ObjectiveTo construct a risk prediction model for carotid artery plaques in high-risk populations of stroke based on five machine learning methods. MethodsThe clinical information of the high-risk population of stroke was collected. Factor analysis and statistical analysis of syndrome elements were conducted on their traditional Chinese medicine （TCM） symptoms and tongue and pulse manifestations. On the basis of the results of factor analysis and variable screening， five machine learning methods-classification and regression tree （CART） decision tree， support vector machine （SVM）， back propagation（BP） neural network， logistic regression， and random forest-were used to construct the risk prediction model for carotid artery plaques. ResultsThe most common TCM syndrome elements in the high-risk population of stroke was Qi deficiency. The scores of Qi deficiency， Yin deficiency， and Yang deficiency in the population with carotid artery plaques were higher than those without carotid artery plaques （P<0.05）. The CART decision tree， SVM， logistic regression， BP neural network， and random forest models showed the areas under the receiver operating characteristic （ROC） curves of 0.71， 0.75， 0.76， 0.76， and 0.75， the accuracy rates of 68.94%， 69.27%， 69.44%， 70.10%， and 69.60%， the precision rates of 68.56%， 68.53%， 68.75%， 69.74%， and 69.42%， the recall rates of 68.91%， 67.93%， 67.92%， 68.10%， and 67.31%， and the F₁ values of 0.69， 0.68， 0.68， 0.68， and 0.68， respectively. ConclusionAmong the high-risk population of stroke， the most frequently distributed TCM syndrome element is Qi deficiency， with the rest mainly being fire heat， Yin deficiency， Yang deficiency， phlegm dampness， blood stasis， and Qi stagnation. Deficiency syndrome may be a major factor leading to carotid artery plaques in the high-risk population of stroke. The BP neural network model demonstrates better performance in predicting the risk of carotid artery plaques in the high-risk population of stroke. People with carotid artery plaques are more likely to present with symptoms such as a heavy head， dizziness， headache， and thready pulse. The primary community benefits more widely when the BP neural network model is adopted to predict the risk of carotid artery plaques in the high-risk population of stroke over 40 years old.

ObjectiveTo construct a risk prediction model for carotid artery plaques in high-risk populations of stroke based on five machine learning methods. MethodsThe clinical information of the high-risk population of stroke was collected. Factor analysis and statistical analysis of syndrome elements were conducted on their traditional Chinese medicine （TCM） symptoms and tongue and pulse manifestations. On the basis of the results of factor analysis and variable screening， five machine learning methods-classification and regression tree （CART） decision tree， support vector machine （SVM）， back propagation（BP） neural network， logistic regression， and random forest-were used to construct the risk prediction model for carotid artery plaques. ResultsThe most common TCM syndrome elements in the high-risk population of stroke was Qi deficiency. The scores of Qi deficiency， Yin deficiency， and Yang deficiency in the population with carotid artery plaques were higher than those without carotid artery plaques （P<0.05）. The CART decision tree， SVM， logistic regression， BP neural network， and random forest models showed the areas under the receiver operating characteristic （ROC） curves of 0.71， 0.75， 0.76， 0.76， and 0.75， the accuracy rates of 68.94%， 69.27%， 69.44%， 70.10%， and 69.60%， the precision rates of 68.56%， 68.53%， 68.75%， 69.74%， and 69.42%， the recall rates of 68.91%， 67.93%， 67.92%， 68.10%， and 67.31%， and the F₁ values of 0.69， 0.68， 0.68， 0.68， and 0.68， respectively. ConclusionAmong the high-risk population of stroke， the most frequently distributed TCM syndrome element is Qi deficiency， with the rest mainly being fire heat， Yin deficiency， Yang deficiency， phlegm dampness， blood stasis， and Qi stagnation. Deficiency syndrome may be a major factor leading to carotid artery plaques in the high-risk population of stroke. The BP neural network model demonstrates better performance in predicting the risk of carotid artery plaques in the high-risk population of stroke. People with carotid artery plaques are more likely to present with symptoms such as a heavy head， dizziness， headache， and thready pulse. The primary community benefits more widely when the BP neural network model is adopted to predict the risk of carotid artery plaques in the high-risk population of stroke over 40 years old.

