Cortical Source Multivariate EEG Synchronization Analysis on Amnestic Mild Cognitive Impairment in Type 2 Diabetes

Is synchronization altered in amnestic mild cognitive impairment (aMCI) and normal cognitive functions subjects in type 2 diabetes mellitus (T2DM)? Resting eye-closed EEG data were recorded in 8 aMCI subjects and 11 age-matched controls in T2DM. Three multivariate synchronization algorithms (S-estimator (S), synchronization index (SI), and global synchronization index (GSI)) were used to measure the synchronization in five ROIs of sLORETA sources for seven bands. Results showed that aMCI group had lower synchronization values than control groups in parietal delta and beta2 bands, temporal delta and beta2 bands, and occipital theta and beta2 bands significantly. Temporal (r=0.629; P=0.004) and occipital (r=0.648; P=0.003) theta S values were significantly positive correlated with Boston Name Testing. In sum, each of methods reflected that the cortical source synchronization was significantly different between aMCI and control group, and these difference correlated with cognitive functions

Analysis of entropies based on empirical mode decomposition in amnesic mild cognitive impairment of diabetes mellitus

EEG characteristics that correlate with the cognitive functions are important in detecting mild cognitive impairment (MCI) in T2DM. To investigate the complexity between aMCI group and age-matched non-aMCI control group in T2DM, six entropies combining empirical mode decomposition (EMD), including Approximate entropy (ApEn), Sample entropy (SaEn), Fuzzy entropy (FEn), Permutation entropy (PEn), Power spectrum entropy (PsEn) and Wavelet entropy (WEn) were used in the study. A feature extraction technique based on maximization of the area under the curve (AUC) and a support vector machine (SVM) were subsequently used to for features selection and classification. Finally, Pearson's linear correlation was employed to study associations between these entropies and cognitive functions. Compared to other entropies, FEn had a higher classification accuracy, sensitivity and specificity of 68%, 67.1% and 71.9%, respectively. Top 43 salient features achieved classification accuracy, sensitivity and specificity of 73.8%, 72.3% and 77.9%, respectively. P4, T4 and C4 were the highest ranking salient electrodes. Correlation analysis showed that FEn based on EMD was positively correlated to memory at electrodes F7, F8 and P4, and PsEn based on EMD was positively correlated to Montreal cognitive assessment (MoCA) and memory at electrode T4. In sum, FEn based on EMD in right-temporal and occipital regions may be more suitable for early diagnosis of the MCI with T2DM

Weighted-Permutation Entropy Analysis of Resting State EEG from Diabetics with Amnestic Mild Cognitive Impairment

Diabetes is a significant public health issue as it increases the risk for dementia and Alzheimer’s disease (AD). In this study, we aim to investigate whether weighted-permutation entropy (WPE) and permutation entropy (PE) of resting-state EEG (rsEEG) could be applied as potential objective biomarkers to distinguish type 2 diabetes patients with amnestic mild cognitive impairment (aMCI) from those with normal cognitive function. rsEEG series were acquired from 28 patients with type 2 diabetes (16 aMCI patients and 12 controls), and neuropsychological assessments were performed. The rsEEG signals were analysed using WPE and PE methods. The correlations between the PE or WPE of the rsEEG and the neuropsychological assessments were analysed as well. The WPE in the right temporal (RT) region of the aMCI diabetics was lower than the controls, and the WPE was significantly positively correlated to the scores of the Auditory Verbal Learning Test (AVLT) (AVLT-Immediate recall, AVLT-Delayed recall, AVLT-Delayed recognition) and the Wechsler Adult Intelligence Scale Digit Span Test (WAIS-DST). These findings were not obtained with PE. We concluded that the WPE of rsEEG recordings could distinguish aMCI diabetics from normal cognitive function diabetic controls among the current sample of diabetic patients. Thus, the WPE could be a potential index for assisting diagnosis of aMCI in type 2 diabetes

Effect of Pilates Training on Alpha Rhythm

In this study, the effect of Pilates training on the brain function was investigated through five case studies. Alpha rhythm changes during the Pilates training over the different regions and the whole brain were mainly analyzed, including power spectral density and global synchronization index (GSI). It was found that the neural network of the brain was more active, and the synchronization strength reduced in the frontal and temporal regions due to the Pilates training. These results supported that the Pilates training is very beneficial for improving brain function or intelligence. These findings maybe give us some line evidence to suggest that the Pilates training is very helpful for the intervention of brain degenerative diseases and cogitative dysfunction rehabilitation

Case report: Treating postpartum SUI with acupuncture and Chinese herbal medicine

