BACKGROUND:Low-grade,chronic inflammation is thought to play a central role in the pathogenesis of osteoarthritis.However,the specific molecular mechanisms are still unclear.OBJECTIVE:To screen and explore the potential hub genes and immune cell infiltration in osteoarthritis.METHODS:We merged data from the GSE206848 on the GPL570 and the GSE55235 and GSE55457 on the GPL96 to form the row dataset.Outlier samples were removed using weighted gene co-expression network analysis,followed by the identification of differentially expressed genes,and subsequent functional enrichment analysis of differentially expressed genes.Further,a protein-protein interaction network of differentially expressed genes was constructed,and hub genes were identified using two different algorithms in Cytoscape.Additionally,the CIBERSORT algorithm was employed to assess differences in immune cell infiltration proportions between osteoarthritis samples and normal controls.Finally,the diagnostic efficacy of hub genes for osteoarthritis was validated using quantitative reverse transcription polymerase chain reaction experiments conducted on synovial tissue samples collected from patients with osteoarthritis,in conjunction with the GSE12021 dataset from the GPL96 sequencing platform as an independent dataset.RESULTS AND CONCLUSION:After eliminating 5 outlier samples,we identified a total of 340 differentially expressed genes,comprising 159 up-regulated genes and 181 down-regulated genes.Six hub genes were obtained by weighted gene co-expression network analysis and Cytoscape.CIBERSORT analysis revealed a difference in the proportion of multiple types of immune cell infiltration in osteoarthritic tissues compared with normal tissues.Moreover,the expression levels of the six hub genes exhibited strong correlation with the relative proportion of multiple immune cells in osteoarthritis.The results of RT-qPCR indicated that the relative expression levels of the six genes were down-regulated relative to normal tissues.However,there was no significant difference in the expression of NFKBIA and PTGS2(P>0.05).Simultaneously,receiver operator characteristic curves in both the original and external datasets demonstrated that the six hub genes exhibited strong diagnostic capabilities for osteoarthritis(area under the curve>0.8).To conclude,four hub genes,CDKN1A,MYC,C-X-C motif chemokine ligand 2,and vascular endothelial growth factor A,are finally identified and may serve as molecular targets for future treatment by mediating immune response and inflammatory processes.

Background and Aims:Obesity is often accompanied by symptoms of disordered eating.Although bariatric metabolic surgery can alleviate these symptoms,there are significant individual differences in postoperative outcomes,and effective predictive indicators are lacking.Liver and kidney function,along with lipid profiles,are closely related to metabolic status and may serve as useful markers for preoperative risk stratification and prognosis prediction.This study was conducted to explore the relationship between preoperative metabolic indicators and symptoms of disordered eating,thereby identifying postoperative recovery patterns among obese patients to support individualized management strategies.Methods:A total of 41 obese patients who underwent sleeve gastrectomy at Shanghai Sixth People's Hospital between September 2020 and June 2023 were enrolled,along with 36 healthy volunteers recruited during the same period.Participants completed the Eating Disorder Inventory-2(EDI-2)questionnaire,and serum samples were collected to assess liver function,kidney function,and lipid levels prior to surgery.The Mantel test was used to analyze correlations between metabolic indicators and EDI-2 scores.Latent profile analysis(LPA)was conducted using the indicators significantly correlated with EDI-2 scores to identify subgroups within the obese cohort.Linear mixed models were then applied to examine the trajectories of postoperative symptom changes across subgroups.Results:Levels of cystatin C,cholinesterase,gamma-glutamyl transferase,triglycerides,and apolipoprotein E were significantly higher in the obese group compared to the healthy group(all P＜0.05),and EDI-2 total score was also significantly elevated(P＜0.05);the prealbumin level in the healthy group was significantly higher than that in the obese group(P＜0.05).These six indicators were positively correlated with EDI-2 score(all r＞0.20,P＜0.05).Based on these markers,the LPA classified the obese group into two subgroups,with subgroup 2 exhibiting higher levels of most metabolic indicators than subgroup 1.During the 18-month postoperative follow-up,both subgroups showed reductions in EDI-2 score,but symptom improvement in subgroup 2 occurred later(month 6)compared to subgroup 1(month 4).Conclusion:Preoperative levels of cholinesterase,gamma-glutamyl transferase,prealbumin,triglycerides,and apolipoprotein E may serve as predictive indicators for improvement in disordered eating symptoms.Recovery patterns after bariatric surgery vary among obese patients with different metabolic profiles,highlighting the need for tailored intervention strategies.

