90 research outputs found

    Alzheimer's disease diagnosis and management: Perspectives from around the world

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    Alzheimer's disease (AD) and other dementias are a global challenge. Early diagnosis is important to manage the disease. However, there are barriers to diagnosis that differ by region. Researchers from Brazil, China, Nigeria, Spain, and Sweden have identified key barriers to AD diagnosis in their countries. In Brazil, socioeconomic inequalities and poor recognition of dementia by physicians can prevent diagnosis. In China, a very large population and lack of physician training in dementia make diagnosis problematic. In Nigeria, socioeconomic inequalities and cultural stigma can stand in the way of diagnosis. In Spain, patient hesitancy and an overloaded health-care system are barriers to diagnosis. In Sweden, inconsistent use of biomarkers is a prominent barrier to diagnosis of AD. To support diagnosis, more focus is needed on education of patients and physicians, increased use of support services, and improved access to biomarkers to accurately diagnose AD

    Workforce Projections 2010-2020: Annual Supply and Demand Forecasting Models for Physical Therapists Across the United States

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    BACKGROUND: Health human resources continue to emerge as a critical health policy issue across the United States. OBJECTIVE: The purpose of this study was to develop a strategy for modeling future workforce projections to serve as a basis for analyzing annual supply of and demand for physical therapists across the United States into 2020. DESIGN: A traditional stock-and-flow methodology or model was developed and populated with publicly available data to produce estimates of supply and demand for physical therapists by 2020. METHODS: Supply was determined by adding the estimated number of physical therapists and the approximation of new graduates to the number of physical therapists who immigrated, minus US graduates who never passed the licensure examination, and an estimated attrition rate in any given year. Demand was determined by using projected US population with health care insurance multiplied by a demand ratio in any given year. The difference between projected supply and demand represented a shortage or surplus of physical therapists. RESULTS: Three separate projection models were developed based on best available data in the years 2011, 2012, and 2013, respectively. Based on these projections, demand for physical therapists in the United States outstrips supply under most assumptions. LIMITATIONS: Workforce projection methodology research is based on assumptions using imperfect data; therefore, the results must be interpreted in terms of overall trends rather than as precise actuarial data-generated absolute numbers from specified forecasting. CONCLUSIONS: Outcomes of this projection study provide a foundation for discussion and debate regarding the most effective and efficient ways to influence supply-side variables so as to position physical therapists to meet current and future population demand. Attrition rates or permanent exits out of the profession can have important supply-side effects and appear to have an effect on predicting future shortage or surplus of physical therapists

    Evaluation of noise regression techniques in resting-state fMRI studies using data of 434 older adults

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    Subject motion is a well-known confound in resting-state functional MRI (rs-fMRI) and the analysis of functional connectivity. Consequently, several clean-up strategies have been established to minimize the impact of subject motion. Physiological signals in response to cardiac activity and respiration are also known to alter the apparent rs-fMRI connectivity. Comprehensive comparisons of common noise regression techniques showed that the Independent Component Analysis based strategy for Automatic Removal of Motion Artifacts (ICA-AROMA) was a preferred pre-processing technique for teenagers and adults. However, motion and physiological noise characteristics may differ substantially for older adults. Here, we present a comprehensive comparison of noise-regression techniques for older adults from a large multi-site clinical trial of exercise and intensive pharmacological vascular risk factor reduction. The Risk Reduction for Alzheimer\u27s Disease (rrAD) trial included hypertensive older adults (60-84 years old) at elevated risk of developing Alzheimer\u27s Disease (AD). We compared the performance of censoring, censoring combined with global signal regression, non-aggressive and aggressive ICA-AROMA, as well as the Spatially Organized Component Klassifikator (SOCK) on the rs-fMRI baseline scans from 434 rrAD subjects. All techniques were rated based on network reproducibility, network identifiability, edge activity, spatial smoothness, and loss of temporal degrees of freedom (tDOF). We found that non-aggressive ICA-AROMA did not perform as well as the other four techniques, which performed table with marginal differences, demonstrating the validity of these techniques. Considering reproducibility as the most important factor for longitudinal studies, given low false-positive rates and a better preserved, more cohesive temporal structure, currently aggressive ICA-AROMA is likely the most suitable noise regression technique for rs-fMRI studies of older adults

