Data and Tools Integration in the Canadian Open Neuroscience Platform.

We present the Canadian Open Neuroscience Platform (CONP) portal to answer the research community's need for flexible data sharing resources and provide advanced tools for search and processing infrastructure capacity. This portal differs from previous data sharing projects as it integrates datasets originating from a number of already existing platforms or databases through DataLad, a file level data integrity and access layer. The portal is also an entry point for searching and accessing a large number of standardized and containerized software and links to a computing infrastructure. It leverages community standards to help document and facilitate reuse of both datasets and tools, and already shows a growing community adoption giving access to more than 60 neuroscience datasets and over 70 tools. The CONP portal demonstrates the feasibility and offers a model of a distributed data and tool management system across 17 institutions throughout Canada.

The C-BIG Repository: an Institution-Level Open Science Platform.

In January 2016, the Montreal Neurological Institute-Hospital (The Neuro) declared itself an Open Science organization. This vision extends beyond efforts by individual scientists seeking to release individual datasets, software tools, or building platforms that provide for the free dissemination of such information. It involves multiple stakeholders and an infrastructure that considers governance, ethics, computational resourcing, physical design, workflows, training, education, and intra-institutional reporting structures. The C-BIG repository was built in response as The Neuro's institutional biospecimen and clinical data repository, and collects biospecimens as well as clinical, imaging, and genetic data from patients with neurological disease and healthy controls. It is aimed at helping scientific investigators, in both academia and industry, advance our understanding of neurological diseases and accelerate the development of treatments. As many neurological diseases are quite rare, they present several challenges to researchers due to their small patient populations. Overcoming these challenges required the aggregation of datasets from various projects and locations. The C-BIG repository achieves this goal and stands as a scalable working model for institutions to collect, track, curate, archive, and disseminate multimodal data from patients. In November 2020, a Registered Access layer was made available to the wider research community at https://cbigr-open.loris.ca , and in May 2021 fully open data will be released to complement the Registered Access data. This article outlines many of the aspects of The Neuro's transition to Open Science by describing the data to be released, C-BIG's full capabilities, and the design aspects that were implemented for effective data sharing.

Modeling the spread of the Zika virus using topological data analysis.

Zika virus (ZIKV), a disease spread primarily through the Aedes aegypti mosquito, was identified in Brazil in 2015 and was declared a global health emergency by the World Health Organization (WHO). Epidemiologists often use common state-level attributes such as population density and temperature to determine the spread of disease. By applying techniques from topological data analysis, we believe that epidemiologists will be able to better predict how ZIKV will spread. We use the Vietoris-Rips filtration on high-density mosquito locations in Brazil to create simplicial complexes, from which we extract homology group generators. Previously epidemiologists have not relied on topological data analysis to model disease spread. Evaluating our model on ZIKV case data in the states of Brazil demonstrates the value of these techniques for the improved assessment of vector-borne diseases.

National Neuroinformatics Framework for Canadian Consortium on Neurodegeneration in Aging (CCNA).

The Canadian Institutes for Health Research (CIHR) launched the "International Collaborative Research Strategy for Alzheimer's Disease" as a signature initiative, focusing on Alzheimer's Disease (AD) and related neurodegenerative disorders (NDDs). The Canadian Consortium for Neurodegeneration and Aging (CCNA) was subsequently established to coordinate and strengthen Canadian research on AD and NDDs. To facilitate this research, CCNA uses LORIS, a modular data management system that integrates acquisition, storage, curation, and dissemination across multiple modalities. Through an unprecedented national collaboration studying various groups of dementia-related diagnoses, CCNA aims to investigate and develop proactive treatment strategies to improve disease prognosis and quality of life of those affected. However, this constitutes a unique technical undertaking, as heterogeneous data collected from sites across Canada must be uniformly organized, stored, and processed in a consistent manner. Currently clinical, neuropsychological, imaging, genomic, and biospecimen data for 509 CCNA subjects have been uploaded to LORIS. In addition, data validation is handled through a number of quality control (QC) measures such as double data entry (DDE), conflict flagging and resolution, imaging protocol checks, and visual imaging quality validation. Site coordinators are also notified of incidental findings found in MRI reads or biosample analyses. Data is then disseminated to CCNA researchers via a web-based Data-Querying Tool (DQT). This paper will detail the wide array of capabilities handled by LORIS for CCNA, aiming to provide the necessary neuroinformatic infrastructure for this nation-wide investigation of healthy and diseased aging.

A prospective pilot study to measure changes in functional status associated with hospitalization in elderly dialysis-dependent patients.

BACKGROUND: Older dialysis patients have a high burden of mortality and morbidity. Frailty and functional disability are common. One of the main determinants of functional disability in nondialysis populations is acute hospitalization. Such episodes are predictive of increased mortality and a future need for long-term care. Based on the high prevalence of disability in the dialysis population, we undertook a pilot study to determine functional impairment at the time of admission and again at 1 week after discharge. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: Prevalent dialysis patients older than 65 years admitted to a single acute-care institution during a 3-month period. OUTCOMES: The proportion of dialysis patients with difficulty with activities of daily living at baseline and 1 week after discharge. MEASUREMENT: Basic activities of daily living; Lawton Brody Instrumental Activities of Daily Living score; timed up-and-go and handgrip tests; Trails A & B, and the clock test. RESULTS: At the time of admission, only 8 of 35 individuals reported being independent with basic activities of daily living. None of the patients was independent with instrumental activities of daily living. At 1 week after discharge, patients showed deterioration in all aspects of function except the ability to use the telephone and manage their financial affairs. A total of 73.3% of patients (95% confidence interval, 54.1 to 87.7) experienced a decline in personal functional independence in association with hospitalization. LIMITATIONS: This is a pilot study with a small number of patients who were studied at only 2 times (admission and 1 week after discharge). CONCLUSIONS: Results of this study suggest that hospitalization is associated with a high rate of disability in elderly dialysis patients. Further study is required to determine whether the functional deterioration seen with hospitalization improves over time.