ObjectiveThis study aimed to investigate the mechanism by which Luoshi Neiyi prescription treats endometriosis （EMs） through regulating ferroptosis， and to screen key metabolites and analyze their association with ferroptosis. MethodsClinical samples of normal endometrium from patients without EMs and eutopic and ectopic endometrium from EMs patients （10 cases each） were collected and divided into control group， eutopic group， and EMs group. Hematoxylin-eosin （HE） staining was performed to observe ectopic lesions of EMs. Immunohistochemistry was used to detect the expression of solute carrier family 7 member 11 （SLC7A11） and glutathione peroxidase 4 （GPX4）. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of malondialdehyde （MDA）， ferrous ion （Fe²⁺）， GPX4 and glutathione （GSH） in endometrial tissues， as well as serum levels of Fe²⁺， GPX4 and GSH. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of SLC7A11， GPX4， transferrin receptor （TFR） and ferritin heavy chain 1 （FTH1）. In the in vitro experiment， primary stromal cells were isolated from ectopic lesions of EMs patients. Cell counting kit-8 （CCK-8） was used to determine the optimal concentration of drug-containing serum for intervention. The level of reactive oxygen species （ROS） was measured， and Real-time PCR was applied to detect ferroptosis-related indicators. In the animal experiments， an EM rat model was established， and the rats were randomly assigned to the sham operation group， EMs group， low-dose Luoshi Neiyi Formula group （7.87 g·kg^-1）， high-dose Luoshi Neiyi prescription group （15.74 g·kg^-1）， and danazol group （42 mg·kg^-1）. Untargeted metabolomics detection and pathway enrichment analysis were conducted on serum samples from patients and rats. Spearman correlation analysis was performed to assess the relationship between differential metabolites and ferroptosis indicators. The correlations between differential metabolites in patient endometrium and serum and key ferroptosis indicators （GPX4， Fe²⁺， MDA， GSH） as well as ferroptosis-related mRNAs （GPX4， SLC7A11， FTH1） were analyzed， and correlation heatmaps were generated accordingly. ResultsCompared with normal eutopic endometrium， ectopic lesions in EMs patients showed glandular disorganization and stromal fibrosis. In ectopic endometrium， the contents of MDA， ROS， and Fe²⁺ decreased， while GPX4 level increased， and the mRNA expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. In serum， the levels of GPX4 and Fe²⁺ were elevated， whereas the GSH level declined， suggesting abnormalities in ferroptosis-related pathways in ectopic lesions （P<0.05， P<0.01）. After intervention with Luoshi Neiyi prescription-containing serum， the intracellular ROS level in ectopic endometrial stromal cells was elevated， the mRNA expression of SLC7A11 and GPX4 was downregulated， and TFR mRNA expression was upregulated （P<0.05， P<0.01）. Metabolomics analysis revealed 1104 and 198 differential metabolites in EMs patients and EMs rats， respectively， compared with their corresponding control groups， and both low-dose and high-dose Luoshi Neiyi prescription were found to regulate this metabolic disturbance， with the core regulatory pathways mainly involving arginine and proline metabolism. Correlation analysis showed that the glycerophospholipids including PI（16∶0/17∶0） and PI［18∶2（9Z，12Z）］ were negatively correlated with GPX4 and positively correlated with MDA， while 17α-hydroxyprogesterone was positively correlated with GPX4， SLC7A11， and FTH1 q<0.05）. ConclusionLuoshi Neiyi prescription may systematically ameliorate disease-associated metabolic dysregulation via modulation of the serum arginine and proline metabolism pathway， and may regulate ferroptosis in ectopic lesions through a mechanism potentially linked to the serum glycerophospholipid and steroid metabolism pathways. Collectively， these findings provide experimental evidence for the clinical application of Luoshi Neiyi prescription.

