Structural characteristics of amygdala subregions in type 2 diabetes mellitus.

Type 2 diabetes mellitus (T2DM) patients often suffer from depressive symptoms, which seriously affect cooperation in treatment and nursing. The amygdala plays a significant role in depression. This study aims to explore the microstructural alterations of the amygdala in T2DM and to investigate the relationship between the alterations and depressive symptoms. Fifty T2DM and 50 healthy controls were included. Firstly, the volumes of subcortical regions and subregions of amygdala were calculated by FreeSurfer. Covariance analysis (ANCOVA) was conducted between the two groups with covariates of age, sex, and estimated total intracranial volume to explore the differences in volume of subcortical regions and subregions of amygdala. Furthermore, the structural covariance within the amygdala subregions was performed. Moreover, we investigate the correlation between depressive symptoms and the volume of subcortical regions and amygdala subregions in T2DM. We observed a reduction in the volume of the bilateral cortico-amygdaloid transition area, left basal nucleus, bilateral accessory basal nucleus, left anterior amygdaloid area of amygdala, the left thalamus and left hippocampus in T2DM. T2DM patients showed decreased structural covariance connectivity between left paralaminar nucleus and the right central nucleus. Moreover, there was a negative correlation between self-rating depression scale scores and the volume of the bilateral cortico-amygdaloid transition area in T2DM. This study reveals extensive structural alterations in the amygdala subregions of T2DM patients. The reduction in the volume of the bilateral cortico-amygdaloid transition area may be a promising imaging marker for early recognition of depressive symptoms in T2DM.

The uses of zebrafish (Danio rerio) as an in vivo model for toxicological studies: A review based on bibliometrics.

An in vivo model is necessary for toxicology. This review analyzed the uses of zebrafish (Danio rerio) in toxicology based on bibliometrics. Totally 56,816 publications about zebrafish from 2002 to 2023 were found in Web of Science Core Collection, with Toxicology as the top 6 among all disciplines. Accordingly, the bibliometric map reveals that "toxicity" has become a hot keyword. It further reveals that the most common exposure types include acute, chronic, and combined exposure. The toxicological effects include behavioral, intestinal, cardiovascular, hepatic, endocrine toxicity, neurotoxicity, immunotoxicity, genotoxicity, and reproductive and transgenerational toxicity. The mechanisms include oxidative stress, inflammation, autophagy, and dysbiosis of gut microbiota. The toxicants commonly evaluated by using zebrafish model include nanomaterials, arsenic, metals, bisphenol, and dioxin. Overall, zebrafish provide a unique and well-accepted model to investigate the toxicological effects and mechanisms. We also discussed the possible ways to address some of the limitations of zebrafish model, such as the combination of human organoids to avoid species differences.

Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals.

An increasing number of recent brain imaging studies are dedicated to understanding the neuro mechanism of cognitive impairment in type 2 diabetes mellitus (T2DM) individuals. In contrast to efforts to date that are limited to static functional connectivity, here we investigate abnormal connectivity in T2DM individuals by characterizing the time-varying properties of brain functional networks. Using group independent component analysis (GICA), sliding-window analysis, and k-means clustering, we extracted thirty-one intrinsic connectivity networks (ICNs) and estimated four recurring brain states. We observed significant group differences in fraction time (FT) and mean dwell time (MDT), and significant negative correlation between the Montreal Cognitive Assessment (MoCA) scores and FT/MDT. We found that in the T2DM group the inter- and intra-network connectivity decreases and increases respectively for the default mode network (DMN) and task-positive network (TPN). We also found alteration in the precuneus network (PCUN) and enhanced connectivity between the salience network (SN) and the TPN. Our study provides evidence of alterations of large-scale resting networks in T2DM individuals and shed light on the fundamental mechanisms of neurocognitive deficits in T2DM.

Abnormal cerebral blood flow and brain function in type 2 diabetes mellitus.