    Rationale and Methods for a Multicenter Clinical Trial Assessing Exercise and Intensive Vascular Risk Reduction in Preventing Dementia (rrAD Study)

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    Alzheimer\u27s Disease (AD) is an age-related disease with modifiable risk factors such as hypertension, hypercholesterolemia, obesity, and physical inactivity influencing the onset and progression. There is however, no direct evidence that reducing these risk factors prevents or slows AD. The Risk Reduction for Alzheimer\u27s Disease (rrAD) trial is designed to study the independent and combined effects of intensive pharmacological control of blood pressure and cholesterol and exercise training on neurocognitive function. Six hundred and forty cognitively normal older adults age 60 to 85 years with hypertension and increased risk for dementia will be enrolled. Participants are randomized into one of four intervention group for two years: usual care, Intensive Reduction of Vascular Risk factors (IRVR) with blood pressure and cholesterol reduction, exercise training (EX), and IRVR+EX. Neurocognitive function is measured at baseline, 6, 12, 18, and 24 months; brain MRIs are obtained at baseline and 24 months. We hypothesize that both IRVR and EX will improve global cognitive function, while IRVR+EX will provide a greater benefit than either IRVR or EX alone. We also hypothesize that IRVR and EX will slow brain atrophy, improve brain structural and functional connectivity, and improve brain perfusion. Finally, we will explore the mechanisms by which study interventions impact neurocognition and brain. If rrAD interventions are shown to be safe, practical, and successful, our study will have a significant impact on reducing the risks of AD in older adults. NCT Registration: NCT02913664

    Association of Accelerometry-Measured Physical Activity and Cardiovascular Events in Mobility-Limited Older Adults: The LIFE (Lifestyle Interventions and Independence for Elders) Study.

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    BACKGROUND:Data are sparse regarding the value of physical activity (PA) surveillance among older adults-particularly among those with mobility limitations. The objective of this study was to examine longitudinal associations between objectively measured daily PA and the incidence of cardiovascular events among older adults in the LIFE (Lifestyle Interventions and Independence for Elders) study. METHODS AND RESULTS:Cardiovascular events were adjudicated based on medical records review, and cardiovascular risk factors were controlled for in the analysis. Home-based activity data were collected by hip-worn accelerometers at baseline and at 6, 12, and 24 months postrandomization to either a physical activity or health education intervention. LIFE study participants (n=1590; age 78.9±5.2 [SD] years; 67.2% women) at baseline had an 11% lower incidence of experiencing a subsequent cardiovascular event per 500 steps taken per day based on activity data (hazard ratio, 0.89; 95% confidence interval, 0.84-0.96; P=0.001). At baseline, every 30 minutes spent performing activities ≥500 counts per minute (hazard ratio, 0.75; confidence interval, 0.65-0.89 [P=0.001]) were also associated with a lower incidence of cardiovascular events. Throughout follow-up (6, 12, and 24 months), both the number of steps per day (per 500 steps; hazard ratio, 0.90, confidence interval, 0.85-0.96 [P=0.001]) and duration of activity ≥500 counts per minute (per 30 minutes; hazard ratio, 0.76; confidence interval, 0.63-0.90 [P=0.002]) were significantly associated with lower cardiovascular event rates. CONCLUSIONS:Objective measurements of physical activity via accelerometry were associated with cardiovascular events among older adults with limited mobility (summary score >10 on the Short Physical Performance Battery) both using baseline and longitudinal data. CLINICAL TRIAL REGISTRATION:URL: http://www.clinicaltrials.gov. Unique identifier: NCT01072500

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment
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