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Background and Aims: Zhi Gan prescription (ZGP) has been clinically proven to exert a favorable therapeutic effect on nonalcoholic steatohepatitis (NASH). This study purpose to reveal the underlying molecular mechanisms of ZGP action in NASH.Methods: Systematic network pharmacology was used to identify bioactive components, potential targets, and the underlying mechanism of ZGP action in NASH. High fat (HF)-induced NASH model rats were used to assess the effect of ZGP against NASH, and to verify the possible molecular mechanisms as predicted by network pharmacology.Results: A total of 138 active components and 366 potential targets were acquired in ZGP. In addition, 823 targets of NASH were also screened. In vivo experiments showed that ZGP significantly improved the symptoms in HF-induced NASH rats. qRT-PCR and western blot analyses showed that ZGP could regulate the hub genes, PTEN, IL-6 and TNF in NASH model rats. In addition, ZGP suppressed mitochondrial autophagy through mitochondrial fusion and fission via the PINK/Parkin pathway.Conclusion: ZGP exerts its effects on NASH through mitochondrial autophagy. These findings provide novel insights into the mechanisms of ZGP in NASH.

Logic-in-memory architecture based on spintronic memories shows fascinating prospects in neural networks (NNs) for its high energy efficiency and good endurance. In this work, we leveraged two magnetic tunnel junctions (MTJs), which are driven by the interplay of field-free spin orbit torque (SOT) and spin transfer torque (STT) effects, to achieve a novel statefullogic-in-memory paradigm for ternary multiplication operations. Based on this paradigm, we further proposed a highly parallel array structure to serve for ternary neural networks (TNNs). Our results demonstrate the advantage of our design in power consumption compared with CPU, GPU and other state-of-the-art works.

Ammonium perchlorate (AP) occupies an important position in solid propellants. However, the increase of moisture content in AP will seriously affect its combustion performance and mechanical properties, resulting in the abnormal use of solid propellants, which may bring serious security risks. There are very few studies on the accurate measurement of AP moisture content, which makes this study of great value and significance. In this paper, the optical parameters of aqueous AP samples were measured by terahertz time domain spectroscopy. Combined with chemometrics, five quantitative prediction models were constructed. The results show that the absorption coefficient based genetic algorithm optimized extreme learning machine model has the best prediction results. This method can achieve accurate prediction for moisture content below 0.1%, and its absolute error is less than 0.001%, and the prediction error of the external verification model of different groups of samples is less than 0.06%. This study provides a reliable basis for rapid, accurate and non-destructive detection of the moisture content of ammonium perchlorate and similar substances.

Karst aquifers are difficult to model due to their complex conduit networks that are heterogeneous and anisotropic. Here, we present a heuristic algorithm for modeling karst networks by calculating minimum-effort paths based on our knowledge of karst evolution that is constrained by field observations. The methodology consists of a) using discrete fracture network models along with fracture-parameter estimates (e.g., frequency, extent, spacing, and apertures) to equivalent porous media properties (e.g., size of the representative elementary volume, hydraulic conductivity tensor), b) rendering the velocity field using the tensor field coupled with the 3D regional hydrogeology that includes likely recharge and discharge locations, and c) generating karst conduits using the Anisotropic Fast Marching Algorithm (AFMA). This approach a) avoids the need to model discrete fractures by replacing them with a tensor that incorporates small-scale, dense and interconnected fractures, b) assumes that conduits follow the minimum-effort path from sinkholes toward springs, and c) efficiently accounts for regional hydrogeology, anisotropy, and regional flow conditions within 3D conduit networks. The application of the proposed approach in Wulongdong Basin in Hubei Province, China is taken as the demonstrate example. Compared to other techniques, this methodology substantially improves computational efficiency and reduces computer memory, thus providing a useful tool for generating ensembles of possible karstic conduit networks to analyze flow and transport prediction uncertainty associated with a lack of knowledge about network geometry.