PURPOSE: Type 2 diabetes mellitus (T2DM) lead to impaired cerebral blood perfusion, which leads to changes in brain function and affects the cognitive function of patients. In this study, cerebral blood flow (CBF) was used to evaluate the effect of T2DM on cerebral perfusion, and functional connectivity (FC) analysis was further used to explore whether the FC between the abnormal CBF region and the whole brain was changed. In addition, amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) were used to investigate the changes in spontaneous activity and connectivity strength of the brain network. METHODS: We recruited 40 T2DM patients and 55 healthy controls (HCs). They underwent 3D-T1WI, rs-fMRI, arterial spin labeling (ASL) sequence scans and a series of cognitive tests. Cognitive test scores and brain imaging indicators were compared between the two groups, and the relationships among laboratory indicators, cognitive test scores, and brain imaging indicators were explored in the T2DM group. RESULTS: Compared to HCs, The CBF values of Calcarine_L and Precuneus_R in the T2DM group were lower. The DC value of Paracentral_Lobule_L and Precuneus_L, and the ALFF value of Hippocampus_L in the T2DM group were higher. In addition, the CBF values of Calcarine_L was negatively correlated with fasting insulin and HOMA_IR. CONCLUSION: This study found that there were regions of cerebral hypoperfusion in T2DM patients, which are associated with insulin resistance. In addition, we found abnormally elevated brain activity and enhanced functional connectivity in T2DM patients, which we speculated was the compensatory mechanism of brain neural activity.

Alterations of peripheral cytokines, BDNF, and surface-based morphometry indices in T2DM patients without cognitive impairment.

Purpose: This study aimed to investigate potential biological mechanisms underlying cognitive function alterations in Type 2 diabetes mellitus (T2DM) patients by integrating cortical morphology with peripheral cytokine levels and brain-derived neurotrophic factor (BDNF) levels, and to offer potential insights for the early detection of T2DM-related cognitive impairment. Methods: This study included 16 T2DM patients with a Montreal Cognitive Assessment (MoCA) score of at least 26 points, as well as 16 healthy controls with normal cognitive function. The participants also completed the digit span test and digit symbol substitution test. Participants' serum levels of Interleukin 4 (IL-4), IL-6, IL-10, tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), and BDNF were also examined. Each subject underwent a high-resolution 3T structural brain MRI scan. Based on the aparc. a2009s atlas, we calculated the cortical thickness, sulcus depth, gyrification index, and fractal dimension for each participant using surface-based morphometry (SBM). Correlation analysis between cognitive measures, serum levels of cytokines and BDNF, and SBM indices were further performed. Results: The levels of IL-4 and BDNF showed significant group differences. In the T2DM group, the sulcus depth exhibited a significant decrease in the left transverse frontopolar gyri and sulci, as well as in the right pole-occipital; the fractal dimension showed a significant increase in the right posterior-dorsal part of the cingulate gyrus; and the gyrification index significantly increased in the left inferior part of the precentral sulcus and right triangular part of the inferior frontal gyrus. Correlation analysis revealed a significant positive correlation between IL-10 levels and the sulcus depth of left transverse frontopolar gyri and sulci; a significant positive correlation between the sulcus depth of the right pole-occipital and the digit span test-forward scores, and a significant negative correlation between the gyrification index of the left inferior part of the precentral sulcus and the digit span test-backward scores among T2DM participants. Conclusion: T2DM patients without cognitive impairment displayed reductions in IL 4 and BDNF levels, as well as significant alterations in their SBM indices, indicating that prior to the emergence of cognitive impairment, the SBM indices, peripheral cytokines, and BDNF may have altered in T2DM patients. IL-10 may lessen inflammation-related brain edema and preserve sulcus depth in T2DM patients through its anti-inflammatory activity.

White Matter Characteristics of Damage Along Fiber Tracts in Patients with Type 2 Diabetes Mellitus.

PURPOSE: The white matter (WM) of the brain of type 2 diabetes mellitus (T2DM) patients is susceptible to neurodegenerative processes, but the specific types and positions of microstructural lesions along the fiber tracts remain unclear. METHODS: In this study 61 T2DM patients and 61 healthy controls were recruited and underwent diffusion spectrum imaging (DSI). The results were reconstructed with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). WM microstructural abnormalities were identified using tract-based spatial statistics (TBSS). Pointwise WM tract differences were detected through automatic fiber quantification (AFQ). The relationships between WM tract abnormalities and clinical characteristics were explored with partial correlation analysis. RESULTS: TBSS revealed widespread WM lesions in T2DM patients with decreased fractional anisotropy and axial diffusivity and an increased orientation dispersion index (ODI). The AFQ results showed microstructural abnormalities in T2DM patients in specific portions of the right superior longitudinal fasciculus (SLF), right arcuate fasciculus (ARC), left anterior thalamic radiation (ATR), and forceps major (FMA). In the right ARC of T2DM patients, an aberrant ODI was positively correlated with fasting insulin and insulin resistance, and an abnormal intracellular volume fraction was negatively correlated with fasting blood glucose. Additionally, negative associations were found between blood pressure and microstructural abnormalities in the right ARC, left ATR, and FMA in T2DM patients. CONCLUSION: Using AFQ, together with DTI and NODDI, various kinds of microstructural alterations in the right SLF, right ARC, left ATR, and FMA can be accurately identified and may be associated with insulin and glucose status and blood pressure in T2DM patients.

