1.Effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis:machine learning and 16S rDNA analysis
Fucheng GU ; Meixin YANG ; Weixin WU ; Weijun CAI ; Yangyi QIN ; Mingyi SUN ; Jian SUN ; Qiudong GENG ; Nan LI
Chinese Journal of Tissue Engineering Research 2026;30(4):1058-1072
BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P<0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P<0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P<0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.
2.Effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis:machine learning and 16S rDNA analysis
Fucheng GU ; Meixin YANG ; Weixin WU ; Weijun CAI ; Yangyi QIN ; Mingyi SUN ; Jian SUN ; Qiudong GENG ; Nan LI
Chinese Journal of Tissue Engineering Research 2026;30(4):1058-1072
BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P<0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P<0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P<0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.
3.Long-term survival outcomes and prognostic factors following radical resection of pancreatic body and tail cancer:a retrospective analysis of 992 patients
Dong XU ; Yang WU ; Kai ZHANG ; Nan LYU ; Qianqian WANG ; Pengfei WU ; Jie YIN ; Baobao CAI ; Guodong SHI ; Jianzhen LIN ; Yazhou WANG ; Lingdi YIN ; Zipeng LU ; Min TU ; Jianmin CHEN ; Feng GUO ; Jishu WEI ; Junli WU ; Wentao GAO ; Cuncai DAI ; Yi MIAO ; Kuirong JIANG
Chinese Journal of Surgery 2026;64(1):46-54
Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.
4.Long-term survival outcomes and prognostic factors following radical resection of pancreatic body and tail cancer:a retrospective analysis of 992 patients
Dong XU ; Yang WU ; Kai ZHANG ; Nan LYU ; Qianqian WANG ; Pengfei WU ; Jie YIN ; Baobao CAI ; Guodong SHI ; Jianzhen LIN ; Yazhou WANG ; Lingdi YIN ; Zipeng LU ; Min TU ; Jianmin CHEN ; Feng GUO ; Jishu WEI ; Junli WU ; Wentao GAO ; Cuncai DAI ; Yi MIAO ; Kuirong JIANG
Chinese Journal of Surgery 2026;64(1):46-54
Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.
5.Waist Circumference Status and Distribution in Chinese Adults: China Nutrition and Health Surveillance (2015-2017).
Jing NAN ; Mu Lei CHEN ; Hong Tao YUAN ; Qiu Ye CAO ; Dong Mei YU ; Wei PIAO ; Fu Sheng LI ; Yu Xiang YANG ; Li Yun ZHAO ; Shu Ya CAI
Biomedical and Environmental Sciences 2025;38(6):757-762
6.Study on LncRNA01004 Promoting Epithelial-mesenchymal Transformation and Accelerating Malignant Progression of Breast Cancer Cells through Up-regulation of CPSF1 Protein Expression
Hongguo GUO ; Nan WU ; Wanling LU ; Jun LIU ; Cai CHENG
Journal of Modern Laboratory Medicine 2025;40(1):32-37,47
Objective To investigate the role of long non-coding RNA 01004 (LncRNA01004) in accelerating the malignant progression of breast cancer cells and its potential regulatory mechanism. Methods Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression level of LncRNA01004 in breast cancer tissues and cells. The Starbase online database predicted the binding of LncRNA01004 to CPSF1 and verified it through RNA binding protein immunoprecipitation(RIP) analysis. MCF-7 cells were transfected with LncRNA01004 interference sequence (sh-LncRNA01004) or overexpressed vector (LncRNA01004),or co-transfected with Cleavage and Polyadenylation Specific Factor 1 (CPSF1) interference sequence (sh-CPSF1). Cell viability,invasion and apoptosis were detected with CCK-8,Transwell and flow cytometry (FCM). The overexpression and silencing efficiency of LINC01004 and CPSF1 were detected by qPCR. Western blot (WB) analysis of CPSF1 protein,apoptosis-related protein[B cell lymphoma/leukemia-2(Bcl-2),Bcl-2 Associated X(Bax)]and Epithelial-Mesenchymal transition (EMT) related protein[Epitheia-cadherin(E-cadherin),Nerve-cadherin(N-cadherin),Vimentin,zinc-finger transcription factor(Snail)],and the activity of Cysteinyl aspartate-specific proteinase-3 (Caspase-3) was determined by enzyme-linked immunosorbent assay. Results LncRNA01004 was significantly up-regulated in breast cancer tissues (5.14±0.33) compared with paracancer