Objective: To investigate the expression of peroxiredoxin 4 (PRDX4) in oral squamous cell carcinoma (OSCC) and its effect on the proliferation, migration, and invasion of OSCC cells. Methods: The Cancer Genome Atlas(TCGA) database was used to analyze the expression of PRDX4 in OSCC. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western Blot (WB) were used to detect the mRNA and protein expression of PRDX4 in OSCC cell lines and normal oral mucosal epithelial cells. PRDX4 was knocked down in CAL-27 cells and divided into two groups: the si-PRDX4 group and si-NC group. SCC-9 cells overexpressing PRDX4 were divided into two groups: the PRDX4 overexpression group (transfected with pcDNA3.1-PRDX4 plasmid) and the vector group (the control group; transfected with pcDNA3.1-NC plasmid). A cell counting kit-8 (CCK-8) and plate colony formation assay were used to detect cell proliferation. Transwell assay and cell scratch test were used to detect cell invasion and migration ability. WB was used to detect the effects of knockdown or overexpression of PRDX4, p38MAPK agonist or inhibitor on the expression of p38MAPK-related signaling pathway proteins, and epithelial mesenchymal transition proteins in OSCC cells. Results: PRDX4 was highly expressed in OSCC tissues and cell lines. The results of qRT-PCR and WB showed that PRDX4 was highly expressed in OSCC cell lines compared with normal oral mucosal epithelial cells. The CCK-8 assay showed that the si-PRDX4 group had significantly lower OD values than the si-NC group at 24, 48, and 72 h (P<0.05). The PRDX4 overexpression group had a significantly higher OD value than the vector group at 24, 48, and 72 h (P<0.05). The plate colony formation assay showed that the si-PRDX4 group had a significantly lower number of colonies than the si-NC group (P<0.05). The number of colonies formed in the PRDX4 overexpression group was significantly higher than that in the vector group (P<0.05). The cell scratch test showed that the wound healing area of the si-PRDX4 group was less than that of the si-NC group (P<0.05). The scratch healing area of the PRDX4 overexpression group was significantly higher than that of the vector group (P<0.05). The Transwell invasion assay showed that the number of transmembrane cells in the si-PRDX4 group was lower than that in the si-NC group (P<0.05). The number of transmembrane cells in the PRDX4 overexpression group was significantly higher than that in the vector group (P<0.05). The WB results showed that knockdown and overexpression of PRDX4 could downregulate and upregulate the expression of the p38MAPK signaling pathway and epithelial-mesenchymal transition related proteins, respectively, and the addition of p38MAPK agonist and inhibitor could significantly reverse the expression of related proteins. Conclusion PRDX4 is highly expressed in OSCC. Knocking down the expression of PRDX4 in OSCC cells can downregulate the expression of p38 MAPK signal axis and EMT-related signal proteins, thereby inhibiting the proliferation, migration, invasion, and epithelial-mesenchymal transition of cells.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Objective To investigate the factors influencing the pregnancy outcomes during frozen-thawed embryo transfer(FET)cycles in patients with polycystic ovary syndrome(PCOS).Methods A retrospective analysis was conducted on patients'data from 882 FET cycles.According to the pregnancy outcome,the patients were divided into non-implantation group(Group A),abortion group(Group B1)and live birth group(Group B2).Clinical data and laboratory parameters were compared among the three groups,and ordered Logistic regression analysis was used to study the factors influencing pregnancy outcomes after FET.Patients were also divided into four groups(C1-C4)based on the number of high-quality embryos obtained(0-3,4-6,7-10,≥11),and their clinical data and laboratory parameters were compared.Results The clinical pregnancy rate,live birth rate,and miscar-riage rate in the 882 treatment cycles were 71.09%(627/882),61.68%(544/882),and 13.24%(83/627),respectively.Single-factor analysis showed significant differences in body mass index(BMI),infertility type,hu-man chorionic gonadotropin(hCG)day estradiol(E2)level,number of retrieved oocytes,and number of high-quality embryos among Groups A,B1,and B2(P<0.05).Further multiple Logistic regression analysis revealed that BMI(OR=1.046,95%CI:1.001-1.093,P=0.044)and a history of previous pregnancy(OR=1.417,95%CI:1.030-1.950,P=0.032)were independent risk factors for successful FET in PCOS patients,while an in-creased number of high-quality embryos was an independent protective factor for successful pregnancy.Based on the results of Group B2,compared to Group A,OR=0.920,95%CI:0.880-0.962,P=0.000;compared to Group B1,OR=0.923,95%CI:0.862-0.988,P=0.022.Compared with the other three groups(C1-C3),the total amount of gonadotropin(Gn)in the C4 group was the lowest and the number of oocytes obtained was the high-est(P<0.05).Multiple comparisons showed that Group C4 had lower BMI,follicle-stimulating hormone(FSH),very low-density lipoprotein(vLDL)levels,a higher luteinizing hormone and follicle-stimulating hormone(LH/FSH)ratio compared to Group C1(P<0.05).Group C4 had lower fasting insulin(FINS)and homeostasis model assessment of insulin resistance(HOMA-IR)levels compared to Group C3,and higher high-density lipoprotein-cholesterol(HDL-C)and apolipoprotein A1(Apo A1)levels compared to Groups C2 and C3(P<0.05).Con-clusion BMI,the history of previous pregnancy and the number of high-quality embryos were both independent factors for predicting pregnancy outcomes in PCOS patients undergoing FET cycles.Patients with a higher number of high-quality embryos have a higher clinical pregnancy rate during FET cycles.