Patient-Reported Outcomes Following the Use of Jiang Tang San Huang Tablets in Type 2 Diabetes Mellitus: A Retrospective Cohort Study in a Chinese Population.

Purpose: We aimed to assess the efficacy of the Jiang Tang San Huang (JTSH) tablet for the treatment of patients with type 2 diabetes mellitus (T2DM). Methods: All data for this retrospective cohort study were acquired from the outpatient clinic database of our institution, and all enrolled patients received JTSH tablet for at least two months. Overall, 147 patients were included in the analysis. The primary outcome was patient-reported outcomes on the efficacy of the JTSH tablets using a questionnaire survey. Correlation analysis evaluated the duration of JTSH tablet administration and glycemic control in patients with T2DM. The secondary outcome measures included: changes in glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), 2-hour postprandial blood glucose, homeostasis model assessment of insulin resistance index (HOMA-IR) and homeostasis model assessment of ß-cell function (HOMA-ß) after 2 months of treatment with JTSH tablets. Results: Overall,120 patients (81.63%) reported a JTSH tablet treatment satisfaction score of ≥60 points, and believed that JTSH tablets had satisfactory hypoglycemic effects and could improve symptoms. The average duration of JTSH tablet treatment was 2.57±1.45 years. Overall, 111 patients achieved good blood glucose control, while 36 patients had poor glycemic control. Multivariate logistic regression model analysis showed that taking JTSH tablets for 1 year might reduce the risk of poor hypoglycemic effect by 17.00% (Risk ratio=0.830, 95% confidence interval:0.578, 1.021, P=0.066). Compared with the baseline data, the levels of HbA1c, FPG and HOMA-IR decreased significantly and HOMA-ß levels increased significantly (P<0.05). Conclusion: Good blood glucose control may be positively correlated with the duration of JTSH tablets administration. Patients with T2DM were satisfied with the anti-diabetic effects of JTSH tablets, which can significantly reduce blood glucose and insulin resistance, and improve the function of islet cells.

Altered cortical thickness, degree centrality, and functional connectivity in middle-age type 2 diabetes mellitus.

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.

Evaluation of Multimedia Courseware-Assisted Teaching Effect of Medical Images Based on the Deep Learning Algorithm.

In order to improve the dynamic evaluation ability of medical image multimedia courseware-assisted teaching effect, the evaluation of medical image multimedia courseware-assisted teaching effect based on a deep learning algorithm is proposed. The statistical data analysis model of medical image multimedia courseware-assisted teaching effect is established to estimate its utilization rate and scale parameters. Based on the prediction of spatial attribute parameters, the classification big data mining model of medical image multimedia courseware-assisted teaching is constructed by using the deep learning algorithm, mining association rules and frequent item sets that can dynamically reflect the quality of medical image multimedia courseware-assisted teaching, and extracting the statistical feature of the dataset of constraint indicators of medical image multimedia courseware-assisted teaching effect to improve the teaching quality of medical imaging course. The simulation results show that this method has a better precision delivery effect, higher dynamic matching degree of teaching evaluation parameters, more than 90% reliability, and better clustering of statistical eigenvalues.

Cortical gray matter microstructural alterations in patients with type 2 diabetes mellitus.