Tumor suppressor genes are frequently deleted or mutated in lung cancer. The RNA-binding motif protein 10 (RBM10) gene has the ability to suppress tumor activity, but the role of RBM10 during the development of lung cancer has yet to be elucidated. The current study investigated the expression levels of RBM10 in non-tumor and tumor tissues obtained from patients with adenocarcinoma using reverse transcription-polymerase chain reaction and western blot analysis, and identified a reduction in RBM10 expression in lung tumor tissue. To investigate the in vitro and in vivo function of RBM10, A549 human non-small cell lung cancer cells were transfected with the pcDNA-RBM10 vector. Flow cytometry was used to analyze the levels of apoptosis in the transfected cells. Western blot analysis was used to evaluate the expression of B-cell lymphoma 2 (Bcl-2), cleaved caspase-3, caspase-9 and poly (ADP-ribose) polymerase (PARP) proteins in A549 cells and tissues from the A549 xenograft Bagg Albino coat (BALB/c) nude mice model. RBM10 mRNA levels were significantly decreased in adenocarcinoma cells, but not in the non-tumor tissues. The A549 cells and tumor tissues exhibited significant growth inhibition following transfection with the pcDNA-RBM10 vector, which was determined using a cell proliferation assay. Flow cytometry analysis of cells stained with Annexin V/propidium iodide indicated that the overexpression of RBM10 induced apoptosis in A549 cells. The present study demonstrated that the expression levels of Bcl-2 protein were decreased and the expression levels of cleaved caspase-3, caspase-9 and PARP proteins were significantly increased in the A549 cells and cells from ex vivo tumor tissues that were injected with RBM10 vector-containing Salmonella enterica subspecies enterica serovar typhimurium. Notably, the current study identified that the accumulated and stable overexpression of RBM10 in the xenograft BALB/c nude mice model significantly inhibited the tumor growth rate. These results may provide novel insights into the use of RBM10 for lung cancer diagnosis and therapy.

This paper proposes an algorithm framework for real-time adjustment of low-power Bluetooth link parameters in a dynamic wireless environment. Firstly, by using the convex function relationship between the device connection parameters and the system power consumption, combined with statistics on the channel packet error rate, the connection parameters suitable for the current channel environment are dynamically selected.; Secondly, conduct real-time monitoring of data buffering between the host and the controller, initiate connection parameter update operations at the appropriate time, and assign different adjustment weights to maintain the connection operation and data transmission operation, making the adjustment of connection parameters more accurate. Through simulation and experiment, it is proved that the algorithm can reduce the system power consumption by up to 34% compared with the traditional connection parameter setting method. At the same time, the connection loss probability is only 20–62% under normal conditions. Low power consumption maintains the stability of the link. This algorithm improves the accuracy and real-time performance of the system parameters as the channel changes.

Background/Aims: Colorectal cancer (CRC) is the third most common type of cancer worldwide. Sprouty proteins are modulators of mitogeninduced signal transduction processes and therefore can influence the process of cancerogenesis. The encoded protein of Sprouty homolog 4 (SPRY4) is associated with various human cancers. However, its biological role and clinical significance in CRC development and progression are unknown. Methods: The aim of this study was to evaluate the expression and biological role of SPRY4 in colorectal cancer. qRT-PCR was performed to investigate the expression of SPRY4 in tumor tissues and corresponding non tumor colorectal tissues from 70 patients. The effect of SPRY4 on proliferation was evaluated by MTT and colony formation assays. CRC cells transfected with SPRY4 were injected into nude mice to study the effect of SPRY4 on tumorigenesis in vivo . Results: The lower expression of SPRY4 was remarkably correlated with deep tumor invasion and advanced TNM stage. Multivariate analyses revealed that SPRY4 expression served as an independent predictor for overall survival. Using 5-aza treatment, we also observed that SPRY4 expression can be affected by DNA methylation. Further experiments revealed that overexpressed SPRY4 significantly inhibited CRC cell proliferation both in vitro and in vivo . Conclusion: Our study demonstrated that SPRY4 is involved in the development and progression of colorectal cancer by regulating cell proliferation and shows that SPRY4 may be a potential diagnostic and prognostic target in patients with colorectal cancer.

This paper aims to identify the main influencing factors of the mental health of ant tribe young intellectuals (ATYIs) and ascertain those factors in favor of mental health. Based on the research findings in cognitive neuroscience, the author explored the main factors affecting the mental health of the ATYIs through a questionnaire survey on 904 youngsters graduated in the past five years. The questionnaire evaluates the overall mental health of the respondents with four psychological test scales, namely Positive PsyCap Questionnaire (PPQ), Symptom Checklist 90 (SCL-90), Adult Dispositional Hope Scale (ADHS), and Perceived Stress Scale (PSS). Through the analysis, it is concluded that family income, academic performance, and interpersonal relationship are the main influencing factors of the mental health among the ATYIs. The research finding provides a reference for mental health education in colleges and points the direction for the ATYIs to improve their mental health.