BackgroundEndometriosis (EM) is a common gynecological disorder that often leads to irregular menstruation and infertility. The pathogenesis of EM remains unclear and delays in diagnosis are common. Thus, it is urgent to explore potential biomarkers and underlying molecular mechanisms for EM diagnosis and therapies.MethodsThree EM-related datasets (GSE11691, GSE25628, and GSE86534) were downloaded from the Gene Expression Omnibus (GEO) which were integrated into a combined dataset after removing batch effect. Differentially expressed immune cell-related genes were obtained by CIBERSORT, WGCNA, and the identification of differentially expressed genes. Random forest model (RF), support vector machine model (SVM), and generalized linear model (GLM) were then constructed and the biomarkers for EM were determined. A nomogram evaluating the risk of disease was constructed and the validity was assessed by the calibration curve, DCA curve, and clinical impact curve. Single-gene Gene Set Enrichment Analysis (GSEA)was performed to explore the molecular mechanisms of biomarkers. The ceRNA regulatory network of biomarkers was created by Cytoscape and potential target drugs were obtained in the DGIdb database (Drug-Gene Interaction database).The expression levels of biomarkers from clinical samples was quantified by RT-qPCR.ResultsThe ratio of eight immune cells was significantly different between the eutopic and ectopic endometrium samples. A total of eight differentially expressed immune cell-related genes were investigated. The SVM model was a relatively suitable model for the prediction of EM and five genes (CXCL12, PDGFRL, AGTR1, PTGER3, and S1PR1) were selected from the model as biomarkers. The calibration curve, DCA curve, and clinical impact curve indicated that the nomogram based on the five biomarkers had a robust ability to predict disease. Single gene GSEA result suggested that all five biomarkers were involved in labyrinthine layer morphogenesis and transmembrane transport-related biological processes in EM. A ceRNA regulatory network containing 184 nodes and 251 edges was constructed. Seven drugs targeting CXCL12, 49 drugs targeting AGTR1, 16 drugs targeting PTGER3, and 21 drugs targeting S1PR1 were extracted as potential drugs for EM therapy. Finally, the expression of PDGFRL and S1PR1 in clinical samples was validated by RT-qPCR, which was consistent with the result of public database.ConclusionsIn summary, we identified five biomarkers (CXCL12, PDGFRL, AGTR1, PTGER3, and S1PR1) and constructed diagnostic model, furthermore predicted the potential therapeutic drugs for EM. Collectively, these findings provide new insights into EM diagnosis and treatment.

Struma ovarii is a rare variety of specialized monodermal mature ovarian teratoma, it is composed predominantly of thyroid tissue. Ascites is present in one third of patients. The combination of struma ovarii, marked ascites and elevated CA125 is a rare condition, which may mimic ovarian cancer. We described two cases presenting with pelvic mass, ascites and elevated serum CA125 levels, frozen section and final pathology turned out to be struma ovarii. Ascites disappeared and the level of CA125 returned to normal level after operation. One of the cases was associated with pleural effusion, leading to a condition called pseudo-Meigs’ syndrome. Then we reviewed the related literatures to explore the possible mechanism of ascites and pleural effusion, the reason of CA125 elevation and imaging manifestations of struma ovarii. In conclusion, struma ovarii should be considered in the differential diagnosis preoperatively, when presented with pelvic mass, ascites and an elevated CA125 level.

Background. The time interval rules and survival outcomes of individuals with synchronous and metachronous breast cancer (BC) and ovarian cancer (OC) were examined in this retrospective population-based investigation. Methods. The National Cancer Institute’s Surveillance, Epidemiology, and End Results database was used to create a cohort of people diagnosed with BC and OC between 1973 and 2015. Patients were separated into three groups: those with main BC followed by primary OC (group 1), those with synchronous primary breast and ovarian cancer (group 2), and those with OC prior to BC (group 3). The Kaplan-Meier technique was used to assess overall survival (OS) and cancer-specific survival (CSS). Results. A total of 4,975 patients were identified: 2,929 patients in group 1, 680 patients in group 2, and 1,366 patients in group 3. The average duration between these tumors was 60 months (range 0–499). Approximately 50% of second primary cancer cases occurred during the first 60 months of the first primary cancer diagnosis, and more than 70% occurred within the first 120 months. The median survival time for 4,975 individuals was 140 months. Group 2 had the smallest median OS (35 months), whereas group 3 had the longest (45 months) (239 months). Conclusions. The majority of second primary cancer cases occurred during the first 120 months following the diagnosis of the first original malignancy. Individuals who had primary OC prior to BC had better prognoses, whereas patients who had synchronous BC and OC had worse prognoses.

Endometriosis (EM) is a chronic gynecological disorder that causes infertility and chronic pelvic pain. The aim of the current study was to identify markers of efferocytosis with utility for EM diagnosis.RNA sequencing profile and single-cell sequencing (scRNA-seq) data were collated from the Gene Expression Omnibus (GEO) database and 46 efferocytosis-related genes (ERGs) from Genecards. Results of single-cell, differential expression and Weighted Gene Co-expression Network Analysis (WGCNA) were combined into a Venn diagram to identify 41 intersecting genes. LGALS2, EGR1 and CLINT1 were shown to be key EM markers by least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Area under the curve (AUC) values were 0.9 for LGALS2, 0.81 for EGR1 and 0.76 for CLINT1, indicating good diagnostic efficacy. Functional annotation analysis revealed the markers to be enriched in cell cycle, DNA repair, neuroactive ligand-receptor interactions, cell cycle, chromosomal segregation and other pathways. Drug-gene interaction network indicated that beta-D-glucose, pseudoephedrine and fostamatinib were potential therapeutic agents, exposing the possibility of personalized medicine for EM. RT-qPCR showed LGALS2 and EGR1 to be more highly expressed in ectopic than in eutopic endometrium. LGALS2 and EGR1 are introduced as potential novel targets for risk prediction, non-invasive diagnosis and health care personalization in EM. The potential for personalized medicine (PPPM) to treat EM patients is illuminated.

The increasing penetration of renewable energy resources in power system has contributed to the increasing demand for operation flexibility. To address the deficiency of flexibility in wind-photovoltaic-storage hybrid system with deepening penetration of intermittent and uncertain renewable energy resources, this paper proposes emerging flexible resources including wind, photovoltaic and energy storage providing flexible ramp capacity to improve flexibility. Considering the uncertainty of load and intermittent generation, the wind-photovoltaic-storage providing flexible ramp capacity are integrated into a two-stage stochastic dispatch model including 1h day-ahead unit commitment and 15min real-time economic dispatch. To test the efficiency of the proposed model, simulation are carried out on a modified IEEE 118-bus with 54 thermal units, the results indicate that wind-photovoltaic-storage providing flexible ramp capacity can effectively alleviate the deficiency of operation flexibility, and improve the overall economic benefit.