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https://www.selleckchem.com/products/jhu395.html OL in HFpEF and for the design of future clinical trials targeting symptom improvement in HFpEF. CLINICAL TRIAL REGISTRATION RELAX, NCT00763867; NEAT-HFpEF, NCT02053493; INDIE-HFpEF, NCT02742129. © 2020 European Society of Cardiology.Invited for the cover of this issue is the group of Cristiano Zuccaccia at the Università degli Studi di Perugia. The image depicts a relation of the nuances of chemical bonding to the diverse ways that animals "bind" to their natural surroundings. Read the full text of the article at 10.1002/chem.201905699. © 2020 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.Despite enthusiasm about the potential for using fMRI-based functional connectomes in the development of biomarkers for autism spectrum disorder (ASD), the literature is full of negative findings-failures to distinguish ASD functional connectomes from those of typically developing controls (TD)-and positive findings that are inconsistent across studies. Here, we report on a new study designed to either better differentiate ASD from TD functional connectomes-or, alternatively, to refine our understanding of the factors underlying the current state of affairs. We scanned individuals with ASD and controls both at rest and while watching videos with social content. Using multiband fMRI across repeat sessions, we improved both data quantity and scanning duration by collecting up to 2 hr of data per individual. This is about 50 times the typical number of temporal samples per individual in ASD fcMRI studies. We obtained functional connectomes that were discriminable, allowing for near-perfect individual identification regardless of diagnosis, and equally reliable in both groups. However, contrary to what one might expect, we did not consistently or robustly observe in the ASD group either reductions in similarity to TD functional connectivity (FC) patterns or shared atypical FC patterns. Accordingly, FC-based predictions of diagnosis group a

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