Background and Aims:Obesity is often accompanied by symptoms of disordered eating.Although bariatric metabolic surgery can alleviate these symptoms,there are significant individual differences in postoperative outcomes,and effective predictive indicators are lacking.Liver and kidney function,along with lipid profiles,are closely related to metabolic status and may serve as useful markers for preoperative risk stratification and prognosis prediction.This study was conducted to explore the relationship between preoperative metabolic indicators and symptoms of disordered eating,thereby identifying postoperative recovery patterns among obese patients to support individualized management strategies.Methods:A total of 41 obese patients who underwent sleeve gastrectomy at Shanghai Sixth People's Hospital between September 2020 and June 2023 were enrolled,along with 36 healthy volunteers recruited during the same period.Participants completed the Eating Disorder Inventory-2(EDI-2)questionnaire,and serum samples were collected to assess liver function,kidney function,and lipid levels prior to surgery.The Mantel test was used to analyze correlations between metabolic indicators and EDI-2 scores.Latent profile analysis(LPA)was conducted using the indicators significantly correlated with EDI-2 scores to identify subgroups within the obese cohort.Linear mixed models were then applied to examine the trajectories of postoperative symptom changes across subgroups.Results:Levels of cystatin C,cholinesterase,gamma-glutamyl transferase,triglycerides,and apolipoprotein E were significantly higher in the obese group compared to the healthy group(all P＜0.05),and EDI-2 total score was also significantly elevated(P＜0.05);the prealbumin level in the healthy group was significantly higher than that in the obese group(P＜0.05).These six indicators were positively correlated with EDI-2 score(all r＞0.20,P＜0.05).Based on these markers,the LPA classified the obese group into two subgroups,with subgroup 2 exhibiting higher levels of most metabolic indicators than subgroup 1.During the 18-month postoperative follow-up,both subgroups showed reductions in EDI-2 score,but symptom improvement in subgroup 2 occurred later(month 6)compared to subgroup 1(month 4).Conclusion:Preoperative levels of cholinesterase,gamma-glutamyl transferase,prealbumin,triglycerides,and apolipoprotein E may serve as predictive indicators for improvement in disordered eating symptoms.Recovery patterns after bariatric surgery vary among obese patients with different metabolic profiles,highlighting the need for tailored intervention strategies.

BACKGROUND:Low-grade,chronic inflammation is thought to play a central role in the pathogenesis of osteoarthritis.However,the specific molecular mechanisms are still unclear.OBJECTIVE:To screen and explore the potential hub genes and immune cell infiltration in osteoarthritis.METHODS:We merged data from the GSE206848 on the GPL570 and the GSE55235 and GSE55457 on the GPL96 to form the row dataset.Outlier samples were removed using weighted gene co-expression network analysis,followed by the identification of differentially expressed genes,and subsequent functional enrichment analysis of differentially expressed genes.Further,a protein-protein interaction network of differentially expressed genes was constructed,and hub genes were identified using two different algorithms in Cytoscape.Additionally,the CIBERSORT algorithm was employed to assess differences in immune cell infiltration proportions between osteoarthritis samples and normal controls.Finally,the diagnostic efficacy of hub genes for osteoarthritis was validated using quantitative reverse transcription polymerase chain reaction experiments conducted on synovial tissue samples collected from patients with osteoarthritis,in conjunction with the GSE12021 dataset from the GPL96 sequencing platform as an independent dataset.RESULTS AND CONCLUSION:After eliminating 5 outlier samples,we identified a total of 340 differentially expressed genes,comprising 159 up-regulated genes and 181 down-regulated genes.Six hub genes were obtained by weighted gene co-expression network analysis and Cytoscape.CIBERSORT analysis revealed a difference in the proportion of multiple types of immune cell infiltration in osteoarthritic tissues compared with normal tissues.Moreover,the expression levels of the six hub genes exhibited strong correlation with the relative proportion of multiple immune cells in osteoarthritis.The results of RT-qPCR indicated that the relative expression levels of the six genes were down-regulated relative to normal tissues.However,there was no significant difference in the expression of NFKBIA and PTGS2(P>0.05).Simultaneously,receiver operator characteristic curves in both the original and external datasets demonstrated that the six hub genes exhibited strong diagnostic capabilities for osteoarthritis(area under the curve>0.8).To conclude,four hub genes,CDKN1A,MYC,C-X-C motif chemokine ligand 2,and vascular endothelial growth factor A,are finally identified and may serve as molecular targets for future treatment by mediating immune response and inflammatory processes.