BACKGROUND AND PURPOSE: Neurodegenerative processes are widespread in the brains of type 2 diabetes mellitus (T2DM) patients; gaps remain to exist in the current knowledge of the associated gray matter (GM) microstructural alterations. METHODS: A cross-sectional study was conducted to investigate alterations in GM microarchitecture in T2DM patients by diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI). Seventy-eight T2DM patients and seventy-four age-, sex-, and education level-matched healthy controls (HCs) without cognitive impairment were recruited. Cortical macrostructure and GM microstructure were assessed by surface-based analysis and GM-based spatial statistics (GBSS), respectively. Machine learning models were trained to evaluate the diagnostic values of cortical intracellular volume fraction (ICVF) for the classification of T2DM versus HCs. RESULTS: There were no differences in cortical thickness or area between the groups. GBSS analysis revealed similar GM microstructural patterns of significantly decreased fractional anisotropy, increased mean diffusivity and radial diffusivity in T2DM patients involving the frontal and parietal lobes, and significantly lower ICVF values were observed in nearly all brain regions of T2DM patients. A support vector machine model with a linear kernel was trained to realize the T2DM versus HC classification and exhibited the highest performance among the trained models, achieving an accuracy of 74% and an area under the curve of 83%. CONCLUSIONS: NODDI may help to probe the widespread GM neuritic density loss in T2DM patients occurs before measurable macrostructural alterations. The cortical ICVF values may provide valuable diagnostic information regarding the early GM microstructural alterations in T2DM.

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features.

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.

Altered Functional Network Connectivity of Precuneus and Executive Control Networks in Type 2 Diabetes Mellitus Without Cognitive Impairment.

In epidemiological studies, type 2 diabetes mellitus (T2DM) has been associated with cognitive impairment and dementia, but studies about functional network connectivity in T2DM without cognitive impairment are limited. This study aimed to explore network connectivity alterations that may help enhance our understanding of damage-associated processes in T2DM. MRI data were analyzed from 82 patients with T2DM and 66 normal controls. Clinical, biochemical, and neuropsychological assessments were conducted in parallel with resting-state functional magnetic resonance imaging, and the cognitive status of the patients was assessed using the Montreal Cognitive Assessment-B (MoCA-B) score. Independent component analysis revealed a positive correlation between the salience network and the visual network and a negative connection between the left executive control network and the default mode network in patients with T2DM. The differences in dynamic brain network connectivity were observed in the precuneus, visual, and executive control networks. Internal network connectivity was primarily affected in the thalamus, inferior parietal lobe, and left precuneus. Hemoglobin A1c level, body mass index, MoCA-B score, and grooved pegboard (R) assessments indicated significant differences between the two groups (p < 0.05). Our findings show that key changes in functional connectivity in diabetes occur in the precuneus and executive control networks that evolve before patients develop cognitive deficits. In addition, the current study provides useful information about the role of the thalamus, inferior parietal lobe, and precuneus, which might be potential biomarkers for predicting the clinical progression, assessing the cognitive function, and further understanding the neuropathology of T2DM.

Changes in the structure, perfusion, and function of the hippocampus in type 2 diabetes mellitus.

Objective: This study aims to explore the changes in the structure, perfusion, and function of the bilateral hippocampus in type 2 diabetes mellitus (T2DM) applying multimodal MRI methods, hoping to provide reliable neuroimaging evidence for the diagnosis of hippocampus-related brain injury in T2DM. Methods: We recruited 30 T2DM patients and 45 healthy controls (HCs), on which we performed 3D T1-weighted images, resting-state functional MRI (rs-fMRI), arterial spin labeling (ASL) sequences, and a series of cognitive tests. Then, we compared the differences of two groups in the cerebral blood flow (CBF) value, amplitude of low-frequency fluctuation (ALFF) value, fractional ALFF (fALFF) value, coherence-based regional homogeneity (Cohe-ReHo) value, and degree centrality (DC) values of the bilateral hippocampus. Results: In the T2DM group, the bilateral hippocampal volumes and the CBF value of the right hippocampus were lower than those in the HCs, while the ALFF value, fALFF value, and Cohe-ReHo value of the bilateral hippocampus were higher than those in the HCs. Correlation analysis showed that fasting blood glucose (FBG) was negatively correlated with the residuals of left hippocampal volume (r = -0.407, P = 0.025) and right hippocampal volume (r = -0.420, P = 0.021). The residual of the auditory-verbal learning test (AVLT) (immediate) score was positively correlated with the residual of right hippocampal volume (r = 0.369, P = 0.045). Conclusion: This study indicated that the volume and perfusion of the hippocampus are decreased in T2DM patients that related to chronic hyperglycemia. Local spontaneous neural activity and coordination are increased in the hippocampus of T2DM patients, possibly as an adaptive compensation for cognitive decline.

