Objective. This study explored the potential therapeutic effect and possible mechanism of Kai-Xin-San (KXS) on doxorubicin-induced cognitive impairment in 4T1 breast cancer mice. Methods. A model of chemotherapy-induced cognitive impairment (CICI) was established with the injection of doxorubicin (DOX, 5 mg/kg) at a 7-day interval in a 4T1 breast cancer mouse. KXS was given (1 g/kg) daily by gavage over three weeks starting at the first week while giving DOX. The Morris water maze task was performed to measure the CICI-like behaviors. Oxidative stress markers in the hippocampus, inflammatory cytokines in the serum and hippocampus, Nissl staining, immunofluorescence staining, and analysis for Glial fibrillary acidic protein and ionized calcium-binding adapter molecule 1 of the hippocampus were examined to explore the effect and mechanism of KXS on DOX-induced CICI. Meanwhile, tumor growth and survival time were tested in this study. Results. CICI-like behaviors induced by DOX occurred earlier and were severer than the cognitive impairment induced by the tumor, and the effect of KXS on improving the cognitive impairment was obvious. KXS protected against DOX-induced neuroinflammation by decreasing levels of proinflammatory cytokines interleukin-6, interleukin-12p70, and tumor necrosis factor-alpha in both serum and brain and interleukin-1β in the brain, increasing the anti-inflammatory cytokines interleukin-4 in the serum and interleukin-10 in the hippocampus, and inhibiting the astrocytic hyperplasia and microglial polarization in the hippocampus. KXS reduced neural degeneration and protected against DOX-induced oxidative stress according to decreased malondialdehyde level, increased glutathione level, and enhanced activities of superoxide dismutase, catalase, and glutathione peroxidase. Moreover, KXS recovered the lost body weights after DOX administration and prolonged the survival times of mice. Conclusions. KXS may attenuate DOX-induced cognitive impairment by regulating inflammatory responses and reducing oxidative stress and neural degeneration. These findings also presented the role of KXS in improving the quality of life and prolonging survival time in breast cancer mice that received chemotherapy.

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.

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.

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.