Objective:To develop and validate a Self-care Ability Scale for Arteriovenous Fistula (AVF) in Maintenance Hemodialysis (MHD) patients.Methods:Guided by Orem's self-care theory, the initial item pool of the scale was developed through a literature review, semi-structured interviews, and group discussions. The initial scale was finalized after two rounds of expert consultation using the Delphi method. A convenience sampling method was used to recruit 418 MHD patients using AVF in January 2024 for item analysis, exploratory factor analysis and reliability testing. Another 293 MHD patients using AVF were recruited in March 2024 for confirmatory factor analysis.Results:The self-care ability scale for AVF in MHD patients included four dimensions: knowledge and skills of AVF self-care, willingness and attitude toward AVF self-care, recognition and prevention of AVF complications, and patient self-adjustment and adaptation, comprising 38 items. The content validity index at the scale level was 0.98. Exploratory factor analysis extracted four common factors with a cumulative variance contribution rate of 84.706%. Confirmatory factor analysis indicated good model fit, strong convergent validity, and ideal discriminant validity. The total Cronbach's α coefficient of the scale was 0.987; the split-half reliability coefficient was 0.902, and the test-retest reliability coefficient was 0.979.Conclusions:The Self-care Ability Scale for AVF in MHD patients demonstrates excellent reliability and validity, making it a suitable tool for assessing patients' ability to self-care for their AVF.

Infectious bone defects refer to bone defects accompanied by infection or those that occur during the treatment of bone infection and require surgical intervention. Due to the prolonged course of the disease and the destruction of the osteogenic microenvironment, the treatment is extremely difficult, and two major problems need to be solved: infection control and bone defect repair. In recent years, breakthrough progress has been made in this field. In mechanism research, the pathways by which pathogenic bacteria activate inflammatory responses to disrupt bone repair and the drug-resistance mechanism of methicillin-resistant Staphylococcus aureus (MRSA) have been clarified, providing molecular targets for targeted intervention. In terms of technology, interdisciplinary breakthroughs, such as the combination of targeted release of antibacterial drugs with microcarrier-controlled release systems, low-temperature additive manufacturing, and percutaneous sealing technology for external fixators, have solved key clinical problems. In material development, functional materials like cobalt-titanium-based implants and composite systems integrating antibiotics with bone growth factors have achieved synergy between anti-infection and bone repair. Clinical translation has yielded systematic solutions, and multicenter trials have confirmed that their efficacy is superior to traditional methods, breaking the dilemma that anti-infection and bone repair cannot be achieved simultaneously. For bone defect repair, bone repair materials include autologous bone, allogeneic bone, heterologous bone, and artificial bone. Autologous bone is regarded as the gold standard, and technologies to enhance biological activity have emerged in recent years. The Masquelet technique (membrane-induced technique) involves a two-stage surgery; the induced membrane exerts multiple effects, and its large-scale application in our center has achieved favorable outcomes. The Ilizarov technique is based on the Law of Tension-Stress, which has both advantages and limitations, and has been modified in multiple dimensions to form a mature technical system. However, the treatment of infectious bone defects still faces challenges such as unclear mechanisms of persistent infection and intracellular colonization of bacteria. In the future, interdisciplinary collaboration is required to establish an infection control-microenvironment remodeling-structural reconstruction system, promoting the development of personalized, minimally invasive, and intelligent treatment. Additionally, synergistic breakthroughs in clinical technology and biomaterials are needed to overcome this intractable orthopedic disease.

Methods: This retrospective study analyzed 32 consecutive IDS patients who underwent UEDD surgery. Clinical features, laboratory data (erythrocyte sedimentation rate and C-reactive protein), and treatment outcomes were analyzed. Results: Definite microorganisms were identified in 27 patients (84.3%), with 24 (88.9%) meeting cure criteria. The cure rate was significantly higher in the detected pathogen group compared to the undetected pathogen group (88.9% vs. 80%; χ²=19.36, p<0.0001). Metagenomic next generation sequencing (mNGS) provided faster diagnosis (41.72±6.81 hours) compared to tissue culture (95.74±35.47 hours, p<0.05). The predominant causative pathogen was Mycobacterium tuberculosis, followed by Staphylococcus aureus. Significant improvements were observed in Visual Analog Scale pain scores, from a mean of 7.9 preoperatively to 1.06 at 1 year postoperatively. The Oswestry Disability Index revealed a similar trend, showing significant improvement (p<0.05). Conclusions UEDD is a viable alternative to traditional open surgery for managing IDS in high-risk patients. UEDD offers a dual therapeutic-diagnostic advantage during the initial admission phase, enabling simultaneous debridement, neurological decompression, and targeted biopsy in a single intervention. Compared with traditional tissue culture, mNGS enables rapid microbiological diagnosis and extensive pathogen coverage.

