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This study aimed to investigate the inhibitory effect of Zuojin Pill (ZJP) on KYSE 150 cells and xenograft tumours of the digestive tract cancer – esophageal cancer (EC) and its underlying mechanism. Initially, in vivo research demonstrated that oral administration of ZJP effectively inhibited the growth of EC tumours, and in vitro studies revealed that ZJP suppressed the proliferation, migration, and invasion of cells. Then, network pharmacology prediction identified the core target, active ingredient, and involvement of the PI3K-Akt signalling pathway in ZJP treatment of EC. Cell studies validated that ZJP affected the expression of core targets, and its active ingredients inhibited the proliferation of cells. Additionally, ZJP was shown to induce cell apoptosis, decrease mitochondrial membrane potential, and increase the level of intracellular oxidative stress. Further experimental verifications suggested that the inhibitory effects of ZJP on EC might be attributed to the modulation of PI3 K/Akt signalling pathways.

Abstract Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject’s phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.

Natural products derived from herbal medicine are a fruitful source of lead compounds because of their structural diversity and potent bioactivities. However, despite the success of active compounds derived from herbal medicine in drug discovery, some approaches cannot effectively elucidate the overall effect and action mechanism due to their multi-component complexity. Fortunately, mass spectrometry-based metabolomics has been recognized as an effective strategy for revealing the effect and discovering active components, detailed molecular mechanisms, and multiple targets of natural products. Rapid identification of lead compounds and isolation of active components from natural products would facilitate new drug development. In this context, mass spectrometry-based metabolomics has established an integrated pharmacology framework for the discovery of bioactivity-correlated constituents, target identification, and the action mechanism of herbal medicine and natural products. High-throughput functional metabolomics techniques could be used to identify natural product structure, biological activity, efficacy mechanisms, and their mode of action on biological processes, assisting bioactive lead discovery, quality control, and accelerating discovery of novel drugs. These techniques are increasingly being developed in the era of big data and use scientific language to clarify the detailed action mechanism of herbal medicine. In this paper, the analytical characteristics and application fields of several commonly used mass spectrometers are introduced, and the application of mass spectrometry in the metabolomics of traditional Chinese medicines in recent years and its active components as well as mechanism of action are also discussed.

Metabolites are closely intertwined genotypes that can provide clear information about the final phenotype. The high-throughput analysis platform used to identify candidate metabolites and describe their contributions can help to quickly detect metabolic characteristics from large spectral data, which may lead to peak data preprocessing, statistical analysis and functional interpretation. Developing a comprehensive strategy for discovering and verifying bioactive metabolites can provide a large number of new functional biomarkers, and then more closely reveal their functional changes, which has relevant biological significance for disease diagnosis and prognosis treatment.

Background: The application of flipped classroom (FC) pedagogy has recently become increasingly popular in Chinese pharmacy education. However, its effectiveness in improving student learning has not yet been assessed. This study aimed to evaluate the effects of teaching with such pedagogical approach by examining studies that compare the FC approach with the traditional lecture-based learning (LBL) module through a systematic review and meta-analysis.Methods: Seven databases, including the PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Chinese Scientific Journals Database, Chinese Wanfang database, and China Biomedical Literature Database, were searched from the inception to 30 June 2021, to identify eligible articles of randomized controlled studies. The primary outcomes included the theoretical and experimental test scores, and the secondary outcomes were the results from questionnaires about the number of students who preferred the FC or endorsed its improving effects on their learning enthusiasm, self-learning ability, thinking skills, communication skills, and learning efficiency. The quantitative synthesis was conducted with Revman V.5.3 software following the Cochrane Reviewer’s Handbook guidelines and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement.Results: Eleven eligible studies published from 2017 to 2020 enrolling 1,200 students were included in this meta-analysis. The quantitative synthesis demonstrated that the FC module presented an overall more significant effectiveness over traditional LBL approach for Chinese pharmacy education in improving student academic performance as measured by theoretical test scores (SMD = 1.08, 95% CI: 0.60–1.56, p < 0.00001) and experimental test scores (MD = 6.62, 95% CI: 4.42–8.82, p < 0.00001). Further sub-group analysis revealed that the preferable effectiveness of FC was also evident in both theory-oriented (SMD = 0.77, 95% CI: 0.10–1.45, p < 0.00001) and experiments-oriented courses (MD = 6.52, 95% CI: 3.48–9.56, p < 0.00001) for both undergraduate (SMD = 0.84, 95% CI: 0.31–1.37, p < 0.00001) and 3-year junior-college students (MD = 8.17, 95% CI: 6.44–9.89, p < 0.00001). Additionally, analysis on the questionnaire outcomes revealed that more respondents preferred for FC and endorsed its improvement effects on developing students’ learning enthusiasm, self-learning ability, thinking skills, communication skills, and learning efficiency.Conclusion: Current evidence suggests that FC pedagogical approach can effectively improve student learning outcomes and is applicable to Chinese pharmacy education.

