plot based normalization method (ZN) assuming that all gene profiles have similar upper tail behaviors in their expression distributions. The new normalization method uses global information of all genes in the same profile without gene-level expression alteration. It doesn't require the majority of genes to be not differentially expressed (DE), and can be applied to data where the majority of genes are weakly or not expressed. Two normalization schemes are implemented with ZN: a linear rescaling scheme and a non-linear transformation scheme. The linear rescaling scheme can be applied alone or together with the non-linear normalization scheme. The performance of ZN is benchmarked against five popular linear normalization methods for RNA-seq data. Results show that the linear rescaling normalization scheme by itself works well and is robust. The non-linear normalization scheme can further improve the normalization outcomes and is optional if the Zipf plots show parallel patterns., Competing Interests: NO authors have competing interests.

Introduction: Research has demonstrated that videogame programs can be an effective intervention targeting social challenges among children with autism spectrum disorder (ASD). Despite the rapid growth in developing videogame programs, incorporation of stakeholders' views has been limited. Objective: This project aimed to identify the design elements that should be considered during development of videogame programs for children with ASD, from the perspectives of stakeholders. Materials and Methods : We involved 26 stakeholders, including parents of children with ASD, youth with ASD, and clinicians working with individuals with ASD in focus groups and interviews. Results: Thematic analysis yielded three themes: (1) addressing heterogeneity and diverse needs; (2) mirroring real world; and (3) teaching strategies. Conclusion: Incorporating these elements during development of videogame programs can help enhance the outcomes for children with ASD. By including stakeholders' voices, it is assumed that the developed videogame programs may serve as user-friendly and engaging tools to potentially complement traditional interventions when overcoming social difficulties in individuals with ASD.

Objectives: The sensitivity for tumor spread through air space (STAS), an independent risk factor for locoregional recurrence after sublobar resection for lung cancer, has been relatively low in frozen sections. We aimed to determine predictors with high negative predictive value for the presence of STAS and to provide the flowchart in combination with these predictors for the decision-making for sublobar resection., Materials and Methods: Between July 2015 and December 2017, 387 patients who underwent surgery for non-small cell lung cancer (NSCLC) with pathologic findings of the total masses measuring ≤ 2 cm were enrolled. The lesions were divided into two groups according to presence of STAS. We compared the preoperative characteristics, operative data, and developed a flowchart for STAS prediction using receiver operator characteristic curve analysis and multivariable logistic regression., Results: The STAS-positive group (N = 111) had a significantly higher preoperative tumor size (1.70 [1.5] vs 1.50 [0.69], p < 0.001) and standardized uptake value tumor-to-liver (SUV T/L) ratio (1.40 [1.60] vs 0.60 [1.10], p < 0.001) and a significantly lower two-dimensional ground-glass opacity (GGO) percentage (35.86 [61.00] vs 78.14 [39.00], p < 0.001). Meanwhile, the STAS-negative group (N = 286) had higher lepidic predominance (41.6% vs. 1.8%, p < 0.001). We developed a flowchart for predicting STAS in combination with two-dimensional GGO percentage on computed tomography (CT), SUV T/L ratio on positron-emission CT, and lepidic predominant pattern. The sensitivity, specificity, and negative predictive value for STAS positivity were 79.3%, 68.5%, and 89.5%, respectively., Conclusions: The stepwise flowchart using two-dimensional GGO percentage on CT, maximum SUV, and lepidic predominance might be helpful in selecting patients with early NSCLC for sublobar resection., Competing Interests: Declaration of Competing Interest None., (Published by Elsevier B.V.)

Purpose: The majority of rehabilitation systems for locked-in patients are used for therapeutic purposes. However, round-the-clock assistance and support are essential after discharge from hospitals or nursing homes. This inspired us to develop a round-the-clock rehabilitation-cum-assistance system operated by eye gazes of locked-in patients. To do this, we aimed to identify the essential daily activities of living for locked-in patients and represent these activities using the most universally acceptable icons/images on the interface for the rehabilitation-cum-assistance system. Method: Activities were selected from available conventions and literature with advice from a local physiotherapy centre. Simple arithmetic averages and weighted averages of recognition rates for different icons representing different daily activities were calculated as per ISO 3864. Universal acceptability of the icons was compared based on responses from 72 locked-in patients across five different age groups. The final icons or images were then selected. Results: Three icons were categorized as identifiable with overall average recognition rates above 66.7%. Icons with average recognition rates 30-60% were considered to have "medium" recognisability and 21 icons were in this category. The average recognition rates of six icons were below 30% and were not acceptable. An overall recognition efficiency of 91% was achieved for participants from all age groups. Conclusions: The most preferred and unambiguous icons or images representing the essential daily activities of living were identified for use on the interface of our rehabilitation-cum-assistance system for round-the-clock operation.Implications for rehabilitationPerforming some of the daily activities by locked-in patients himself/herself is essential for self-independence as well as measures the level of regular improvement.Assistive technologies have huge potential for application for the purpose, especially the vision-based systems.Present technology is useful for development of a vision-based rehabilitation-cum-assistance system for 24 × 7 assistance for the locked-in patients.A new approach for real-time, user-based field evaluation of icons representing daily activities of living using statistical method of averaging of the recognition rates.

