Duchenne muscular dystrophy (DMD) is an X-linked recessive genetic disorder caused by mutations in the dystrophin gene, classified as a rare congenital muscular disease. Its clinical features include progressive skeletal muscle weakness, often involving respiratory and cardiac muscles, and frequently associated with spinal deformities. This paper reports the diagnosis, perioperative management, and follow-up of a case of DMD with multisystem involvement and severe scoliosis, aiming to provide a reference for clinicians in the diagnosis and treatment of such diseases.

Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

The disease-syndrome combination animal model in traditional Chinese medicine （TCM） andrology serves as an important bridge linking TCM theory with modern medical research， providing a key experimental platform for elucidating the 'syndrome-disease' correlation mechanism in male-specific diseases and for screening effective prescriptions. This article reviews recent progress in animal model research on common TCM andrological diseases， including prostatic diseases， sexual dysfunction， and male infertility， with a focus on analyzing the application， advantages， and disadvantages of various modeling strategies， such as immune induction， hormonal intervention， and multi-factor combination across different syndrome types. However， despite breakthroughs in model construction techniques， current research still faces several challenges， including insufficient standardization of syndrome differentiation and difficulties in quantifying TCM-specific indicators. Future studies need to optimize model evaluation systems by integrating modern technologies， in order to promote the standardization and internationalization of TCM andrology research.

Methods: Fifty patients who underwent UBE-TLIF and 50 patients who underwent W-TLIF, each with >2 years of follow-up, were retrospectively analyzed. Outcomes included operative parameters, time to postoperative mobilization, paravertebral muscle atrophy and fat infiltration rates, clinical scores (Visual Analog Scale [VAS], Oswestry Disability Index [ODI], Japanese Orthopaedic Association [JOA]), modified Macnab criteria, fusion rates, and complications. Results: Compared with W-TLIF, the UBE-TLIF group had significantly less intraoperative blood loss, shorter operative times, and lower postoperative drainage volumes (p <0.05). The UBE-TLIF group showed faster postoperative recovery and shorter hospital stays. At 6 months, 1 year, and 2 years, W-TLIF patients had higher multifidus and erector spinae atrophy, and greater paravertebral muscle fat infiltration (p <0.05). The UBE-TLIF group also had lower VAS and ODI scores at 1 year and 2 years (p <0.05) and fewer surgical complications (6% vs. 10%). Fusion rates (94% vs. 92%) and modified Macnab outcomes (88% vs. 86%) were comparable (p >0.05). Conclusions UBE-TLIF is associated with reduced intraoperative trauma, quicker recovery, and fewer complications. In the long-term, it better preserves paravertebral muscle integrity and provides superior pain and functional outcomes.

Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

Although epilepsy is first known as a disease of seizures and convulsions, most patients with epilepsy also suffer from seizure-associated behavioral abnormalities in motor functions, psychiatric status, and cognition. These neurobehavioral comorbidities may have greater impacts on the quality of life of people with epilepsy than the seizures themselves and can profoundly interfere with the treatment compliance. While repeated seizures often lead to behavioral comorbidities, certain types of comorbid conditions may potentially increase the risk for epileptic seizures, indicative of some common mechanisms that might underlie these two conditions. As such, emerging evidence supports that inflammation within the brain might represent a key component of such a shared mechanism, given that neuroinflammation can be induced by seizures and various behavioral stressors, and in turn may exacerbate both conditions. Among inflammatory pathways that arise after prolonged seizures, PGE₂ signaling via the EP2 receptor promotes cytokine induction, blood-brain barrier disruption, reactive gliosis, neuronal death, and eventually, contributes to behavioral dysfunctions. Pharmacological inhibition of EP2 by small-molecule drug-like antagonists affords broad therapeutic benefits including anti-inflammatory and neuroprotective effects in several rodent seizure models, leading to long-lasting alleviation of neurobehavioral comorbidities, particularly cognitive impairments. Targeting this key inflammatory prostaglandin receptor might provide an adjunctive strategy, along with the current anti-seizure medications, to mitigate cognitive dysfunctions associated with seizure disorders.