ObjectiveThis study aimed to investigate the mechanism by which Luoshi Neiyi prescription treats endometriosis （EMs） through regulating ferroptosis， and to screen key metabolites and analyze their association with ferroptosis. MethodsClinical samples of normal endometrium from patients without EMs and eutopic and ectopic endometrium from EMs patients （10 cases each） were collected and divided into control group， eutopic group， and EMs group. Hematoxylin-eosin （HE） staining was performed to observe ectopic lesions of EMs. Immunohistochemistry was used to detect the expression of solute carrier family 7 member 11 （SLC7A11） and glutathione peroxidase 4 （GPX4）. Enzyme-linked immunosorbent assay （ELISA） was adopted to determine the levels of malondialdehyde （MDA）， ferrous ion （Fe²⁺）， GPX4 and glutathione （GSH） in endometrial tissues， as well as serum levels of Fe²⁺， GPX4 and GSH. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of SLC7A11， GPX4， transferrin receptor （TFR） and ferritin heavy chain 1 （FTH1）. In the in vitro experiment， primary stromal cells were isolated from ectopic lesions of EMs patients. Cell counting kit-8 （CCK-8） was used to determine the optimal concentration of drug-containing serum for intervention. The level of reactive oxygen species （ROS） was measured， and Real-time PCR was applied to detect ferroptosis-related indicators. In the animal experiments， an EM rat model was established， and the rats were randomly assigned to the sham operation group， EMs group， low-dose Luoshi Neiyi Formula group （7.87 g·kg^-1）， high-dose Luoshi Neiyi prescription group （15.74 g·kg^-1）， and danazol group （42 mg·kg^-1）. Untargeted metabolomics detection and pathway enrichment analysis were conducted on serum samples from patients and rats. Spearman correlation analysis was performed to assess the relationship between differential metabolites and ferroptosis indicators. The correlations between differential metabolites in patient endometrium and serum and key ferroptosis indicators （GPX4， Fe²⁺， MDA， GSH） as well as ferroptosis-related mRNAs （GPX4， SLC7A11， FTH1） were analyzed， and correlation heatmaps were generated accordingly. ResultsCompared with normal eutopic endometrium， ectopic lesions in EMs patients showed glandular disorganization and stromal fibrosis. In ectopic endometrium， the contents of MDA， ROS， and Fe²⁺ decreased， while GPX4 level increased， and the mRNA expression of SLC7A11 and GPX4 was upregulated （P<0.05， P<0.01）. In serum， the levels of GPX4 and Fe²⁺ were elevated， whereas the GSH level declined， suggesting abnormalities in ferroptosis-related pathways in ectopic lesions （P<0.05， P<0.01）. After intervention with Luoshi Neiyi prescription-containing serum， the intracellular ROS level in ectopic endometrial stromal cells was elevated， the mRNA expression of SLC7A11 and GPX4 was downregulated， and TFR mRNA expression was upregulated （P<0.05， P<0.01）. Metabolomics analysis revealed 1104 and 198 differential metabolites in EMs patients and EMs rats， respectively， compared with their corresponding control groups， and both low-dose and high-dose Luoshi Neiyi prescription were found to regulate this metabolic disturbance， with the core regulatory pathways mainly involving arginine and proline metabolism. Correlation analysis showed that the glycerophospholipids including PI（16∶0/17∶0） and PI［18∶2（9Z，12Z）］ were negatively correlated with GPX4 and positively correlated with MDA， while 17α-hydroxyprogesterone was positively correlated with GPX4， SLC7A11， and FTH1 q<0.05）. ConclusionLuoshi Neiyi prescription may systematically ameliorate disease-associated metabolic dysregulation via modulation of the serum arginine and proline metabolism pathway， and may regulate ferroptosis in ectopic lesions through a mechanism potentially linked to the serum glycerophospholipid and steroid metabolism pathways. Collectively， these findings provide experimental evidence for the clinical application of Luoshi Neiyi prescription.

