Functional constipation (FC), a condition characterized by heterogeneous symptoms (infrequent bowel movements, hard stools, excessive straining, or a sense of incomplete evacuation), is prevalent ...over the world. It is a multifactorial disorder and can be categorized into four subgroups according to different pathological mechanisms: normal transit constipation (NTC), slow transit constipation (STC), defecatory disorders (DD), and mixed type. Recently, growing evidence from human and animals has pointed that there was a strong association between gut microbiota and FC based on the brain-gut-microbiome axis. Studies have reported that the main characteristics of gut microbiota in FC patients were the relative decrease of beneficial bacteria such as Lactobacillus and Bifidobacterium, the relative increase of potential pathogens, and the reduced species richness. Gut microbiota can modulate gut functions through the metabolites of bacterial fermentation, among which short-chain fatty acids (SCFAs), secondary bile salts (BAs), and methane occupied more important positions and could trigger the release of gut hormones from enteroendocrine cells (EECs), such as 5-hydroxytryptamine (5-HT), peptide YY (PYY), and glucagon-like peptide-1 (GLP-1). Subsequently, these gut hormones can influence gut sensation, secretion, and motility, primarily through activating specific receptors distributed on smooth muscle cells, enteric neurons, and epithelial cells. However, research findings were inconsistent and even conflicting, which may be partially due to various confounding factors. Future studies should take the associated confounders into consideration and adopt multiomics research strategies to obtain more complete conclusions and to provide reliable theoretical support for exploring new therapeutic targets.
Compressed air energy storage (CAES) can mitigate fluctuations of renewable-energy output due to its large-scale storage capacities, high ramp rate, and quick start-up time. It has become a novel ...choice for energy storage in microgrids. An islanded microgrid, which consists of wind turbines (WTs), photovoltaic (PV) array, diesel generators, and CAES, is investigated in this paper. The constant-pressure CAES is modeled in terms of its power capacity and energy capacity. A bi-level program (BLP) is proposed for the microgrid planning problem. It considers optimization of operation at the design stage of microgrids. The sizing problem is formulated on the upper level (UL), while the unit commitment (UC) problem with spinning-reserve requirement for the microgrid is described on the lower level (LL). The effectiveness of the approach is validated by case studies where the proposed methodology is compared to other similar ones.
The use of machine learning in physicochemical properties modeling has great potential to accelerate the application of emerging materials. Deep eutectic solvents (DESs), an emerging class of ...solvents, are promising for applications as inexpensive “designer” solvents. Due to the unique structure of DESs, the hydrogen bond donor and hydrogen bond acceptor can be varied to create a mixture with specific physical properties. In this work, we proposed random forest (RF) models to predict the densities and the surface tensions of DESs, which are essential for the separation process. In the proposed models, the structural information and the calculated critical properties were used as two different types of features, respectively. The results demonstrate that the RF models predict the densities and surface tensions of DESs with high accuracy, with absolute average relative deviation (AARD%) less than 1% in the prediction of density and 3% in the prediction of surface tension.
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It finds that CQDs synthesized by hydrothermal method possess obvious upconversion properties that could transfer low energy photons to high energy photons, resulting in enhanced ...visible light response and utilization. Herein, carbon quantum dots (CQDs) modified TiO2 photocatylysts were successfully prepared by a facile sol-gel method. Photophysical and surficial properties of the as-prepared composite photocatalyst were investigated in details. Furthermore, photocatalytic performance was tested by degrading methylene blue (MB) under visible light irradiation. The degradation efficiency of methylene blue (MB) is as high as 90% within 120min, which is 3.6 times higher than that of pure TiO2.
As the typical clean and renewable energy, wind energy has witnessed a continuous annual increase in the last few decades. Due to the random and intermittent characteristics, the wind producers in ...the electric market meet serious financial losses caused by the deviation between the actual power output and forecasting result. It is difficult to increase the accuracy of forecasting in a short time. How to improve the financial income has become a major task to wind producers and academia. Being the backbone network of the offshore wind farms (OWFs), voltage source converter-based multi-terminal HVdc system (VSC-MTdc) has been regarded as one of the effective solutions to transport wind power. In this paper, an optimal distribution method is proposed for VSC-MTdc system integrating OWFs to reduce the financial loss due to wind power output deviation. The proposed method could be divided into two optimizing functions. The first optimizing function of the proposed method is to analyze the onshore external system according to the historical system operation data and adjust the droop coefficient with the analytic hierarchy process. The second optimizing function of the proposed method is to do further adjusting with the regulating price. With the case study, the proposed optimal distribution method has proved that it can bring more benefit to wind producers.