OBJECTIVE: To review the application progress of customized steel plates in osteotomy and orthopedic treatment for knee osteoarthritis (KOA), and provide reference for orthopedic surgeons and researchers. METHODS: Extensive review of the literature on customized steel plates for osteotomies and knee-preserving surgeries for KOA, 2015-2025, with an overview of the principles of customized steel plate design, clinical applications, and future directions, describing their advantages and shortcomings. RESULTS: Customized steel plates have demonstrated many advantages in osteotomy and orthopedic treatment of KOA, which not only enhance surgical outcomes and optimize mechanical properties, but also reduce the incidence of postoperative complications. However, high cost, long manufacturing period, and selection of patient indications are still important factors restricting their use. CONCLUSION Customized steel plates show promising potential in treating KOA. Not only do they reduce surgical duration and enhance postoperative healing outcomes, but they also effectively lower the incidence of postoperative complications, thereby improving patients' quality of life.
Humans ; Osteoarthritis, Knee/surgery* ; Osteotomy/methods* ; Bone Plates ; Postoperative Complications/epidemiology* ; Steel ; Quality of Life ; Treatment Outcome ; Knee Joint/surgery*

BACKGROUND: Premature menopause, defined as natural menopause before age 40, is associated with diminished ovarian reserve. Despite growing concerns regarding environmental pollutants, no large-scale population-based studies have systematically examined the association between urinary polycyclic aromatic hydrocarbon metabolites (UPAHMs) and premature menopause. METHODS: This cross-sectional study analyzed 2001-2020 NHANES data, including urinary levels of six PAH metabolites: 1-naphthol (1-NAP), 2-naphthol (2-NAP), 3-fluorene (3-FLU), 2-fluorene (2-FLU), 1-phenanthrene (1-PHE), and 1-pyrene (1-PYR). Premature menopause was self-reported as natural menopause occurring before age 40. Multivariable logistic regression assessed UPAHMs' association with premature menopause, with restricted cubic splines (RCS) evaluating nonlinear trends. Subgroup analyses examined demographic interactions. RESULTS: Among 2,565 participants, 662 reported premature menopause. Multivariable logistic regression showed significant associations between elevated urinary levels of 1-NAP (OR: 1.01, 95% CI: 1.00-1.02, P = 0.02), 2-NAP (OR: 1.01, 95% CI: 1.00-1.02, P = 0.02), and 3-FLU (OR: 1.03, 95% CI: 1.01-1.05, P = 0.01) and increased risk of premature menopause. RCS analysis revealed significant nonlinear relationships for 2-NAP, 3-FLU, 2-FLU, 1-PHE, and 1-PYR with premature menopause risk. White participants showed greater susceptibility to UPAHMs. CONCLUSION Elevated UPAHMs, particularly 1-NAP, 2-NAP, and 3-FLU, were linked to higher premature menopause risk, with nonlinear trends observed. White individuals demonstrated greater vulnerability, emphasizing the need for targeted interventions to reduce PAH exposure.
Humans ; Female ; Cross-Sectional Studies ; United States/epidemiology* ; Polycyclic Aromatic Hydrocarbons/urine* ; Adult ; Middle Aged ; Environmental Pollutants/urine* ; Nutrition Surveys ; Menopause, Premature/urine* ; Young Adult ; Environmental Exposure