A mixed-method evaluation of the relationship between Oxford classification scores and longitudinal changes in proteinuria in patients with immunoglobulin A nephropathy.

Introduction: This study aimed to investigate the relationship between Oxford Classification scores and longitudinal changes in proteinuria in patients with immunoglobulin A nephropathy (IgAN). Methods: The study was a single-center retrospective cohort study involving 358 patients with primary IgAN who were treated at the Shenzhen Second People's Hospital, China, between January 2011 and May 2021. Multivariate linear regression and generalized additive mixed models (GAMMs), adjusted for traditional risk confounders, were used to evaluate the correlation between scores for mesangial hypercellularity (M), endocapillary hypercellularity (E), segmental glomerulosclerosis (S), tubular atrophy/interstitial fibrosis (T), and crescents (C) (known as the Oxford Classification MEST-C score system), with proteinuria/creatinine ratio (PCR) at the time of renal biopsy and longitudinal changes in PCR, respectively. Results: The median PCR was 1061 mg/g, and it increased on average by 68.82 mg/g per year in these patients. Among patients with renal insufficiency, compared with patients without relative lesions, those with E present (E1) (1153.44; 95% confidence interval [CI], 188.99-2117.89 mg/g) and C > 0 (C1/2) (1063.58; 95% CI, 185.25-1941.90 mg/g) were associated with increased PCR levels at the time of renal biopsy. What's more, S present (S1) (194.96; 95% CI, 54.50-335.43 mg/g per year) was associated with the fastest PCR increase; C > 0 (C1/2) (147.59; 95% CI, 8.32-286.86 mg/g per year) and T >25% (T1/2) (77.04; 95% CI, 7.18-146.89 mg/g per year), were also correlated with a faster PCR increase. In patients with normal kidney function, associations between S1 (55.46; 95% CI, 8.93-101.99 mg/g per year) and E1 (94.02; 95% CI, 21.47-166.58 mg/g per year) and PCR change could be observed. Additionally, in patients with overweight/obesity, S1 (156.09; 95% CI, 52.41-259.77 mg/g per year), E1 (143.34; 95% CI, 35.30-251.38 mg/g per year), T1/2 (116.04; 95% CI, 22.58-209.51 mg/g per year), as well as C1/2 (134.03; 95% CI, 41.73-226.32 mg/g per year) were associated with noticeably quicker PCR increase. Conclusions: Overall, E1 and C1/2 were independently associated with raised proteinuria levels at the time of renal biopsy, and S1, E1, T1/2, C1/2 were independently associated with a longitudinal increase in proteinuria in the patients with IgAN, especially in those with renal insufficiency or overweight/obesity, suggesting that currently available treatments might not be satisfactory, and weight control might be beneficial. Individual therapy development might benefit from the use of the Oxford Classification system.

AS3MT Polymorphism: A Risk Factor for Epilepsy Susceptibility and Adverse Drug Reactions to Valproic Acid and Oxcarbazepine Treatment in Children From South China.

Epilepsy is a common neurologic disorder characterized by intractable seizures, involving genetic factors. There is a need to develop reliable genetic markers to predict the risk of epilepsy and design effective therapies. Arsenite methyltransferase (AS3MT) catalyzes the biomethylation of arsenic and hence regulates arsenic metabolism. AS3MT variation has been linked to the progression of various diseases including schizophrenia and attention deficit or hyperactivity disorder. Whether genetic polymorphism of AS3MT contributes to epilepsy remains unclear. In this study, we investigated the association of AS3MT gene polymorphism with susceptibility to epilepsy in children from south China. We also explored the effect of AS3MT variation on the safety of antiepileptic drugs. Genotypic analysis for AS3MT rs7085104 was performed using samples from a Chinese cohort of 200 epileptic children and 244 healthy individuals. The results revealed a genetic association of AS3MT rs7085104 with susceptibility to pediatric epilepsy. Mutant homozygous GG genotype exhibited a lower susceptibility to childhood epilepsy than AA genotype. Carriers of AS3MT rs7085104 AA genotype exhibited a higher risk of digestive adverse drug reactions (dADRs) in children when treated with valproic acid (VPA) or oxcarbazepine (OXC). Additionally, bioinformatics analysis identified eight AS3MT target genes related to epilepsy and three AS3MT-associated genes in VPA-related dADRs. The effects of AS3MT on epilepsy might involve multiple targets including CNNM2, CACNB2, TRIM26, MTHFR, GSTM1, CYP17A1, NT5C2, and YBX3. This study reveals that AS3MT may be a new gene contributing to epileptogenesis. Hence, analysis of AS3MT polymorphisms will help to evaluate susceptibility to pediatric epilepsy and drug safety.

