OBJECTIVE: To investigate the clinical utility of novel of new hematological markers in the preoperative diagnosis of periprosthetic joint infection (PJI). METHODS: A retrospective analysis was conducted on a total of 149 patients who underwent revision of total hip arthroplasty (THA) or total knee arthroplasty (TKA) at a single center between January 2016 and June 2022, including 63 males and 86 females, aged from 47 to 93 years old with an average of (69.5±11.8) years old. Of them, 46 were diagnosed as PJI(PJI group), including 22 males and 24 females. The mean age was (71.3±12.5) years old. The body mass index (BMI) was (26.4±3.1) kg·m^-2. And 103 patients were diagnosed as aseptic prosthesis loosening (aseptic group), including 41 males and 62 females. The mean age was (68.7±11.4) years old. The BMI was (25.8±3.5) kg·m^-2. Preoperatively analyzed clinical parameters included C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), albumin, globulin, albumin-to-globulin ratio (AGR), plasma D-dimer, and plasma fibrinogen. The receiver operating characteristic curve (ROC), sensitivity, and specificity analysis were employed to compare the diagnostic value of each blood marker in preoperative PJI diagnosis. RESULTS: In the PJI group, the levels of CRP were 16.6 (7.6, 4.5) mg·L^-1, ESR was 17.0 (12.8, 35.5) mm·h^-1, plasma D-dimer was 1.0 (0.5, 3.1) μg·L^-1, and plasma fibrinogen was 4.2 (3.2, 3.1) mg·L^-1;all of which were higher compared to the aseptic group with CRP at 4.2 (2.6, 7.8) mg·L^-1, ESR at 12.0(8.0, 20.0 )mm·h^-l, D-dimer at 0.4(0.2, 0.7)μg·L^-1, and fibrinogen at 2.8(2.4, 3.3 ) g·L^-1(P<0.05). However, the albumin level of 35.3 (32.3, 37.5) g·L^-1 and the WBC ratio of 1.0(0.9, 1.1) in the PJI group were significantly lower compared to the aseptic group with levels of 39.8 (36.1, 41.8) g·L^-1 and 1.4 (1.3, 1.5), respectively (P<0.05). Only the area under the curve (AUC) of AGR and plasma fibrinogen were greater than 0.8. The optimal predictive cut-1off, AUC, sensitivity and specificity were 3.4 g·L-1, 0.820, 69.57% and 84.47% for plasma fibrinogen; 1.18, 0.813, 82.61% and 78.64% for AGR, respectively. CONCLUSION AGR and plasma fibrinogen are promising blood markers for improving the diagnosis of PJI.
Humans ; Female ; Fibrinogen/metabolism* ; Male ; Middle Aged ; Aged ; Prosthesis-Related Infections/blood* ; Retrospective Studies ; Biomarkers/blood* ; Aged, 80 and over ; Arthroplasty, Replacement, Knee/adverse effects* ; Arthroplasty, Replacement, Hip/adverse effects* ; Leukocyte Count