The development of longitudinal cohorts has made the identification and surveillance of multiple biological markers and behavioral factors which influence disease course or health status become possible. However, traditional statistical methods typically use univariate longitudinal data for research, failing to fully exploit the information from multivariate longitudinal data. The group-based multi-trajectory model (GBMTM) emerged as a method to study the developmental trajectory of multivariate data in recent years. GBMTM has distinct advantages in analyzing multivariate longitudinal data by identifying potential subgroups of populations following similar trajectories by multiple indicators that influence the outcome of interest. In this study, we introduced the application of GBMTM by explaining the fundamental principles and using the data from a health management study in the elderly by using smart wearing equipment to investigate the relationship between multiple life-related variables and hypertension to promote the wider use of GBMTM in longitudinal cohort studies.

Objective To investigate the correlation between the expression of hsa_circ_0001785 in triple negative breast cancer(TNBC)and the efficacy of neoadjuvant chemotherapy(NAC).Methods A total of 129 patients with triple negative breast cancer who were admitted to our hospital from October 2021 to February 2023 were regarded as the study group,and 125 patients with benign breast lesions who underwent surgery in our hospital were served as the control group.The influencing factors of NAC efficacy in TNBC patients were analyzed by multivariate logistic regression model;receiver operating characteristic(ROC)curve was applied to analyze the predictive value of hsa_circ_0001785 level for NAC efficacy in triple negative breast cancer patients.Results Compared with the control group(1.05±0.16),the expression level of hsa_circ_0001785 in the study group(2.47±0.39)increased(P＜0.05);compared with the effective group(2.34±0.35),the expression level of hsa_circ_0001785 in the ineffective group(3.48±0.56)increased(P＜0.05);hsa_circ_0001785 was highly expressed in triple negative breast cancer patients with tumor diameter＞2 cm,lymph node metastasis and high tissue grade(P＜0.05);high expression of hsa_circ_0001785,tumor diameter＞2 cm,occurrence of lymph node metastasis and high histological grade were risk factors for NAC efficacy in triple negative breast cancer patients(P＜0.05).Hsa_circ_0001785 level has certain predictive value for NAC efficacy in TNBC patients.Conclusion Hsa_circ_0001785 is highly expressed in triple negative breast cancer,and the level of hsa_circ_0001785 has a certain predictive value for the efficacy of NAC in patients.

