Procrustes analysis for diffusion tensor image processing

There is an increasing need to develop processing tools for diffusion tensor image data with the consideration of the non-Euclidean nature of the tensor space. In this paper Procrustes analysis, a non-Euclidean shape analysis tool under similarity transformations (rotation, scaling and translation), is proposed to redefine sample statistics of diffusion tensors. A new anisotropy measure Procrustes Anisotropy (PA) is defined with the full ordinary Procrustes analysis. Comparisons are made with other anisotropy measures including Fractional Anisotropy and Geodesic Anisotropy. The partial generalized Procrustes analysis is extended to a weighted generalized Procrustes framework for averaging sample tensors with different fractions of contributions to the mean tensor. Applications of Procrustes methods to diffusion tensor interpolation and smoothing are compared with Euclidean, Log-Euclidean and Riemannian methods

Bayesian multi-tensor diffusion MRI and tractography

Bayesian multi-tensor diffusion MRI and tractograph

Weighted generalised Procrustes analysis of diffusion tensors

Weighted generalised Procrustes analysis of diffusion tensor

Demise of mcr-1 and mcr-3.19 mediated by plasmid elimination and ISApl1

The sequences in the three files were assembled sequenes of plasmids found in three danghter clones with flye tool based on Nanopore MinION long-read data

Data_Sheet_1_Dietary behaviors of rural residents in northeastern China: implications for designing intervention information and targeting high-risk population.docx

BackgroundDietary behavior is a pivotal modifiable determinant in reducing the occurrence of obesity/overweight and chronic non-communicable diseases. Improving the dietary behavior of rural residents in China is imminent due to the poor performance of their dietary behavior. Nutrition knowledge and health literacy are considered as elements that are linked intimately to healthy dietary behaviors but lack research in the Chinese setting.PurposeThe study is designed to explore the relationship between nutritional knowledge, health literacy and dietary behaviors and to analyze the performance under different demographic characteristics.MethodsA face-to-face survey of 400 rural residents on their nutrition knowledge, functional health literacy and dietary intake of five food categories consisting of 32 items was conducted based on a validated questionnaire. Descriptive analysis, difference test including ANOVA, t-test and non-parametric test, and multivariate linear regression were used for data analysis.ResultsThe results indicate that declarative nutrition knowledge, individuals’ information application capacity, and dietary behaviors, especially the intake of fruits, dairy and beans, and vegetable are not ideal and requires improvement. Male, elder, low-income, unmarried, and low-education populations performed significantly worse and were the high-risk group. Procedural nutrition knowledge, information access capacity, information understanding capacity, and information application capacity have remarkable effects on better dietary behavior.ConclusionThis study provides evidence-based guidance for prioritizing information and populations for healthy dietary interventions.</p

Comprehensive understanding of co-evolution and fitness cost of mcr-1 and mcr-3 in E. coli strains via long-read sequencing

The complete genome sequences of five E. coli strains coharboring mcr-1 and mcr-3 variants were submitted here for reference.</div

Additional file 1: of County-level heat vulnerability of urban and rural residents in Tibet, China

Proportions and vulnerability scores of urban and rural residents in each county. (DOC 157 kb

Procrustes analysis of diffusion tensor data

Diffusion tensor imaging (DTI) is becoming increasingly important in clinical studies of diseases such as multiple sclerosis and schizophrenia, and also in investigating brain connectivity. Hence, there is a growing need to process diffusion tensor (DT) images within a statistical framework based on appropriate mathematical metrics. However, the usual Euclidean operations are often unsatisfactory for diffusion tensors due to the symmetric, positive-definiteness property. A DT is a type of covariance matrix and non-Euclidean metrics have been adapted naturally for DTI processing [1]. In this paper, Procrustes analysis has been used to define a weighted mean of diffusion tensors that provides a suitable average of a sample of tensors. For comparison, six geodesic paths between a pair of diffusion tensors are plotted using the Euclidean as well as various non-Euclidean distances. We also propose a new measure of anisotropy -Procrustes anisotropy (PA). Fractional anisotropy (FA) and PA maps from an interpolated and smoothed diffusion tensor field from a healthy human brain are shown as an application of the Procrustes method

DataSheet_1_Extracellular vesicles as potential biomarkers and treatment options for liver failure: A systematic review up to March 2022.docx

IntroductionExtracellular vesicles (EVs) carrying functional cargoes are emerging as biomarkers and treatment strategies in multiple liver diseases. Nevertheless, the potential of EVs in liver failure remains indistinct. In this systematic review, we comprehensively analyzed the potential of EVs as biomarkers of liver failure and the therapeutic effects and possible mechanisms of EVs for liver failure.MethodsWe conducted a systematic review by comprehensively searching the following electronic databases: PubMed, Web of Science, Embase and Cochrane Central Register of Controlled Trials from inception to March 2022. The used text words (synonyms and word variations) and database-specific subject headings included “Extracellular Vesicles”, “Exosomes”, “Liver Failure”, “Liver Injury”, etc.ResultsA total of 1479 studies were identified. After removing 680 duplicate studies and 742 irrelevant studies, 57 studies were finally retained and analyzed. Fourteen studies revealed EVs with functional cargoes could be used to make the diagnosis of liver failure and provide clues for early warning and prognostic assessment of patients with liver failure. Forty-three studies confirmed the administration of EVs from different sources alleviated hepatic damage and improved survival through inhibiting inflammatory response, oxidative stress as well as apoptosis or promoting hepatocyte regeneration and autophagy.ConclusionsEVs and their cargoes can be used not only as superior biomarkers of early warning, early diagnosis and prognostic assessments for liver failure, but also as potentially effective treatment options for liver failure. In the future, large-scale studies are urgently needed to verify the diagnostic, predictive and therapeutic value of EVs for liver failure.</p

Automated segmentation of retinal layers from optical coherence tomography images using geodesic distance

Optical coherence tomography (OCT) is a noninvasive imaging technique that can produce images of the eye at the microscopic level. OCT image segmentation to detect retinal layer boundaries is a fundamental procedure for diagnosing and monitoring the progression of retinal and optical nerve diseases. In this paper, we introduce a novel and accurate segmentation method based on geodesic distance for both two and three dimensional OCT images. The geodesic distance is weighted by an exponential function, which takes into account both horizontal and vertical intensity variations in the image. The weighted geodesic distance is efficiently calculated from an Eikonal equation via the fast sweeping method. Segmentation then proceeds by solving an ordinary differential equation of the geodesic distance. The performance of the proposed method is compared with manual segmentation. Extensive experiments demonstrate that the proposed method is robust to complex retinal structures with large curvature variations and irregularities and it outperforms the parametric active contour algorithm as well as graph based approaches for segmenting retinal layers in both healthy and pathological images