Objective: We aimed to evaluate the activity of the human glymphatic system in type 2 diabetes mellitus (T2DM) using diffusion tensor image analysis along with the perivascular space (DTI-ALPS).Methods: Diffusion tensor images were acquired to calculate the diffusivities in the direction of the x-axis (right-to-left; Dx), y-axis (anterior-to-posterior; Dy), and z-axis (inferior-to-superior; Dz) of the plane of the lateral ventricle body in 20 patients with type 2 diabetes and 10 people in a control group. We evaluated the diffusivity along with the perivascular spaces, as well as the projection fibers and association fibers, separately. The analysis along the perivascular space (ALPS-index) was defined as the mean (Dxpro, Dypro)/mean (Dypro, Dzasc), where the Dxpro and Dxasc were the Dx values in the projection and association fiber areas, respectively.Results: There were significant differences in diffusivity along the projection fibers and the association fibers among the groups. The significant differences among the groups along the perivascular spaces, shown as the ALPS-index and medical history of T2DM, indicating lower water diffusivity along the perivascular space concerning type 2 diabetes severity, was also observed.Conclusion: Lower diffusivity along the perivascular space on DTI-APLS can reflect impairment of the glymphatic system in T2DM. This study showed that the activity of the glymphatic system could be evaluated by diffusion tensor image analysis.

Schizophrenia (SZ) is a severe psychiatric illness, and it affects around 1% of the general population; however, its reliable diagnosis is challenging. Functional MRI (fMRI) and structural MRI (sMRI) are useful techniques for investigating the functional and structural abnormalities of the human brain, and a growing number of studies have reported that multimodal brain data can improve diagnostic accuracy. Machine learning (ML) is widely used in the diagnosis of neuroscience and neuropsychiatry diseases, and it can obtain high accuracy. However, the conventional ML which concatenated the features into a longer feature vector could not be sufficiently effective to combine different features from different modalities. There are considerable controversies over the use of global signal regression (GSR), and few studies have explored the role of GSR in ML in diagnosing neurological diseases. The current study utilized fMRI and sMRI data to implement a new method named multimodal imaging and multilevel characterization with multiclassifier (M3) to classify SZs and healthy controls (HCs) and investigate the influence of GSR in SZ classification. We found that when we used Brainnetome 246 atlas and without performed GSR, our method obtained a classification accuracy of 83.49%, with a sensitivity of 68.69%, a specificity of 93.75%, and an AUC of 0.8491, respectively. We also got great classification performances with different processing methods (with/without GSR and different brain parcellation schemes). We found that the accuracy and specificity of the models without GSR were higher than that of the models with GSR. Our findings indicate that the M3 method is an effective tool to distinguish SZs from HCs, and it can identify discriminative regions to detect SZ to explore the neural mechanisms underlying SZ. The global signal may contain important neuronal information; it can improve the accuracy and specificity of SZ detection.

Background. The definitive mechanisms of CI-AKI include contrast medium (CM) nephrotoxicity and CM disturbances in renal blood flow, but how the immune system responds to CM has rarely been mentioned in previous studies, and different cell death pathways have not been clearly distinguished. Aim. To confirm whether MRI detect early CI-AKI and to investigate whether immunity-related responses, pyroptosis, and mitophagy participate in contrast-induced acute renal injury (CI-AKI). Methods. C57BL/6 mice with CI-AKI were established by tail vein injection of iodixanol 320. Magnetic resonance imaging of 9.4 T scanner and microscopic appearance of renal H&E staining were tools to test the occurrence of CI-AKI at different times. Immunohistochemistry and NGAL were used to examine the immune responses in the kidneys with CI-AKI. Transmission electron microscopy and western blot methods were used to distinguish various cell death pathways in CI-AKI. Key Results. The densitometry of T2WI, DTI, and BOLD presents CI-AKI in a regular way. The microscopic appearance presents the strongest renal damage in CI-AKI mice that existed between 12 h ( ) and 24 h ( ) after contrast medium (CM) injection. Strong correlation may exist between MRI densitometry (T2WI, DTI, and BOLD) and pathology. Neutrophil and macrophage chemotaxis occurred in CI-AKI, and we observed that Ly6G was the strongest at 48 h ( ). Pyroptosis (Nlrp3/caspase-1, ), mitophagy (BNIP/Nix, ), and apoptosis (Bax, ) occurred in CI-AKI. Conclusions. fMRI can detect early CI-AKI immediately after CM injection. NLRP3 inflammasomes are involved in CI-AKI, and mitophagy may play a role in mitigating kidney injury. The mitochondrion is one of the key organelles in the tubular epithelium implicated in CI-AKI.

Corrigendum: Evaluation of Glymphatic System Using Diffusion MR Technique in T2DM Cases

The effectiveness of Gamma Knife radiosurgery (GKRS) in treating trigeminal neuralgia (TN) has been demonstrated by a number of previous studies. However, there is a lack of research specifically documenting the initial and long-term outcomes of paroxysmal and persistent pain respectively following GKRS for TN with concomitant continuous pain (CCP). This study retrospectively analyzed pain outcomes and complications in 46 TN patients with CCP and 112 patients without CCP who underwent GKRS as initial surgical intervention at our institution from January 2019 to January 2024. Pain outcomes were classified as excellent (BNI I), good (BNI II–IIIa), and poor (BNI IIIb–V). Demographic and clinical data, pain outcomes, and complications were compared between patients with and without CCP. Subsequently, risk factors for poor outcomes after GKRS were evaluated using univariate and multivariate Cox regression analysis. The initial rate of poor outcomes in TN patients with CCP was similar to that of patients without CCP (15.8% vs 14.4%, P = .878). Following a minimum 6-month follow-up, the rate of poor pain outcomes increased to 37.0% in patients with CCP, compared to 38.4% in those without CCP (P = .968). Notably, the rate of long-term complete pain relief in patients without CCP was significantly higher than in those with CCP (35.7% vs 15.2%, P < .001). Poor response to medication (P < .001) was identified as an independent risk factors for poor outcomes after GKRS. While most TN patients with or without CCP can achieve favorable pain outcomes after GKRS, individuals with CCP were less likely to achieve complete pain relief compared to those without CCP.