Hockey Concussion Education Project, Part 1. Susceptibility-weighted imaging study in male and female ice hockey players over a single season: Clinical article

Object. Concussion, or mild traumatic brain injury (mTBI), is a commonly occurring sports-related injury, especially in contact sports such as hockey. Cerebral microbleeds (CMBs), which appear as small, hypointense lesions on T2*-weighted images, can result from TBI. The authors use susceptibility-weighted imaging (SWI) to automatically detect small hypointensities that may be subtle signs of chronic and acute damage due to both subconcussive and concussive injury. The goal was to investigate how the burden of these hypointensities changes over time, over a playing season, and postconcussion, in comparison with subjects who did not suffer a medically observed and diagnosed concussion. Methods. Images were obtained in 45 university-level adult male and female ice hockey players before and after a single Canadian Interuniversity Sports season. In addition, 11 subjects (5 men and 6 women) underwent imaging at 72 hours, 2 weeks, and 2 months after concussion. To identify subtle changes in brain tissue and potential CMBs, nonvessel clusters of hypointensities on SWI were automatically identified, and a hypointensity burden index was calculated for all subjects at the beginning of the season (BOS), the end of the season (EOS), and at postconcussion time points (where applicable). Results. A statistically significant increase in the hypointensity burden, relative to the BOS, was observed for male subjects with concussions at the 2-week postconcussion time point. A smaller, nonsignificant rise in the burden for female subjects with concussions was also observed within the same time period. There were no significant changes in burden for nonconcussed subjects of either sex between the BOS and EOS time points. However, there was a statistically significant difference in the burden between male and female subjects in the nonconcussed group at both the BOS and EOS time points, with males having a higher burden. Conclusions. This method extends the utility of SWI from the enhancement and detection of larger (\u3e 5 mm) CMBs, which are often observed in more severe cases of TBI, to cases involving smaller lesions in which visual detection of injury is difficult. The hypointensity burden metric proposed here shows statistically significant changes over time in the male subjects. A smaller, nonsignificant increase in the burden metric was observed in the female subjects. ©AANS, 2014

Data sharing in neuroimaging research

Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging

Multi-Vendor and Multisite Evaluation of Cerebrovascular Reactivity Mapping Using Hypercapnia Challenge

Cerebrovascular reactivity (CVR), which measures the ability of cerebral blood vessels to dilate or constrict in response to vasoactive stimuli such as CO2 inhalation, is an important index of the brain\u27s vascular health. Quantification of CVR using BOLD MRI with hypercapnia challenge has shown great promises in research and clinical studies. However, in order for it to be used as a potential imaging biomarker in large-scale and multi-site studies, the reliability of CO2-CVR quantification across different MRI acquisition platforms and researchers/raters must be examined. The goal of this report from the MarkVCID small vessel disease biomarkers consortium is to evaluate the reliability of CO2-CVR quantification in three studies. First, the inter-rater reliability of CO2-CVR data processing was evaluated by having raters from 5 MarkVCID sites process the same 30 CVR datasets using a cloud-based CVR data processing pipeline. Second, the inter-scanner reproducibility of CO2-CVR quantification was assessed in 10 young subjects across two scanners of different vendors. Third, test-retest repeatability was evaluated in 20 elderly subjects from 4 sites with a scan interval of less than 2 weeks. In all studies, the CO2 CVR measurements were performed using the fixed inspiration method, where the subjects wore a nose clip and a mouthpiece and breathed room air and 5% CO2 air contained in a Douglas bag alternatively through their mouth. The results showed that the inter-rater CoV of CVR processing was 0.08 ± 0.08% for whole-brain CVR values and ranged from 0.16% to 0.88% in major brain regions, with ICC of absolute agreement above 0.9959 for all brain regions. Inter-scanner CoV was found to be 6.90 ± 5.08% for whole-brain CVR values, and ranged from 4.69% to 12.71% in major brain regions, which are comparable to intra-session CoVs obtained from the same scanners on the same day. ICC of consistency between the two scanners was 0.8498 for whole-brain CVR and ranged from 0.8052 to 0.9185 across major brain regions. In the test-retest evaluation, test-retest CoV across different days was found to be 18.29 ± 17.12% for whole-brain CVR values, and ranged from 16.58% to 19.52% in major brain regions, with ICC of absolute agreement ranged from 0.6480 to 0.7785. These results demonstrated good inter-rater, inter-scanner, and test-retest reliability in healthy volunteers, and suggested that CO2-CVR has suitable instrumental properties for use as an imaging biomarker of cerebrovascular function in multi-site and longitudinal observational studies and clinical trials