Objective:To compare the clinical efficacy of Minimally Invasive Surgery (MIS) and traditional Posterior Spinal Fusion (PSF) in treating children with paralytic scoliosis with pelvic obliquity (PSPO) following spinal cord injury.Methods:A retrospective analysis was conducted on the data of 25 patients with PSPO who underwent surgical treatment at the Drum Tower Hospital affiliated with Nanjing University Medical School from January 2017 to June 2023. The cohort included 4 males and 21 females, aged 12.3±2.8 years (range 9-14 years). Patients were divided into the MIS group (12 cases) and the PSF group (13 cases). Radiological parameters were measured preoperatively, postoperatively, and at the last follow-up. Surgical time, intraoperative blood loss, intraoperative blood transfusion volume, length of hospital stay, total hospitalization costs, and complications were recorded. The Scoliosis Research Society questionnaires-22 (SRS-22) Chinese version were used to assess patient satisfaction and efficacy.Results:There were no statistically significant differences between the MIS and PSF groups in age, gender, Risser sign, preoperative Cobb angle for scoliosis, pelvic tilt angle, or local kyphosis angle ( P>0.05). The MIS group demonstrated surgical time of 176±30 minutes, intraoperative blood loss of 300±70 ml, blood transfusion volume of 280±175 ml, and total hospitalization costs of 87'800± 13'300 yuan, all of which were lower than PSF group, with values of 280±91 minutes, 1'433±116 ml, 1'351±996 ml, and 14'8400±26'100 yuan, respectively. These differences were statistically significant ( t=3.789, P=0.001; t=29.328, P<0.001; t=3.667, P=0.001; t=7.271, P<0.001). In the MIS group, preoperative, postoperative, and last follow-up Cobb angles were 79.11°±6.74°, 35.86°±4.98°, and 36.27°±4.84° respectively; pelvic tilt angles were 24.79°±5.58°, 9.18°±3.32°, and 8.79°±2.94°; local kyphosis angles were 38.84°±4.18°, 12.96°±4.87°, and 11.43°±6.08°, respectively. Postoperative and last follow-up angles were significantly reduced compared to preoperative values, with statistically significant differences ( P<0.05). In the PSF group, preoperative, postoperative, and last follow-up Cobb angles were 82.06°±9.26°, 34.75°±5.14°, and 35.15°±5.04° respectively; pelvic tilt angles were 26.60°±6.21°, 10.12°±3.21°, and 9.91°±2.97°; local kyphosis angles were 40.92°±7.04°, 10.92°±7.26°, and 14.02°±5.58°, respectively. Differences from preoperative to postoperative measurements were statistically significant ( P<0.05). At the last follow-up, both groups showed no significant loss of scoliosis correction, and there were no statistically significant differences between the groups postoperatively or at the last follow-up ( P>0.05). In the MIS group, one case of superficial surgical site infection and one case of postoperative atelectasis occurred. In the PSF group, two cases of deep surgical site infection, one case of poor screw placement, and two cases were transferred to the ICU postoperatively due to excessive intraoperative bleeding. Preoperative SRS-22 total scores were 2.0±0.6 for PSF and 2.1±0.4 for MIS. Postoperative SRS-22 total scores (excluding satisfaction) were 3.0±0.5 for PSF and 2.9±0.3 for MIS. The within-group differences from preoperative to postoperative were statistically significant ( P<0.05), while the between-group differences from preoperative to postoperative were not statistically significant ( P>0.05). Conclusion:Compared to the PSF technique, MIS can shorten surgery time, reduce intraoperative blood loss and perioperative complications, and decrease hospitalization costs. MIS can achieve similar early clinical efficacy.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Vertebral refracture following percutaneous vertebral augmentation (PVA) is commonly seen in elderly patients with osteoporotic thoracolumbar compression fractures (OTLCF). It can lead to recurrent pain, loss of vertebral height, progression of kyphosis, and even neurological dysfunction, significantly impairing patients′ quality of life. Current diagnosis and treatment face multiple challenges, including high misdiagnosis rate, difficulty in choosing between surgical and non-surgical treatment options, lack of standardized surgical protocols, interference from intralesional bone cement during procedures, inadequate stability of internal fixation in osteoporotic bone, and suboptimal compliance of anti-osteoporotic therapy. Establishing a standardized diagnostic and therapeutic framework is urgently needed. To standardize the management process and improve outcomes for vertebral refractures after PVA in elderly OTLCF patients, Spinal Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field to develop Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures ( version 2025), based on current literature and clinical experience, and adhering to principles of scientific rigor and clinical applicability. A total of 11 recommendations were proposed, encompassing diagnosis, treatment, and rehabilitation of vertebral refracture after PVA in elderly patients with OTLCF, aiming to provide a foundation for a standardized management.