Background::Total human immunodeficiency virus (HIV) DNA and integrated HIV DNA are widely used markers of HIV persistence. Droplet digital polymerase chain reaction (ddPCR) can be used for absolute quantification without needing a standard curve. Here, we developed duplex ddPCR assays to detect and quantify total HIV DNA and integrated HIV DNA.Methods::The limit of detection, dynamic ranges, sensitivity, and reproducibility were evaluated by plasmid constructs containing both the HIV long terminal repeat (LTR) and human CD3 gene (for total HIV DNA) and ACH-2 cells (for integrated HIV DNA). Forty-two cases on stable suppressive antiretroviral therapy (ART) were assayed in total HIV DNA and integrated HIV DNA. Correlation coefficient analysis was performed on the data related to DNA copies and cluster of differentiation 4 positive (CD4 +) T-cell counts, CD8 + T-cell counts and CD4/CD8 T-cell ratio, respectively. The assay linear dynamic range and lower limit of detection (LLOD) were also assessed. Results::The assay could detect the presence of HIV-1 copies 100% at concentrations of 6.3 copies/reaction, and the estimated LLOD of the ddPCR assay was 4.4 HIV DNA copies/reaction (95% confidence intervals [CI]: 3.6-6.5 copies/reaction) with linearity over a 5-log 10-unit range in total HIV DNA assay. For the integrated HIV DNA assay, the LLOD was 8.0 copies/reaction (95% CI: 5.8-16.6 copies/reaction) with linearity over a 3-log 10-unit range. Total HIV DNA in CD4 + T cells was positively associated with integrated HIV DNA ( r = 0.76, P <0.0001). Meanwhile, both total HIV DNA and integrated HIV DNA in CD4 + T cells were inversely correlated with the ratio of CD4/CD8 but positively correlated with the CD8 + T-cell counts. Conclusions::This ddPCR assay can quantify total HIV DNA and integrated HIV DNA efficiently with robustness and sensitivity. It can be readily adapted for measuring HIV DNA with non-B clades, and it could be beneficial for testing in clinical trials.

Objective To analyze the prevalence and related risk factors of mild cognitive impairment (MCI) in the elderly in Zhoukanghang region of Pudong New Area,Shanghai. Methods Clinical data of 1537 elderly people (aged≥60 years old) in Zhoukanghang region of Pudong New Area,Shanghai from Aug. 2019 to Sep. 2022 were collected. Demographic data,cardiovascular risk factors (blood pressure,blood glucose,blood lipids,etc.),family history of dementia,cerebrovascular history,and hippocampal magnetic resonance imaging data were collected,and the MCI was tested by the simple mental state scale (MMSE) and Montreal cognitive assessment (MoCA). According to the clinical diagnostic criteria of MCI,the subjects were divided into MCI group and non-MCI group. The clinical data were compared between the 2 groups,and the independent risk factors of MCI were analyzed by multivariate logistic regression analysis. Results Among the 1537 subjects,226 cases (14.70％) were MCI patients and 1311 cases (85.30％) were non-MCI individuals. Among the 226 patients with MCI,138 had single domain amnestic MCI,33 had multiple domain amnestic MCI,11 had single domain non-amnestic MCI,and 7 had multiple domain non-amnestic MCI. The proportions of male,diabetes mellitus,hyperlipidemia,family history of dementia and cerebrovascular disease in the MCI group were significantly higher than those in the non-MCI group (all P<0.05),and the hippocampal atrophy was significantly higher than that in the non-MCI group (P<0.01). Multivariate logistic regression analysis showed that family history of dementia,cerebrovascular history and hippocampal atrophy were independent risk factors for MCI in the elderly (all P<0.05). Totally 214 patients with MCI were followed up to Feb. 2023,of which 20 cases (9.35％) were diagnosed as Alzheimer's disease and 4 cases (1.87％) as Lewy bodies dementia. Conclusion The prevalence of MCI in the elderly in Zhoukanghang region of Pudong New Area,Shanghai is 14.70％. Family history of dementia,cerebrovascular disease and hippocampal atrophy are independent factors for MCI in the elderly.

Objective:To establish a bacterial endotoxin test method for nafamostat mesilate for injection.Methods:The interference test of the bacterial endotoxin test method-kinetic chromogenic assay was carried out according to the Chinese Pharmacopoeia 2020 Volume Ⅳ general chapter 1143.Results:The interference effect of naphtholimus mesylate can be effectively eliminated by treating the test solution with an alkaline regulator for a certain period of time and diluting it.Conclusion:The bacteria endotoxin test-kinetic chromogenic assay for nafa-mostat mesilate for injection is applicable.