tissues (1.02±0.03),with the statistically significant difference (t=-78.637,P<0.001);LncRNA01004 expression in breast cancer cells was significantly higher than that in normal breast epithelial cells,the difference between groups is statistically significant (F=142.248,P<0.001). Compared with the Control group,LncRNA01004 significantly inhibited the proliferation (42.15±2.11 vs 100.02±0.65) and invasion (18.65%±1.44% vs 41.36%±1.57%) of MCF-7 cells,induced apoptosis (16.58%±1.52% vs 5.24%±1.12%),increased the activity of Caspase-3 (2.93±0.711. vs 51±0.43) and the expression of Bax (2.74±0.39 vs 1.01±0.02) protein,and inhibited the expression of BcL-2 (0.32±0.07 vs 1.02±0.03) protein,with the statistically significant difference (t=3.075~19.332,all P<0.05). Significantly increased compared with Control group,the silent LncRNA01004 E-cadherin (3.06±0.37 vs 1.01±0.02) protein levels,lower N-cadherin (0.44±0.11 vs 1.00±0.01),Vimentin (0.39±0.13 vs 1.02±0.03) and Snail(0.30±0.08 vs 1.01±0.03) protein levels,with the statistically significant difference (t=9.989~17.164,all P<0.05).LncRNA01004 binds to CPSF1 and promotes CPSF1 protein expression.Silencing CPSF1 inhibited the proliferation and invasion of MCF-7 cells,induced cell apoptosis,and counteracted the effect of LncRNA01004 overexpression on MCF-7 cells. Conclusion LncRNA01004 may promote EMT through up-regulation of CPSF1,and then promote proliferation and invasion of breast cancer cells,inhibit cell apoptosis,and participate in the malignant progression of breast cancer.
7.Intrinsic specific TGF-β signaling in myofibers attenuates mouse acute skeletal myositis via LRP1
Qihui CAI ; Haiqiang LAN ; Bojun XIAN ; Nan WANG ; Xiaolei HUANG ; Xiaolu NIU ; Xinyu HU ; Chen LI ; Junyi XIE ; Zhaohong LIAO
Chinese Journal of Pathophysiology 2025;41(7):1365-1374
AIM:To investigate the effect of intrinsic specific transforming growth factor-β(TGF-β)signaling on regeneration and repair of myofibers in acute skeletal myositismice model induced by cardiotoxin(CTX).METHODS:One hundred and eighty-six wild C57BL/6 mice and one hundred and thirty-eight mice with conditional knockout of TGF-β receptor 2(TGF-βr2)in myofibers(SM TGF-βr2-/-mice)were selected.CTX injection to anterior tibial muscle(TA)in-duced acute myoinjury in mice.Some SM TGF-βr2-/-mice were given Smad signaling agonist SRI-011381(SRI)intramus-cular injection.All mice were mainly divided into the following groups:control group,SM TGF-βr2-/-group and SM TGF-βr2-/-+SRI group.Twenty-four mice were selected in each group.RT-qPCR and immunofluorescence staining were used to detect the relative mRNA level,protein expression of inflammatory cytokines and low-density lipoprotein receptor-related protein 1(LRP1),respectively,while the relative protein expression of myosin heavy chain 3(MHY3)and embryonic myosine heavy chain(eMHC)in damaged muscle was detected by Western blot and immunofluorescence staining.In vi-tro,after being extracted from neonatal mice,myogenic precursor cells(MPCs)were cultured in an pro-inflammatory mi-lieu and treated with SRI,recombinant mouse extracellular matrix protein 1(rmECM1)alone or in combination.Hereby,they were divided into the following seven groups:control-MPCs group,control-MPCs+LPS group,TGF-βr2-/--MPCs group,TGF-βr2-/--MPCs+LPS group,TGF-βr2-/--MPCs+LPS+SRI group,TGF-βr2-/--MPCs+LPS+rmECM1 group,and TGF-βr2-/--MPCs+LPS+SRI+rmECM1 group.Six mice were selected in each group.RT-qPCR and Western blot were used to detect the relative mRNA level,protein expression of major histocompatibility complex class I molecules(MHC-I/H-2Kb),major histocompatibility complex class II molecules(MHC-II/H2-Eα),Toll-like receptor 3(TLR3),and LRP1.And the relative protein expression of MoyD and myogenin in myotubes was detected by immunofluorescence staining.RE-SULTS:In vivo,compared with control group,SM TGF-βr2-/-group showed the significant upregulation of pro-inflamma-tory cytokines(P<0.05),and the opposite trend of anti-inflammatory cytokines,LRP1,MHY3,eMHC in the injured muscle(P<0.05),with delayed