Vertebral refracture following percutaneous vertebral augmentation (PVA) is commonly seen in elderly patients with osteoporotic thoracolumbar compression fractures (OTLCF). It can lead to recurrent pain, loss of vertebral height, progression of kyphosis, and even neurological dysfunction, significantly impairing patients′ quality of life. Current diagnosis and treatment face multiple challenges, including high misdiagnosis rate, difficulty in choosing between surgical and non-surgical treatment options, lack of standardized surgical protocols, interference from intralesional bone cement during procedures, inadequate stability of internal fixation in osteoporotic bone, and suboptimal compliance of anti-osteoporotic therapy. Establishing a standardized diagnostic and therapeutic framework is urgently needed. To standardize the management process and improve outcomes for vertebral refractures after PVA in elderly OTLCF patients, Spinal Trauma Group of the Orthopedic Branch of Chinese Medical Doctor Association organized experts in the field to develop Guideline for the diagnosis and treatment of vertebral refracture after percutaneous vertebral augmentation in elderly patients with osteoporotic thoracolumbar compression fractures ( version 2025), based on current literature and clinical experience, and adhering to principles of scientific rigor and clinical applicability. A total of 11 recommendations were proposed, encompassing diagnosis, treatment, and rehabilitation of vertebral refracture after PVA in elderly patients with OTLCF, aiming to provide a foundation for a standardized management.

Objective:To compare the clinical efficacy of Minimally Invasive Surgery (MIS) and traditional Posterior Spinal Fusion (PSF) in treating children with paralytic scoliosis with pelvic obliquity (PSPO) following spinal cord injury.Methods:A retrospective analysis was conducted on the data of 25 patients with PSPO who underwent surgical treatment at the Drum Tower Hospital affiliated with Nanjing University Medical School from January 2017 to June 2023. The cohort included 4 males and 21 females, aged 12.3±2.8 years (range 9-14 years). Patients were divided into the MIS group (12 cases) and the PSF group (13 cases). Radiological parameters were measured preoperatively, postoperatively, and at the last follow-up. Surgical time, intraoperative blood loss, intraoperative blood transfusion volume, length of hospital stay, total hospitalization costs, and complications were recorded. The Scoliosis Research Society questionnaires-22 (SRS-22) Chinese version were used to assess patient satisfaction and efficacy.Results:There were no statistically significant differences between the MIS and PSF groups in age, gender, Risser sign, preoperative Cobb angle for scoliosis, pelvic tilt angle, or local kyphosis angle ( P>0.05). The MIS group demonstrated surgical time of 176±30 minutes, intraoperative blood loss of 300±70 ml, blood transfusion volume of 280±175 ml, and total hospitalization costs of 87'800± 13'300 yuan, all of which were lower than PSF group, with values of 280±91 minutes, 1'433±116 ml, 1'351±996 ml, and 14'8400±26'100 yuan, respectively. These differences were statistically significant ( t=3.789, P=0.001; t=29.328, P<0.001; t=3.667, P=0.001; t=7.271, P<0.001). In the MIS group, preoperative, postoperative, and last follow-up Cobb angles were 79.11°±6.74°, 35.86°±4.98°, and 36.27°±4.84° respectively; pelvic tilt angles were 24.79°±5.58°, 9.18°±3.32°, and 8.79°±2.94°; local kyphosis angles were 38.84°±4.18°, 12.96°±4.87°, and 11.43°±6.08°, respectively. Postoperative and last follow-up angles were significantly reduced compared to preoperative values, with statistically significant differences ( P<0.05). In the PSF group, preoperative, postoperative, and last follow-up Cobb angles were 82.06°±9.26°, 34.75°±5.14°, and 35.15°±5.04° respectively; pelvic tilt angles were 26.60°±6.21°, 10.12°±3.21°, and 9.91°±2.97°; local kyphosis angles were 40.92°±7.04°, 10.92°±7.26°, and 