Chronic fatigue syndrome (CFS) is a common problem in military maritime navigation, which greatly affects the safety of military missions. The use of animal models to carry out research on the mechanism of CFS and treatment measures is a common method. This paper systematically introduced the construction methods of CFS models such as single-factor and multi-factor models, summarized common evaluation indicators of CFS, including behavioral and biochemical indicators, and summed up key characteristics of CFS animal models in military oceanic navigation combined with common causes of CFS in military contexts, such as prolonged continuous work, high-intensity physical activity, sleep deprivation, psychological stress, and extreme environmental conditions. The key characteristics of the animal models included, but not limited to, chronic fatigue, sleep disorders, impaired cognitive function, psychological stress responses, and abnormal biochemical indicators. Furthermore, this article identified future research directions for CFS animal models in military oceanic navigation to enhance the application value of the models and provide robust support for the health protection and disease prevention of military personnel.

With the main pathological features of glomerulosclerosis and interstitial fibrosis， renal fibrosis is a key pathological process causing chronic kidney disease to progress to end-stage disease. As a cellular autophagic process， mitochondrial autophagy plays a crucial role in maintaining mitochondrial mass and functional stability. Mitochondrial dysfunction is considered to be one of the key factors driving the progression of fibrosis. Phosphatase and tension protein homologue （PTEN） induce various signalling pathways such as putative kinase 1/parkin， Nip3-like protein X/Bcl-2 interacting protein 3， and FUN14 structural domain-containing protein 1 to activate mitochondrial autophagy to participate in the regulation of fibrogenic factors， amelioration of oxidative stress， and inhibition of inflammatory response and apoptosis， which in turn effectively slows down the progression of renal fibrosis. Studies have shown that traditional Chinese medicine monomers and compound preparations， including phenolics， terpenoids， ketones， and alkaloids， can regulate mitochondrial autophagy-related signalling pathways and achieve significant clinical efficacy in intervening in the progression of renal fibrosis for the treatment of chronic kidney disease. This paper summarized the mechanism of mitochondrial autophagy and the research progress of traditional Chinese medicine intervention in renal fibrosis to provide new ideas for the study of the mechanism of traditional Chinese medicine in treating renal fibrosis.

With the main pathological features of glomerulosclerosis and interstitial fibrosis， renal fibrosis is a key pathological process causing chronic kidney disease to progress to end-stage disease. As a cellular autophagic process， mitochondrial autophagy plays a crucial role in maintaining mitochondrial mass and functional stability. Mitochondrial dysfunction is considered to be one of the key factors driving the progression of fibrosis. Phosphatase and tension protein homologue （PTEN） induce various signalling pathways such as putative kinase 1/parkin， Nip3-like protein X/Bcl-2 interacting protein 3， and FUN14 structural domain-containing protein 1 to activate mitochondrial autophagy to participate in the regulation of fibrogenic factors， amelioration of oxidative stress， and inhibition of inflammatory response and apoptosis， which in turn effectively slows down the progression of renal fibrosis. Studies have shown that traditional Chinese medicine monomers and compound preparations， including phenolics， terpenoids， ketones， and alkaloids， can regulate mitochondrial autophagy-related signalling pathways and achieve significant clinical efficacy in intervening in the progression of renal fibrosis for the treatment of chronic kidney disease. This paper summarized the mechanism of mitochondrial autophagy and the research progress of traditional Chinese medicine intervention in renal fibrosis to provide new ideas for the study of the mechanism of traditional Chinese medicine in treating renal fibrosis.

