Mangiferin ameliorates insulin resistance in a rat model of polycystic ovary syndrome via inhibition of inflammation

Purpose: To examine the effect of mangiferin on insulin resistance (IR) in a rat polycystic ovary syndrome (PCOS) model.Methods: The rat PCOS model was established via subcutaneous injection of 6 mg/kg of dehydroepiandrosterone (DHEA), and mangiferin was orally administered. Body and ovarian weights were recorded. Serum levels of glucose, insulin, and related inflammatory cytokines were evaluated by quantitative real-time polymerase chain reaction (qRT-PCR) and enzyme-linked immunosorbent assay, while the expression levels of key proteins were analyzed by western blotting.Results: DHEA significantly increased ovarian weight and the ratio of ovarian weight/body weight (p <0.001), while mangiferin treatment decreased them (p < 0.001). Mangiferin also lowered DHEA-induced enhancements in serum glucose and insulin levels (p < 0.001). The mRNA and, expression and concentrations of inflammatory cytokines (interleukin-6(IL-6), interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α)) were also significantly reduced by mangiferin treatment (p < 0.001). Furthermore, mangiferin suppressed phosphorylation of nuclear factor-kappa B (NF-κB) but increased the phosphorylation of protein kinase B (AKT, p < 0.001).Conclusion: These results reveal that mangiferin not only decreases inflammatory cytokine levels by regulating NF-κB signaling pathway but also ameliorates IR in a rat PCOS model via regulating AKT signaling pathway. Thus, mangiferin is a potential therapeutic strategy for the management of PCOS. Keywords: Polycystic ovary syndrome, Mangiferin, Inflammation, Insulin resistance, NF-κB, AK

The enteric nervous system deficits in autism spectrum disorder

Gastrointestinal (GI) disorders are common comorbidities in individuals with autism spectrum disorder (ASD), and abnormalities in these issues have been found to be closely related to the severity of core behavioral deficits in autism. The enteric nervous system (ENS) plays a crucial role in regulating various aspects of gut functions, including gastrointestinal motility. Dysfunctional wiring in the ENS not only results in various gastrointestinal issues, but also correlates with an increasing number of central nervous system (CNS) disorders, such as ASD. However, it remains unclear whether the gastrointestinal dysfunctions are a consequence of ASD or if they directly contribute to its pathogenesis. This review focuses on the deficits in the ENS associated with ASD, and highlights several high-risk genes for ASD, which are expressed widely in the gut and implicated in gastrointestinal dysfunction among both animal models and human patients with ASD. Furthermore, we provide a brief overview of environmental factors associated with gastrointestinal tract in individuals with autism. This could offer fresh perspectives on our understanding of ASD

Association between acute kidney injury and prognoses of cardiac surgery patients: Analysis of the MIMIC-III database

BackgroundAcute kidney injury (AKI) is the most common major complication of cardiac surgery field. The purpose of this study is to investigate the association between acute kidney injury and the prognoses of cardiac surgery patients in the Medical Information Mart for Intensive Care III (MIMIC-III) database.MethodsClinical data were extracted from the MIMIC-III database. Adult (≥18 years) cardiac surgery patients in the database were enrolled. Multivariable logistic regression analyses were employed to assess the associations between acute kidney injury (AKI) comorbidity and 30-day mortality, 90-day mortality and hospital mortality. Different adjusting models were used to adjust for potential confounders.ResultsA total of 6,002 patients were involved, among which 485 patients (8.08%) had comorbid AKI. Patients with AKI were at higher risks of prolonged ICU stay, hospital mortality, 90-day mortality (all P < 0.001), and 30-day mortality (P = 0.008). AKI was a risk factor for hospital mortality [Model 1, OR (95% CI) = 2.50 (1.45–4.33); Model 2, OR (95% CI) = 2.44 (1.48–4.02)], 30-day mortality [Model 1, OR (95% CI) = 1.84 (1.05–3.24); Model 2, OR (95% CI) = 1.96 (1.13–3.22)] and 90-day mortality [Model 1, OR (95% CI) = 2.05 (1.37–3.01); Model 2, OR (95% CI) = 2.76 (1.93–3.94)]. Higher hospital mortality, 30-day mortality and 90-day mortality was observed in higher KDIGO grade for cardiac surgery patients with AKI (all P < 0.05).ConclusionComorbid AKI increased the risk of hospital mortality, 30-day mortality, and 90-day mortality of cardiac surgery patients in the MIMIC-III database

Decreased expression of dual-specificity phosphatase 9 is associated with poor prognosis in clear cell renal cell carcinoma