Methods: This retrospective study analyzed 32 consecutive IDS patients who underwent UEDD surgery. Clinical features, laboratory data (erythrocyte sedimentation rate and C-reactive protein), and treatment outcomes were analyzed. Results: Definite microorganisms were identified in 27 patients (84.3%), with 24 (88.9%) meeting cure criteria. The cure rate was significantly higher in the detected pathogen group compared to the undetected pathogen group (88.9% vs. 80%; χ²=19.36, p<0.0001). Metagenomic next generation sequencing (mNGS) provided faster diagnosis (41.72±6.81 hours) compared to tissue culture (95.74±35.47 hours, p<0.05). The predominant causative pathogen was Mycobacterium tuberculosis, followed by Staphylococcus aureus. Significant improvements were observed in Visual Analog Scale pain scores, from a mean of 7.9 preoperatively to 1.06 at 1 year postoperatively. The Oswestry Disability Index revealed a similar trend, showing significant improvement (p<0.05). Conclusions UEDD is a viable alternative to traditional open surgery for managing IDS in high-risk patients. UEDD offers a dual therapeutic-diagnostic advantage during the initial admission phase, enabling simultaneous debridement, neurological decompression, and targeted biopsy in a single intervention. Compared with traditional tissue culture, mNGS enables rapid microbiological diagnosis and extensive pathogen coverage.

Methods: This retrospective study analyzed 32 consecutive IDS patients who underwent UEDD surgery. Clinical features, laboratory data (erythrocyte sedimentation rate and C-reactive protein), and treatment outcomes were analyzed. Results: Definite microorganisms were identified in 27 patients (84.3%), with 24 (88.9%) meeting cure criteria. The cure rate was significantly higher in the detected pathogen group compared to the undetected pathogen group (88.9% vs. 80%; χ²=19.36, p<0.0001). Metagenomic next generation sequencing (mNGS) provided faster diagnosis (41.72±6.81 hours) compared to tissue culture (95.74±35.47 hours, p<0.05). The predominant causative pathogen was Mycobacterium tuberculosis, followed by Staphylococcus aureus. Significant improvements were observed in Visual Analog Scale pain scores, from a mean of 7.9 preoperatively to 1.06 at 1 year postoperatively. The Oswestry Disability Index revealed a similar trend, showing significant improvement (p<0.05). Conclusions UEDD is a viable alternative to traditional open surgery for managing IDS in high-risk patients. UEDD offers a dual therapeutic-diagnostic advantage during the initial admission phase, enabling simultaneous debridement, neurological decompression, and targeted biopsy in a single intervention. Compared with traditional tissue culture, mNGS enables rapid microbiological diagnosis and extensive pathogen coverage.

Objective To establish an individualized nomogram model and evaluate its efficacy to provide a possible evaluation basis for the prognosis of lower third and abdominal part of oesophageal adenocarcinoma (EAC). Methods Lower third and abdominal part of EAC patients from 2010 to 2015 were chosen from the SEER Research Plus Database (17 Regs, 2022nov sub). The patients were randomly allocated to the training cohort and the internal validation cohort with a ratio of 7∶3 using bootstrap resampling. The Cox proportional hazards regression analysis was used to determine significant contributors to overall survival (OS) in EAC patients, which would be elected to construct the nomogram prediction model. C-index, calibration curve and receiver operating characteristic (ROC) curve were performed to evaluate its efficacy. Finally, the efficacy to evaluate the OS of EAC patients was compared between the nomogram prediction model and TNM staging system. Results In total, 3945 patients with lower third and abdominal part of EAC were enrolled, including 3475 males and 470 females with a median age of 65 (57-72) years. The 2761 patients were allocated to the training cohort and the remaining 1184 patients to the internal validation cohort. In the training and the internal validation cohorts, the C-index of the nomogram model was 0.705 and 0.713, respectively. Meanwhile, the calibration curve also suggested that the nomogram model had a strong capability of predicting 1-, 3-, and 5-year OS rates of EAC patients. The nomogram also had a higher efficacy than the TNM staging system in predicting 1-, 3-, and 5-year OS rates of EAC patients. Conclusion This nomogram prediction model has a high efficiency for predicting OS in the patients with lower third and abdominal part of EAC, which is higher than that of the current TNM staging system.