There has been an increasing interest in examining organisational principles of the cerebral cortex (and subcortical regions) using different MRI features such as structural or functional connectivity. Despite the widespread interest, introductory tutorials on the underlying technique targeted for the novice neuroimager are sparse in the literature. Articles that investigate various "neural gradients" (for example based on region studied "cortical gradients," "cerebellar gradients," "hippocampal gradients" etc … or feature of interest "functional gradients," "cytoarchitectural gradients," "myeloarchitectural gradients" etc …) have increased in popularity. Thus, we believe that it is opportune to discuss what is generally meant by "gradient analysis". We introduce basics concepts in graph theory, such as graphs themselves, the degree matrix, and the adjacency matrix. We discuss how one can think about gradients of feature similarity (the similarity between timeseries in fMRI, or streamline in tractography) using graph theory and we extend this to explore such gradients across the whole MRI scale; from the voxel level to the whole brain level. We proceed to introduce a measure for quantifying the level of similarity in regions of interest. We propose the term "the Vogt-Bailey index" for such quantification to pay homage to our history as a brain mapping community. We run through the techniques on sample datasets including a brain MRI as an example of the application of the techniques on real data and we provide several appendices that expand upon details. To maximise intuition, the appendices contain a didactic example describing how one could use these techniques to solve a particularly pernicious problem that one may encounter at a wedding. Accompanying the article is a tool, available in both MATLAB and Python, that enables readers to perform the analysis described in this article on their own data. We refer readers to the graphical abstract as an overview of the analysis pipeline presented in this work.
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http://dx.doi.org/10.1016/j.neuroimage.2020.117140 | DOI Listing |
Int J Integr Care
December 2024
Julius Global Health, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
Introduction: The SCUBY project aimed to provide knowledge on the scaling-up of an Integrated Care Package (ICP) for type 2 diabetes and hypertension across three distinct health systems (Cambodia, Slovenia, and Belgium). Here, we analyse the different elements of the country-specific scale-up roadmaps to identify similarities and differences, and share lessons learned.
Methods: Thematic analysis was used to derive crucial roadmap elements from key SCUBY documents (n = 20), including policy briefs, interim reports, research outputs, and consortium meeting notes.
Oropouche virus is an arbovirus endemic to the Americas. Periodic outbreaks have occurred since its description in 1955. In late 2023, an outbreak occurred in Peru, centered in and around Iquitos in the Eastern Peruvian Amazon.
View Article and Find Full Text PDFRecent advancements in Parkinson's disease (PD) drug development have been significantly driven by genetic research. Importantly, drugs supported by genetic evidence are more likely to be approved. While genome-wide association studies (GWAS) are a powerful tool to nominate genomic regions associated with certain traits or diseases, pinpointing the causal biologically relevant gene is often challenging.
View Article and Find Full Text PDFFront Plant Sci
December 2024
College of Big Data, Yunnan Agricultural University, Kunming, China.
Introduction: The assessment of the severity of fruit disease is crucial for the optimization of fruit production. By quantifying the percentage of leaf disease, an effective approach to determining the severity of the disease is available. However, the current prediction of disease degree by machine learning methods still faces challenges, including suboptimal accuracy and limited generalizability.
View Article and Find Full Text PDFCytochromes P450 (CYP) form one of the largest enzyme superfamilies on Earth, with similar structural fold but biological functions varying from synthesis of physiologically essential compounds to metabolism of myriad xenobiotics. Here we determined the crystal structures of Coryphaenoides armatus and human sterol 14α-demethylases (CYP51s). Both structures reveal elements that imply elevated conformational flexibility, uncovering molecular basis for faster catalytic rates, lower substrate selectivity, and resistance to inhibition.
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