Epidemiology of gestational diabetes mellitus according to IADPSG/WHO 2013 criteria among obese pregnant women in Europe

Aims/hypothesis: Accurate prevalence estimates for gestational diabetes mellitus (GDM) among pregnant women in Europe are lacking owing to the use of a multitude of diagnostic criteria and screening strategies in both high-risk women and the general pregnant population. Our aims were to report important risk factors for GDM development and calculate the prevalence of GDM in a cohort of women with BMI ≥29 kg/m2 across 11 centres in Europe using the International Association of the Diabetes and Pregnancy Study Groups (IADPSG)/WHO 2013 diagnostic criteria. Methods: Pregnant women (n = 1023, 86.3% European ethnicity) with a BMI ≥29.0 kg/m2 enrolled into the Vitamin D and Lifestyle Intervention for GDM Prevention (DALI) pilot, lifestyle and vitamin D studies of this pan-European multicentre trial, attended for an OGTT during pregnancy. Demographic, anthropometric and metabolic data were collected at enrolment and throughout pregnancy. GDM was diagnosed using IADPSG/WHO 2013 criteria. GDM treatment followed local policies. Results: The number of women recruited per country ranged from 80 to 217, and the dropout rate was 7.1%. Overall, 39% of women developed GDM during pregnancy, with no significant differences in prevalence across countries. The prevalence of GDM was high (24%; 242/1023) in early pregnancy. Despite interventions used in the DALI study, a further 14% (94/672) had developed GDM when tested at mid gestation (24–28 weeks) and 13% (59/476) of the remaining cohort at late gestation (35–37 weeks). Demographics and lifestyle factors were similar at baseline between women with GDM and those who maintained normal glucose tolerance. Previous GDM (16.5% vs 7.9%, p = 0.002), congenital malformations (6.4% vs 3.3%, p = 0.045) and a baby with macrosomia (31.4% vs 17.9%, p = 0.001) were reported more frequently in those who developed GDM. Significant anthropometric and metabolic differences were already present in early pregnancy between women who developed GDM and those who did not. Conclusions/interpretation: The prevalence of GDM diagnosed by the IADPSG/WHO 2013 GDM criteria in European pregnant women with a BMI ≥29.0 kg/m2 is substantial, and poses a significant health burden to these pregnancies and to the future health of the mother and her offspring. Uniform criteria for GDM diagnosis, supported by robust evidence for the benefits of treatment, are urgently needed to guide modern GDM screening and treatment strategies

Engineered SH2 domains with tailored specificities and enhanced affinities for phosphoproteome analysis

Protein phosphorylation is the most abundant post-translational modification in cells. Src homology 2 (SH2) domains specifically recognize phosphorylated tyrosine (pTyr) residues to mediate signaling cascades. A conserved pocket in the SH2 domain binds the pTyr side chain and the EF and BG loops determine binding specificity. By using large phage-displayed libraries, we engineered the EF and BG loops of the Fyn SH2 domain to alter specificity. Engineered SH2 variants exhibited distinct specificity profiles and were able to bind pTyr sites on the epidermal growth factor receptor, which were not recognized by the wild-type Fyn SH2 domain. Furthermore, mass spectrometry showed that SH2 variants with additional mutations in the pTyr-binding pocket that enhanced affinity were highly effective for enrichment of diverse pTyr peptides within the human proteome. These results showed that engineering of the EF and BG loops could be used to tailor SH2 domain specificity, and SH2 variants with diverse specificities and high affinities for pTyr residues enabled more comprehensive analysis of the human phosphoproteome. Statement: Src Homology 2 (SH2) domains are modular domains that recognize phosphorylated tyrosine embedded in proteins, transducing these post-translational modifications into cellular responses. Here we used phage display to engineer hundreds of SH2 domain variants with altered binding specificities and enhanced affinities, which enabled efficient and differential enrichment of the human phosphoproteome for analysis by mass spectrometry. These engineered SH2 domain variants will be useful tools for elucidating the molecular determinants governing SH2 domains binding specificity and for enhancing analysis and understanding of the human phosphoproteome