regeneration and repair of myofibers.In vitro,compared with control-MPCs+LPS group,LRP1,MoyD and myogenin significantly downregulated in TGF-βr2-/--MPCs+LPS group,but the downregulation trend was corrected after giving SRI treatment(P<0.05).In addition,compared with the TGF-βr2-/--MPCs+LPS group,the combi-nation of rmECM1 and SRI significantly upregulated the protein expression of MyoD and myogenin(P<0.05).CONCLU-SION:In a mouse model of acute skeletal myositis,intrinsic TGF-β signaling specifically in myofibers regulates local im-mune behavior.It promotes the expression of LRP1 in damaged muscle via Smad2/3 signaling,and LRP1 can then fully bind to ECM1,thereby facilitating muscle regeneration and repair,and improving the prognosis of acute skeletal myositis.
8.Prevalence and influencing factors of chronic somatic comorbidities in patients with schizophrenia in Shanghai communities
Wei-bo ZHANG ; Jiang-nan LI ; Yan-li LIU ; Yi-zhou JIANG ; Yi ZHU ; Na WANG ; Jun CAI
Fudan University Journal of Medical Sciences 2025;52(4):484-491,499
Objective To investigate the prevalence of chronic somatic comorbidities in schizophrenic patients in Shanghai communities,and to explore the factors influencing comorbidities.Methods Based on Shanghai community-based severe mental disorders cohort,5 422 patients with schizophrenia(SCZ)were included in the study.12 common chronic somatic diseases,defined by patients'self-report,were selected to analyze the prevalence of comorbidity,and Logistic regression model was used to analyze the factors influencing the number of somatic comorbidities.Results The total prevalence of somatic comorbidity was 37.0%in 5 422 patients with SCZ,with the highest prevalence of hypertension(22.6%)and diabetes mellitus(13.1%)among 12 somatic diseases selected.Older age was the main factor associated with chronic somatic comorbidities in community schizophrenic patients.The risk of 1-2 comorbidities in patients aged≥60 years was 3.34(95%CI:2.74-4.07)times higher than those aged<45 years,while the risk of≥3 comorbidities was 3.27(95%CI:2.11-5.09)times higher,correspondingly.Female gender,marriage,smoking,and longer duration of illness were also risk factors for comorbidity.Women after menopause had higher risk of comorbidity than perimenopausal women.Conclusion Cardiovascular and metabolic diseases were common somatic comorbidities among schizophrenic patients in Shanghai communities.Older age,female gender,marriage,smoking,and longer duration of illness were risk factors for increasing number of comorbidities.
9.Perineural invasion is an independent risk factor for poor prognosis of cervical cancer patients , and the occurrence of perineural invasion can be effectively predicted by the constructed multivariate mode.
Ran Tang ; Gege Jiang ; Xiangwen Meng ; Zheng Cai ; Li Jin ; Nan Xiang ; Min Zhang ; Xiaoyi Jia
Acta Universitatis Medicinalis Anhui 2025;60(12):2368-2377
Objective:
To predict and screen potential biomarkers of systemic lupus eythematosus(SLE) based on machine learning algorithms and structural biology, and to reveal their mechanisms of action and to provide new targets for disease diagnosis and treatment.
Methods:
Four machine learning algorithms, random forest(RF), eXtreme gradient boosting(XGBoost), support vector machine(SVM), least absolute shrinkage and selection operator(LASSO), were used to analyze the gene expression data of SLE patients in GEO(datasets: GSE121239 and GSE11907) to analyze the gene expression data of SLE patients and screen key markers. Peripheral blood single nucleated cells(PBMCs) from SLE patients were collected and RT-qPCR was used to detect differential gene expression levels. Subsequently, GSEA enrichment analysis was used to identify biomarker-related pathways. CIBERSORT immune infiltration analysis and protein interactions network were applied to calculate the sample immune cell infiltration abundance. Single-cell data were analyzed for gene expression specificity in immune cells. Interaction relationships in combination with AlphaFold3(AF3) were predicted.