Cardiovascular complications combined with COVID-19 (SARS-CoV-2) lead to a poor prognosis in patients. The common pathogenesis of ischemic cardiomyopathy (ICM) and COVID-19 is still unclear. Here, we explored potential molecular mechanisms and biomarkers for ICM and COVID-19. Common differentially expressed genes (DEGs) of ICM (GSE5406) and COVID-19 (GSE164805) were identified using GEO2R. We performed enrichment and protein–protein interaction analyses and screened key genes. To confirm the diagnostic performance for these hub genes, we used external datasets (GSE116250 and GSE211979) and plotted ROC curves. Transcription factor and microRNA regulatory networks were constructed for the validated hub genes. Finally, drug prediction and molecular docking validation were performed using cMAP. We identified 81 common DEGs, many of which were enriched in terms of their relation to angiogenesis. Three DEGs were identified as key hub genes (HSP90AA1, HSPA9, and SRSF1) in the protein–protein interaction analysis. These hub genes had high diagnostic performance in the four datasets (AUC > 0.7). Mir-16-5p and KLF9 transcription factor co-regulated these hub genes. The drugs vindesine and ON-01910 showed good binding performance to the hub genes. We identified HSP90AA1, HSPA9, and SRSF1 as markers for the co-pathogenesis of ICM and COVID-19, and showed that co-pathogenesis of ICM and COVID-19 may be related to angiogenesis. Vindesine and ON-01910 were predicted as potential therapeutic agents. Our findings will contribute to a deeper understanding of the comorbidity of ICM with COVID-19.

Citri Reticulatae Pericarpium (CRP), also known as “chenpi”, is the most common qi-regulating drug in traditional Chinese medicine. It is often used to treat cough and indigestion, but in recent years, it has been found to have multi-faceted anti-cancer effects. This article reviews the pharmacology of CRP and the mechanism of the action of flavonoids, the key components of CRP, against cancers including breast cancer, lung cancer, prostate cancer, hepatic carcinoma, gastric cancer, colorectal cancer, esophageal cancer, cervical cancer, bladder cancer and other cancers with a high diagnosis rate. Finally, the specific roles of CRP in important phenotypes such as cell proliferation, apoptosis, autophagy and migration–invasion in cancer were analyzed, and the possible prospects and deficiencies of CRP as an anticancer agent were evaluated.

BackgroundChinese herbal footbaths are an external therapy of traditional Chinese medicine that has been widely used to treat dysmenorrhea. This review aims to systematically evaluate its efficacy and safety for the treatment of dysmenorrhea.MethodsDatabases of PubMed, EMBASE, Cochrane Library, CIHAHL, Web of Science, Chinese National Knowledge Infrastructure(CNKI), Chinese Scientific Journals Database (VIP), Wanfang Database, China Biomedical Literature Database(CBM), and Chinese Biomedical Literature Service System (SinoMed) will be searched from the inception to September 30, 2020. The eligible randomized controlled trials (RCTs) will be identified and included. The primary outcomes include pain intensity measured by validated scales of visual analog scale, numeric rating scale, and response rate of symptom reduction. The secondary outcomes are scores on validated pain questionnaires, quality of life measured by SF-36 or other validated scales, and adverse events. Study selection, data extraction, and assessment of bias risk will be conducted by two reviewers independently. RevMan software (V.5.3.5) will be utilized to perform data synthesis. Subgroup and sensitivity analysis will be performed when necessary. The strength of the evidence will be evaluated with the Grading of Recommendations Assessment, Development and Evaluation System.ResultsA high-quality synthesis of current evidence of Chinese herbal footbaths for patients with dysmenorrhea will be provided in this study.ConclusionThis systematic review will provide evidence of whether Chinese herbal footbaths are an effective and safe intervention for the treatment of dysmenorrhea.Systematic review registrationPROSPERO CRD42020188256.

