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Multilayer network analysis in patients with end-stage kidney disease

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  • معلومة اضافية
    • بيانات النشر:
      Nature Portfolio, 2024.
    • الموضوع:
      2024
    • Collection:
      LCC:Medicine
      LCC:Science
    • نبذة مختصرة :
      Abstract This study aimed to investigate alterations in a multilayer network combining structural and functional layers in patients with end-stage kidney disease (ESKD) compared with healthy controls. In all, 38 ESKD patients and 43 healthy participants were prospectively enrolled. They exhibited normal brain magnetic resonance imaging (MRI) without any structural lesions. All participants, both ESRD patients and healthy controls, underwent T1-weighted imaging, diffusion tensor imaging (DTI), and resting-state functional MRI (rs-fMRI) using the same three-tesla MRI scanner. A structural connectivity matrix was generated using the DTI and DSI programs, and a functional connectivity matrix was created using the rs-fMRI and SPM programs in the CONN toolbox. Multilayer network analysis was conducted based on structural and functional connectivity matrices using BRAPH. Significant differences were observed at the global level in the multilayer network between patients with ESKD and healthy controls. The weighted multiplex participation was lower in patients with ESKD than in healthy controls (0.6454 vs. 0.7212, adjusted p = 0.049). However, other multilayer network measures did not differ. The weighted multiplex participation in the right subcentral gyrus, right opercular part of the inferior frontal gyrus, right occipitotemporal medial lingual gyrus, and right postcentral gyrus in patients with ESKD was lower than that in the corresponding regions in healthy controls (0.6704 vs. 0.8562, 0.8593 vs. 0.9388, 0.7778 vs. 0.8849, and 0.6825 vs. 0.8112; adjusted p
    • File Description:
      electronic resource
    • ISSN:
      2045-2322
    • Relation:
      https://doaj.org/toc/2045-2322
    • الرقم المعرف:
      10.1038/s41598-024-80645-2
    • الرقم المعرف:
      edsdoj.2a5d0d158f04b6c8bf18dc940b98cd2