The Dyslexic Issue: Resources for Parents, Teachers, and Related Professionals

This handbook and website project gives a thorough explanation of dyslexia, the history of dyslexia, and the latest resources available for parents, teachers, and related professionals who support students with dyslexia. The handbook and webpage will provide parents, teachers, and related professionals information which they may access in order to support students with dyslexia throughout their academic career. These resources will offer much-needed support for parents, teachers, and related professionals in learning how to properly identify the characteristics which are most often associated with dyslexia. Furthermore, they will provide an important myriad of resources for intervention for students with dyslexia for parents, teachers, and related professionals

Query Health: standards-based, cross-platform population health surveillance

Objective: Understanding population-level health trends is essential to effectively monitor and improve public health. The Office of the National Coordinator for Health Information Technology (ONC) Query Health initiative is a collaboration to develop a national architecture for distributed, population-level health queries across diverse clinical systems with disparate data models. Here we review Query Health activities, including a standards-based methodology, an open-source reference implementation, and three pilot projects. Materials and methods Query Health defined a standards-based approach for distributed population health queries, using an ontology based on the Quality Data Model and Consolidated Clinical Document Architecture, Health Quality Measures Format (HQMF) as the query language, the Query Envelope as the secure transport layer, and the Quality Reporting Document Architecture as the result language. Results: We implemented this approach using Informatics for Integrating Biology and the Bedside (i2b2) and hQuery for data analytics and PopMedNet for access control, secure query distribution, and response. We deployed the reference implementation at three pilot sites: two public health departments (New York City and Massachusetts) and one pilot designed to support Food and Drug Administration post-market safety surveillance activities. The pilots were successful, although improved cross-platform data normalization is needed. Discussions This initiative resulted in a standards-based methodology for population health queries, a reference implementation, and revision of the HQMF standard. It also informed future directions regarding interoperability and data access for ONC's Data Access Framework initiative. Conclusions: Query Health was a test of the learning health system that supplied a functional methodology and reference implementation for distributed population health queries that has been validated at three sites

Unweaving the population structure and genetic diversity of Canadian shrub willow

Perennial shrub willow are increasingly being promoted in short-rotation coppice systems as biomass feedstocks, for phytoremediation applications, and for the diverse ecosystem services that can accrue. This renewed interest has led to widespread willow cultivation, particularly of non-native varieties. However, Canadian willow species have not been widely adopted and their inherent diversity has not yet been thoroughly investigated. In this study, 324 genotypes of Salix famelica and Salix eriocephala collected from 33 sites of origin were analyzed using 26,016 single nucleotide polymorphisms to reveal patterns of population structure and genetic diversity. Analyses by Bayesian methods and principal component analysis detected five main clusters that appeared to be largely shaped by geoclimatic variables including mean annual precipitation and the number of frost-free days. The overall observed (HO) and expected (HE) heterozygosity were 0.126 and 0.179, respectively. An analysis of molecular variance revealed that the highest genetic variation occurred within genotypes (69%), while 8% of the variation existed among clusters and 23% between genotypes within clusters. These findings provide new insights into the extent of genetic variation that exists within native shrub willow species which could be leveraged in pan-Canadian willow breeding programs.Fil: Murphy, Emily K. University of British Columbia. Faculty of Forestry. Department of Wood Science; CanadáFil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Soolanayakanahally, Raju Y. Agriculture and Agri-Food Canada. Indian Head Research Farm; Canadá. Agriculture and Agri-Food Canada. Saskatoon Research and Development Centre; Canadá.Fil: El-Kassaby, Yousry A. University of British Columbia. Faculty of Forestry. Department of Forest and Conservation Sciences; CanadáFil: Parkin, Isobel A.P. Agriculture and Agri-Food Canada. Saskatoon Research and Development Centre; Canadá.Fil: Schroeder, William R. Agriculture and Agri-Food Canada. Indian Head Research Farm; CanadáFil: Mansfield, Shawn D. University of British Columbia. Faculty of Forestry. Department of Wood Science; Canad

