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Objective The aim of this study was to draw single-cell transcriptome profiles of high-grade serous ovarian cancer(HGSOC),borderline ovarian cancer(OC),and normal ovaries in order to identify biomarkers that can diagnose and predict the prognosis of OC.Methods The differentially expressed genes between HGSOC,borderline OC,and normal ovarian tissues were ana-lyzed using single-cell data sequenced(SRA database:PRJNA756768).The cell subsets associated with tumor progression were screened by functional enrichment,cell communication between different subsets was analyzed by Cellchat,and cell differentiation traj-ectories were explored by pseudotime analysis to finally determine the subsets most relevant to tumor progression.Combined with OC transcriptome data of OC from the Cancer Genome Atlas(TCGA)with patient prognosis,biomarkers for diagnosing and predicting sur-vival of OC patients were ultimately screened.Results After using t-distribution stochastic neighbor embedding(t-SNE)for di-mensionality reduction,nine cell subpopulations were obtained:endothelial cells,myeloid cells,fibroblasts,T cells,stromal cells,B cells,and 3 epithelial cell subpopulations(C1,C4,and C7).Further analysis revealed that copy number variation(CNV)in the C4 group had the highest score in HGSOC,higher than those of borderline OC and normal ovaries,and was negatively correlated with prognosis.DMKN was a key marker gene in this group.Transcriptome analysis of OC in the TCGA database showed a close correlation between DMKN and poor prognosis(P=0.026),and the diagnostic efficacy of DMKN for OC was significant(A UC=0.906).Con-clusion This study is based on single-cell sequencing data to screen for DMKN,which can effectively diagnose and predict the prognosis of OC.This study provides new ideas for the diagnosis and prognosis prediction of OC.
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Objective To analyze the characteristics of elderly frequent clinic attenders in a Shanghai community health service center.Methods The medical records of patients over 60 year who visited Shanghai Weifang Community Health Center clinic from October 2014 to October 2017 were obtained from the hospital outpatient management system.The persistent frequent attenders were defined as whose visiting times were among the top 10％ of attendance in the three consecutive years.The general condition and disease characteristics of persistent frequent attenders were analyzed and compared with those of non-frequent attenders and transient frequent attenders.Results There were total 19 240 patients paying 1 171 thousand clinic visits in the center for three years,the persistent frequent attenders accounted for 5.3％ (1 029) of total patients and had 21.4％ of total visits (251 thousand);those figures for transient frequent attenders were 10.2％(1 965) and 23.9％ (280 thousand);for non-frequent attenders were 84.5％ (16 246) and 54.7％(640 thousand),respectively.The average annual visits of three groups were (81.4 ± 27.5),(47.5 ± 21.4) and (13.1± 11.1) times,respectively.The reasons for encounter in persistent frequent attenders were:coronary heart disease (11.2％,48 thousand),cerebral insufficiency (3.5％,15 thousand),joint pain (2.5％,11 thousand),osteoporosis (2.9％,13 thousand) and sequelae of stroke (2.1％,9 thousand).Age above 70(OR=2.163,95％CI:1.872-2.498),age above 80 (OR=2.243,95％CI 1.895-2.655),female sex (OR=1.426,95％CI:1.249-1.627) and contracting general practitioners (OR=5.665,95％CI 4.217-7.611) were associated with persistent frequent attendance (P＜0.05).Conclusion Elderly frequent attenders occupy large outpatient resources of community health center,and age,gender and contracting status could affect their attending frequency.