Secondary osteoporosis is common in patients with early breast cancer, manifesting as low back pain, bone and joint symptoms, and osteoporotic fractures. Bisphosphonate and denosumab can reduce the incidence of fractures by minimizing bone loss, though they differ in efficacy, treatment course, and side effects. Patients should consider the pros and cons when selecting a drug. Recent studies also focus on decreasing the incidence of bone metastases. This article reviews recent advancements in the use of these two drugs for managing bone health in early breast cancer.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Objective:To investigate the impact of frailty on post-stroke depression (PSD) in patients with acute ischemic stroke and to identify risk factors for PSD in order to construct a risk prediction model.Methods:A convenience sampling method was used to recruit a total of 450 patients with acute ischemic stroke who were treated in the Department of Neurology at the Affiliated Hospital of Jining Medical University from March 2023 to April 2024. Data were collected using the Edmonton Frail Scale, Hamilton Depression Rating Scale, Barthel Index (Activities of Daily Living, ADL), Pittsburgh Sleep Quality Index, and Morse Fall Scale. Binary logistic regression analysis was performed to explore the impact of frailty on PSD and to identify other risk factors. Based on the results, a predictive model was developed.Results:A total of 450 questionnaires were distributed, with 412 valid responses returned, yielding a valid response rate of 91.56%. The incidence of PSD among the 412 patients was 45.63% (188/412). Binary Logistic regression analysis showed that frailty, sleep disturbance, C-reactive protein (CRP), and ADL score were the influencing factors for PSD in patients with acute ischemic stroke ( P<0.05). These factors were incorporated into the predictive model, and a risk nomogram was constructed. The area under the curve of the model was 0.764 [95% CI (0.716, 0.811) ], indicating good discriminative ability. Internal validation of the nomogram using the Hosmer-Lemeshow goodness-of-fit test showed χ 2=5.883, P=0.66 ( P>0.05), suggesting good calibration of the model. Conclusions:Frailty increases the risk of post-stroke depression in patients with acute ischemic stroke. Sleep disturbance, CRP level, and ADL score are important screening indicators for PSD risk. Targeted assessment and early intervention are recommended to reduce the likelihood of PSD.

Secondary osteoporosis is common in patients with early breast cancer, manifesting as low back pain, bone and joint symptoms, and osteoporotic fractures. Bisphosphonate and denosumab can reduce the incidence of fractures by minimizing bone loss, though they differ in efficacy, treatment course, and side effects. Patients should consider the pros and cons when selecting a drug. Recent studies also focus on decreasing the incidence of bone metastases. This article reviews recent advancements in the use of these two drugs for managing bone health in early breast cancer.

OBJECTIVE To investigate the effects of osthole(OST)on skin wound healing and angiogenesis in rats by regulating the sonic hedgehog(SHH)signaling pathway.METHODS Full-layer skin defect wound model rats were established and then randomly separated into Model group,OST low-dose,medium-dose and high-dose groups(OST-L group,OST-M group,OST-H group,20,30,40 mg/kg OST),high-dose OST+SHH inhibitor cyclopamide group(OST-H+cyclopamide group,40 mg/kg OST+10 mg/kg cyclopamide),with 12 rats in each group.Another 12 rats were selected as the control group.The wound healing of rats on 1,7 and 14 days of administration was observed,and the wound healing rate of rats in each group was measured.The pathological changes and collagen deposition in rat wound tissue were observed;the levels of angiopoietin-1(Ang-1)and basic fibroblast growth factor(bFGF)in wound tissue of rats were detected;the relative expressions of vascular endothelial growth factor A(VEGFA)and vascular endothelial growth factor receptor-2(VEGFR-2)mRNA were also detected in wound tissue of rats;the protein expressions of VEGFA,VEGFR-2,SHH and glioma-associated oncogene homolog-1(GLI1)were determined in wound tissue of rats.RESULTS Compared with Model group,the healing rate of skin wound,relative expression of collagen protein,the levels of Ang-1 and bFGF,the mRNA and protein expressions of VEGFA and VEGFR-2,and the protein expressions of SHH and GLI1 were all significantly increased in OST-M and OST-H groups(P＜0.05).The wound tissue underwent significant re-epithelialization,with reduced inflammatory cell infiltration and granulation tissue edema,and an increase in the number of new blood vessels.SHH inhibitor cycloparamide weakened the promoting effects of OST on skin wound healing and angiogenesis in rats.CONCLUSIONS OST may promote skin wound healing and angiogenesis in rats by activating the SHH signaling pathway.