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 protective effects of remimazolam(Remi),a novel benzodiazepine sedative,on intestinal barrier function in septic mice.Methods A mouse model of sepsis was established using cecal ligation and puncture(CLP).A total of 96 SPF-grade adult male C57BL/6 mice were randomized into sham operation(Sham),sepsis(Sepsis),and sepsis with Remi intervention(Sepsis+Remi)groups.Survival rate and survival time were recorded within 72 h after modeling.Intestinal pathological alterations,barrier functional indicators,ZO-1 expression,and macrophage polarization status were observed and detected to evaluate the effects of Remi.Lipopolysaccharide(LPS)was used to treat RAW264.7 cells for 24 h to simulate in vitro sepsis model.The cells were divided into control(Control),LPS,and LPS+Remi groups.Immunofluorescence staining was performed to assess macrophage phenotype,mitochondrial morphology,and mitochondrial reactive oxygen species(MtROS),and Western blotting was applied to detect the protein expression of iNOS and CD206.Results Compared with the sepsis group,Remi intervention significantly improved the survival rate of septic mice from 12.50%to 68.75%and markedly prolonged survival duration(P<0.05).Histopathological analysis demonstrated partial restoration of intestinal villus architecture,accompanied with attenuated interstitial edema and reduced inflammatory cell infiltration after Remi intervention.Furthermore,the intervention group demonstrated significant improvement in functional indicators.Both in vivo and in vitro experiments demonstrated elevated iNOS and decreased CD206 expression in the septic mice and LPS-stimulated macrophages(P<0.05),which were partially reversed after Remi intervention.Furthermore,LPS-stimulated macrophages exhibited fragmented mitochondria and elevated MtROS level,whereas Remi intervention ameliorated these conditions(P<0.05).Conclusion Remi protects intestinal barrier function in septic mice by mitigating mitochondrial dynamics imbalance-induced oxidative damage and ameliorating inflammatory macrophage activation.

Objective:To explore the clinical characteristics of neonatal necrotizing enterocolitis（NEC）and analyze the risk factors for early-onset NEC.Methods:A total of 220 children with NEC admitted to the Department of Pediatrics，Tianjin Medical University General Hospital from January 1st，2018 to February 29th，2024 were retrospectively selected as the research objects. According to the time of onset，the early-onset group（ n=120）and the late-onset group（ n=100）were established，and the clinical characteristics of the two groups were compared. Another 150 cases of normal healthy newborns born in this hospital in the same period were selected as the control group，and the clinical data of the control group were collected. The clinical characteristics of the early-onset group and the control group were compared，and the risk factors of early-onset NEC were analyzed by multivariate Logistic regression. Results:Compared with the late-onset group，the early-onset group had fever［50.0%（60/120）vs. 40%（40/100）， χ2=7.333， P=0.007］，apnea［39.17%（47/120）vs. 28%（28/100）， χ2=7.568， P=0.006］，no rise in body temperature［56.67%（68/120）vs. 39%（39/100）， χ2=6.815， P=0.009］，abdominal distension［25%（30/120）vs. 40%（40/100）， χ2=13.200， P<0.001］，vomiting［30.83%（37/120）vs. 45%（45/100）， χ2=12.797， P<0.001］was significantly different（all P<0.05）；Multivariate Logistic regression analysis：weight<1 500 g（ OR=5.871，95% CI：3.153～9.673， P<0.001），gestational age<30 weeks（ OR=4.256，95% CI：2.641～7.896， P=0.007），hemodynamically significant patent ductus arteriosus（hs-PDA）（ OR=3.113，95% CI：1.865～5.133， P=0.033），severe anemia（ OR=3.057，95% CI：2.165～4.802， P=0.001），feeding intolerance（ OR=4.215，95% CI：1.579～10.802， P=0.005），amniotic fluid pollution（ OR=2.452，95% CI：1.579～3.111， P<0.001）were the independent risk factors for early-onset NEC（all P<0.05）. Conclusion:Weight<1 500 g，gestational age<30 weeks，hs-PDA，severe anemia，feeding intolerance，and amniotic fluid contamination are independent risk factors for early-onset NEC. In clinical practice，more attention should be paid to these factors for disease prevention，early identification，and timely intervention in newborns to reduce the occurrence of NEC.

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.

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.

The prevention and control requirements for HIV/AIDS vary significantly among different populations,posing substantial challenges to the formulation and implementation of intervention strategies.Dynamically assessing the heterogeneity and disease progression trajectories of various groups is crucial.Latent class growth model(LCGM)serves as a statistical approach that fits a longitudinal data into N subgroups of individual development trajectories,identifying and analyzing the progression paths of different subgroups,thereby offering a novel perspective for disease control strategies.LCGM has shown significant advantages in the application of HIV/AIDS prevention and control,especially in gaining a deeper understanding and analysis of epidemiological characteristics,risk behaviors,psychological research,heterogeneity in testing,and dynamic changes.Summarizing the advantages and limitations of applying LCGM can provide a reliable basis for precise prevention and control of HIV/AIDS.