One-arcsecond line-of-sight pointing control on exoplanetsat, a three-unit CubeSat

ExoplanetSat is a proposed 10×10×34-cm space telescope designed to detect down to Earth-sized exoplanets in an orbit out to the habitable zone of bright, Sun-like stars via the transit method. Achieving this science objective requires one-arcsecond line-of-sight pointing control for the science CCD detector, an unprecedented requirement for CubeSats. A two-stage control architecture that coordinates coarse rigid-body attitude control with fine line-of-sight pointing control will be employed to meet this challenging pointing requirement. Detailed testing of the reaction wheels and CMOS detectors has been performed to extract key performance parameters used in simulations. The results of these simulations indicate that a 1.4 arcsecond pointing precision (3σ) is achievable. To meet the 1.0-arcsecond pointing requirement, several options are analyzed. In particular, a new technique to estimate reaction wheel vibrations for feed forward cancellation of reaction wheel vibrations is presented. This estimator adaptively estimates disturbances from noisy sensor measurements and effectively stores disturbance amplitude and phase in memory as a function of wheel speed. In addition to these simulation results, testing results from a hardware-in-the-loop (HWIL) testbed demonstrate the capability of the fine pointing control loop. Future plans for complete HWIL testing of the coarse and fine control loops are presented

Evolving Research Data Sharing Networks to Clinical App Sharing Networks

Research networks for data sharing are growing into a large platform for pragmatic clinical trials to generate quality evidence for shared medical decision-making. Institutions partnering in the networks have made large investments in developing the infrastructure for sharing data. We investigate whether institutions partnering on Patient-Centered Outcomes Research Institute’s (PCORI) network can share clinical apps. At two different sites, we imported patient data in PCORI’s clinical data model (CDM) format into i2b2 repositories, and adapted the SMART-on-FHIR cell to perform CDM-to-FHIR translation, serving demographics, laboratory results and diagnoses. We performed manual validations and tested the platform using four apps from the SMART app gallery. Our study demonstrates an approach to extend the research infrastructure to allow the partnering institutions to run shared clinical apps, and highlights the involved challenges. Our results, tooling and publically accessible data service can potentially transform research networks into clinical app sharing networks and pave the way towards a learning health system

Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS): Architecture

We describe the architecture of the Patient Centered Outcomes Research Institute (PCORI) funded Scalable Collaborative Infrastructure for a Learning Healthcare System (SCILHS, http://www.SCILHS.org) clinical data research network, which leverages the $48 billion dollar federal investment in health information technology (IT) to enable a queryable semantic data model across 10 health systems covering more than 8 million patients, plugging universally into the point of care, generating evidence and discovery, and thereby enabling clinician and patient participation in research during the patient encounter. Central to the success of SCILHS is development of innovative ‘apps’ to improve PCOR research methods and capacitate point of care functions such as consent, enrollment, randomization, and outreach for patient-reported outcomes. SCILHS adapts and extends an existing national research network formed on an advanced IT infrastructure built with open source, free, modular components

The Co-Morbidity Burden of Children and Young Adults with Autism Spectrum Disorders