Recent miniaturization of electronic components and advances in image processing software have facilitated the entry of extended reality technology into clinical practice. In the last several years, the number of applications in cardiology has multiplied, with many promising to become standard of care. We review many of these applications in the areas of patient and physician education, cardiac rehabilitation, pre-procedural planning and intraprocedural use. The rapid integration of these approaches into the many facets of cardiology suggests that they will one day become an every-day part of physician practice., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: In the past decade, with the ever-increasing growth of information and communication technologies, telerehabilitation, especially home-based rehabilitation (HBR), has been widely considered by researchers. Many software systems are developed to address HBR programs, which includes various functionalities. The aim of this study is to review the functional features of these systems designed for remote supervising of HBR programs., Methods: Scopus, PubMed, EMBASE, ISI Web of Science, Cochrane Library, IEEE Xplore Digital Library, and ProQuest databases were searched for English-language articles published between January 2008 and February 2018 to retrieve studies reported an home-based telerehabilitation software system aiming to remotely supervise HBR program., Results: A total of fifty studies that reported twenty-two unique systems met the inclusion criteria. Various functional features were identified including but not limited to exercise plan management, report/statistics generating, patient education, and task scheduling. Disorders or diseases addressed by these systems could mainly be grouped into five categories: musculoskeletal, neurological, respiratory, cardiovascular, and other health-related problems. Usability and acceptability, and clinical/patient outcomes were the most reported outcomes and data analysis was used by the majority of included studies to measure the outcomes., Conclusions: Systems developed for supervising of HBR program are diverse. However, preliminary results of this review revealed that these systems share more or less common functionalities. However, further research is needed to determine the requirements, structure, and effectiveness of these systems in real-life settings.

Background: During the process of decision-making for long-term care, clients are often dependent on informal support and available information about quality ratings of care services. However, clients do not take ratings into account when considering preferred care, and need assistance to understand their preferences. A tool to elicit preferences for long-term care could be beneficial. Therefore, the aim of this qualitative descriptive study is to understand the user requirements and develop a web-based preference elicitation tool for clients in need of long-term care., Methods: We applied a user-centred design in which end-users influence the development of the tool. The included end-users were clients, relatives, and healthcare professionals. Data collection took place between November 2017 and March 2018 by means of meetings with the development team consisting of four users, walkthrough interviews with 21 individual users, video-audio recordings, field notes, and observations during the use of the tool. Data were collected during three phases of iteration: Look and feel, Navigation, and Content. A deductive and inductive content analysis approach was used for data analysis., Results: The layout was considered accessible and easy during the Look and feel phase, and users asked for neutral images. Users found navigation easy, and expressed the need for concise and shorter text blocks. Users reached consensus about the categories of preferences, wished to adjust the content with propositions about well-being, and discussed linguistic difficulties., Conclusion: By incorporating the requirements of end-users, the user-centred design proved to be useful in progressing from the prototype to the finalized tool 'What matters to me'. This tool may assist the elicitation of client's preferences in their search for long-term care.

Background: Informatics tools to support the integration and subsequent interrogation of spatiotemporal data such as clinical data and environmental exposures data are lacking. Such tools are needed to support research in environmental health and any biomedical field that is challenged by the need for integrated spatiotemporal data to examine individual-level determinants of health and disease., Results: We have developed an open-source software application-FHIR PIT (Health Level 7 Fast Healthcare Interoperability Resources Patient data Integration Tool)-to enable studies on the impact of individual-level environmental exposures on health and disease. FHIR PIT was motivated by the need to integrate patient data derived from our institution's clinical warehouse with a variety of public data sources on environmental exposures and then openly expose the data via ICEES (Integrated Clinical and Environmental Exposures Service). FHIR PIT consists of transformation steps or building blocks that can be chained together to form a transformation and integration workflow. Several transformation steps are generic and thus can be reused. As such, new types of data can be incorporated into the modular FHIR PIT pipeline by simply reusing generic steps or adding new ones. We validated FHIR PIT in the context of a driving use case designed to investigate the impact of airborne pollutant exposures on asthma. Specifically, we replicated published findings demonstrating racial disparities in the impact of airborne pollutants on asthma exacerbations., Conclusions: While FHIR PIT was developed to support our driving use case on asthma, the software can be used to integrate any type and number of spatiotemporal data sources at a level of granularity that enables individual-level study. We expect FHIR PIT to facilitate research in environmental health and numerous other biomedical disciplines.