OBJECTIVE: To investigate the variability of bone metabolism levels among different populations and its association with knee osteoarthritis (KOA) pain. METHODS: A total of 50 people (control group) who participated in physical examination from January 2023 to June 2023 were selected, including 26 males and 24 females, wtih a mean aged of (52.14±9.04) years old ranging 41 to 65 years old. The other 50 patients with knee osteoarthritis(case group) who attended the outpatient clinic of the Orthopedics and Traumatology Department in the same time period, including 19 males and 31 females, with a mean age of (53.60±7.76) years old ranging 40 to 65 years. The two groups of Western Ontario and McMaster Universities Osteoarthritis Index(WOMAC) and bone metabolism markers, such as 25-hydroxy-cholecalciferol[25(OH)D], β-isomerized typeⅠcollagen C-telopeptide breakdown products (β-CTX), total typeⅠprocollagen N-terminal propeptide (t-PINP), osteocalcin (OC), parathormone (PTH) levels were compared. Pearson correlation analysis was used to compare the correlation between two groups of bone metabolism related markers and WOMAC. RESULTS: The WOMAC score of the case group (39.90±2.34) was higher than that of the control group (3.60±0.57), with significant difference (P<0.05). There was no significant difference between the two groups of 25 (OH)D, β-CTX and PTH (P>0.05). The t-PINP and OC of the case group were (62.90±52.40) and (19.88±10.15) ng·ml-1, respectively, and those of the control group were (38.86±10.82) and (14.90±3.62) ng·ml^-1, respectively;the t-PINP and OC of the case group were higher than those of the control group, with significant difference (P<0.05). Pearson correlation analysis showed that t-PINP was positively correlated with WOMAC pain score in the case group (r²=0.045, P<0.01). CONCLUSION Bone metabolism levels in the serum of patients with knee osteoarthritis are different from those of healthy people, and the difference between OC and t-PINP is the most obvious, and the concentration of t-PINP levels is positively correlated with pain symptoms in patients with KOA. However, the specific mechanism of correlation between the bone metabolism levels of patients with KOA and their pain symptoms needs to be further elucidated by basic experimental research as well as by enlarging the samples.
Humans ; Female ; Male ; Middle Aged ; Osteoarthritis, Knee/metabolism* ; Aged ; Adult ; Bone and Bones/metabolism* ; Pain/etiology* ; Biomarkers/metabolism*

Objective To explore the clinical and immunological significance of CCDC97 in hepatocellular carcinoma (HCC). Methods Clinical data and RNA sequencing results from HCC patients were retrieved from TCGA and ICGC databases. Bioinformatics analysis and in vitro experiments were performed to investigate the role of CCDC97 in HCC. Results The expression level of CCDC97 was elevated in HCC patients and HCC cells, closely associated with pathological features and prognosis. CCDC97 was identified as a novel prognostic biomarker. It is linked to the spliceosome pathway, which is significantly active in tumors and potentially promotes carcinogenesis. CCDC97 is also highly expressed in various immune cells and is associated with microenvironment. Furthermore, knocking down CCDC97 in vitro suppressed cell migration, invasion, and proliferation. Conclusion CCDC97 plays a critical role in HCC progression and the immune microenvironment, making it a potential target for prognosis and therapeutic intervention.
Humans ; Carcinoma, Hepatocellular/metabolism* ; Liver Neoplasms/metabolism* ; Tumor Microenvironment/genetics* ; Cell Movement/genetics* ; Cell Proliferation ; Prognosis ; Cell Line, Tumor ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/genetics* ; Male

Objective To investigate the clinical relevance and diagnostic or prognostic value of ST3β-galactoside α-2, 3-sialyltransferase 1 (ST3GAL1) in glioma and to confirm its role in promoting malignant phenotypes. Methods Using data from The Cancer Genome Atlas (TCGA) database, we analyzed the correlation between ST3GAL1 expression levels in glioma and clinical parameters to evaluate its diagnostic and prognostic value. The impact of ST3GAL1 on malignant phenotypes of glioma cells-including proliferation, cell cycle progression, apoptosis, and invasion was further validated through ST3GAL1 knockdown experiments. Results The expression level of ST3GAL1 was significantly higher in glioma tissues compared to healthy brain tissues and showed a strong correlation with clinical characteristics of glioma patients. Survival analysis and receiver operating characteristic (ROC) curve demonstrated that ST3GAL1 could serve as a potential diagnostic and prognostic biomarker for glioma. Knockdown of ST3GAL1 suppressed proliferation, invasion, and migration capabilities of glioma cell lines, and induced G1-phase cell cycle arrest. Conclusion ST3GAL1 promotes malignant phenotypes in glioma and plays a critical role in its malignant progression, suggesting its potential as a biomarker for glioma diagnosis and prognosis.
Humans ; Sialyltransferases/metabolism* ; Glioma/diagnosis* ; Cell Proliferation/genetics* ; Cell Line, Tumor ; Brain Neoplasms/enzymology* ; beta-Galactoside alpha-2,3-Sialyltransferase ; Disease Progression ; Prognosis ; Cell Movement/genetics* ; Apoptosis/genetics* ; Male ; Female ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/metabolism* ; Middle Aged

