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Addressing heavy metal contamination in leafy vegetables is critically important due to its adverse effects on human health. In this study, we investigated the inhibitory effects of foliar spraying with four nanoparticles (CeO2, ZnO, SiO2, and S NPs) on arsenic (As) stress in pakchoi (Brassica rapa var. Chinensis). The findings reveal that foliar application of ZnO NPs at 1 ~ 2.5 mg plant-1 and CeO2 NPs at 5 mg plant-1 significantly reduces As in shoots by 40.9 ~ 47.3% and 39.4%, respectively. Moreover, 5 mg plant-1 CeO2 NPs increased plant height by 6.06% and chlorophyll a (Chla) content by 30.2% under As stress. Foliar spraying of CeO2 NPs at 0.2-5 mg plant-1 also significantly enhanced superoxide dismutase (SOD) activity in shoots by 9.4 ~ 13.9%, lowered H2O2 content by 42.4 ~ 53.25%, and increased root protein contents by 79 ~ 109.2%. CeO2 NPs regulate the As(III)/As(V) ratio, aiding in As efflux from roots and thereby reducing As toxicity to plants. In vitro digestion experiments reveal that the consumption of CeO2 NPs carries the lowest health risk of As. In addition, foliar spraying of ZnO NPs at 1 ~ 2.5 mg plant-1 can suppress plant As uptake by modulating enzyme activity, reducing leaf damage, and enhancing chlorophyll content. The study demonstrates that high CeO2 NP concentrations and suitable ZnO NP concentrations can alleviate As toxicity in pakchoi, consequently reducing human health risks.
Subject(s)
Arsenic , Arsenic/toxicity , Brassica rapa/drug effects , Nanostructures , Cerium , Plant Leaves/drug effects , ChlorophyllABSTRACT
Introduction: Over the past decades, immune dysregulation has been consistently demonstrated being common charactoristics of endometriosis (EM) and Inflammatory Bowel Disease (IBD) in numerous studies. However, the underlying pathological mechanisms remain unknown. In this study, bioinformatics techniques were used to screen large-scale gene expression data for plausible correlations at the molecular level in order to identify common pathogenic pathways between EM and IBD. Methods: Based on the EM transcriptomic datasets GSE7305 and GSE23339, as well as the IBD transcriptomic datasets GSE87466 and GSE126124, differential gene analysis was performed using the limma package in the R environment. Co-expressed differentially expressed genes were identified, and a protein-protein interaction (PPI) network for the differentially expressed genes was constructed using the 11.5 version of the STRING database. The MCODE tool in Cytoscape facilitated filtering out protein interaction subnetworks. Key genes in the PPI network were identified through two topological analysis algorithms (MCC and Degree) from the CytoHubba plugin. Upset was used for visualization of these key genes. The diagnostic value of gene expression levels for these key genes was assessed using the Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) The CIBERSORT algorithm determined the infiltration status of 22 immune cell subtypes, exploring differences between EM and IBD patients in both control and disease groups. Finally, different gene expression trends shared by EM and IBD were input into CMap to identify small molecule compounds with potential therapeutic effects. Results: 113 differentially expressed genes (DEGs) that were co-expressed in EM and IBD have been identified, comprising 28 down-regulated genes and 86 up-regulated genes. The co-expression differential gene of EM and IBD in the functional enrichment analyses focused on immune response activation, circulating immunoglobulin-mediated humoral immune response and humoral immune response. Five hub genes (SERPING1ãVCAM1ãCLUãC3ãCD55) were identified through the Protein-protein Interaction network and MCODE.High Area Under the Curve (AUC) values of Receiver Operating Characteristic (ROC) curves for 5hub genes indicate the predictive ability for disease occurrence.These hub genes could be used as potential biomarkers for the development of EM and IBD. Furthermore, the CMap database identified a total of 9 small molecule compounds (TTNPBãCAY-10577ãPD-0325901 etc.) targeting therapeutic genes for EM and IBD. Discussion: Our research revealed common pathogenic mechanisms between EM and IBD, particularly emphasizing immune regulation and cell signalling, indicating the significance of immune factors in the occurence and progression of both diseases. By elucidating shared mechanisms, our study provides novel avenues for the prevention and treatment of EM and IBD.
