Deeply involved with dyslipidemia, cardiovascular disease has becoming the leading cause of mortality since the early twentieth century in the modern world. Whose correlation with metabolic syndrome ...(MetS), hypertension and type 2 diabetes mellitus (T2DM) has been well established. We conducted a 9-year longitudinal study to identify the association between easily measured lipid parameters, future MetS, hypertension and T2DM by gender and age distribution. Divided into three groups by age (young age: < 40, middle age: ≥ 40 and < 65 and old age: ≥ 65), 7670 participants, receiving standard medical inspection at Tri-Service General Hospital (TSGH) in Taiwan, had been enrolled in this study. Atherogenic index of plasma (AIP) was a logarithmically transformed ratio of triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C). Through multivariate regression analyses, the hazard ratio (HR) of AIP for MetS, hypertension and T2DM were illustrated. AIP revealed significant association with all the aforementioned diseases through the entire three models for both genders. Additionally, AIP revealed significant correlation which remained still after fully adjustment in MetS, hypertension, and T2DM groups for subjects aged 40-64-year-old. Nevertheless, for participants aged above 65-year-old, AIP only demonstrated significant association in MetS group. Our results explore the promising value of AIP to determine the high-risk subjects, especially meddle-aged ones, having MetS, hypertension, and T2DM in the present and the future.
Circular RNAs are a class of regulatory RNA transcripts, which are ubiquitously expressed in eukaryotes. In the current study, we evaluate the function of a novel circRNA derived from the β-catenin ...gene locus, circβ-catenin.
Circβ-catenin is predominantly localized in the cytoplasm and displays resistance to RNase-R treatment. We find that circβ-catenin is highly expressed in liver cancer tissues when compared to adjacent normal tissues. Silencing of circβ-catenin significantly suppresses malignant phenotypes in vitro and in vivo, and knockdown of this circRNA reduces the protein level of β-catenin without affecting its mRNA level. We show that circβ-catenin affects a wide spectrum of Wnt pathway-related genes, and furthermore, circβ-catenin produces a novel 370-amino acid β-catenin isoform that uses the start codon as the linear β-catenin mRNA transcript and translation is terminated at a new stop codon created by circularization. We find that this novel isoform can stabilize full-length β-catenin by antagonizing GSK3β-induced β-catenin phosphorylation and degradation, leading to activation of the Wnt pathway.
Our findings illustrate a non-canonical function of circRNA in modulating liver cancer cell growth through the Wnt pathway, which can provide novel mechanistic insights into the underlying mechanisms of hepatocellular carcinoma.
In this work, we propose a scheme for cosmic evolution in a generalized Rastall gravity. In our approach, the role of dark energy is taken by the non-conserved sector of the stress energy–momentum ...tensor. The resultant cosmic evolution is found to naturally consists of three stages, namely, radiation dominated, ordinary matter dominated, as well as dark energy and dark matter dominated eras. Furthermore, for the present model, it is demonstrated that the eventual fate of the Universe is mostly insensitive to the initial conditions, in contrast to the standard
Λ
CDM
model. In particular, the solution displays the properties of a dynamic attractor, which is reminiscent of quintessence and k-essence models. Subsequently, the cosmic coincidence problem is averted. The amount of deviation from a conserved stress energy–momentum tensor is shown to be more remarkable during the period when the dark energy evolves more rapidly. On the other hand, the conservation law is largely restored for the infinite past and future. The implications of the present approach are addressed.
Photocatalysts derived from semiconductor heterojunctions that harvest solar energy and catalyze reactions still suffer from low solar‐to‐hydrogen conversion efficiency. Now, MXene (Ti3C2TX) ...nanosheets (MNs) are used to support the in situ growth of ultrathin ZnIn2S4 nanosheets (UZNs), producing sandwich‐like hierarchical heterostructures (UZNs‐MNs‐UZNs) for efficient photocatalytic H2 evolution. Opportune lateral epitaxy of UZNs on the surface of MNs improves specific surface area, pore diameter, and hydrophilicity of the resulting materials, all of which could be beneficial to the photocatalytic activity. Owing to the Schottky junction and ultrathin 2D structures of UZNs and MNs, the heterostructures could effectively suppress photoexcited electron–hole recombination and boost photoexcited charge transfer and separation. The heterostructure photocatalyst exhibits improved photocatalytic H2 evolution performance (6.6 times higher than pristine ZnIn2S4) and excellent stability.
