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.

Juvenile idiopathic arthritis (JIA) is the most common condition of chronic rheumatic disease in children. JIA is an autoimmune or autoinflammatory disease, with unclear mechanism and limited treatment efficacy. Recent studies have found a number of alterations in gut microbiota and its metabolites in children with JIA, which are related to the development and progression of JIA. This review focuses on the influence of the gut microbiota and its metabolites on immune function and the intestinal mucosal barrier and discuss the key role of the gut-joint axis in the pathogenesis of JIA and emerging treatment methods based on gut microbiota and its metabolites. This review could help elucidate the pathogenesis of JIA and identify the potential therapeutic targets for the prevention and treatment of JIA.
Humans ; Arthritis, Juvenile/physiopathology* ; Gastrointestinal Microbiome/physiology* ; Child ; Intestinal Mucosa

OBJECTIVE: To analyze the clinical efficacy of manual reduction combined with 3D printing small splint external fixation and synchronous manual reduction combined with traditional small splint external fixation in the treatment of humeral shaft. METHODS: Between January 2021 and December 2022, 40 patients with humeral shaft fractures were treated with 3D printing small splints and traditional small splints. They were divided into 3D group and traditional group according to different fixation methods. Among them, there were 15 males and 5 females in the 3D group, aged from 20 to 52 years old with an average of (36.3±15.6) years old. In the traditional group there were 17 males and 3 females, aged from16 to 51 years old with an average of (32.9±17.2) years old. The occurrence of complications, duration of fracture healing, rate of fracture healing, subjective evaluation scores for brace comfort at 1 week and 4 weeks, as well as the Constant-Murley shoulder function score and Mayo elbow function score at 8 weeks and 16 weeks were compared between the two groups. RESULTS: All patients were followed up for 16 weeks. The 3D group did not experience any complications, while there were two cases of complications in the traditional group. However, this difference was not found to be statistically significant (χ²=2.105, P=0.146). The fracture healing time of the 3D group (90.1±4.5) days was significantly shorter compared to that of the traditional group (93.3±3.8) days (P<0.05). The subjective evaluation scores for brace comfort in the 3D group (53.7±2.3) points and (62.8±1.1) points were significantly higher than those in the traditional group (45.6±2.4) points and (52.3±1.4) points at 1 and 4 weeks after reduction (P<0.05). After 8 weeks of reduction, the Constant-Murley shoulder function score in the 3D group was(68.1±5.3) points, which demonstrated a statistically significant improvement compared to the traditional group(54.3±4.9) points (P<0.05). However, at 16 weeks post-reduction, there were no significant differences observed between the two groups (P>0.05). The Mayo elbow function score of the 3D group (84.1±7.5) points was significantly superior to that of the traditional group (79.5±6.8) points at 8 weeks post-reduction (P<0.05). However, there was no statistically significant difference between the two groups at 16 weeks post-reduction (P>0.05). CONCLUSION For humeral shaft fractures with conservative treatment indications, manual reduction combined with 3D printed small splints is a good choice for treatment. The patient's comfort level is higher, which can not only reduce the occurrence of complications, but also improve the fracture healing rate and joint function to a certain extent, and improve the patient's quality of life.
Humans ; Female ; Male ; Adult ; Middle Aged ; Humeral Fractures/physiopathology* ; Printing, Three-Dimensional ; Splints ; Adolescent ; Young Adult ; Fracture Healing

Objective To investigate the clinical manifestations,molecular genetics and gonadal pathol-ogy characteristics of patients with disorders of sex development(DSD),and to summarize the clinical experi-ence of identifying rare diseases from common symptoms.Methods The clinical data of 416 patients with DSD diagnosed and treated in the multidisciplinary center of DSD of Guangzhou Women and Children's Medical Cen-ter from May 2018 to August 2023 were retrospectively analyzed,summarized and discussed.Results Accord-ing to chromosome karyotype,416 cases of DSD were classified into three types:92 cases(22.1％)of abnormal sex chromosome karyotype,285 cases(68.5％)of 46,XY karyotype and 39 cases(9.4％)of 46,XX karyotype.Among the 92 patients with abnormal sex chromosome karyotype,59 cases were raised as males,18 cases(30.5％)complained of short penis with hypospadias and cryptorchidism.The most common karyotype was 45,X/46,XY(58 cases,63.0％).Among the 285 patients with 46,XY karyotype,238 cases were raised as males,and 63 cases(26.5％)complained of short penis and hypospadias;47 cases were raised as females,and 13 ca-ses(27.7％)complained of inguinal mass.A total of 216 patients with 46,XY karyotype were subjected to whole exome gene detection,and 155 cases(71.8％)were found to have molecular pathogenesis with the clinical phe-notype.Among the 39 patients with 46,XX karyotype,19 cases were raised as males,and 8 cases(42.1％)com-plained of short penis and hypospadias.In the 18 cases of gonad biopsy,17 cases showed testicular tissue in go-nads.Whole exome sequencing was performed in 14 cases.NR5A1 gene heterozygous mutation,SRY gene muta-tion and SOX3 gene mutation were found in 2 cases,respectively(14.3％).Twenty cases were raised as females,and 14 cases(70.0％)complained of clitoral hypertrophy.Gonad biopsy was performed in 8 cases,with 7 cases of ovotestis(87.5％)and 1 case of NR5A1 gene heterozygous mutation(14.3％).Conclusions The etiologies of DSD are complex and diverse,and the clinical manifestations are various,which can be manifested as hypospa-dias,micropenis,cryptorchidism and other common symptoms of the urinary system.Different etiologies have dif-ferent treatment options.Therefore,chromosome karyotype,molecular genetic testing and gonadal pathology can be used to clarify the cause of disease,especially for rare diseases,improve the detection rate,reduce the rate of missed diagnosis,and ensure reasonable treatment,especially sex selection.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.