The compound (E)-1-(4-(3-(5-chloro-6-oxo-3,6-dihydropyridin-1(2H)-yl)-3-oxo-propyl-1-ene-1-yl) phenyl)-3-(4-fluorophenyl) urea (C12), a novel derivative of piperlongumine previously synthesized by our research group, was investigated in this study to examine its effects on human non-small cell lung cancer cell line H1299 in vitro and elucidate its potential mechanism of action. The impact of C12 on the proliferation, migration, and invasion abilities of H1299 cells were assessed using methyl thiazolyl tetrazolium (MTT) assay, wound healing assay, cloning formation assay, and Transwell assay. Flow cytometry was employed to evaluate the influence of C12 on cell cycle progression, reactive oxygen species (ROS) production, mitochondrial membrane potential (MMP), and apoptosis induction in H1299 cells. Western blot analysis was conducted to investigate the expression levels of p21, Cyclin B1, CDK1, Bax, Bcl-2, JNK, p-JNK, Erk1/2, p-Erk1/2, p38 and p-p38 proteins for exploring the anti-tumor mechanism underlying C12's actions. The results demonstrated that C12 exerted inhibitory effects on the proliferation, migration, and invasion capacities of H1299 cells in a time-dependent and concentration-dependent manner. Moreover, C12 induced G2/M phase arrest in the cell cycle, reduced MMP levels, elevated ROS production, and triggered apoptotic processes. Flow cytometry analysis revealed that C12 downregulated Cyclin B1 and CDK1 protein expressions, resulting in G2/M phase arrest. C12 also upregulated Bax/Bcl-2 ratio, promoting apoptosis. Furthermore, C12 activated MAPK signaling pathway by enhancing phosphorylation levels of JNK, Erk1/2, and p38 proteins. In conclusion, C12 significantly suppressed proliferation, migration, and invasion capabilities while inducing cell cycle arrest and apoptosis in H1299 cells. These effects may be attributed to activation of the MAPK signaling pathway.

In this study, plasma, urine and fecal samples were collected from rats after intragastric administration of novel insulin sensitizer Zg02 (20 mg·kg^-1). The ultra-performance liquid chromatography-quadrupole-time-of-flight-tandem mass spectrometry (UPLC-Q-TOF/MS^E) techniques was used to obtain the molecular ion and mass spectrometry fragment ion information of the compound, and the metabolites were quickly analyzed by combining with UNIFI metabolite software. The results showed that a total of 12 metabolites were inferred in rats after a single gavage of Zg02 (20 mg·kg^-1), including 5, 7 and 11 metabolites in plasma, urine and feces (including cross-analysis), and the metabolic pathways were mainly glucuronidation and glucosylation. All animal protocols were approved by the Animal Ethics Committee of Guizhou Medical University (No. 2100856).

This research established a simple, rapid and sensitive ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) method to investigate the metabolic profiles of cajanonic acid A (CAA) in rats. After intragastric administration of CAA (30 mg·kg^-1) to rats, the biological samples were detected by UPLC-Q-TOF-MS/MS. Relevant data was collected and processed, the accurate mass and MS² spectra of the metabolites were compared with the parent compound. As a result, a total of 23 metabolites were detected, including 15 in urine, 11 in bile, 11 in feces, and 9 in plasma. The major metabolic pathways related to CAA included dehydrogenation, reduction, hydroxylation, methylation and glucuronide conjugation. This experiment was approved by Animal Ethics Committee of Guizhou Medical University (approval number: 1603137).