Background: The molecular mechanisms involved in the development and progression of clear cell renal cell carcinomas (ccRCCs) are poorly understood. The objective of this study was to analyze the expression of dual-specificity phosphatase 9 (DUSP-9) and determine its clinical significance in human ccRCCs. Methods: The expression of DUSP-9 mRNA was determined in 46 paired samples of ccRCCs and adjacent normal tissues by using real-time qPCR. The expression of the DUSP-9 was determined in 211 samples of ccRCCs and 107 paired samples of adjacent normal tissues by immunohistochemical analysis. Statistical analysis was performed to define the relationship between the expression of DUSP-9 and the clinical features of ccRCC. Results: The mRNA level of DUSP-9, which was determined by real-time RT-PCR, was found to be significantly lower in tumorous tissues than in the adjacent non-tumorous tissues (p < 0.001). An immunohistochemical analysis of 107 paired tissue specimens showed that the DUSP-9 expression was lower in tumorous tissues than in the adjacent non-tumorous tissues (p < 0.001). Moreover, there was a significant correlation between the DUSP-9 expression in ccRCCs and gender (p = 0.031), tumor size (p = 0.001), pathologic stage (p = 0.001), Fuhrman grade (p = 0.002), T stage (p = 0.001), N classification (p = 0.012), metastasis (p = 0.005), and recurrence (p < 0.001). Patients with lower DUSP-9 expression had shorter overall survival time than those with higher DUSP-9 expression (p < 0.001). Multivariate analysis indicated that low expression of the DUSP-9 was an independent predictor for poor survival of ccRCC patients. Conclusion: To our knowledge, this is the first study that determines the relationship between DUSP-9 expression and prognosis in ccRCC. We found that decreased expression of DUSP-9 is associated with poor prognosis in ccRCC. DUSP-9 may represent a novel and useful prognostic marker for ccRCC

Lipid profiles in the cerebrospinal fluid of rats with 6-hydroxydopamine-induced lesions as a model of Parkinson’s disease

BackgroundParkinson’s disease (PD) is a progressive neurodegenerative disease with characteristic pathological abnormalities, including the loss of dopaminergic (DA) neurons, a dopamine-depleted striatum, and microglial activation. Lipid accumulation exhibits a close relationship with these pathologies in PD.MethodsHere, 6-hydroxydopamine (6-OHDA) was used to construct a rat model of PD, and the lipid profile in cerebrospinal fluid (CSF) obtained from model rats was analyzed using lipidomic approaches.ResultsEstablishment of this PD model was confirmed by apomorphine-induced rotation behaviors, loss of DA neurons, depletion of dopamine in the striatum, and microglial activation after 6-OHDA-induced lesion generation. Unsupervised and supervised methods were employed for lipid analysis. A total of 172 lipid species were identified in CSF and subsequently classified into 18 lipid families. Lipid families, including eicosanoids, triglyceride (TG), cholesterol ester (CE), and free fatty acid (FFA), and 11 lipid species exhibited significantly altered profiles 2 weeks after 6-OHDA administration, and significant changes in eicosanoids, TG, CE, CAR, and three lipid species were noted 5 weeks after 6-OHDA administration. During the period of 6-OHDA-induced lesion formation, the lipid families and species showed concentration fluctuations related to the recovery of behavior and nigrostriatal abnormalities. Correlation analysis showed that the levels of eicosanoids, CE, TG families, and TG (16:0_20:0_18:1) exhibited positive relationships with apomorphine-induced rotation behaviors and negative relationships with tyrosine hydroxylase (TH) expression in the midbrain.ConclusionThese results revealed that non-progressive nigrostriatal degeneration induced by 6-OHDA promotes the expression of an impairment-related lipidomic signature in CSF, and the level of eicosanoids, CE, TG families, and TG (16:0_20:0_18:1) in CSF may reveal pathological changes in the midbrain after 6-OHDA insult

Audio Signal and Troubleshooting System Based on Wireless Sensor

To explore the application of audio signal in the troubleshooting system, a sound detection system was designed. The system consists of three parts: voice acquisition node, aggregation node and host computer monitoring software. Time protocol synchronization (TPSN) algorithm was used to realize the synchronization between nodes. The algorithm and the trilateration method were applied to the system. The applications of the sound detection system in the field of fault sound source localization were realized.Wireless sensor networks were used in sound detection systems, which had many advantages. On the one hand, complicated wiring was avoided. It had the advantages of easy to set up and easy to move.On the other hand, some self-organizing and adaptive features in wireless sensor networks and some methods of synchronization and localization could be introduced. Thewhole system was more flexible and its application was more extensive.Using monitoring software, users can remotely access to the scene of the voice signal.The results showed that the system had high transmission rate, stable operation and small positioning error. Therefore, it has good application prospects

DE_PSO_SVM: An Alternative Wine Classification Method Based on Machine Learning

Accurate classification of wine quality may help to improve making technology of wine. For achieving more effective quality classification, a classification method named DE_PSO_SVM (dataset enhancement (DE)_particle swarm optimization (PSO)_support vector machine (SVM)) is proposed. The correlation between feature attributes and classification labels of wine samples were analyzed to achieve dimension reduction. DE was achieved by calculating the different weight sums of adjacent odd and even rows, both of which belong to the same class of samples. PSO was used to search for the optimal parameters of a Gaussian kernel function, which were substituted in the SVM model to classify wine. K-nearest-neighbor (KNN), random forest (RF) and classification and regression tree (CART) were also used to test the wine classification. In 7-fold cross-validation on three wine datasets, the average Precision, Recall, and F1score of DE_PSO_SVM were best. The results show that enhancing datasets with small samples and searching for the optimal super parameters by PSO improved the performance of the wine classification model