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 systematically evaluated clinical efficacy of Kirschner's needle and elastic intramedullary nail fixation in treating proximal humeral fractures in children by Meta-analysis. METHODS: Literature on the treatment of proximal humeral fractures in children with Kirschler needles and elastic intramedullary nails published on Wanfang, VIP, CNKI and China biology medicine (CBM), PubMed, Embase, and Web of Science databases were searched from the establishment of databases to October, 2023. Literature extraction, management and data entry were performed by Endnote X9 and Excel 2019, and Meta-analysis was conducted by RevMan 5.3 software. The operation time, hospital stay, fracture healing time, shoulder joint extension range of motion, disabilities of arm, shoulder and hand(DASH) questionnaire score, Neer score or Constant-Murley score and complications were compared between two groups. RESULTS: A total of 7 literatures were included, 1 was prospective study, 6 were retrospective cohort study. There were 521 children, 264 children in Kirschner wire group and 257 children in elastic intramedullary nail fixation group. The results of Meta analysis showed operation time[WMD=-12.61, 95%CI(-24.89, -0.33), P=0.04], fracture healing time[WMD=-0.26, 95%CI(-0.49, -0.02), P=0.03], total complication rate [OR=6.83, 95%CI(3.33, 14.01), P<0.001], nail tract infection rate[OR=6.77, 95%CI(1.72, 26.69), P=0.006] and displacement fracture rate[OR=3.57, 95%CI(1.35, 9.44), P=0.01] between two groups had statistically differences(P>0.05), while there were no statistically significant difference in comparison of hospital stay, shoulder joint extension range of motion, DASH, Neer score, Constant-Murley score, and incidence of skin irritation between two groups (P>0.05). CONCLUSION Kirschner's needle internal fixation has a short operation time and simple operation, but it has a higher incidence of complications compared with elastic nail internal fixation technique. In terms of efficacy and safety, elastic intramedullary nail fixation is one of the options for the treatment of proximal humeral fractures in children.
Humans ; Fracture Fixation, Intramedullary/instrumentation* ; Child ; Shoulder Fractures/physiopathology* ; Bone Nails ; Bone Wires ; Male ; Needles ; Female