MXene nanosheets are used to support the in situ growth of ultrathin ZnIn2S4. The obtained sandwich‐like hierarchical heterostructure could effectively suppress photoexcited electron–hole recombination and boost photoexcited charge transfer and separation, exhibiting efficient photocatalytic H2 evolution performance and excellent stability.
•The interaction between urbanization, economic growth, and environmental pollution in three directions is investigated.•A model of “urbanization-economic growth” and a “simultaneous equation model” ...are constructed.•There is an environmental Kuznets inverted U curve between economic growth and environmental pollution.
As the state is vigorously promoting the construction of new urbanization in China, it is of great practical significance to study the interaction between urbanization, economic growth, and environmental pollution in three directions for the scientific planning of urbanization. Based on panel data of 30 provinces and cities in China during 2006–2015, we built the “Urbanization economic growth model” and a “simultaneous equation model.” The results show that urbanization promotes economic growth through the accumulation of physical capital, knowledge capital, and human capital; that the relationship between economic growth and urbanization is a benign interaction; that environmental pollution has a significant inhibitory effect on urbanization; and that there is an environmental Kuznets inverted U curve between economic growth and environmental pollution, and between urbanization and environmental pollution. On this basis, this paper puts forward some policy suggestions on how to enhance the positive interaction between urbanization and economic growth and promote the construction of new green urbanization.
•This paper proposes a hybrid time-series ANFIS model based on EMD to forecast stock price.•In order to evaluate the forecasting performances, the proposed model is compared with other models.•The ...experimental results show that proposed model is superior to the listing models.
Time series forecasting is an important and widely popular topic in the research of system modeling, and stock index forecasting is an important issue in time series forecasting. Accurate stock price forecasting is a challenging task in predicting financial time series. Time series methods have been applied successfully to forecasting models in many domains, including the stock market. Unfortunately, there are 3 major drawbacks of using time series methods for the stock market: (1) some models can not be applied to datasets that do not follow statistical assumptions; (2) most time series models that use stock data with a significant amount of noise involutedly (caused by changes in market conditions and environments) have worse forecasting performance; and (3) the rules that are mined from artificial neural networks (ANNs) are not easily understandable.
To address these problems and improve the forecasting performance of time series models, this paper proposes a hybrid time series adaptive network-based fuzzy inference system (ANFIS) model that is centered around empirical mode decomposition (EMD) to forecast stock prices in the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and Hang Seng Stock Index (HSI). To measure its forecasting performance, the proposed model is compared with Chen's model, Yu's model, the autoregressive (AR) model, the ANFIS model, and the support vector regression (SVR) model. The results show that our model is superior to the other models, based on root mean squared error (RMSE) values.
Abstract
Supported metal nanoparticles are of universal importance in many industrial catalytic processes. Unfortunately, deactivation of supported metal catalysts via thermally induced sintering is ...a major concern especially for high-temperature reactions. Here, we demonstrate that the particle distance as an inherent parameter plays a pivotal role in catalyst sintering. We employ carbon black supported platinum for the model study, in which the particle distance is well controlled by changing platinum loading and carbon black supports with varied surface areas. Accordingly, we quantify a critical particle distance of platinum nanoparticles on carbon supports, over which the sintering can be mitigated greatly up to 900 °C. Based on in-situ aberration-corrected high-angle annular dark-field scanning transmission electron and theoretical studies, we find that enlarging particle distance to over the critical distance suppress the particle coalescence, and the critical particle distance itself depends sensitively on the strength of metal-support interactions.