Objective Through integrative bioinformatics analysis of multi-source transcriptomic data, potential biomarkers to asthma epithelial cells were identified. The expression of these candidate target was subsequently validated in lung tissues and epithelial cells from asthma models. Methods The gene expression profile data of epithelial cells from three asthma patient cohorts and corresponding healthy controls were integrated from the Gene Expression Omnibus (GEO) database. Differential expression analysis and gene co-expression network analysis were performed to identify key genes and biological pathways associated with asthma. The key genes were validated in lung tissues and epithelial cells in asthma animal models. Results Differential gene expression analysis revealed 1121 upregulated and 1484 downregulated genes in epithelial cells from asthma patients compared with healthy controls. The biological pathway enrichment analysis revealed that the upregulated genes were mainly involved in glycosylation processes, whereas the downregulated genes were mainly associated with immune cell differentiation process. The gene co-expression network analysis revealed that module 9, enriched in glycosylation-related pathways, was significantly positively correlated with asthma, whereas module 17, associated with insulin and other signaling pathways, showed a significant negative correlation with asthma. We identified the genes of polypeptide N-acetylgalactosaminyltransferase 5 (GALNT5), pyrroline-5-carboxylate reductase 1 (PYCR1), and carcinoembryonic antigen-related cell adhesion molecule 5 (CEACAM5) as key genes within module 9, all of which were significantly upregulated in asthma. Finally, we validated that the expression levels of GALNT5, PYCR1, and CEACAM5 were significantly upregulated in epithelial cells from asthmatic lung tissue. Additionally, using a rat asthma model, we further confirmed that the protein levels of these three genes were significantly upregulated in lung tissues of the model group. Conclusion Through data integration and experimental validation, this study identified key genes and biological pathways closely associated with asthma pathogenesis. These findings provide a novel theoretical basis and potential targets for the diagnosis and treatment of asthma.
Asthma/metabolism* ; Humans ; Epithelial Cells/metabolism* ; Animals ; Biomarkers/metabolism* ; Gene Expression Profiling ; Transcriptome ; Gene Regulatory Networks ; Rats ; Computational Biology

Objective TXN is a thioredoxin (TXN) that participates in many redox reactions and plays a crucial role in various signaling pathways. However, the role of TXN in many cancers is still unclear. The objective of this study is to investigate and visualize the diagnostic, prognostic, and immunological implications of TXN expression across various cancer types. Methods The clinical data were downloaded from the cancer genome mapping project(TCGA) database to analyze the expression level of TXN in pan cancer, and the expression level was preliminarily verified by human protein mapping (HPA)(https://www.proteinatlas.org/)database. The ESTIMATE algorithm and CIBERSORT algorithm were applied to calculate the correlation between TXN expression and immune cell infiltration. The correlation between TXN and microsatellite instability (MSI) and tumor mutation burden (TMB) was analyzed using Spearman method. Gene Set Enrichment Analysis (GSEA) is used for gene biology functional analysis and sensitivity analysis of genes to pan cancer therapeutic drugs. Results TXN is highly expressed in most malignant tumors. The high expression of TXN is associated with overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression free interval (PFI) in various cancers. Moreover, TXN expression is associated with TMB, MSI, tumor microenvironment, chemotherapy sensitivity and so on. Conclusion TXN may become a potential prognostic biomarker in pan cancer, providing strong theoretical basis for future tumor diagnosis and prognosis judgment. The retinoic acid-inducible gene-I (RIG-I)-like receptor signaling pathway, Toll-like receptor (TLR) signaling pathway, and nucleotide binding oligomerization domain (NOD)-like receptor signaling pathway may be crucial pathways through which TXN influences tumor immunity.
Humans ; Prognosis ; Neoplasms/diagnosis* ; Thioredoxins/metabolism* ; Microsatellite Instability ; Gene Expression Regulation, Neoplastic ; Biomarkers, Tumor/genetics* ; Mutation ; Tumor Microenvironment