Subject(s)
Endometriosis , Inflammatory Bowel Diseases , Protein Interaction Maps , Transcriptome , Humans , Endometriosis/immunology , Endometriosis/genetics , Female , Inflammatory Bowel Diseases/genetics , Inflammatory Bowel Diseases/immunology , Computational Biology/methods , Gene Expression Profiling , Databases, Genetic , Gene Regulatory Networks , Biomarkers , Gene Expression RegulationABSTRACT
Background: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that affects multiple systems. Patients with SLE are prone to a variety of malignancies, especially neoplasms of the female reproductive tract. Synchronous tumors, considered to involve multiple sites, are rare in the female reproductive tract. There are hardly any reports of SLE with synchronous reproductive tract tumors. Case presentation: We report the occurrence of two to three reproductive tract tumors in two women with SLE. A 52-year-old woman was diagnosed with vulvar cancer and cervical cancer. Another woman, aged 67, was diagnosed with concurrent vulvar cancer, vaginal cancer, and cervical cancer and also presented with a suspected lung cancer. Conclusion: The presence of synchronous tumors of the reproductive tract in patients with SLE is uncommon and can be easily disregarded. It is crucial to highlight that SLE patients with multiple primary malignancies exhibit notable late-stage presentation at the time of diagnosis, inadequate disease-free survival, poor overall survival, rapid progression rates, and mortality. Consequently, greater awareness must be raised regarding synchronous reproductive tract tumors in patients with SLE. Regular comprehensive cancer screening and management should be implemented for individuals diagnosed with SLE.
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Growth hormone (GH) has a long-standing history of use as an adjunctive therapy in the treatment of poor ovarian response (POR), but the optimal dosage and timing remains unclear. The aim of this study was to evaluate and compare the efficacy of different GH supplementation protocols through a network meta-analysis (NMA) and determine the optimal treatment protocol. This study was reported based on the Preferred Reporting Items for Systematic Reviews for Network Meta-Analysis (PRISMA-NMA) statement. Databases including PubMed, Web of Science, Cochrane Library and Embase were searched until June 2023. A total of 524 records were retrieved in our search, and 23 clinical studies comprising 4889 cycles were involved. Seven different GH protocols were identified. Results showed that compared to the control group, daily administration of 4-8 IU of GH during the follicular phase of the stimulation cycle had the best comprehensive therapeutic effects on improving the number of retrieved oocytes, mature oocytes, endometrial thickness, and reducing gonadotropin requirements in POR patients undergoing assisted reproductive therapy, with a relatively brief treatment duration and a moderate total GH dose. Subgroup analysis demonstrated that this protocol could significantly improve the clinical pregnancy rate of POR patients in the randomized controlled trials (RCT) subgroup and the African subgroup. Therefore, its clinical application is suggested. Besides, the potential advantages of long-term GH supplementation protocol (using GH for at least 2 weeks before oocyte retrieval) has merit for further research. Rigorous and well-designed multi-arm RCTs are needed in the future to confirm the conclusions drawn from this study.
Subject(s)
Growth Hormone , Human Growth Hormone , Pregnancy , Female , Humans , Growth Hormone/therapeutic use , Network Meta-Analysis , Ovulation Induction/methods , Reproductive Techniques, Assisted , Pregnancy Rate , Human Growth Hormone/therapeutic use , Dietary Supplements , Fertilization in Vitro/methods , Gonadotropin-Releasing Hormone , Meta-Analysis as TopicABSTRACT
Background: Endometriosis (EM) is a common gynecological condition in women of reproductive age, with diverse causes and a not yet fully understood pathogenesis. Traditional diagnostics rely on single diagnostic biomarkers and does not integrate a variety of different biomarkers. This study introduces multiple machine learning techniques, enhancing the accuracy of predictive models. A novel diagnostic approach that combines various biomarkers provides a new clinical perspective for improving the diagnostic efficiency of endometriosis, holding significant potential for clinical application. Methods: In this study, GSE51981 was used as a test set, and 11 machine learning algorithms (Lasso, Stepglm, glmBoost, Support Vector Machine, Ridge, Enet, plsRglm, Random Forest, LDA, XGBoost, and NaiveBayes) were employed to construct 113 predictive models for endometriosis. The optimal model was determined based on the AUC values derived from various algorithms. These genes were then evaluated using nine machine learning algorithms (Random Forest, SVM, Gradient Boosting Machine, LASSO, XGB, NNET, Generalized Linear Model, KNN, and Decision Tree) to assess significance scores and identify diagnostic genes for each algorithm. The diagnostic value of these genes was further validated in external datasets from GSE7305, GSE11691, and GSE120103. Results: Analysis of the GSE51981 dataset revealed 62 DEGs. The Stepglm [Both] and plsRglm algorithms identified 30 genes with the most potential using the AUC evaluation. Subsequently, nine machine learning algorithms were applied to select diagnostic genes, leading to the identification of five key diagnostic genes using the LASSO algorithm. The ADAT1 gene exhibited the best single-gene predictive performance, with an AUC of 0.785. A combination of genes (FOS, EPHX1, DLGAP5, PCSK5, and ADAT1) achieves an AUC of 0.836 in the test dataset. Moreover, these genes consistently exhibited an AUC exceeding 0.78 in all validation datasets, demonstrating superior predictive performance. Furthermore, correlation analysis with immune infiltration strengthened their predictive value by demonstrating the close relationship of the diagnostic genes with immune infiltrating cells. Conclusion: A combination of biomarkers consisting of FOS, EPHX1, DLGAP5, PCSK5, and ADAT1 can serve as a diagnostic tool for endometriosis, enhancing diagnostic efficiency. The association of these genes with immune infiltrating cells reveals their potential role in the pathogenesis of endometriosis, providing new insights for early detection and treatment.
