This study aims to explore whether Naoxintong Capsules improve multiple cerebral infarctions and myocardial injury via promoting angiogenesis, thereby exerting a simultaneous treatment effect on both the brain and heart. Male SD rats were randomly divided into six groups: sham-operated group, model group, high-dose, medium-dose, and low-dose groups of Naoxintong Capsules(440, 220, and 110 mg·kg~(-1)), and nimodipine group(10.8 mg·kg~(-1)). Rat models of multiple cerebral infarctions were established by injecting autologous thrombus, and samples were collected and tested seven days after modeling. Evaluations included multiple cerebral infarction model assessments, neurological function scores, grip strength tests, and rotarod tests, so as to evaluate neuromotor functions. Morphological structures of brain and heart tissue were observed using hematoxylin-eosin(HE) staining, Nissl staining, and Masson staining. Network pharmacology was employed to screen the mechanisms of Naoxintong Capsules in improving multiple cerebral infarctions and myocardial injury. Neuronal and myocardial cell ultrastructures were observed using transmission electron microscopy. Apoptosis rate in brain neuronal cells was detected by TdT-mediated dUTP nick end labeling(TUNEL) staining, and reactive oxygen species(ROS) levels in myocardial cells were measured. Immunofluorescence was used to detect the expression of platelet endothelial cell adhesion molecule-1(CD31), antigen identified by monoclonal antibody Ki67(Ki67), hematopoietic progenitor cell antigen CD34(CD34), and hypoxia inducible factor-1α(HIF-1α) in brain and myocardial tissue. Western blot, and real-time quantitative polymerase chain reaction(RT-qPCR) were used to detect the expression of HIF-1α, vascular endothelial growth factor(VEGF), vascular endothelial growth factor receptor 2(VEGFR2), sarcoma(Src), basic fibroblast growth factor(bFGF), angiopoietin-1(Ang-1), and TEK receptor tyrosine kinase(Tie-2). Compared with the model group, the medium-dose group of Naoxintong Capsules showed significantly lower neurological function scores, increased grip strength, and prolonged time on the rotarod. Pathological damage in brain and heart tissue was reduced, with increased and more orderly arranged mitochondria in neurons and cardiomyocytes. Apoptosis in brain neuronal cells was decreased, and ROS levels in cardiomyocytes were reduced. The microvascular density and endothelial cells of new blood vessels in brain and heart tissue increased, with increased overlapping regions of CD31 and Ki67 expression. The relative protein and mRNA expression levels of HIF-1α, VEGF, VEGFR2, Src, Ang-1, Tie-2, and bFGF were elevated in brain tissue and myocardial tissue. Naoxintong Capsules may improve multiple cerebral infarctions and myocardial injury by mediating HIF-1α/VEGF expression to promote angiogenesis.
Animals ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Rats ; Cerebral Infarction/genetics* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Vascular Endothelial Growth Factor A/genetics* ; Capsules ; Signal Transduction/drug effects* ; Humans ; Brain/metabolism* ; Myocardium/metabolism* ; Apoptosis/drug effects*

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BACKGROUND:There are many treatment methods for knee osteoarthritis,among which electroacupuncture,as an important non-drug treatment,is effective in the treatment of knee osteoarthritis,but its exact mechanism is not clear. OBJECTIVE:Effect of electroacupuncture on the expression of p53 and P21 in articular cartilage and subchondral bone of aged rats with knee osteoarthritis. METHODS:Eight 6-month-old male Sprague-Dawley rats were included in the young group and sixteen 24-month-old male Sprague-Dawley rats were randomly divided into old group(n=8)and electroacupuncture group(n=8).The rats in the electroacupuncture group received electroacupuncture stimulation once a day,5 days a week,for 8 continuous weeks,and the other two groups did not do any treatment.Eight weeks later,the level of type Ⅱ collagen C-terminal peptide in peripheral blood was detected by ELISA,the morphology of left knee cartilage and subchondral bone was observed by safranin O-fast green staining,the degree of knee cartilage degeneration was evaluated by modified Mankin's score,the microstructure of left knee cartilage and subchondral bone was detected by micro-CT,and the expression levels of matrix metalloproteinase 13,P53,P21 Mrna and protein were detected by RT-PCR and western blot respectively. RESULTS AND CONCLUSION:Compared with the young group,the level of C-terminal peptide of type Ⅱ collagen in the peripheral blood was increased in the old group(P<0.05).The micro-CT results showed that the bone volume fraction,bone mineral density and the number of bone trabeculae were decreased in the old group compared with the young group(P<0.05),while the trabecular separation increased(P<0.05).Safranin O-fast green staining showed that in the old group,the surface layer of cartilage was uneven with fissures,the morphology of chondrocytes was irregular and stained unevenly,the boundary between the cartilage and subchondral bone was blurred,and the matrix loss was serious.The Mankin's score was higher in the old group than the young group(P<0.05).The expression of matrix metalloproteinase 13,P53,P21 at Mrna and protein levels increased in the old group compared with the young group(P<0.05).Compared with the old group,electroacupuncture decreased the level of C-terminal peptide of type Ⅱ collagen(P<0.05),increased the bone volume fraction,bone mineral density and the number of bone trabeculae(P<0.05),and decreased the trabecular separation(P<0.05).Safranin O-fast green staining showed that in the electroacupuncture group,the surface of cartilage was smooth and red staining was uniform,and the cell morphology and structure were between the young group and the old group.Following electroacupuncture treatment,the Mankin's score(P<0.05),matrix metalloproteinase 13 and P21 Mrna expression(P<0.05),and matrix metalloproteinase 13 and P53 protein expression decreased(P<0.05),while there was a decreasing trend of P53 Mrna and P21 protein expression,but with no statistical significance(P>0.05).To conclude,electroacupuncture may delay articular cartilage degeneration and subchondral osteoporosis in aged rats by inhibiting the expression of P53 and P21,so as to protect joints and delay joint aging.

