Solvothermal syntheses of Cd(NO(3))(2)·4H(2)O and R-isophthalic acids (R = H, OH and t-Bu) in the presence of Ca(II) or Sr(II) lead to four new three-dimensional Cd(II)/Ca(II) or Cd(II)/Sr(II) heterometallic frameworks: [CdCa(m-BDC)(2)(DMF)(2)] (1), [CdSr(2)(m-BDC)(2)(NO(3))(2)(DMF)(4)] (2), [CdCa(OH-m-BDC)(2)(H(2)O)(2)]·2Me(2)NH (3), and (Me(2)NH(2))(2)[Cd(2)Ca(Bu(t)-m-BDC)(4)] (4) (m-H(2)BDC = isophthalate, OH-m-H(2)BDC = 5-hydroxyisophthalate and Bu(t)-m-H(2)BDC = 5-butylisophthalate). All of these compounds except for 4 crystallize in acentric (or chiral) space groups and the bulk materials for 1 and 3 display strong powder SHG efficiencies, approximately 1.54 and 2.31 times than that of a potassium dihydrogen phosphate (KDP) powder. Topological analyses show that 1 and 2 have structures with sxb and dia topologies, respectively, while both 3 and 4 exhibit pcu topological nets when the metal carboxylate clusters are viewed as nodes. The fluorescence properties and thermal stabilities for these compounds are also investigated.
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http://dx.doi.org/10.1039/c0dt00390e | DOI Listing |
J Cell Mol Med
January 2025
Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
This study aims to elucidate the potential genetic commonalities between metabolic syndrome (MetS) and rheumatic diseases through a disease interactome network, according to publicly available large-scale genome-wide association studies (GWAS). The analysis included linkage disequilibrium score regression analysis, cross trait meta-analysis and colocalisation analysis to identify common genetic overlap. Using modular partitioning, the network-based association between the two disease proteins in the protein-protein interaction set was divided and quantified.
View Article and Find Full Text PDFBrain Res Bull
January 2025
School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou 511442, China; Guangdong Province Key Laboratory of Biomedical Engineering, South China University of Technology, Guangzhou 510006, China; Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai 980-8575, Japan. Electronic address:
The methodology of machine learning with multi-omics data has been widely adopted in the discriminative analyses of schizophrenia, but most of these studies ignored the cooperative interactions and topological attributes of multi-omics networks. In this study, we constructed three types of brain graphs (BGs), three types of gut graphs (GGs), and nine types of brain-gut combined graphs (BGCGs) for each individual. We proposed a novel methodology of multi-omics graph convolutional network (MO-GCN) with an attention mechanism to construct a classification model by integrating all BGCGs.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Xuanwu Hospital, Capital Medical University, Beijing, China.
Background: Graph theory is an advanced method for analyzing the balance of brain networks. However, the changes in white matter (WM) and metabolic networks and their correlation with clinical features in patients with posterior cortical atrophy (PCA) require further investigation. This study aims to clarify the structural, metabolic, WM, and metabolic topological network in PCA, and explore their correlation with clinical features.
View Article and Find Full Text PDFBackground: Postmortem MRI allows brain anatomy to be examined at high-resolution linking pathology with morphometric measurements. However, automated methods for analyzing postmortem MRI are not well developed. We present a deep learning-based framework for automated segmentation of cortical mantle, subcortical structures (caudate, putamen, globus pallidus, and thalamus), white matter hyperintensities (WMH), and normal appearing white matter in (n=135) postmortem human brain tissue specimens (Table 1) imaged at 0.
View Article and Find Full Text PDFBackground: Predictive biomarkers characterizing disease progression are called for in the context of emerging treatments for Alzheimer's disease. We implemented a link prediction model on morphometric correlation networks(MCN) generated from structural MRI.
Method: High-resolution T1MPRAGE images were retrospectively collected at two timepoints (interval 2.
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