Predictors of Driving in Individuals with Relapsing–Remitting Multiple Sclerosis

Evaluations on fitness-to-drive of individuals with multiple sclerosis (MS) usually involve the administration of several physical, visual, and cognitive tests. In some instances, a practical road test is also administered. The use of several tests, many of which are only remotely driving-related, increases the time, cost, and human resources involved in the evaluation process, and sometimes lead to erroneous decisions. In this study, we investigated the usefulness of using a short battery of a few highly predictive tests to predict fitness-to-drive of individuals with MS. Fortyfour individuals with relapsing–remitting MS (age = 46 ± 11 years, 37 females) and Expanded Disability Status Scale values between 1 and 7 were administered selected physical, visual and cognitive tests including the Stroke Driver Screening Assessment (SDSA) battery. Performance on 12 cognitive and three visual tests were significantly associated with participants’ performance on a practical road test. The Stroop Color test, Direction, Compass, and Road Sign Recognition tests from the SDSA, and the Speed of Processing test from Useful Field of View test battery together explained 59% of the variance and predicted the pass or fail outcome on the road test with 91% accuracy, 70% sensitivity, and 97% specificity. The five psychometric/off-road tests, which together can be administered in less than 45 minutes, cost approximately $150, and is 91% accurate, can be used as a screening battery. Those who pass should be further tested on-road to finally decide their fitness-to-drive while those of fail should be further evaluated, trained, or advised on alternative transportation means. Future studies are needed to confirm and validate the findings in this study

Comparison of Commercial and Self-Initiated Weight Loss Programs in People With Prediabetes: A Randomized Control Trial

To determine if a widely available weight-management program (Weight Watchers) could achieve sufficient weight loss in persons with prediabetes compared with a Diabetes Prevention Program-based individual counseling program supported by National Diabetes Education Program materials. METHODS: We conducted an individual, randomized intervention trial in Indianapolis, Indiana, in 2013 to 2014, in 225 persons with prediabetes. We compared the Weight Watchers weight-management program (n = 112) with Your Game Plan to Prevent Type 2 Diabetes, a program developed by the National Diabetes Education Program. Outcomes were weight and metabolic markers measured at baseline, 6 months, and 12 months. RESULTS: Intervention participants lost significantly more weight than controls at 6 months (5.5% vs 0.8%) and 12 months (5.5% vs 0.2%; both P < .001). The intervention group also had significantly greater improvements in hemoglobin A1c and high-density lipoprotein cholesterol level than did controls. CONCLUSIONS: A large weight-management program is effective for achieving lifestyle changes associated with diabetes prevention. Such programs could significantly increase the availability of diabetes prevention programs worldwide making an immediate and significant public health impact

Vitamin D Supplementation and Prevention of Type 2 Diabetes

BACKGROUND Observational studies support an association between a low blood 25-hydroxyvitamin D level and the risk of type 2 diabetes. However, whether vitamin D supplementation lowers the risk of diabetes is unknown. METHODS We randomly assigned adults who met at least two of three glycemic criteria for prediabetes (fasting plasma glucose level, 100 to 125 mg per deciliter; plasma glucose level 2 hours after a 75-g oral glucose load, 140 to 199 mg per deciliter; and glycated hemoglobin level, 5.7 to 6.4%) and no diagnostic criteria for diabetes to receive 4000 IU per day of vitamin D3 or placebo, regardless of the baseline serum 25-hydroxyvitamin D level. The primary outcome in this time-to-event analysis was new-onset diabetes, and the trial design was event-driven, with a target number of diabetes events of 508. RESULTS A total of 2423 participants underwent randomization (1211 to the vitamin D group and 1212 to the placebo group). By month 24, the mean serum 25-hydroxyvitamin D level in the vitamin D group was 54.3 ng per milliliter (from 27.7 ng per milliliter at baseline), as compared with 28.8 ng per milliliter in the placebo group (from 28.2 ng per milliliter at baseline). After a median follow-up of 2.5 years, the primary outcome of diabetes occurred in 293 participants in the vitamin D group and 323 in the placebo group (9.39 and 10.66 events per 100 person-years, respectively). The hazard ratio for vitamin D as compared with placebo was 0.88 (95% confidence interval, 0.75 to 1.04; P = 0.12). The incidence of adverse events did not differ significantly between the two groups. CONCLUSIONS Among persons at high risk for type 2 diabetes not selected for vitamin D insufficiency, vitamin D3 supplementation at a dose of 4000 IU per day did not result in a significantly lower risk of diabetes than placebo. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases and others; D2d ClinicalTrials.gov number, NCT01942694.

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

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

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

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

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

Attention bias to emotional faces varies by IQ and anxiety in Williams syndrome

Individuals with Williams syndrome (WS) often experience significant anxiety. A promising approach to anxiety intervention has emerged from cognitive studies of attention bias to threat. To investigate the utility of this intervention in WS, this study examined attention bias to happy and angry faces in individuals with WS (N=46). Results showed a significant difference in attention bias patterns as a function of IQ and anxiety. Individuals with higher IQ or higher anxiety showed a significant bias toward angry, but not happy faces, whereas individuals with lower IQ or lower anxiety showed the opposite pattern. These results suggest that attention bias interventions to modify a threat bias may be most effectively targeted to anxious individuals with WS with relatively high IQ

Mitigating effects of vaccination on influenza outbreaks given constraints in stockpile size and daily administration capacity

<p>Abstract</p> <p>Background</p> <p>Influenza viruses are a major cause of morbidity and mortality worldwide. Vaccination remains a powerful tool for preventing or mitigating influenza outbreaks. Yet, vaccine supplies and daily administration capacities are limited, even in developed countries. Understanding how such constraints can alter the mitigating effects of vaccination is a crucial part of influenza preparedness plans. Mathematical models provide tools for government and medical officials to assess the impact of different vaccination strategies and plan accordingly. However, many existing models of vaccination employ several questionable assumptions, including a rate of vaccination <it>proportional </it>to the population at each point in time.</p> <p>Methods</p> <p>We present a SIR-like model that explicitly takes into account vaccine supply and the <it>number </it>of vaccines administered per day and places data-informed limits on these parameters. We refer to this as the <it>non-proportional </it>model of vaccination and compare it to the proportional scheme typically found in the literature.</p> <p>Results</p> <p>The proportional and non-proportional models behave similarly for a few different vaccination scenarios. However, there are parameter regimes involving the vaccination campaign duration and daily supply limit for which the non-proportional model predicts smaller epidemics that peak later, but may last longer, than those of the proportional model. We also use the non-proportional model to predict the mitigating effects of variably timed vaccination campaigns for different levels of vaccination coverage, using specific constraints on daily administration capacity.</p> <p>Conclusions</p> <p>The non-proportional model of vaccination is a theoretical improvement that provides more accurate predictions of the mitigating effects of vaccination on influenza outbreaks than the proportional model. In addition, parameters such as vaccine supply and daily administration limit can be easily adjusted to simulate conditions in developed and developing nations with a wide variety of financial and medical resources. Finally, the model can be used by government and medical officials to create customized pandemic preparedness plans based on the supply and administration constraints of specific communities.</p

Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

Publisher Copyright: © 2021, The Author(s).Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.Peer reviewe