Results:
Multiple algorithms were screened together to identify the unique marker gene HERC5 , and expression analysis of multiple datasets showed that HERC5 was highly expressed in SLE compared to the normal group (P < 0. 05) , and RT⁃qPCR verified the same trend (P = 0. 006 2) . Functional enrichment analysis identified the major pathway promoted by HERC5 in SLE as the interferon receptor signalling pathway (P < 0. 05) . Immune infiltration analysis showed that HERC5 was closely associated with immune cells (Neutrophils : r = 0. 39 , P < 0. 05 ; Memory B cells : r = 0. 33 , P < 0. 05 ; Activated dendritic cell : r = 0. 52 , P < 0. 05) . Most HERC5 ⁃related interacting proteins were associated with SLE ,and potential transcription factors of HERC5 and its related genes were also significantly associated with immune responses.
Conclusion
The HERC5 gene is an important biomarker for SLE , which upregulates the interferon pathway to promote SLE progression and provides a new target for SLE diagnosis and treatment.
10.Single-cell transcriptomics identifies PDGFRA+ progenitors orchestrating angiogenesis and periodontal tissue regeneration.
Jianing LIU ; Junxi HE ; Ziqi ZHANG ; Lu LIU ; Yuan CAO ; Xiaohui ZHANG ; Xinyue CAI ; Xinyan LUO ; Xiao LEI ; Nan ZHANG ; Hao WANG ; Ji CHEN ; Peisheng LIU ; Jiongyi TIAN ; Jiexi LIU ; Yuru GAO ; Haokun XU ; Chao MA ; Shengfeng BAI ; Yubohan ZHANG ; Yan JIN ; Chenxi ZHENG ; Bingdong SUI ; Fang JIN
International Journal of Oral Science 2025;17(1):56-56
Periodontal bone defects, primarily caused by periodontitis, are highly prevalent in clinical settings and manifest as bone fenestration, dehiscence, or attachment loss, presenting a significant challenge to oral health. In regenerative medicine, harnessing developmental principles for tissue repair offers promising therapeutic potential. Of particular interest is the condensation of progenitor cells, an essential event in organogenesis that has inspired clinically effective cell aggregation approaches in dental regeneration. However, the precise cellular coordination mechanisms during condensation and regeneration remain elusive. Here, taking the tooth as a model organ, we employed single-cell RNA sequencing to dissect the cellular composition and heterogeneity of human dental follicle and dental papilla, revealing a distinct Platelet-derived growth factor receptor alpha (PDGFRA) mesenchymal stem/stromal cell (MSC) population with remarkable odontogenic potential. Interestingly, a reciprocal paracrine interaction between PDGFRA+ dental follicle stem cells (DFSCs) and CD31+ Endomucin+ endothelial cells (ECs) was mediated by Vascular endothelial growth factor A (VEGFA) and Platelet-derived growth factor subunit BB (PDGFBB). This crosstalk not only maintains the functionality of PDGFRA+ DFSCs but also drives specialized angiogenesis. In vivo periodontal bone regeneration experiments further reveal that communication between PDGFRA+ DFSC aggregates and recipient ECs is essential for effective angiogenic-osteogenic coupling and rapid tissue repair. Collectively, our results unravel the importance of MSC-EC crosstalk mediated by the VEGFA and PDGFBB-PDGFRA reciprocal signaling in orchestrating angiogenesis and osteogenesis. These findings not only establish a framework for deciphering and promoting periodontal bone regeneration in potential clinical applications but also offer insights for future therapeutic strategies in dental or broader regenerative medicine.
Receptor, Platelet-Derived Growth Factor alpha/metabolism*
;
Humans
;
Neovascularization, Physiologic/physiology*
;
Dental Sac/cytology*
;
Single-Cell Analysis
;
Transcriptome
;
Mesenchymal Stem Cells/metabolism*
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Bone Regeneration
;
Animals
;
Dental Papilla/cytology*
;
Periodontium/physiology*
;
Stem Cells/metabolism*
;
Regeneration
;
Angiogenesis


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