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PURPOSE: To explore the therapeutic effects of Bu-Shen-Ning-Xin decoction (BSNXD) on POI and the underlying mechanism. METHODS: VCD was used to induce the in vivo and in vitro POI model. HE staining was used to evaluate the pathological state of ovarian tissues. ELISA was used to detect the production of hormones in the serum and granule cells (GCs). An immunohistochemical assay was used to determine the expression of ATG7 and p-AKT in the ovarian tissues. The number of oocytes in POI rats was counted. The mitochondrial membrane potential (MMP) in oocytes and GCs was detected by flow cytometry. A Western blot assay was used to measure the expression of AKT, p-AKT, p-mTOR, mTOR, S6K, p-S6K, ULK1, p-ULK1, Beclin-1, Bcl-2, LC3-II, LC3-I, ATG7, and cleaved Caspase3. The numbers of autophagosomes were detected by transmission electron microscope and autophagic flux assay. The CCK-8 assay was used to detect the cell viability. RESULTS: Decreased primary follicles in the ovarian tissues, elevated concentration of FSH, and LH, suppressed concentration of E2 and AMH in the serum, reduced number of oocytes, and mitochondrial dysfunction in oocytes induced by VCD were significantly reversed by BSNXD. Activated autophagy state and inhibited PI3K/AKT/mTOR pathway stimulated by VCD in both ovarian tissues and GCs were dramatically reversed by BSNXD. The protective effect of BSNXD on VCD-treated GCs was abolished by LY294002, an inhibitor of the PI3K/AKT/mTOR pathway. CONCLUSION: Our data revealed that BSNXD alleviated POI by regulating autophagy of granule cells through activating PI3K/AKT/mTOR pathway.
Subject(s)
Menopause, Premature , Primary Ovarian Insufficiency , Animals , Apoptosis , Autophagy , Beclin-1/pharmacology , Drugs, Chinese Herbal , Female , Follicle Stimulating Hormone/therapeutic use , Humans , Phosphatidylinositol 3-Kinases/metabolism , Primary Ovarian Insufficiency/chemically induced , Proto-Oncogene Proteins c-akt/metabolism , Proto-Oncogene Proteins c-bcl-2/metabolism , Rats , Signal Transduction , TOR Serine-Threonine Kinases/metabolismABSTRACT
Extracellular beta-amyloid (Abeta) deposit is considered as one of the primary factors in inducing Alzheimer's disease (AD). However, the mechanism of Abeta deposition on the cell membrane and the induced cytotoxicity are still unclear. On the basis of the previous reports and results, we propose the "Recruiting Hypothesis" on the interaction between the plasma membrane and Abeta. Recently, many studies focused on cholesterol, which is considered as an important factor for AD. The most challenging issue in studying the cholesterol is non-ideal mixing behavior and non-dynamic analysis. In the present study, we investigated the cholesterol recruitment in the lipid monolayer during the interaction between beta-amyloid peptides Abeta (1-40) and lipid monolayers by dynamic fluorescent imaging analysis. Results from lipid monolayer trough studies showed that the rate of Abeta adsorption onto lipid monolayer is mainly due to the electrostatic effect which is sensitive to the lipid monolayer composition. From the fluorescence imaging analysis, the interaction of Abeta with lipid monolayer containing negative charge lipid and cholesterol brings out the recruiting behavior of the cholesterol and reduces the fluidity of lipid. The present study not only demonstrates the technical application for monitoring the dynamic molecular behaviors at the interface but also reveals the roles to distinguish lipid molecules on the Abeta-membrane interaction.