Introduction To date, no specific antivirus drugs or vaccines have been available to prevent or treat the COVID-19 pandemic. Mesenchymal stem cell (MSC) therapy may be a promising therapeutic approach that reduces the high mortality in critical cases. This protocol is proposed for a systematic review and meta-analysis that aims to evaluate the efficacy and safety of MSC therapy on patients with COVID-19.Methods and analysis Ten databases including PubMed, EMBASE, Cochrane Library, CINAHL, Web of Science, Chinese National Knowledge Infrastructure (CNKI), Chinese Scientific Journals Database (VIP), Wanfang database, China Biomedical Literature Database (CBM) and Chinese Biomedical Literature Service System (SinoMed) will be searched from inception to 1 December 2020. All published randomised controlled trials, clinical controlled trials and case series that meet the prespecified eligibility criteria will be included. The primary outcomes include mortality, incidence and severity of adverse events, respiratory improvement, days from ventilator, duration of fever, progression rate from mild or moderate to severe, improvement of such serious symptoms as difficulty breathing or shortness of breath, chest pain or pressure, and loss of speech or movement, biomarkers of laboratory examination and changes in CT. The secondary outcomes include dexamethasone doses and quality of life. Two reviewers will independently perform study selection, data extraction and assessment of bias risk. Data synthesis will be conducted using RevMan software (V.5.3.5). If necessary, subgroup and sensitivity analysis will be performed. Grading of Recommendations Assessment, Development and Evaluation system will be used to assess the strength of evidence.Ethics and dissemination Ethical approval is not necessary since no individual patient or privacy data have been collected. The results of this review will be disseminated in a peer-reviewed journal or an academic conference presentation.PROSPERO registration number CRD42020190079.

Panoramic stitching technology provides an effective solution for expanding visual detection range of the autonomous underwater vehicle. However, absorption and scattering of light in the water seriously deteriorate the underwater imaging in terms of distance and quality, especially the scattering sharply decreases the underwater image contrast and results in serious blur. This reduces the number of matching feature points between the underwater images to be stitched, while fewer matched points generated make image registration and stitching difficult. To solve the problem, a joint framework is established, which firstly involves a convolutional neural network-like algorithm composed of a symmetric convolution and deconvolution framework for underwater image enhancement. Then, it proposes an improved convolutional neural network-random sample consensus method based on VGGNet-16 framework to generate more correct matching feature points for image registration. The fusion method based on Laplacian pyramid is applied to eliminate artificial stitching traces and correct the position of stitching seam. Experimental results indicate that the proposed framework can restore the color and detail information of underwater images and generate more effective and sufficient matching feature points for underwater sequence images stitching.

Autonomous underwater vehicles (AUVs) rely on a mechanically scanned imaging sonar that is fixedly mounted on AUVs for underwater target barrier-avoiding and tracking. When underwater targets cross or approach each other, AUVs sometimes fail to track, or follow the wrong target because of the incorrect association of the multi-target. Therefore, a tracking method adopting the cloud-like model data association algorithm is presented in order to track underwater multiple targets. The clustering cloud-like model (CCM) not only combines the fuzziness and randomness of the qualitative concept, but also achieves the conversion of the quantitative values. Additionally, the nearest neighbor algorithm is also involved in finding the cluster center paired to each target trajectory, and the hardware architecture of AUVs is proposed. A sea trial adopting a mechanically scanned imaging sonar fixedly mounted on an AUV is carried out in order to verify the effectiveness of the proposed algorithm. Experiment results demonstrate that compared with the joint probabilistic data association (JPDA) and near neighbor data association (NNDA) algorithms, the new algorithm has the characteristic of more accurate clustering.

Xuefu Zhuyu Tang (XFZY), a famous formula in traditional Chinese medicine, has been demonstrated to show good therapeutic effects on diseases caused by blood stasis syndrome. Two of its eleven herbs, Radix Platycodonis and Radix Cyathulae, have been considered as Shi ingredients in the hierarchy of traditional formula compatibility and proven possessing synergistic properties that strengthen the formula's potency of activating blood circulation and resolving blood stagnation. However, its mechanism is still not clearly elucidated. In our previous study, we observed their effects on paeoniflorin pharmacokinetics of XFZY in rats. In this study, we continued by detecting and comparing their effect on the tissue distribution of paeoniflorin after oral administration of XFZY and its three variants (XFZY without Radix Platycodonis or/and Radix Cyathulae) in blood-stasis mice via HPLC assay. The results indicated that combining usage of Radix Platycodonis and Radix Cyathula increased the distribution of paeoniflorin in the lung and kidney and introduced the paeoniflorin into the liver, spleen and heart. It might explain their synergistic properties that strengthen the formula's effect of invigorating blood and dissolving stasis and provide experimental evidence to understand the pharmacological effects of Shi herbs in the hierarchy of traditional formula compatibility. [ABSTRACT FROM AUTHOR]