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Prevalence of Age-Related Macular Degeneration in Europe: The Past and the Future

Purpose Age-related macular degeneration (AMD) is a frequent, complex disorder in elderly of European ancestry. Risk profiles and treatment options have changed considerably over the years, which may have affected disease prevalence and outcome. We determined the prevalence of early and late AMD in Europe from 1990 to 2013 using the European Eye Epidemiology (E3) consortium, and made projections for the future. Design Meta-analysis of prevalence data. Participants A total of 42 080 individuals 40 years of age and older participating in 14 population-based cohorts from 10 countries in Europe. Methods AMD was diagnosed based on fundus photographs using the Rotterdam Classification. Prevalence of early and late AMD was calculated using random-effects meta-analysis stratified for age, birth cohort, gender, geographic region, and time period of the study. Best-corrected visual acuity (BCVA) was compared between late AMD subtypes; geographic atrophy (GA) and choroidal neovascularization (CNV). Main Outcome Measures Prevalence of early and late AMD, BCVA, and number of AMD cases. Results Prevalence of early AMD increased from 3.5% (95% confidence interval [CI] 2.1%–5.0%) in those aged 55–59 years to 17.6% (95%

Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

Characterization of Diffusion Metric Map Similarity in Data From a Clinical Data Repository Using Histogram Distances

As the sharing of data is mandated by funding agencies and journals, reuse of data has become more prevalent. It becomes imperative, therefore, to develop methods to characterize the similarity of data. While users can group data based on the acquisition parameters stored in the file headers, these gives no indication whether a file can be combined with other data without increasing the variance in the data set. Methods have been implemented that characterize the signal-to-noise ratio or identify signal drop-outs in the raw image files, but potential users of data often have access to calculated metric maps and these are more difficult to characterize and compare. Here we describe a histogram-distance-based method applied to diffusion metric maps of fractional anisotropy and mean diffusivity that were generated using data extracted from a repository of clinically-acquired MRI data. We describe the generation of the data set, the pitfalls specific to diffusion MRI data, and the results of the histogram distance analysis. We find that, in general, data from GE scanners are less similar than are data from Siemens scanners. We also find that the distribution of distance metric values is not Gaussian at any selection of the acquisition parameters considered here (field strength, number of gradient directions, b-value, and vendor)

Characterization of Diffusion Metric Map Similarity in Data From a Clinical Data Repository Using Histogram Distances

As the sharing of data is mandated by funding agencies and journals, reuse of data has become more prevalent. It becomes imperative, therefore, to develop methods to characterize the similarity of data. While users can group data based on the acquisition parameters stored in the file headers, these gives no indication whether a file can be combined with other data without increasing the variance in the data set. Methods have been implemented that characterize the signal-to-noise ratio or identify signal drop-outs in the raw image files, but potential users of data often have access to calculated metric maps and these are more difficult to characterize and compare. Here we describe a histogram-distance-based method applied to diffusion metric maps of fractional anisotropy and mean diffusivity that were generated using data extracted from a repository of clinically-acquired MRI data. We describe the generation of the data set, the pitfalls specific to diffusion MRI data, and the results of the histogram distance analysis. We find that, in general, data from GE scanners are less similar than are data from Siemens scanners. We also find that the distribution of distance metric values is not Gaussian at any selection of the acquisition parameters considered here (field strength, number of gradient directions, b-value, and vendor)