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Purpose: The objective of this study was to investigate alterations in functional connectivity density (FCD) mapping and their impact on functional connectivity (FC) among individuals diagnosed with Type 2 diabetes mellitus (T2DM) across different cognitive states. Moreover, the study sought to explore the potential association between aberrant FCD/FC patterns and clinical or cognitive variables., Methods: A total of 211 participants were recruited for this study, consisting of 75 healthy controls (HCs), 89 T2DM patients with normal cognitive function (DMCN), and 47 T2DM patients with mild cognitive impairment (DMCI). The study employed FCD analysis to pinpoint brain regions exhibiting significant FCD alterations. Subsequently, these regions showing abnormal FCD served as seeds for FC analysis. Exploratory partial correlations were conducted to explore the relationship between clinical biochemical indicators, neuropsychological test scores, and altered FCD or FC., Results: The FCD analysis revealed an increased trend in global FCD (gFCD), local FCD (lFCD), and long-range FCD (lrFCD) within the bilateral supramarginal gyrus (SMG) among individuals with DMCN. Additionally, significant lFCD alterations were observed in the right inferior frontal gyrus and left precuneus when comparing DMCN to HCs and DMCI., Conclusion: When comparing individuals with T2DM and healthy controls (HCs), it was revealed that DMCN exhibited significant improvements in FCD. This suggests that the brain may employ specific compensatory mechanisms to maintain normal cognitive function at this stage. Our findings provide a novel perspective on the neural mechanisms involved in cognitive decline associated with T2DM., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ge, Cao, Sun, Yue, Rao, Zhao, Qiu, Li, Lu and Qiu.)

Purpose: This study aimed to investigate the changes in brain structure and function in middle-aged patients with type 2 diabetes mellitus (T2DM) using morphometry and blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI)., Methods: A total of 44 middle-aged patients with T2DM and 45 matched healthy controls (HCs) were recruited. Surface-based morphometry (SBM) was used to evaluate the changes in brain morphology. Degree centrality (DC) and functional connectivity (FC) were used to evaluate the changes in brain function., Results: Compared with HCs, middle-aged patients with T2DM exhibited cortical thickness reductions in the left pars opercularis, left transverse temporal, and right superior temporal gyri. Decreased DC values were observed in the cuneus and precuneus in T2DM. Hub-based FC analysis of these regions revealed lower connectivity in the bilateral hippocampus and parahippocampal gyrus, left precuneus, as well as left frontal sup., Conclusion: Cortical thickness, degree centrality, as well as functional connectivity were found to have significant changes in middle-aged patients with T2DM. Our observations provide potential evidence from neuroimaging for analysis to examine diabetes-related brain damage., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Kang, Chen, Wu, Liang, Rao, Yue, Lyu, Li, Tan, Huang and Qiu.)

Purpose: Cognitive impairment is generally found in individuals with type 2 diabetes mellitus (T2DM). Although they may not have visible symptoms of cognitive impairment in the early stages of the disorder, they are considered to be at high risk. Therefore, the classification of these patients is important for preventing the progression of cognitive impairment., Methods: In this study, a convolutional neural network was used to construct a model for classifying 107 T2DM patients with and without cognitive impairment based on T1-weighted structural MRI. The Montreal cognitive assessment score served as an index of the cognitive status of the patients., Results: The classifier could identify T2DM-related cognitive decline with a classification accuracy of 84.85% and achieved an area under the curve of 92.65%., Conclusions: The model can help clinicians analyze and predict cognitive impairment in patients and enable early treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer FL declared a past co-authorship with the author SQ to the handling editor., (Copyright © 2022 Tan, Wu, Ma, Kang, Yue, Rao, Li, Huang, Chen, Lyu, Qin, Li, Feng, Liang and Qiu.)