ObjectiveTo investigate the optimal ratio of goat horn replacing antelope horn in Fufang Lingjiao Jiangya pills and the blood pressure-lowering mechanism of this medicine. MethodsThe blood pressure-lowering efficacy of Fufang Lingjiao Jiangya pills with varying proportions of goat horn replacing antelope horn was evaluated on spontaneous hypertensive rats （SHR）. In this experiment， 50 SHR rats were randomly grouped as follows： model （n=8）， captopril （0.01 g·kg^-1） （n=6）， low-dose blank Fufang Lingjiao Jiangya pills （0.342 g·kg^-1） （n=6）， high-dose blank Fufang Lingjiao Jiangya pills （0.684 g·kg^-1） （n=6）， low-dose antelope horn-containing Fufang Lingjiao Jiangya pills （0.378 g·kg^-1） （n=6）， high-dose antelope horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1） （n=6）， low-dose goat horn-containing Fufang Lingjiao Jiangya pills （0.378 g·kg^-1） （n=6）， and high-dose goat horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1） （n=6）. Additionally， 8 WKY rats were used as the normal group. Drugs were administered by gavage for 4 weeks while an equal volume of distilled water was administered for the normal and model groups. Blood pressure was measured before administration， 3 h post administration， and biweekly thereafter. In the experiment for Fufang Lingjiao Jiangya pills with goat horn replacing antelope horn in different proportions， 48 SHR rats were randomly grouped as follows： model， blank Fufang Lingjiao Jiangya pills （0.684 g·kg^-1）， antelope horn-containing Fufang Lingjiao Jiangya pills （0.756 g·kg^-1）， 2× goat horn-containing Fufang Lingjiao Jiangya pills （0.824 g·kg^-1）， 4× goat horn Fufang Lingjiao Jiangya pills （0.969 g·kg^-1）， and 6× goat horn Fufang Lingjiao Jiangya pills （1.112 g·kg^-1）. The normal group included 8 WKY rats， and the normal group and model group received an equal volume of distilled water. The treatment lasted for 2 weeks， and blood pressure was recorded at various time points （pre-administration， 3 h post administration， and on days 4， 7， 10， and 14 of administration）. Serum levels of angiotensin-converting enzyme （ACE）， angiotensin Ⅱ（Ang Ⅱ）， renin， and interleukin-6 （IL-6） were measured by enzyme-linked immunosorbent assay. Histopathological changes in the heart， kidney， and thoracic aorta were observed by hematoxylin-eosin staining. The protein levels of ACE2， angiotensin Ⅱ type 1 receptor （AT1R）， and angiotensinogen （AGT） in the kidney tissue were determined by Western blot， while the expression of nuclear factor （NF）-κB p65 and Toll-like receptor 4 （TLR4） in the thoracic aorta tissue was assessed by immunohistochemistry. ResultsCompared with the model group， all treatment groups showed lowered blood pressure （P<0.05， P<0.01）， and the 6× goat horn-containing Fufang Lingjiao Jiangya pills group showed consistent blood pressure-lowering effect with the antelope horn-containing Fufang Lingjiao Jiangya pills group. Compared with the normal group， the model group showed elevated serum levels of ACE， Ang Ⅱ， renin， and IL-6， while the elevations were declined in the Fufang Lingjiao Jiangya pills groups （P<0.05， P<0.01）. Pathological changes in the heart， kidney， and thoracic aorta were alleviated in all the treatment groups， with the 6× goat horn- and antelope horn-containing Fufang Lingjiao Jiangya pills groups exhibited the best effect. Western blot and immunohistochemistry results showed that all the treatment groups exhibited down-regulated protein levels of AT1R， AGT， NF-κB p65， and TLR4 and up-regulated protein levels of ACE2 （P<0.05， P<0.01） compared with model group， with the 6×goat horn- and antelope horn-containing Fufang Lingjiao Jiangya pills groups showcasing the best effect. ConclusionReplacing antelope horn with 6×goat horn in Fufang Lingjiao Jiangya pills can achieve consistent blood pressure-lowering effect with the original prescription. The prescription may exert the effect by inhibiting the renin-angiotensin-aldosterone system （RAAS） and TLR4/NF-κB signaling pathways.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

This study aims to investigate the potential effect of the water extract of fresh Rehmanniae Radix on hypercholesterolemia in mice that was induced by a high-fat and high-cholesterol diet and explore its possible mechanism from bile acid reabsorption. Male C57BL/6 mice were randomly assigned into the following groups: control, model, low-and high-dose(4 and 8 g·kg~(-1), respectively) fresh Rehmanniae Radix, and positive drug(simvastatin, 0.05 g·kg~(-1)). Other groups except the control group were fed with a high-fat and high-cholesterol diet for 6 consecutive weeks to induce hypercholesterolemia. From the 6th week, mice were administrated with corresponding drugs daily via gavage for additional 6 weeks, while continuing to be fed with a high-fat and high-cholesterol diet. Serum levels of total cholesterol(TC), triglycerides(TG), low density lipoprotein-cholesterol(LDL-c), high density lipoprotein-cholesterol(HDL-c), and total bile acid(TBA), as well as liver TC and TG levels and fecal TBA level, were determined by commercial assay kits. Hematoxylin-eosin(HE) staining, oil red O staining, and transmission electron microscopy were performed to observe the pathological changes in the liver. Three livers samples were randomly selected from each of the control, model, and high-dose fresh Rehmanniae Radix groups for high-throughput transcriptome sequencing. Differentially expressed genes were mined and KEGG pathway enrichment analysis was performed to predict the key pathways and target genes of the water extract of fresh Rehmanniae Radix in the treatment of hypercholesterolemia. RT-qPCR was employed to measure the mRNA levels of cholesterol 7α-hydroxylase(CYP7A1) and cholesterol 27α-hydroxylase(CYP27A1) in the liver. Western blot was employed to determine the protein levels of CYP7A1 and CYP27A1 in the liver as well as farnesoid X receptor(FXR), apical sodium-dependent bile acid transporter(ASBT), and ileum bile acid-binding protein(I-BABP) in the ileum. The results showed that the water extract of fresh Rehmanniae Radix significantly lowered the levels of TC and TG in the serum and liver, as well as the level of LDL-c in the serum. Conversely, it elevated the level of HDL-c in the serum and TBA in feces. No significant difference was observed in the level of TBA in the serum among groups. HE staining, oil red O staining, and transmission electron microscopy showed that the water extract reduced the accumulation of lipid droplets in the liver. Further mechanism studies revealed that the water extract of fresh Rehmanniae Radix significantly down-regulated the protein levels of FXR and bile acid reabsorption-related proteins ASBT and I-BABP. Additionally, it enhanced CYP7A1 and CYP27A1, the key enzymes involved in bile acid synthesis. Therefore, it is hypothesized that the water extract of fresh Rehmanniae Radix may exert an anti-hypercholesterolemic effect by regulating FXR/ASBT/I-BABP signaling, inhibiting bile acid reabsorption, and increasing bile acid excretion, thus facilitating the conversion of cholesterol to bile acids.
Animals ; Male ; Bile Acids and Salts/metabolism* ; Mice, Inbred C57BL ; Mice ; Diet, High-Fat/adverse effects* ; Cholesterol/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Hypercholesterolemia/genetics* ; Receptors, Cytoplasmic and Nuclear/genetics* ; Rehmannia/chemistry* ; Liver/drug effects* ; Humans ; Cholesterol 7-alpha-Hydroxylase/genetics* ; Plant Extracts

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*