Explore the vast range of titles available.

We tried to identify the function of LINC01614 in lung adenocarcinoma (LUAD) and reveal its underlying mechanisms. qRT‐PCR was applied to assess the expression of LINC016014 in LUAD tissues, noncancerous tissues and cells. Through colony formation assay, MTT assay and apoptosis analysis, we examined the variation of cell proliferation and apoptosis ability after silencing LINC01614. Moreover, the targeting interactions among LINC01614, miR‐217 and FOXP1 were validated via luciferase reporter assay, and then, we regulated the expression of miR‐217 and FOXP1 to ascertain their importance in cell proliferation and apoptosis. LINC01614 and FOXP1 were found to be up‐regulated in LUAD tumours and cells, whereas miR‐217 was down‐regulated. The experiment showed that target‐specific selectivity exists between LINC01614‐miR‐217 and miR‐217‐FOXP1 3′UTR. Furthermore, we disclosed that inhibition of LINC01614 could activate miR‐217, which subsequently restrained FOXP1. It was proved that LINC01614 promoted FOXP1 by inhibiting miR‐217, which ultimately stimulated the development of LUAD.

Alzheimer’s disease (AD) is a complex disorder influenced by both genetic and environmental components and has become a major public health issue throughout the world. Oxidative stress and inflammation play important roles in the evolution of those major pathological symptoms. Jatrorrhizine (JAT), a main component of a traditional Chinese herbal, coptidis rhizome, has been shown to have neuroprotective effects and we previously showed that it is also able to clear oxygen free radicals and reduce inflammatory responses. In this study, we demonstrated that JAT administration could alleviate the learning and memory deficits in AD. Furthermore, we also found that JAT treatment reduced the levels of Aβ plaques in the cortex and hippocampus of APP/PS1 double-transgenic mice. Other studies suggest that there are gut microbiome alterations in AD. In order to explore the underlying mechanisms between gut microbiota and AD, DNA sequencing for 16s rDNA V3-V4 was performed in fecal samples from APP/PS1 transgenic mice and C57BL/6 wild-type (WT) mice. Our results indicated that APP/PS1 mice showed less Operational Taxonomic Units (OTUs) abundance in gut microbiota than WT mice and with different composition. Furthermore, JAT treatment enriched OTUs abundance and alpha diversity in APP/PS1 mice compared to WT mice. High dose of JAT treatment altered the abundance of some specific gut microbiota such as the most predominant phylum Firmicutes and Bacteroidetes in APP/PS1 mice. In conclusion, APP/PS1 mice display gut dysbiosis, and JAT treatment not only improved the memory deficits, but also regulated the abundance of the microbiota. This may provide a therapeutic way to balance the gut dysbiosis in AD patients.

A new algorithm called maximum correntropy unscented Kalman filter (MCUKF) is proposed and applied to relative state estimation in space communication networks. As is well known, the unscented Kalman filter (UKF) provides an efficient tool to solve the non-linear state estimate problem. However, the UKF usually plays well in Gaussian noises. Its performance may deteriorate substantially in the presence of non-Gaussian noises, especially when the measurements are disturbed by some heavy-tailed impulsive noises. By making use of the maximum correntropy criterion (MCC), the proposed algorithm can enhance the robustness of UKF against impulsive noises. In the MCUKF, the unscented transformation (UT) is applied to obtain a predicted state estimation and covariance matrix, and a nonlinear regression method with the MCC cost is then used to reformulate the measurement information. Finally, the UT is adopted to the measurement equation to obtain the filter state and covariance matrix. Illustrative examples demonstrate the superior performance of the new algorithm.