Background: Stress urinary incontinence (SUI), is the most common type of urinary incontinence affecting women. SUI has a significant impact on psychosocial functioning and quality of life. Biomedical treatments, such as surgery, often result in post-operative complications. In China, traditional Chinese medicine tends to be the treatment of choice for SUI. Case presentation: We present a 35-year-old patient who developed SUI following forceps delivery and was treated successfully with acupuncture and Chinese herbs. Traditional Chinese diagnosis, including channel and acupoint palpation revealed the patient had a syndrome pattern of liver/kidney deficiency, disordered bladder qi transformation, all of which lead to enuresis. Acupuncture, both body and scalp needling, were performed. Herbs were prescribed adjunctively. Conclusion: Traditional Chinese medicine modalities may be considered for treatment of SUI based on appropriate syndrome pattern assessment

Effective recycling of Co and Sr from Co/Sr-bearing wastewater via an integrated Fe coagulation and hematite precipitation approach

Flocculant overdose has been considered an inefficient technique for precipitating heavy metals from wastewater at low levels due to the high yield of hazardous waste sludge that should be treated properly before it can be disposed of safely in landfills. This problem was effectively solved in this study via a novel method that recycles sludge separately into high-purity hematite and heavy metal-bearing products. The wastewater, which contained 10.3 mg/L of Co and 4.8 mg/L of Sr, was coagulated by adding ferric salt to generate Co/Sr-bearing sludge. The sludge was dissolved in HNO3, followed by hydrothermal treatment with the addition of organic matter (e.g. methanol or isopropanol). Without the addition of organic matter, only 56.5% of total Fe was removed as irregular hematite particles, whilst Co/Sr remained unchanged in the acid. Over 99.5% of total Fe was eliminated as hematite nanoparticles with 97.7% Fe2O3 content, but more than 98% Co/Sr remained in the acid when methanol with a molar ratio (Mmethanol/MFe) of 5 was added. Nearly 100% Co was precipitated by adjusting the pH of the acid to 8 to generate Co hydroxide with 83.9% purity. Meanwhile, the residual Sr was further precipitated by adding Na2CO3 to generate SrCO3 with 96.8% purity. Isopropanol achieved total Fe removal similar to that of methanol. The optimal molar ratio (MIsopropanol/MFe) was 1, which corresponded to the removal of 98.7% total Fe. Methanol and isopropanol can react with NO3− in acid to reduce NO2− concentration and improve acid pH, promoting hydrolysis followed by the crystallisation of ferric Fe with hematite as the final product. This paper is the first report on an environment-friendly method for enriching Co/Sr without generating any waste

Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China

County-based spatial distribution characteristics and the related geological factors for iodine in drinking-water were studied in Shandong Province (China). Spatial autocorrelation analysis and spatial scan statistic were applied to analyze the spatial characteristics. Generalized linear models (GLMs) and geographically weighted regression (GWR) studies were conducted to explore the relationship between water iodine level and its related geological factors. The spatial distribution of iodine in drinking-water was significantly heterogeneous in Shandong Province (Moran’s I = 0.52, Z = 7.4, p < 0.001). Two clusters for high iodine in drinking-water were identified in the south-western and north-western parts of Shandong Province by the purely spatial scan statistic approach. Both GLMs and GWR indicated a significantly global association between iodine in drinking-water and geological factors. Furthermore, GWR showed obviously spatial variability across the study region. Soil type and distance to Yellow River were statistically significant at most areas of Shandong Province, confirming the hypothesis that the Yellow River causes iodine deposits in Shandong Province. Our results suggested that the more effective regional monitoring plan and water improvement strategies should be strengthened targeting at the cluster areas based on the characteristics of geological factors and the spatial variability of local relationships between iodine in drinking-water and geological factors

H-1 NMR relaxation and theoretical calculation study on Tris (pentafluorophenyl)borane as a catalyst in preparation of Poly(carborane-siloxane) polymers

Poly(carborane-siloxane) polymers were successfully synthesized by tris(pentafluorophenyl)borane catalyzing diorganohydroxysilanes (Si-OH) and dihydrosilanes (Si-H) to form siloxane bond and release hydrogen. The structure of monomers and polymers were characterized by H-1, C-13, Si-29 NMR and FI-IR. Furthermore, in the present study, the qualitative characterization of silicon hydrogen bond in dihydrosilanes activated by catalyst B (C6F5)(3) was investigated by H-1 NMR relaxation test and theoretical calculation. The results shown that silicon hydrogen bond (Si-H) and B(C6F5)(3) form the complex [Si center dot center dot center dot H center dot center dot center dot B(C6F5)(3)] which is relevant to chemical re-activity. In addition, dihydrosilanes exhibit the following reactive activity order: 1,1,3,3-tetra-methyldisiloxane > 1,7-bis(3-hydridotetramethyldisiloxanyl)-m-carborane > diphenylsilane > methylphenylsilane > 1,7-bis(dimethylsilyl)-m-carborane. This synthetic method offers a new effective approach to synthesize poly(carborane-siloxane) polymers and the reactive activity order has a guide significance for experimental system design