Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Objective To establish evaluation of ozagrel sodium by weighted TOPSIS method so as to provide a reference for improving the rational use of ozagrel sodium.Methods Based on the drug instructions,guidelines,relevant literatures and Delphi method,the evaluation criteria for the clinical rationality of ozagrel sodium were formulated.Attribute hierarchical model(AHM)was used to assign weights to the indicators,the weighted TOPSIS method was employed to analyze and evaluate the rationality of 108 patients that discharged from the Third People's Hospital of Henan Province from January 2021 to April 2022.Results The reponse rates of two rounds of expert advice questionnaires were 100％,the authoritative coefficients(Cr)were 0.85,0.83(＞0.70),and the experts fully affirmed the items of the standard.Among the 108 cases evaluated,37 cases(34.26％)were judged to be reasonable,52 cases(48.15％)were judged to be basically reasonable and 19 cases(17.59％)were judged to be unreasonable.The main unreasonable problems were manifested in indications,the timing of administration,drug course and monitoring of efficacy and laboratory parameters.Conclusion The method of DUE of ozagrel sodium based on weighted TOPSIS is more comprehensively and intuitively.The application of ozagrel sodium in the hospital is relatively standardized,but there are problems in the course of medication,indications,and timing of administration.So it is necessary to promote the rational use by strengthening the cooperation between pharmacists and physicians,and improving pharmaceutical intervention.

Objective To explore the application value of multidetector computed tomography(MDCT),computed tomography cholangiography(CTC)and computed tomography angiography(CTA)reconstruction technology in the diagnosis and classification and the evaluation of the efficacy of biliary drainage in advanced hilar cholangiocarcinoma(HCCA).Methods A total of 44 patients of inoperable advanced HCCA were collected.Conventional CT plain scan and enhanced multi-phase scan were performed before treat-ment.Minimum intensity projection(MinIP)combined with curve planar reformation(CPR)was used to perform CTC.CTA of the portal vein,hepatic artery and hepatic vein were performed by maximum intensity projection(MIP),volume rendering(VR)or CPR,respectively.CT was reexamined after biliary drainage treatment.The study included the comparison between reconstruction technology of CTC and CTA and conventional CT scanning technology,CTC in the classification and diagnosis of HCCA,CTA in the evaluation of vascular invasion,and the evaluation of the effect of jaundice drainage by biliary imaging before and after biliary drain-age treatment.Results All HCCA cases obtained clear location diagnosis,including 39 cases of Bismuth-Corlette type Ⅳ and 5 cases of type Ⅲ.There were 40 cases of hepatic vascular involvement,including 15 cases of bilateral portal vein invasion by tumor,12 cases of portal vein constriction,8 cases of portal vein tumor thrombosis,4 cases of bilateral hepatic arteries involvement,and 1 case of hepatic vein involvement.CTC and CTA could better display a full view of the bile duct and blood vessel than conventional CT scanning ima-ges,and provided more accurate analysis of tumor classification and degree of vascular invasion.Before treatment,CT showed severe dila-tion of bile duct in 21 cases and moderate dilation in 20 cases,severe dilation of the intrahepatic bile duct in the left lobe but mild dilation of the intrahepatic bile duct in the right lobe in 3 cases.After drainage treatment,the contraction rate of intrahepatic bile duct dilation was＜25％in 4 cases,25％to 49％in 13 cases,50％to 74％in 18 cases,and ≥75％in 9 cases.The bile duct contraction rate was positively correlated with the decrease in total bilirubin(TBIL).Conclusion MDCT,CTC and CT A reconstruction technology can well complete the diagnosis of advanced HCCA,Bismuth-Corlette typing,and vascular evaluation.Observing the contraction rate of the intrahepatic bile duct after biliary drainage treatment can evaluate the efficacy of jaundice drainage.