To detect the levels of plasma High-Mobility Group Box-1(HMGB1) in Chinese subject with obesity and type 2 diabetes mellitus (T2DM), and to investigate the correlations between plasma HMGB1 concentration and parameters of body fat, insulin resistance (IR) metabolism and inflammation. This study recruited 79 normal glucose tolerance (NGT) subjects and 76 newly diagnosed T2DM patients. NGT and T2DM groups were divided into normal weight (NW) and obese (OB)subgroups respectively. Anthropometric parameters such as height, weight, waist circumference, hip circumference and blood pressure were measured. Plasma concentrations of HMGB1, IL-6, fasting plasma glucose (FPG), 2 hours post challenge plasma glucose (2hPG), serum lipid, glycated hemoglobin (HbA1C) and fasting insulin (FINS) were examined. The homeostasis model assessment (HOMA) was performed to assess IR status. Plasma HMGB1 levels were higher in T2DM group than that in NGT group. The concentrations of serum HMGB1 were also higher in subjects with OB than those in subjects with NW both in NGT and T2DM groups. Plasma levels of HMGB1 were positively correlated with waist hip ratio (WHR), blood pressure, FPG, FINS, HOMA-IR, TG, IL-6 and negatively correlated with HOMA-βand high-density lipoprotein-cholesterol (HDL-c) independent of age, gender and BMI. Plasma levels of HMGB1 were significantly correlated with diabetes in fully adjusted models. Plasma HMGB1 levels were increased in Chinese subjects with pure T2DM, which might be caused by IR. Serum HMGB1 participated in the pathological process of obesity and T2DM via its proinflammatory effect.

Background. Adipokines are reported to participate in many common pathologic processes of glucose dysregulation, such as insulin resistance, β-cell dysfunction, and chronic inflammation. Objective. To detect the concentrations of plasma asprosin in subjects with impaired glucose regulation (IGR) and newly diagnosed type 2 diabetes (nT2DM) and its relationship to parameters of glucose and lipid metabolism, insulin resistance, and pancreatic β-cell function. Methods. 143 eligible participants were included and were divided into three groups including normal glucose regulation (NGR, n=52), IGR (n=40), and nT2DM group (n=51). The intravenous glucose tolerance test (IVGTT) and clinical and biochemical parameters were measured in all participants. Results. Plasma asprosin levels were higher in IGR (82.40 ± 91.06 ng/mL, P<0.001) and nT2DM (73.25 ± 91.69 ng/mL, P<0.001) groups compared with those in the NGR (16.22 ± 9.27 ng/mL) group, especially in IGR subjects. Correlation analysis showed that plasma asprosin levels were positively correlated with waist circumference (Wc), fasting plasma glucose (FPG), postchallenge plasma glucose (2hPG), HbA1c, triglyceride (TG), and homeostasis model assessment for insulin resistance (HOMA-IR) and negatively correlated with homeostasis model assessment for β-cell function (HOMA-β), area under the curve of the first-phase (0–10 min) insulin secretion (AUC), acute insulin response (AIR), and glucose disposition index (GDI) (all P<0.05). Multiple logistical regression analyses revealed that plasma asprosin concentrations were significantly correlated with IGR and nT2DM after controlling for age, sex, BMI, and WHR. Conclusions. Circulating asprosin might be a predictor of early diagnosis in DM and might be a potential therapeutic target for prediabetes and T2DM.

Vehicle exhaust emissions are identified as one of the main determinants of air pollution and play an important role in the environmental sustainable improvement of countries. This research utilizes a panel data of 30 Chinese provinces during the period between 1997 and 2012 to examine the existence of inverted U-shaped relationship between public healthcare expenditure per capita and private car ownership across geographical regions (east, middle and west China) employing panel generalized method of moments estimates for robust estimates. The findings also show the income per capita significantly and positively impacts on health expenditure per capita at the national level. The other results indicate that sulfur dioxide emissions and people over age 65 significantly increase healthcare expenditure per capita except the western region; soot emissions have a significantly positive impact on public health expenditure per capita for only the whole country and the western region; the number of doctors per capita may decrease public health expenditure per capita caused by environmental pollution. These results have important policy implications for promotion of new energy vehicles and for improving air quality and medical and health services.

