Summary Background Elevated blood pressure and glucose, serum cholesterol, and body mass index (BMI) are risk factors for cardiovascular diseases (CVDs); some of these factors also increase the risk of chronic kidney disease (CKD) and diabetes. We estimated CVD, CKD, and diabetes mortality attributable to these four cardio-metabolic risk factors for all countries and regions between 1980 and 2010. Methods We used data on risk factor exposure by country, age group, and sex from pooled analysis of population-based health surveys. Relative risks for cause-specific mortality were obtained from pooling of large prospective studies. We calculated the population attributable fractions (PAF) for each risk factor alone, and for the combination of all risk factors, accounting for multi-causality and for mediation of the effects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specific PAFs by the number of disease-specific deaths from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all inputs to the final estimates. Findings In 2010, high blood pressure was the leading risk factor for dying from CVDs, CKD, and diabetes in every region, causing over 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths; and cholesterol for 10%. After accounting for multi-causality, 63% (10.8 million deaths; 95% confidence interval 10.1–11.5) of deaths from these diseases were attributable to the combined effect of these four metabolic risk factors, compared with 67% (7.1 million deaths; 6.6–7.6) in 1980. The mortality burden of high BMI and glucose nearly doubled between 1980 and 2010. At the country level, age-standardised death rates attributable to these four risk factors surpassed 925 deaths per 100,000 among men in Belarus, Mongolia, and Kazakhstan, but were below 130 deaths per 100,000 for women and below 200 for men in some high-income countries like Japan, Singapore, South Korea, France, Spain, The Netherlands, Australia, and Canada. Interpretations The salient features of the cardio-metabolic epidemic at the beginning of the twenty-first century are the large role of high blood pressure and an increasing impact of obesity and diabetes. There has been a shift in the mortality burden from high-income to low- and middle-income countries.

The advent of mammalian gene engineering and genetically modified mouse models has led to renewed interest in developing resources for referencing and quantitative analysis of mouse brain anatomy. In this study, we used diffusion tensor imaging (DTI) for quantitative characterization of anatomical phenotypes in the developing mouse brain. As an anatomical reference for neuroscience research using mouse models, this paper presents DTI based atlases of ex vivo C57BL/6 mouse brains at several developmental stages. The atlas complements existing histology and MRI-based atlases by providing users access to three-dimensional, high-resolution images of the developing mouse brain, with distinct tissue contrasts and segmentations of major gray matter and white matter structures. The usefulness of the atlas and database was demonstrated by quantitative measurements of the development of major gray matter and white matter structures. Population average images of the mouse brain at several postnatal stages were created using large deformation diffeomorphic Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author ManuscriptNeuroimage. Author manuscript; available in PMC 2012 January 1. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript metric mapping and their anatomical variations were quantitatively characterized. The atlas and database enhance our ability to examine the neuroanatomy in normal or genetically engineered mouse strains and mouse models of neurological diseases.

RESULTS The number of fibres and ROI-based fractional anisotropy values of both tracts were significantly lower in children with CP than in the comparison group (p<0.05-0.001). Additionally, there was significant negative correlation between GMFCS level and motor-sensory parameters (p<0.001-0.05).INTERPRETATION DTI parameters of the CST and PTR in children with CP were significantly lower than in comparison children. In addition, these parameters were significantly correlated with GMFCS level.

Amide proton transfer (APT) magnetic resonance imaging is gaining attention for its capability for grading glial tumors. Usually, a representative slice is analyzed. Different definitions of tumor areas have been employed in previous studies. We hypothesized that the accuracy of APT imaging for brain tumor grading may depend upon the analytical methodology used, such as selection of regions of interest (ROIs), single or multiple tumor slices, and whether or not there is normalization to the contralateral white matter. This study was approved by the institutional review board, and written informed consent was waived. Twenty-six patients with histologically proven glial tumors underwent preoperative APT imaging with a three-dimensional gradient-echo sequence. Two neuroradiologists independently analyzed APT asymmetry (APTasym) images by placing ROIs on both a single representative slice (RS) and all slices including tumor (i.e. whole tumor: WT). ROIs indicating tumor extent were separately defined on both FLAIR and, if applicable, contrast-enhanced T1-weighted images (CE-T1WI), yielding four mean APTasym values (RS-FLAIR, WT-FLAIR, RS-CE-T1WI, and WT-CE-T1WI). The maximum values were also measured using small ROIs, and their differences among grades were evaluated. Receiver operating characteristic (ROC) curve analysis was also conducted on mean and maximum values. Intra-class correlation coefficients for inter-observer agreement were excellent. Significant differences were observed between high- and low-grade gliomas for all five methods (P < 0.01). ROC curve analysis found no statistically significant difference among them. This study clarifies that single-slice APT analysis is robust despite tumor heterogeneity, and can grade glial tumors with or without the use of contrast material.