Altered Hippocampal Subfields Volumes Is Associated With Memory Function in Type 2 Diabetes Mellitus.

Objective: Cognitive impairment in type 2 diabetes mellitus (T2DM) patients is related to changes in hippocampal structure and function. However, the alternation of hippocampal subfields volumes and their relationship with cognitive function are unclear. This study explored morphological alterations in the hippocampus and its subfields in T2DM patients and their relationship with cognitive function. Methods: Thirty T2DM patients and 20 healthy controls (HCs) were recruited and underwent 3-dimensional, high-resolution T1-weighted sequence (3D-T1) and a battery of cognitive tests. Freesurfer 6.0 was performed to segment the hippocampus into 12 subregions automatically. Then relationships between hippocampal subfield volumes and neurocognitive scale scores in the T2DM group were evaluated. Results: Immediate memory scores on the auditory verbal learning test (AVLT) and Montreal Cognitive Assessment (MoCA) scores in T2DM patients were lower than in the HCs. T2DM patients showed that volumes of the bilateral hippocampus were significantly reduced, mainly in the bilateral molecular layer, granule cell and molecular layer of the dentate gyrus (GC-ML-DG), cornu ammonis 4 (CA4), fimbria, and left subiculum and the right hippocampus amygdala transition area (HATA) compared to HCs. In addition, T2DM patients showed the FINS was negatively correlated with volume of left GC-ML-DG (r = -0.415, P = 0.035) and left CA4 (r = -0.489, P = 0.011); the FBG was negatively correlated with volume of right fimbria (r = -0.460, P = 0.018); the HOMA-IR was negatively correlated with volume of left GC-ML-DG (r = -0.367, P = 0.046) and left CA4(r = 0.462, P = 0.010). Partial correlation analysis found that the volume of right HATA in T2DM group was positively correlated with AVLT (immediate) scores (r = 0.427, P = 0.03). Conclusion: This study showed the volumes of multiple hippocampal subfields decreased and they were correlated with FINS, FBG and HOMA-IR in T2DM patients. We hypothesized that decreased hippocampal subfields volumes in T2DM patients was related to insulin resistance and impaired vascular function. In addition, we also found that abnormal hippocampal subfields volumes were related to memory function in T2DM patients, suggesting that reduced volumes in specific hippocampal subfields may be the potential mechanism of memory dysfunction in these patients.

Identifying Type 2 Diabetic Brains by Investigating Disease-Related Structural Changes in Magnetic Resonance Imaging.

Diabetes with high blood glucose levels may damage the brain nerves and thus increase the risk of dementia. Previous studies have shown that dementia can be reflected in altered brain structure, facilitating computer-aided diagnosis of brain diseases based on structural magnetic resonance imaging (MRI). However, type 2 diabetes mellitus (T2DM)-mediated changes in the brain structures have not yet been studied, and only a few studies have focused on the use of brain MRI for automated diagnosis of T2DM. Hence, identifying MRI biomarkers is essential to evaluate the association between changes in brain structure and T2DM as well as cognitive impairment (CI). The present study aims to investigate four methods to extract features from MRI, characterize imaging biomarkers, as well as identify subjects with T2DM and CI.

Altered Gray Matter Volume, Functional Connectivity, and Degree Centrality in Early-Onset Type 2 Diabetes Mellitus.

