Objective: Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG) could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI) from normal cognitive function in type 2 diabetes.Materials and Methods: In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls) were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well.Results: The main findings of this study were that: (1) compared with the control group, the ratios of power in theta band [P(theta)] vs. power in alpha band [P(alpha)] [P(theta)/P(alpha)] in the frontal region and left temporal region were significantly higher for aMCI, and (2) for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC) and left posterior-right posterior (LP-RP) regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT) region were increased.Conclusion: The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

Purpose: Diabetes is a great risk factor for dementia and mild cognitive impairment (MCI). This study investigates whether complex network-derived features in resting state EEG (rsEEG) could be applied as a biomarker to distinguish amnestic mild cognitive impairment (aMCI) from normal cognitive function in subjects with type 2 diabetes (T2D).Method: In this study, EEG was recorded in 28 patients with T2D (16 aMCI patients and 12 controls) during a no-task eyes-closed resting state. Pair-wise synchronization of rsEEG signals were assessed in six frequency bands (delta, theta, lower alpha, upper alpha, beta, and gamma) using phase lag index (PLI) and grouped into long distance (intra- and inter-hemispheric) and short distance interactions. PLI-weighted connectivity networks were also constructed, and characterized by mean clustering coefficient and path length. The correlation of these features and Montreal Cognitive Assessment (MoCA) scores was assessed.Results: Main findings of this study were as follows: (1) In comparison with controls, patients with aMCI had a significant decrease of global mean PLI in lower alpha, upper alpha, and beta bands. Lower functional connection at short and long intra-hemispheric distance mainly appeared on the left hemisphere. (2) In the lower alpha band, clustering coefficient was significantly lower in aMCI group, and the path length significantly increased. (3) Cognitive status measured by MoCA had a significant positive correlation with cluster coefficient and negative correlation with path length in lower alpha band.Conclusions: The brain network of aMCI patients displayed a disconnection syndrome and a loss of small-world architecture. The correlation between cognitive states and network characteristics suggested that the more in deterioration of the diabetes patients' cognitive state, the less optimal the network organization become. Hence, the complex network-derived biomarkers based on EEG could be employed to track cognitive function of diabetic patients and provide a new diagnosis tool for aMCI.

In recent study, microRNAs have various important functions in diverse biological processes and progression of cancer. In human breast cancer, microRNA-22 has been reported to be downregulated. However, molecular mechanism of microRNA-22 in breast cancer progression and chemosensitivity has not been well studied. In our study, these results demonstrated that microRNA-22 expression levels were significantly reduced in 40 pairs of human breast cancer tissues when compared to normal tissues. Enforced expression of microRNA-22 inhibited activity of cell proliferation and cell migration in breast cancer cells. Furthermore, microRNA-22 targeted NRAS proto-oncogene, GTPase (NRAS) in breast cancer cells. The expression levels of NRAS in human clinical specimens were higher in breast cancer tissues when compared to normal tissues. Moreover, microRNA-22 sensitized breast cancer cells to paclitaxel by regulation of NRAS. Our results then demonstrated that microRNA-22 functioned as a tumor suppressor microRNA and indicated potential application for the diagnosis and treatment of cancer in the future.

These data were the first objective evidence of heat-sensitization responses during suspended moxibustion, which were characterized by widespread oscillatory changes in scalp EEG.

These results showed that the coupling strength or directionality of EEG signals calculated by PCMI might be used as a biomarker in distinguishing the aMCI from NC with T2DM.

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Background: Benzodiazepines (BZDs) and Non-BZDs (NBZDs) have been widely used for patients with chronic insomnia. Long-term uses of BZDs may cause cognitive impairment and increase the risk for dementia in older patients. NBZD as an agonist of the GABAA receptor complex includes eszopiclone, zopiclone, zolpidem, and zaleplon, also collectively known as Z drugs. However, evaluations for an association between cognitive impairment and Z drug use have been limitedly performed. This study aimed to investigate the association between the risk of cognitive decline and exposure to Z drugs in middle-aged and older patients with chronic insomnia.Methods: Investigations were performed on patients with chronic insomnia who visited the outpatient Department of Neurology, Beijing Friendship Hospital, and were assessed for the global cognitive function (MoCA) and memory (AVLT), executive function (TMT-B), visuospatial ability (CDT), verbal function (BNT-30), and attention (DST). Multiple regression analysis was conducted to determine the independent factors of cognition and evaluated the effect of Z drug use (zolpidem and zopiclone) on cognition.Results: A total of 120 subjects were identified. In our analysis, BZD exposure density (P = 0.025, OR = 1.43, 95% CI, 1.25–1.86) was an independent risk factor of cognitive impairment in middle-aged and older patients with chronic insomnia. Neither Z drug use (P = 0.103) nor Z drug exposure density (P = 0.765) correlated with global cognitive function. Moreover, there was a positive association between Z drug use and attention [(P = 0.002, OR = 0.42, 95% CI, 0.24–0.73)]. Additionally, income level (P = 0.001, OR = 0.23, 95% CI, 0.10–0.53), severity of insomnia (P = 0.019, OR = 1.20, 95% CI, 1.03–1.40) and age (P = 0.044, OR = 1.07, 95% CI, 1.00–1.14) were also independent factors of global cognitive function.Conclusion: BZD exposure density was an independent risk factor of cognitive impairment in middle-aged and older patients with chronic insomnia, but no correlation was found between Z drug use and cognitive impairment. Moreover, the use of Z drugs seemed to be associated with protection for attention. The use for prescription of BZDs, in this case, should be avoided or limited to low doses. Due to the addiction and tolerance, Z drugs should also be prescribed with great caution in middle-aged and elderly patients.