Objective To investigate the expression of blood basophil activation markers in patients with allergic rhinitis (AR) and the effects of allergens on their expression. Methods The blood samples were collected from the following four groups: healthy control (HC), AR patients with negative skin prick test (nAR), seasonal AR patients (sAR) and perennial AR patients (pAR). Flow cytometry was employed to analyze the expression of basophil activation markers Immunoglobulin E receptor I alpha(FcepsilonRIα), CD63 and CD203c in AR patients. Plasma levels of interleukin 4 (IL-4) and IL-8 were measured by liquid-phase chip technology, and their correlations with the percentages of activated basophils were further analyzed. An ovalbumin-induced AR mouse model was established, and the expression levels of FcepsilonRIα and CD63 on blood basophils were detected. Results The expression of FcepsilonRIα, CD203c and CD63 on basophils were increased in nAR, sAR and pAR patients. Allergens enhanced the mean florescence intensity expression of CD63 and CD203c on basophils of sAR and pAR patients. The plasma levels of IL-4 and IL-8 were elevated in nAR, sAR and pAR patients, showing moderate to high correlations with the expression levels of basophil activation markers. The FcepsilonRIαand CD63 expression on basophils of AR mice were increased. Conclusion Allergens may contribute to AR pathogenesis by upregulating the expression of FcepsilonRIα, CD63 and CD203c, as well as promoting the secretion of IL-4 and IL-8.
Basophils/metabolism* ; Humans ; Allergens/immunology* ; Animals ; Rhinitis, Allergic/blood* ; Female ; Male ; Adult ; Mice ; Biomarkers/blood* ; Tetraspanin 30/blood* ; Interleukin-4/blood* ; Interleukin-8/blood* ; Receptors, IgE/blood* ; Phosphoric Diester Hydrolases ; Young Adult ; Pyrophosphatases ; Middle Aged ; Mice, Inbred BALB C

Varicocele (VC) is a common cause of male infertility, yet there is a lack of molecular information for VC-associated male infertility. This study investigated alterations in the seminal plasma metabolomic and lipidomic profiles of infertile male VC patients. Twenty infertile males with VC and twenty-three age-matched healthy controls (HCs) were recruited from Peking Union Medical College Hospital (Beijing, China) between October 2019 and April 2021. Untargeted metabolite and lipid profiles from seminal plasma were analyzed using mass spectrometry. Four hundred and seventy-six metabolites and seventeen lipids were significantly different in infertile male VC patients compared to HCs. The top enriched pathways among these significantly different metabolites are protein digestion and absorption, aminoacyl-transfer RNA (tRNA) biosynthesis, and biosynthesis of amino acids. Different key lipid species, including triglyceride (TG), diacylglycerol (DG), ceramides (Cer), and phosphatidylserine (PS), varied between VC and HC groups. The distinct metabolites and lipids were moderately correlated. DL-3-phenyllactic acid is a potential diagnostic biomarker for VC-related male infertility (area under the curve [AUC] = 0.893), positively correlating with sperm count, concentration, and motility. Furthermore, DL-3-phenyllactic acid is the only metabolite shared by all four comparisons (VC vs HC, VC-induced oligoasthenospermia [OAS] vs VC-induced asthenospermia [AS], OAS vs HC, and AS vs HC). DL-3-phenyllactic acid significantly decreased in OAS than AS. Metabolite-targeting gene analysis revealed carbonic anhydrase 9 (CA9) might be the strongest candidate associated with the onset and severity of VC. The seminal plasma metabolite and lipid profiles of infertile males with VC differ significantly from those of HCs. DL-3-phenyllactic acid could be a promising biomarker.
Humans ; Male ; Varicocele/complications* ; Infertility, Male/etiology* ; Semen/metabolism* ; Lipidomics ; Adult ; Metabolomics ; Case-Control Studies ; Biomarkers/metabolism*