Asprosin is a white adipose tissue-derived hormone that increases abnormally in mammals with insulin resistance. However, the role of asprosin in polycystic ovary syndrome (PCOS), a disease partly characterized by insulin resistance, and its potential connection with type 2 diabetes mellitus (T2DM) and PCOS has not been thoroughly elucidated to date. To investigate the association of asprosin with metabolic profiles, sex-related hormones, or inflammation in females with T2DM or PCOS, plasma asprosin and metabolic indicators were measured in 66 healthy females, 53 female patients with T2DM, and 41 patients with PCOS. Spearman’s correlation analysis and binary logistic regression analysis models were used. Plasma asprosin was significantly higher in T2DM females than in healthy subjects (P<0.001) and was positively correlated with fasting blood glucose (FBG), hemoglobin A1c (HbA1c), and HOMA-IR (P<0.05). Asprosin in PCOS subjects was also higher than in healthy subjects (P<0.001) but lower than in T2DM subjects (P<0.05), and it was positively correlated with FBG, HbA1c, HOMA-IR, LDL-c, APOB, APOE, and testosterone (P<0.05). The BMI-categorized subgroups of PCOS subjects also showed correlations of asprosin with metabolic profiles and sex-related hormones. Binary logistic regression analysis revealed that plasma asprosin level acted as an independent risk factor for T2DM or PCOS. These findings suggest the correlation of plasma asprosin level with glucose metabolism, lipid metabolism, sex-related hormones, and inflammation in females, supporting asprosin as a potential predictive factor for females with metabolic-related diseases. This trial is registered with ChiCTR-ROC-17010719.

Our prior study (Tarasov et al., 2022) discovered that numerous adaptive mechanisms emerge in response to cardiac-specific overexpression of adenylyl cyclase type 8 (TGAC8) which included overexpression of a large number of proteins. Here, we conducted an unbiased phosphoproteomics analysis in order to determine the role of altered protein phosphorylation in the adaptive heart performance and protection profile of adult TGAC8 left ventricle (LV) at 3–4 months of age, and integrated the phosphoproteome with transcriptome and proteome. Based on differentially regulated phosphoproteins by genotype, numerous stress-response pathways within reprogrammed TGAC8 LV, including PKA, PI3K, and AMPK signaling pathways, predicted upstream regulators (e.g. PDPK1, PAK1, and PTK2B), and downstream functions (e.g. cell viability, protein quality control), and metabolism were enriched. In addition to PKA, numerous other kinases and phosphatases were hyper-phosphorylated in TGAC8 vs. WT. Hyper-phosphorylated transcriptional factors in TGAC8 were associated with increased mRNA transcription, immune responses, and metabolic pathways. Combination of the phosphoproteome with its proteome and with the previously published TGAC8 transcriptome enabled the elucidation of cardiac performance and adaptive protection profiles coordinately regulated at post-translational modification (PTM) (phosphorylation), translational, and transcriptional levels. Many stress-response signaling pathways, i.e., PI3K/AKT, ERK/MAPK, and ubiquitin labeling, were consistently enriched and activated in the TGAC8 LV at transcriptional, translational, and PTM levels. Thus, reprogramming of the cardiac phosphoproteome, proteome, and transcriptome confers resilience to chronic adenylyl cyclase-driven stress. We identified numerous pathways/function predictions via gene sets, phosphopeptides, and phosphoproteins, which may point to potential novel therapeutic targets to enhance heart adaptivity, maintaining heart performance while avoiding cardiac dysfunction.

Network function virtualization (NFV) is a key technology to decouple hardware device and software function. Several virtual network functions (VNFs) combine into a function sequence in a certain order, that is defined as service function chain (SFC). A significant challenge is guaranteeing reliability. First, deployment server is selected to place VNF, then, backup server is determined to place the VNF as a backup which is running when deployment server is failed. Moreover, how to determine the accurate locations dynamically with machine learning is challenging. This paper focuses on resource requirements of SFC to measure its priority meanwhile calculates node priority by current resource capacity and node degree, then, a novel priority-awareness deep reinforcement learning (PA-DRL) algorithm is proposed to implement reliable SFC dynamically. PA-DRL determines the backup scheme of each VNF, then, the model jointly utilizes delay, load balancing of network as feedback factors to optimize the quality of service. In the experimental results, resource efficient utilization, survival rate, and load balancing of PA-DRL were improved by 36.7%, 35.1%, and 78.9% on average compared with benchmark algorithm respectively, average delay was reduced by 14.9%. Therefore, PA-DRL can effectively improve reliability and optimization targets compared with other benchmark methods.