OBJECTIVE: To analyze the differences in the effects of different mechanical stimuli on cells, cytokines, and proteins in synovial fluid of osteoarthritis joints, and to elucidate the indirect mechanism by which mechanical signals remodel the synovial fluid microenvironment through tissue cells. METHODS: Systematically integrate recent literature, focusing on the regulatory effects of different mechanical stimuli on the physicochemical properties of synovial fluid. Analyze the dynamic process by which mechanical stimuli regulate secretory and metabolic activities through tissue cells, thereby altering the physicochemical properties of cytokines and proteins. RESULTS: Appropriate mechanical stimuli activate mechanical signals in chondrocytes, macrophages, and synovial cells, thereby influencing cellular metabolic activities, including inhibiting the release of pro-inflammatory factors and promoting the secretion of anti-inflammatory factors, and regulating the expression of matrix and inflammation-related proteins such as cartilage oligomeric matrix protein, peptidoglycan recognition protein 4, and matrix metalloproteinases. CONCLUSION Mechanical stimuli act on tissue cells, indirectly reshaping the synovial fluid microenvironment through metabolic activities, thereby regulating the pathological process of osteoarthritis.
Humans ; Osteoarthritis/physiopathology* ; Synovial Fluid/chemistry* ; Chondrocytes/metabolism* ; Cytokines/metabolism* ; Macrophages/metabolism* ; Stress, Mechanical ; Cartilage Oligomeric Matrix Protein/metabolism* ; Matrix Metalloproteinases/metabolism* ; Synovial Membrane/cytology*

Objective:To explore the influencing factors for skin pruritus and to construct a nomogram prediction model in peritoneal dialysis (PD) patients.Methods:It was a retrospective cross-sectional investigation study. The PD patients who were regularly followed up between July, 2023 and April, 2024 in PD center of the First Affiliated Hospital of Sun Yat-sen University were enrolled in this study. The pruritus status was evaluated by the 14-Item UP-Dial Scale. The general demographic data and clinical data were collected. The patients were divided into pruritus group and non-pruritus group according to the presence or absence of skin itching. The differences of clinical data and laboratory results were compared between the two groups. Logistic regression was used to analyze the associated factors for pruritus in PD patients. The nomogram model was constructed by R software. The receiver operating characteristic (ROC) curve analysis and the Hosmer-Lemeshow goodness-of-fit test were used to evaluate the performance of the model, and its clinical effectiveness was evaluated using the calibration curve.Results:A total of 315 PD patients were enrolled in this study, with age of (48.0±12.9) years, including 134 females (42.5%). Among them, 161 patients (51.1%) experienced skin pruritus. Of whom, 111 patients (68.9%) had mild pruritus, 34 patients (21.1%) had moderate pruritus, 16 patients (9.9%) had severe pruritus. The age ( t=-2.266, P=0.024), proportion of diabetes mellitus ( χ2=3.910, P=0.048), Charson comorbidity index ( Z=-2.458, P=0.014), blood eosinophil percentage ( Z=-2.385, P=0.017), C-reactive protein ( Z=-2.590, P=0.010), serum phosphorus ( Z=-3.233, P=0.001) and β2 microglobulin ( Z=-2.756, P=0.006) level in the pruritus group were higher than those in the non-pruritus group, and the measured glomerular filtration rate (mGFR) level ( Z=-3.708, P<0.001) of patients in the pruritus group was lower than that in the non-pruritus group. There were 262 patients in the training set and 53 patients in the validation set. The multivariate logistic regression analysis in the training set revealed that advanced age ( OR=1.032, 95% CI 1.010-1.054, P=0.004), lower mGFR ( OR=0.758, 95% CI 0.648-0.886, P<0.001), higher serum phosphorus ( OR=2.761, 95% CI 1.282-6.024, P=0.010), and elevated blood eosinophil percentage ( OR=1.098, 95% CI 1.012-1.191, P=0.025) were independent factors associated with pruritus in PD patients. The nomogram model constructed based on these indicators demonstrated good discrimination and calibration. In the training set, the area under the ROC curve ( AUC) was 0.757 (95% CI 0.699-0.816), with Hosmer-Lemeshow test χ2=4.979, P=0.760. In the validation set, the AUC was 0.779 (95% CI 0.651-0.907), and Hosmer-Lemeshow test χ2=12.938, P=0.114. Conclusions:The prevalence of skin pruritus is 51.1% in PD patient. Advanced age, lower mGFR, higher serum phosphorus and higher blood eosinophil percentage are the independent influencing factors for pruritus in PD patients. The nomogram model constructed based on these indicators shows excellent predictive performance for skin pruritus in PD patients.