OBJECTIVES: To explore the lipidomic characteristics of children with bronchial asthma (hereafter referred to as asthma) and identify potential biomarkers for asthma. METHODS: A total of 26 asthmatic children were prospectively enrolled as the asthma group, and 20 healthy children served as the healthy control group. The asthma group was further divided into atopic (n=13) and non-atopic (n=13) subgroups based on IgE levels. Serum lipid metabolites were analyzed using liquid chromatography-mass spectrometry, followed by statistical analysis and data visualization. RESULTS: A total of 1 435 lipids were detected in the 46 children, primarily glycerophospholipids (625/1 435, 43.55%). Significant differences were observed in serum lipid profiles between the asthma and control groups. Twelve significantly differential lipids were identified, with receiver operating characteristic curve analysis showing that phosphatidylserine (PS)(18:0/20:4) and ceramide (Cer)(c16:0) exhibited the highest diagnostic value for asthma. The relative abundances of PS(18:0/20:4) and PS(18:0/22:6) were higher in the atopic subgroup than in the non-atopic subgroup (P<0.05) and positively correlated with total IgE levels in asthmatic children (r=0.675 and 0.740, respectively; P<0.05). CONCLUSIONS Asthmatic children exhibit significant lipid metabolic disturbances, primarily characterized by abnormal glycerophospholipid metabolism. Among these, PS(18:0/20:4) and Cer(c16:0) demonstrate specific alterations and may serve as potential diagnostic biomarkers for asthma. Furthermore, the positive correlation between PS(18:0/20:4) and PS(18:0/22:6) levels and serum total IgE suggests their possible involvement in immune regulation in asthma.
Humans ; Asthma/metabolism* ; Male ; Child ; Female ; Prospective Studies ; Mass Spectrometry/methods* ; Lipids/blood* ; Chromatography, Liquid/methods* ; Child, Preschool ; Immunoglobulin E/blood* ; Biomarkers/blood* ; Adolescent ; Liquid Chromatography-Mass Spectrometry

OBJECTIVES: To investigate the correlation between bone mineral density (BMD) and bone metabolic markers in preschool children and the influencing factors for BMD, and to provide a clinical basis for promoting bone health in children. METHODS: A retrospective analysis was performed for the data of 127 preschool children who underwent physical examination in the Department of Child Health Care of the First Affiliated Hospital of Xinjiang Medical University, from June to December 2024. BMD and bone metabolic markers were measured, and physical examination was performed. A multiple linear regression analysis was used to investigate the effect of general information on BMD Z-score in preschool children. Spearman's rank correlation test was used to investigate the correlation of BMD Z-score with 25-hydroxyvitamin D (25-OHD), serum bone Gla protein (BGP), and parathyroid hormone (PTH). RESULTS: BMD Z-score significantly differed by ethnicity, weight category, and height category (all P<0.05). The multiple linear regression analysis indicated that weight and height significantly influenced BMD Z-score (P<0.05), whereas sex, age, ethnicity, and parental education level did not (P>0.05). In children, BMD Z-score was positively correlated with 25-OHD level (r_s=0.260, P<0.001) and BGP level (r_s=0.075, P=0.025) and was negatively correlated with PTH level (r_s=-0.043, P=0.032). CONCLUSIONS Weight, height, 25-OHD, BGP, and PTH are influencing factors for BMD in preschool children. In clinical practice, combined measurement of bone metabolic markers may provide a scientific basis for early identification of children with abnormal BMD and prevention of osteoporosis and osteomalacia.
Humans ; Bone Density ; Child, Preschool ; Female ; Male ; Retrospective Studies ; Vitamin D/blood* ; Parathyroid Hormone/blood* ; Biomarkers/blood* ; Osteocalcin/blood* ; Bone and Bones/metabolism* ; Calcium-Binding Proteins/blood* ; Linear Models ; Matrix Gla Protein ; Extracellular Matrix Proteins/blood* ; Body Weight ; Infant