Objectives: Use electronic health records Autism Spectrum Disorder (ASD) to assess the comorbidity burden of ASD in children and young adults. Study Design: A retrospective prevalence study was performed using a distributed query system across three general hospitals and one pediatric hospital. Over 14,000 individuals under age 35 with ASD were characterized by their co-morbidities and conversely, the prevalence of ASD within these comorbidities was measured. The comorbidity prevalence of the younger (Age<18 years) and older (Age 18–34 years) individuals with ASD was compared. Results: 19.44% of ASD patients had epilepsy as compared to 2.19% in the overall hospital population (95% confidence interval for difference in percentages 13.58–14.69%), 2.43% of ASD with schizophrenia vs. 0.24% in the hospital population (95% CI 1.89–2.39%), inflammatory bowel disease (IBD) 0.83% vs. 0.54% (95% CI 0.13–0.43%), bowel disorders (without IBD) 11.74% vs. 4.5% (95% CI 5.72–6.68%), CNS/cranial anomalies 12.45% vs. 1.19% (95% CI 9.41–10.38%), diabetes mellitus type I (DM1) 0.79% vs. 0.34% (95% CI 0.3–0.6%), muscular dystrophy 0.47% vs 0.05% (95% CI 0.26–0.49%), sleep disorders 1.12% vs. 0.14% (95% CI 0.79–1.14%). Autoimmune disorders (excluding DM1 and IBD) were not significantly different at 0.67% vs. 0.68% (95% CI −0.14-0.13%). Three of the studied comorbidities increased significantly when comparing ages 0–17 vs 18–34 with p<0.001: Schizophrenia (1.43% vs. 8.76%), diabetes mellitus type I (0.67% vs. 2.08%), IBD (0.68% vs. 1.99%) whereas sleeping disorders, bowel disorders (without IBD) and epilepsy did not change significantly. Conclusions: The comorbidities of ASD encompass disease states that are significantly overrepresented in ASD with respect to even the patient populations of tertiary health centers. This burden of comorbidities goes well beyond those routinely managed in developmental medicine centers and requires broad multidisciplinary management that payors and providers will have to plan for

iTools: A Framework for Classification, Categorization and Integration of Computational Biology Resources

The advancement of the computational biology field hinges on progress in three fundamental directions – the development of new computational algorithms, the availability of informatics resource management infrastructures and the capability of tools to interoperate and synergize. There is an explosion in algorithms and tools for computational biology, which makes it difficult for biologists to find, compare and integrate such resources. We describe a new infrastructure, iTools, for managing the query, traversal and comparison of diverse computational biology resources. Specifically, iTools stores information about three types of resources–data, software tools and web-services. The iTools design, implementation and resource meta - data content reflect the broad research, computational, applied and scientific expertise available at the seven National Centers for Biomedical Computing. iTools provides a system for classification, categorization and integration of different computational biology resources across space-and-time scales, biomedical problems, computational infrastructures and mathematical foundations. A large number of resources are already iTools-accessible to the community and this infrastructure is rapidly growing. iTools includes human and machine interfaces to its resource meta-data repository. Investigators or computer programs may utilize these interfaces to search, compare, expand, revise and mine meta-data descriptions of existent computational biology resources. We propose two ways to browse and display the iTools dynamic collection of resources. The first one is based on an ontology of computational biology resources, and the second one is derived from hyperbolic projections of manifolds or complex structures onto planar discs. iTools is an open source project both in terms of the source code development as well as its meta-data content. iTools employs a decentralized, portable, scalable and lightweight framework for long-term resource management. We demonstrate several applications of iTools as a framework for integrated bioinformatics. iTools and the complete details about its specifications, usage and interfaces are available at the iTools web page http://iTools.ccb.ucla.edu

Principles of Glomerular Organization in the Human Olfactory Bulb – Implications for Odor Processing

Olfactory sensory neurons (OSN) in mice express only 1 of a possible 1,100 odor receptors (OR) and axons from OSNs expressing the same odor receptor converge into ∼2 of the 1,800 glomeruli in each olfactory bulb (OB) in mice; this yields a convergence ratio that approximates 2∶1, 2 glomeruli/OR. Because humans express only 350 intact ORs, we examined human OBs to determine if the glomerular convergence ratio of 2∶1 established in mice was applicable to humans. Unexpectedly, the average number of human OB glomeruli is >5,500 yielding a convergence ratio of ∼16∶1. The data suggest that the initial coding of odor information in the human OB may differ from the models developed for rodents and that recruitment of additional glomeruli for subpopulations of ORs may contribute to more robust odor representation

The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers. MATERIALS AND METHODS: The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics. RESULTS: Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access. CONCLUSIONS: The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19