Abstract Structural optimization is essential to improve the performance of mixing equipment. An efficient optimization strategy based on computational fluid dynamics, machine learning, and the ...multi‐objective genetic algorithm was proposed to predict and optimize the performance of the stirred tank. Single‐factor analysis was performed to study the effects of structural parameters on power consumption and mixing time, which were reduced by 16.0% and 1.4%, respectively, in the optimized stirred vessel. To further optimize the stirred tank geometries and maximize the integrated performance, XGB coupled NSGA‐ІІ were utilized to minimize the power consumption and mixing time. The optimal design parameters from the Pareto front were identified by two well‐known decision‐making methods (LINMAP and TOPSIS), which decreased power consumption and mixing time by 12.3% and 13.4% compared to the stirred tank with the baseline structure. This research further confirmed the accuracy and reliability of the machine learning‐based optimization method.
Non-invasive optical examination plays a crucial role in various aspects of dermatology, such as diagnosis, management and research. Multiphoton microscopy uses a unique submicron technology to ...stimulate autofluorescence (AF), allowing for the observation of cellular structure, assessment of redox status and quantification of collagen fibres. This advanced imaging technique offers dermatologists novel insights into the skin's structure, positioning it as a promising 'stethoscope' for future development in the field. This review provides an overview of multiphoton microscopy's principles, technology and application in studying normal skin, tumour and inflammatory diseases, as well as collagen-related and pigmentary diseases.
Aberrant expression of microRNAs (miRs) has been shown to play a critical role in the pathogenesis and progression of tumors. microRNA‐219‐5p (miR‐219‐5p) has been reported to be abnormally expressed ...in some types of human tumors. However, the mechanism between miR‐219‐5p and colorectal cancer (CRC) metastasis remains unclear. In the present study, miR‐219‐5p was found to be downregulated in CRC tissue compared with matched normal tissue. Through luciferase reporter assay, we demonstrated lymphoid enhancer‐binding factor 1 (LEF1) as a direct target of miR‐219‐5p. Overexpression of miR‐219‐5p could inhibit motility, migration and invasion of CRC cells, and inhibit epithelial‐mesenchymal transition (EMT). Furthermore, silencing LEF1 phenocopied this metastasis‐suppressive function. The recovery experiment showed that re‐expression of LEF1 rescued this suppressive effect on tumor metastasis and reversed the expression of EMT markers caused by miR‐219‐5p. Additionally, we demonstrated that miR‐219‐5p exerted this tumor‐suppressive function by blocking activation of the AKT and ERK pathways. Finally, a nude mice experiment showed that miR‐219‐5p reduced the lung metastasis ability of CRC cells. Taken together, our findings indicate that miR‐219‐5p inhibits metastasis and EMT of CRC by targeting LEF1 and suppressing the AKT and ERK pathways, which may provide a new antitumor strategy to delay CRC metastasis.
We determined miR‐219‐5p as a tumor suppressor that can block the expression of LEF1, thereby inhibiting EMT in CRC via inactivating the AKT and MAPK signaling pathways. This presents a promising strategy for treating CRC metastasis. Targets of miR‐219 other than LEF1 need to be identified to fully understand its activity. Our elucidation of the roles of miR‐219‐5p in EMT and metastasis of CRC will enable the discovery of specific therapeutic approaches for CRC patients.
The steady-state performance of modular multilevel converter (MMC) can be optimized by the following methods: circulating current injection, third-harmonic signal injection, and average capacitor ...voltage control. However, most of the papers, due to the deficiencies of their MMC models, are limited to the study of adopting just one method and only optimizing a single-aspect of the performance. Thus, this article proposes a general MMC model for the comprehensive study of the steady-state performance optimization. The general model is built based on an equilibrium equation between the internal quantities and the external quantities of the MMC. This general model is capable of analyzing the optimization where the optimizing methods are combined and used to improve the multiaspect performance of the MMC. In addition, more influence factors are taken into account; hence, the calculation error can be smaller than 1% and even the minor effect of each optimizing method can be reflected. The proposed model is compared with traditional models; and it is found that both dc and fundamental components in modulation signals will be affected by the injected circulating current, rather than the constant values in the traditional models. Finally, the proposed MMC model is verified by both simulation and experiment.
The capacitance of sub-module capacitor has a great impact on the cost, size, and operation of the modular multi-level converter (MMC). However, the capacitance selected by the existing methods does ...not always meet the requirement in practice. To find out the reasons for this improper selection, the existing selection methods are analyzed in this paper. Based on the analysis, a new capacitance-selection method is proposed. In the new method, the problems of the existing methods are solved, and the calculation of capacitor voltage is based on a proposed capacitor-voltage model whose calculation error can be smaller than 0.1%. Furthermore, the Secant Method is used in the capacitance selection to quickly calculate the required capacitance. The new capacitance-selection method can be applicable to the MMC not having a circular operating region. In addition, this paper found that the capacitor voltage and the capacitor-voltage ripple reach their maximum values when the power-factor angles of the MMC are -π/2 and π/2, respectively, and the dc component in the capacitor voltage changes according to the operating condition of the MMC. Finally, the proposed selection method and theoretical analyses are verified by both simulation and experiment.
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