OBJECTIVE To establish the analysis methods of 33 banned pesticides in Ginkgo Biloba leaves and the extracts, and conduct the risk assessment study. METHODS One hundred and thirty-six batches of Ginkgo Biloba leaves and 58 batches of Ginkgo Biloba leaves extract were detected by UPLC-MS and GC-MS. The acute and chronic intake risk of pesticide residues in samples were calculated by point assessment method, and the risk scores of the pesticides were calculated by the Britain veterinary residues matrix ranking. RESULTS Six kinds of banned pesticides were detected in 136 batches of Ginkgo Biloba leaves, the total detection rate was 35.29%, and the detection amount was 0.002−0.210 mg·kg−1. The chronic dietary intake risk was 0.018%−0.620%, and the acute dietary intake risk was 0.000 1%−0.014 0%, indicated that the dietary exposure risk of pesticides in Ginkgo biloba leaves was at a low level. Two kinds of banned pesticides were detected in 58 batches of Ginkgo Biloba leaves extract, the detection rate was 55.17%, and the detection amount was 0.002−1.788 mg·kg−1. The percentage of acceptable daily intake was 0.003%−0.143%, and the percentage of acute reference dose was 0.002 4%, which was also at a low level. Risk ranking results indicated that the risk of phorate was the highest and should be focused on the production and safety supervision. CONCLUSION The method has good stability, high precision and promising repeatability, which can be used for the detection of 33 prohibited pesticides in Ginkgo biloba leaves and their extracts. The results show that the residual amounts of 33 banned pesticides in Ginkgo Biloba leaves and its extracts were extremely low, and there is no significant health risks.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.

ERK1/2 is a key protein that mediates cell signal transduction,and it is involved in regulating biological processes such as chromatin remodeling,nuclear disintegration,proliferation,survival,metabolism,and cell migration and differentiation.Its overactivation is closely related to the occurrence and progression of cancer,and the mechanism is manifested as the overactivation of ERK1/2 by gene mutations of upstream pathway molecules or regulators and the reactivation of ERK1/2 after inhibition against the above targets.ERK1/2 is a potentially valuable target.In this review,the mechanism of post-translational modification and spatial regulation of ERK1/2 and the application status of corresponding small-molecule inhibitors were discussed.The current antitumor strategy of targeting and regulating ERK1/2 was summarized,and the possibility of exploring potential targets was elucidated,thus providing new insights into the developmental research of ERK1/2 as an ideal anticancer target.

Objective:To explore the differential impact of the alignment between service capability and job satisfaction on job performance among primary general practitioner,and to provide a reference for enhancing their job performance.Methods:A survey was conducted with 620 primary general practitioner using questionnaires.The relationships among service capability,job satisfaction,and job performance were analyzed using polynomial regression and response surface analysis methods.Results:Under the condition of"service capability—job satisfaction alignment,"compared to the scenario of"low service capability—low job satisfaction,"primary general practitioner with"high service capability—high job satisfaction"demonstrated significantly higher job performance(a1=0.875,P＜0.001;a2=-0.068,P＞0.05).In the misalignment condition,compared to"low service capability—high job satisfaction,"those with"high service capability—low job satisfaction"also showed higher job performance(a3=0.265,P＜0.001;a4=-0.064,P＞0.05).Conclusion:Both service capability and job satisfaction significantly influence job performance among primary general practitioner,with service capability being a key factor for achieving high work performance.It is essential to enhance the service capability of primary general practitioner and adopt multiple strategies to improve job satisfaction,thereby effectively boosting work performance.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.