Background: Structural and functional brain alterations that underlie cognitive decline have been observed in elderly adults with type 2 diabetes mellitus (T2DM); however, whether these alterations can be observed in patients with early-onset T2DM remains unclear. Therefore, we aimed to describe the abnormalities in brain volume and functional patterns in patients with early-onset T2DM in the present study. Methods: We enrolled 20 patients with early-onset T2DM and 20 healthy controls (HCs). Changes in brain volume were assessed using voxel-based morphology (VBM), while changes in brain function were assessed using degree centrality (DC) and functional connectivity (FC). Results: Compared to HCs, patients with early-onset T2DM exhibited gray matter reductions in the left orbital superior, middle, and inferior frontal gyri as well as the right superior frontal gyrus. The gray matter reductions in the right superior frontal gyrus were negatively associated with the urine albumin to creatinine ratio. Furthermore, increased DC values were observed in the left superior temporal gyrus, left Heschl gyrus, and left hippocampus in patients with early-onset T2DM. An FC analysis of these regions revealed elevated connectivity in the right precuneus, left inferior parietal gyrus, left Heschl gyrus, bilateral post-central gyrus, bilateral insula, bilateral superior temporal gyrus, and bilateral medial and paracingulate gyrus. Furthermore, the FC of the hubs to the superior temporal gyrus, insula, and Heschl gyrus was increased and positively correlated with trail making test-B. Conclusion: Decreased local gray matter volume and increased DC and FC may represent the neurobiological mechanism underlying cognitive dysfunction in patients with early-onset T2DM.

Classification of type 2 diabetes mellitus with or without cognitive impairment from healthy controls using high-order functional connectivity.

Type 2 diabetes mellitus (T2DM) is associated with cognitive impairment and may progress to dementia. However, the brain functional mechanism of T2DM-related dementia is still less understood. Recent resting-state functional magnetic resonance imaging functional connectivity (FC) studies have proved its potential value in the study of T2DM with cognitive impairment (T2DM-CI). However, they mainly used a mass-univariate statistical analysis that was not suitable to reveal the altered FC "pattern" in T2DM-CI, due to lower sensitivity. In this study, we proposed to use high-order FC to reveal the abnormal connectomics pattern in T2DM-CI with a multivariate, machine learning-based strategy. We also investigated whether such patterns were different between T2DM-CI and T2DM without cognitive impairment (T2DM-noCI) to better understand T2DM-induced cognitive impairment, on 23 T2DM-CI and 27 T2DM-noCI patients, as well as 50 healthy controls (HCs). We first built the large-scale high-order brain networks based on temporal synchronization of the dynamic FC time series among multiple brain region pairs and then used this information to classify the T2DM-CI (as well as T2DM-noCI) from the matched HC based on support vector machine. Our model achieved an accuracy of 79.17% in T2DM-CI versus HC differentiation, but only 59.62% in T2DM-noCI versus HC classification. We found abnormal high-order FC patterns in T2DM-CI compared to HC, which was different from that in T2DM-noCI. Our study indicates that there could be widespread connectivity alterations underlying the T2DM-induced cognitive impairment. The results help to better understand the changes in the central neural system due to T2DM.

Aberrant Brain Spontaneous Activity and Synchronization in Type 2 Diabetes Mellitus Subjects Without Mild Cognitive Impairment.

Objective: We aimed to explore whether the percent amplitude of fluctuation (PerAF) measurement could provide supplementary information for amplitude of low-frequency fluctuation (ALFF) about spontaneous activity alteration in type 2 diabetes mellitus (T2DM) subjects without mild cognitive impairment (MCI). Then we further evaluated the synchronization through the method of functional connectivity (FC) to better demonstrate brain changes in a more comprehensive manner in T2DM. Methods: Thirty T2DM subjects without MCI and thirty well-matched healthy subjects were recruited in this study. Subjects' clinical data, neuropsychological test results, and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired. Voxel-based group difference comparisons between PerAF and ALFF were conducted. Then, seed-based FC between the recognized brain regions based on PerAF and ALFF and the rest of the whole brain was performed. Results: Compared with healthy group, T2DM group had significantly decreased PerAF in the bilateral middle occipital gyrus and the right calcarine, increased ALFF in the right orbital inferior frontal gyrus and decreased ALFF in the right calcarine. Seed-based FC analysis showed that the right middle occipital gyrus of T2DM subjects exhibited significantly decreased FC with the right caudate nucleus and right putamen. According to the partial correlation analyses, hemoglobin A1c (HbA1c) and immediate memory scores on the auditory verbal learning test (AVLT) were negatively correlated in the T2DM group. However, we found that total cholesterol was positively correlated with symbol digit test (SDT) scores. Conclusion: PerAF and ALFF may have different sensitivities in detecting the abnormal spontaneous brain activity in T2DM subjects. We suggest PerAF values may add supplementary information and indicate additional potential neuronal spontaneous activity in T2DM subjects without MCI, which may provide new insights into the neuroimaging mechanisms underlying early diabetes-associated cognitive decline.