Objective To investigate the feasibility of granzyme B(GB)promoter-controlled ferritin heavy chain(FTH1)reporter gene expression for monitoring the activation status of chimeric antigen receptor T cells(CAR-T)by magnetic resonance imaging(MRI).Methods Cytotoxic T lymphocytes(CTLs)were screened by Ficoll density gradient centrifugation and flow sorting.The GB promoter and FTH1 gene were ligated together with disialoganglioside 2(GD2)CAR,and lentiviral vectors were transfected into CTLs to construct GD2-CAR-T/pGB-FTH1 cells.GD2-CAR-T/pCMV-FTH1,GD2-CAR-T,and T cells served as control cells.CytoTox96@non-radioactive cytotoxicity was used to detect the killing effect of each group of cells after co-culture with human neuroblastoma cells(SK-N-SH).ELISA was employed to detect the coincubation factor as well as the amount of GB secretion.Western blotting,Prussian blue staining and cellular MRI were applied to detect the expression of the FTH1 gene after co-culture.Results CTLs were successfully obtained,and then GD2-CAR-T/pGB-FTH1,GD2-CAR-T/pCMV-FTH1 and GD2-CAR-T cells were constructed.The killing effect,co-incubation factor and GB secretion of the above 3 groups of cells were significantly higher than those of the T cells,and the level of GB expression was highest at day 1,and then decreased in order at day 3 and day 7 after co-culturing with SK-N-SH cells.The relative expression of FTH1 and iron content of the GD2-CAR-T/pGB-FTH1 cells showed the same trend as GB expression,and the MRI signals were gradually increased.There were no significant differences in the relative expression of FTH1,iron content and MRI signals in the GD2-CAR-T/pCMV-FTH1 cells at all time points.No FTH1 expression or iron aggregation was observed in the GD2-CAR-T and T cells groups.Conclusion MRI based on the FTH1 reporter gene driven by the granzyme B promoter can reflect the GB expression level and tumor killing effect of CAR-T cells,which provides a potential real-time visual means to monitor the cell activation status for CAR-T therapy.

Background::Dual-energy computed tomography (DECT) is purported to accurately distinguish uric acid stones from non-uric acid stones. However, whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown. Therefore, we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them.Methods::This research included two steps. For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones, 178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled. For model construction, 93, 40, and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training, internal validation, and external validation sets, respectively. Radiomics features were extracted from non-contrast CT images, and the least absolute shrinkage and selection operator (LASSO) algorithm was used to develop a radiomics signature. Then, a radiomics model incorporating the radiomics signature and clinical predictors was constructed. The performance of the model (discrimination, calibration, and clinical usefulness) was evaluated.Results::When patients with ammonium urate stones were included in the analysis, the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased. Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT. A radiomics model incorporating the radiomics signature, urine pH value, and urine white blood cell count was constructed. The model achieved good calibration and discrimination {area under the receiver operating characteristic curve (AUC; 95% confidence interval [CI]), 0.944 (0.899–0.989)}, which was internally and externally validated with AUCs of 0.895 (95% CI, 0.796–0.995) and 0.870 (95% CI, 0.769–0.972), respectively. Decision curve analysis revealed the clinical usefulness of the model.Conclusions::DECT cannot accurately differentiate ammonium urate stones from uric acid stones. Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.

Objective To establish the drug use evaluation(DUE)criteria of recombinant human prourokinase(rhPro-UK),and to provide reference for the rational clinical application of rhPro-UK.Methods Based on the drug instructions of rhPro-UK,DUE standard rules were established by referring to relevant guidelines,expert consensus,authoritative literature and expert consultation.The medical records of hospitalized patients treated with rhPro-UK from January 2019 to May 2022 in Xilin Gol League Central Hospital were evaluated by retrospective investigation.The effectiveness of rhPro-UK was evaluated based on clinical outcome,and its safety was evaluated based on the incidence and severity of adverse reactions.Results A total of 230 cases were included,and 4 cases fully met the evaluation criteria(medication indication,medication process,medication results),accounting for 1.74％.There were 226 patients(98.26％)with irrational drug use,mainly manifested in two aspects of drug indication and drug process(administration mode and dosage).Treatment was effective in 221 patients,with an overall effective rate of 96.09％;139 patients experienced adverse reactions,with an incidence rate of 60.43％.Conclusion The clinical use of rhPro-UK in our hospital is irrational in the indication of medication and the process of medication,and the establishment of the DUE standard rules of rhPro-UK can provide a reference to standardize the clinical application of rhPro-UK and promote its rational use.