14.02°±5.58°, respectively. Differences from preoperative to postoperative measurements were statistically significant ( P<0.05). At the last follow-up, both groups showed no significant loss of scoliosis correction, and there were no statistically significant differences between the groups postoperatively or at the last follow-up ( P>0.05). In the MIS group, one case of superficial surgical site infection and one case of postoperative atelectasis occurred. In the PSF group, two cases of deep surgical site infection, one case of poor screw placement, and two cases were transferred to the ICU postoperatively due to excessive intraoperative bleeding. Preoperative SRS-22 total scores were 2.0±0.6 for PSF and 2.1±0.4 for MIS. Postoperative SRS-22 total scores (excluding satisfaction) were 3.0±0.5 for PSF and 2.9±0.3 for MIS. The within-group differences from preoperative to postoperative were statistically significant ( P<0.05), while the between-group differences from preoperative to postoperative were not statistically significant ( P>0.05). Conclusion:Compared to the PSF technique, MIS can shorten surgery time, reduce intraoperative blood loss and perioperative complications, and decrease hospitalization costs. MIS can achieve similar early clinical efficacy.

Objective:To predict mechanical complications (MC) following spinal deformity surgery for adult spine deformity (ASD) using machine learning models, identify key risk factors, and develop a visualizable tool for individualized risk assessment.Methods:Clinical and radiological data from 525 patients with ASD who underwent surgery in our hospital between January 2017 and December 2021 were collected. Patients were randomly assigned to a training set (70%) and a test set (30%) for model development. The cohort included 88 males and 437 females, with a mean age of 42.2±18.1 years. Variables included demographic data, comorbidities, local and systemic radiological parameters, paraspinal muscle fat infiltration (FI), and vertebral bone quality (VBQ) scores. Multiple machine learning algorithms: Random Forest (RF), Gaussian Naive Bayes (GNB), Light GBM, Support Vector Machine (SVM), XGBoost (XGB), and Logistic Regression (LR) were trained and evaluated. Model performance was compared using the receiver operating characteristic curve (ROC) and precision-recall curve (PRC). SHAP (Shapley Additive Explanations) was used to rank risk factors, while LIME (Local Interpretable Model-Agnostic Explanations) was applied to visualize MC risk in individual cases.Results:Of the 525 patients, 135 (25.7%) developed postoperative MC. Among these, 80 (59.3%) experienced proximal junction kyphosis or failure (PJK/PJF), 7 (5.2%) had distal junction kyphosis or failure (DJK/DJF), 28 (20.7%) sustained rod fractures, and 29 (21.5%) showed significant loss of correction. In the validation cohort, the RF model achieved the highest area under the curve (AUC=0.80), followed by GNB (0.77), XGB (0.76), LR (0.74), LightGBM (0.73), and SVM (0.66). The RF model also demonstrated the best PRC value (0.58), highest sensitivity (0.65), and lowest Brier score (0.20). GNB, Light GBM, and LR models achieved the highest accuracy (0.78 each), while LightGBM exhibited the highest specificity (0.93). SHAP analysis identified higher preoperative VBQ scores, larger T 1 pelvic angle (TPA), and higher paraspinal muscle FI as the main risk factors for MC. Based on the RF model, a LIME-based tool was successfully constructed for individualized MC risk estimation. Conclusion:The RF model demonstrated the best overall predictive performance for MC. A machine learning-based prediction model has the potential to provide valuable guidance for surgical decision-making in ASD patients.

Humans ; Transcatheter Aortic Valve Replacement ; Aortic Valve/surgery* ; Stents ; Aortic Valve Stenosis/surgery* ; Treatment Outcome ; Heart Valve Prosthesis

Humans ; Transcatheter Aortic Valve Replacement ; Aortic Valve/surgery* ; Stents ; Aortic Valve Stenosis/surgery* ; Treatment Outcome ; Heart Valve Prosthesis