Breast cancer is the most common cancer in women and one of the deadliest cancers worldwide.According to the distribution of tumor tissue,breast cancer can be divided into invasive and non-invasive forms.The cancer cells in invasive breast cancer pass through the breast and through the immune system or systemic circulation to different parts of the body,forming metastatic breast cancer.Drug resistance and distant metastasis are the main causes of death from breast cancer.Research on breast cancer has attracted extensive attention from researchers.In vitro construction of tumor models by tissue engineering methods is a common tool for studying cancer mechanisms and anticancer drug screening.The tumor microenvironment consists of cancer cells and various types of stromal cells,including fibroblasts,endothelial cells,mesenchymal cells,and immune cells embedded in the extracellular matrix.The extracellular matrix contains fibrin proteins(such as types Ⅰ,Ⅱ,Ⅲ,Ⅳ,Ⅵ,and Ⅹcollagen and elastin)and glycoproteins(such as proteoglycan,laminin,and fibronectin),which are involved in cell signaling and binding of growth factors.The current traditional two-dimensional(2D)tumor models are limited by the growth environment and often cannot accurately reproduce the heterogeneity and complexity of tumor tissues in vivo.Therefore,in recent years,research on three-dimensional(3D)tumor models has gradually increased,especially 3D bioprinting models with high precision and repeatability.Compared with a 2D model,the 3D environment can better simulate the complex extracellular matrix components and structures in the tumor microenvironment.Three-dimensional models are often used as a bridge between 2D cellular level experiments and animal experiments.Acellular matrix,gelatin,sodium alginate,and other natural materials are widely used in the construction of tumor models because of their excellent biocompatibility and non-immune rejection.Here,we review various natural scaffold materials and construction methods involved in 3D tissue-engineered tumor models,as a reference for research in the field of breast cancer.

Nonalcoholic fatty liver disease (NAFLD) is a leading cause of liver disease worldwide. The estimated global incidence of NAFLD is 47 cases per 1,000 population and is higher among males than females. The estimated global prevalence of NAFLD among adults is 32% and is higher among males (40%) compared to females (26%). The global prevalence of NAFLD has increased over time, from 26% in studies from 2005 or earlier to 38% in studies from 2016 or beyond. The prevalence of NAFLD varies substantially by world region, contributed by differing rates of obesity, and genetic and socioeconomic factors. The prevalence of NAFLD exceeds 40% in the Americas and South-East Asia. The prevalence of NAFLD is projected to increase significantly in multiple world regions by 2030 if current trends are left unchecked. In this review, we discuss trends in the global incidence and prevalence of NAFLD and discuss future projections.

Abstract OBJECTIVE To explore the material basis and mechanism of Crataegi Fructus in improving metabolic hypertension(MH) by using network pharmacology and molecular docking technique.METHODS The components of Crataegi Fructus were collected by HERB, ETCM database and literature survey; screening all ingredients of Crataegi Fructus to improve MH targets through databases such as SwissTargetPrediction and GeneCards; build "active ingredient-target-disease" network of Crataegi Fructus with Cytoscape software; DAVID was used to analyze GO enrichment and KEGG pathway. The core components and core targets were verified by molecular docking with Autodock software. RESULTS The total of 89 active components were screened from Crataegi Fructus and acted on 84 targets. Among them, the core active components of Crataegi Fructus to improve MH were maslinic acid, fomefficinic acid B, linolenic acid, linoleic acid, methyl-n-nonylketone, apigenin, ursolic acid, etc. The core targets were CYP19A1, PPARA, ESR1, PTGS2, PPARG, NR3C1, MMP9, TNF, etc. The mechanism of action mainly involved multiple signaling pathways such as inflammation, glycolipid metabolism, and vascular endothelial function. Molecular docking showed that the core active ingredients of Crataegi Fructus had high affinity with core targets. CONCLUSION Crataegi Fructus may regulate multiple signaling pathways such as TNF, IL-17, AGE-RAGE, HIF-1, cGMP-PKG through multi-component regulation, thereby inhibiting inflammatory response, improving glucose and lipid metabolism abnormalities, and improving vascular endothelial function, so as to comprehensively exert the role of improving MH in various aspects.

Background/Aims: Depression and anxiety are associated with poorer outcomes in patients with hepatocellular carcinoma (HCC). However, the prevalence of depression and anxiety in HCC are unclear. We aimed to establish the prevalence of depression and anxiety in patients with HCC. Methods: MEDLINE and Embase were searched and original articles reporting prevalence of anxiety or depression in patients with HCC were included. A generalized linear mixed model with Clopper-Pearson intervals was used to obtain the pooled prevalence of depression and anxiety in patients with HCC. Risk factors were analyzed via a fractional-logistic regression model. Results: Seventeen articles involving 64,247 patients with HCC were included. The pooled prevalence of depression and anxiety in patients with HCC was 24.04% (95% confidence interval [CI], 13.99–38.11%) and 22.20% (95% CI, 10.07–42.09%) respectively. Subgroup analysis determined that the prevalence of depression was lowest in studies where depression was diagnosed via clinician-administered scales (16.07%;95% CI, 4.42–44.20%) and highest in self-reported scales (30.03%; 95% CI, 17.19–47.01%). Depression in patients with HCC was lowest in the Americas (16.44%; 95% CI, 6.37–36.27%) and highest in South-East Asia (66.67%; 95% CI, 56.68–75.35%). Alcohol consumption, cirrhosis, and college education significantly increased risk of depression in patients with HCC. Conclusions One in four patients with HCC have depression, while one in five have anxiety. Further studies are required to validate these findings, as seen from the wide CIs in certain subgroup analyses. Screening strategies for depression and anxiety should also be developed for patients with HCC.