Functional connectivity and effective connectivity of the human brain, representing statistical dependence and directed information flow between cortical regions, significantly contribute to the ...study of the intrinsic brain network and its functional mechanism. Many recent studies on electroencephalography (EEG) have been focusing on modeling and estimating brain connectivity due to increasing evidence that it can help better understand various brain neurological conditions. However, there is a lack of a comprehensive updated review on studies of EEG‐based brain connectivity, particularly on visualization options and associated machine learning applications, aiming to translate those techniques into useful clinical tools. This article reviews EEG‐based functional and effective connectivity studies undertaken over the last few years, in terms of estimation, visualization, and applications associated with machine learning classifiers. Methods are explored and discussed from various dimensions, such as either linear or nonlinear, parametric or nonparametric, time‐based, and frequency‐based or time‐frequency‐based. Then it is followed by a novel review of brain connectivity visualization methods, grouped by Heat Map, data statistics, and Head Map, aiming to explore the variation of connectivity across different brain regions. Finally, the current challenges of related research and a roadmap for future related research are presented.
This article reviews EEG‐based functional and effective connectivity studies undertaken over the last few years, in terms of estimation, visualization, and applications associated with machine learning classifiers. Methods are explored and discussed from various dimensions, such as either linear or nonlinear, parametric, or nonparametric, time‐based, frequency‐based or time‐frequency‐based. Then it is followed by a novel review of brain connectivity visualization methods, grouped by Heat Map, data statistics and Head Map, aiming to explore the variation of connectivity across different brain regions. Finally, the current challenges of related research and a roadmap for future related research are presented.
Sarcopenia and cognitive impairment are two of the most prevalent causes of disability in the aging population. Despite the vast amount of research that has been done to quantify the association ...between these two conditions, extensive systematic reviews and meta-analyses remain limited.
We performed a systematic review using the PubMed, EMBASE, Scopus, and Google Scholar databases. Sarcopenia was defined as the loss of skeletal muscle mass and muscle function, as measured by muscle strength or performance. Cognitive impairment was diagnosed by validated cognitive or neuropsychological tests.
We identified 303 potentially relevant articles in the initial search. Observational studies quantifying a relationship between sarcopenia and cognitive impairment were selected. Information was extracted from 15 studies, and random-effects models were used for the meta-analysis. The pooled odds ratios for cognitive impairment for patients with sarcopenia compared with patients without sarcopenia were 2.85 (95% confidence interval: 2.19–3.72) in the unadjusted analysis and 2.25 (95% confidence interval: 1.70–2.97) in the adjusted meta-analysis. These results remained constant in subgroup analyses by study population, study region, the definition of sarcopenia, and cognitive impairment. Although half of the studies (8 out of 15) were of fair quality, we conducted a sensitivity analysis to exclude studies with fair quality and obtained similar results.
Sarcopenia is associated with an increased risk of cognitive impairment independent of study population, the definition of sarcopenia, and cognitive impairment. This suggests the importance of the early recognition of sarcopenia for the prevention of cognitive impairment in clinical practice.
Major depressive disorder (MDD) is a debilitating psychiatric illness. However, there is currently no objective laboratory-based diagnostic tests for this disorder. Although, perturbations in ...multiple neurotransmitter systems have been implicated in MDD, the biochemical changes underlying the disorder remain unclear, and a comprehensive global evaluation of neurotransmitters in MDD has not yet been performed. Here, using a GC-MS coupled with LC-MS/MS-based targeted metabolomics approach, we simultaneously quantified the levels of 19 plasma metabolites involved in GABAergic, catecholaminergic, and serotonergic neurotransmitter systems in 50 first-episode, antidepressant drug-naïve MDD subjects and 50 healthy controls to identify potential metabolite biomarkers for MDD (training set). Moreover, an independent sample cohort comprising 49 MDD patients, 30 bipolar disorder (BD) patients and 40 healthy controls (testing set) was further used to validate diagnostic generalizability and specificity of these candidate biomarkers. Among the 19 plasma neurotransmitter metabolites examined, nine were significantly changed in MDD subjects. These metabolites were mainly involved in GABAergic, catecholaminergic and serotonergic systems. The GABAergic and catecholaminergic had better diagnostic value than serotonergic pathway. A panel of four candidate plasma metabolite biomarkers (GABA, dopamine, tyramine, kynurenine) could distinguish MDD subjects from health controls with an AUC of 0.968 and 0.953 in the training and testing set, respectively. Furthermore, this panel distinguished MDD subjects from BD subjects with high accuracy. This study is the first to globally evaluate multiple neurotransmitters in MDD plasma. The altered plasma neurotransmitter metabolite profile has potential differential diagnostic value for MDD.
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