SARS-CoV-2 is an emerging viral pathogen and a major global public health challenge since December of 2019, with limited effective treatments throughout the pandemic. As part of the innate immune response to viral infection, type I interferons (IFN-I) trigger a signaling cascade that culminates in the activation of hundreds of genes, known as interferon stimulated genes (ISGs), that collectively foster an antiviral state. We report here the identification of a group of type I interferon suppressed genes, including fatty acid synthase (FASN), which are involved in lipid metabolism. Overexpression of FASN or the addition of its downstream product, palmitate, increased viral infection while knockout or knockdown of FASN reduced infection. More importantly, pharmacological inhibitors of FASN effectively blocked infections with a broad range of viruses, including SARS-CoV-2 and its variants of concern. Thus, our studies not only suggest that downregulation of metabolic genes may present an antiviral strategy by type I interferon, but they also introduce the potential for FASN inhibitors to have a therapeutic application in combating emerging infectious diseases such as COVID-19.

Adult ; Cities ; Humans ; Middle Aged ; Proportional Hazards Models ; Quality of Life ; Risk Factors ; Silicosis

BACKGROUND: The current deep learning diagnosis of breast masses is mainly reflected by the diagnosis of benign and malignant lesions. In China, breast masses are divided into four categories according to the treatment method: inflammatory masses, adenosis, benign tumors, and malignant tumors. These categorizations are important for guiding clinical treatment. In this study, we aimed to develop a convolutional neural network (CNN) for classification of these four breast mass types using ultrasound (US) images. METHODS: Taking breast biopsy or pathological examinations as the reference standard, CNNs were used to establish models for the four-way classification of 3623 breast cancer patients from 13 centers. The patients were randomly divided into training and test groups (n = 1810 vs. n = 1813). Separate models were created for two-dimensional (2D) images only, 2D and color Doppler flow imaging (2D-CDFI), and 2D-CDFI and pulsed wave Doppler (2D-CDFI-PW) images. The performance of these three models was compared using sensitivity, specificity, area under receiver operating characteristic curve (AUC), positive (PPV) and negative predictive values (NPV), positive (LR+) and negative likelihood ratios (LR-), and the performance of the 2D model was further compared between masses of different sizes with above statistical indicators, between images from different hospitals with AUC, and with the performance of 37 radiologists. RESULTS: The accuracies of the 2D, 2D-CDFI, and 2D-CDFI-PW models on the test set were 87.9%, 89.2%, and 88.7%, respectively. The AUCs for classification of benign tumors, malignant tumors, inflammatory masses, and adenosis were 0.90, 0.91, 0.90, and 0.89, respectively (95% confidence intervals [CIs], 0.87-0.91, 0.89-0.92, 0.87-0.91, and 0.86-0.90). The 2D-CDFI model showed better accuracy (89.2%) on the test set than the 2D (87.9%) and 2D-CDFI-PW (88.7%) models. The 2D model showed accuracy of 81.7% on breast masses ≤1 cm and 82.3% on breast masses >1 cm; there was a significant difference between the two groups (P < 0.001). The accuracy of the CNN classifications for the test set (89.2%) was significantly higher than that of all the radiologists (30%). CONCLUSIONS: The CNN may have high accuracy for classification of US images of breast masses and perform significantly better than human radiologists. TRIAL REGISTRATION Chictr.org, ChiCTR1900021375; http://www.chictr.org.cn/showproj.aspx?proj=33139.
Area Under Curve ; Breast/diagnostic imaging* ; Breast Neoplasms/diagnostic imaging* ; China ; Deep Learning ; Humans ; ROC Curve ; Sensitivity and Specificity