ObjectiveBased on multi-index and multi-method detection， the quality of Rukuaixiao preparations was systematically evaluated from the perspective of characteristic components， and the existing problems were analyzed. MethodsLiquid chromatography-mass spectrometry（LC-MS） for the determination of 16 characteristic components was established to evaluate the quality of 129 batches of Rukuaixiao preparations. High performance liquid chromatography（HPLC） was established to determine the contents of salvianolic acids and tanshinones， investigate the rationality of quality control index of Salviae Miltiorrhizae Radix et Rhizoma in the standard for Rukuaixiao preparations in the 2020 edition of Pharmacopoeia of the People's Republic of China（hereinafter referred to as Chinese Pharmacopoeia） （volume Ⅰ）， and trace the causes of significant difference among different batches. The processing and different extraction methods of Vaccariae Semen were tested， analyzing the impact of formulation changes across different editions of Chinese Pharmacopoeia. The LC-MS was established for determining the changes in the ratio of toosendanin and isotoosendanin after water extraction of Toosendan Fructus. The contents of active components in different parts of Gleditsiae Spina were determined to identify the reason of the low contents of characteristic components in some enterprises. ResultsBased on the comprehensive analysis of the samples from different dosage forms， the contents of characteristic components of Vaccariae Semen and Gleditsiae Spina in tablets from manufacturer B and granules from manufacturer D were significantly higher than those in tablets from manufacturer A， and tablets and capsules from manufacturer C. The contents of tanshinones in some batches of products from manufacturer A were abnormally high， potentially linked to the use of 70% ethanol reflux during extraction of Salviae Miltiorrhizae Radix et Rhizoma. All samples from manufacturer C exhibited abnormally high proportions of salvianic acid A and 3，4-dihydroxybenzaldehyde（salvianolic acid degradation products） to the total seven phenolic acids， indicating a risk of blindly pursuing tanshinol content and neglecting more effective components. The extraction rate of the characteristic components from Vaccariae Semen by decocting with water was obviously higher than that by reflux extraction with 70% ethanol. However， using the stir-fried Vaccariae Semen could reduce the loss of ingredients. The content ratio of toosendanin and isotoosendanin decreased from the crude herb to the prepared medicine when Toosendan Fructus was prepared by water decoction. The reason for the low component content of Gleditsiae Spina may be attributed to manufacturers using excessive non-medicinal parts in their formulations. ConclusionIt is suggested that enterprises should ensure the quality of raw material inputs， especially those without quality-control items in the standard， reduce the use of non-medicinal parts， and prohibit arbitrary alterations to manufacturing methods or processes. It is also recommended that Vaccariae Semen in Rukuaixiao capsules and granules should be changed to the stir-fried processed products. Isotoosendanin should be taken into consideration in the drug supervision when Toosendan Fructus is prepared into medicine by water decoction. Salvianolic acid B should be set as a quality control index for Salviae Miltiorrhizae Radix et Rhizoma when revising the pharmacopoeia standard of Rukuaixiao preparations.

ObjectiveBased on multi-index and multi-method detection， the quality of Rukuaixiao preparations was systematically evaluated from the perspective of characteristic components， and the existing problems were analyzed. MethodsLiquid chromatography-mass spectrometry（LC-MS） for the determination of 16 characteristic components was established to evaluate the quality of 129 batches of Rukuaixiao preparations. High performance liquid chromatography（HPLC） was established to determine the contents of salvianolic acids and tanshinones， investigate the rationality of quality control index of Salviae Miltiorrhizae Radix et Rhizoma in the standard for Rukuaixiao preparations in the 2020 edition of Pharmacopoeia of the People's Republic of China（hereinafter referred to as Chinese Pharmacopoeia） （volume Ⅰ）， and trace the causes of significant difference among different batches. The processing and different extraction methods of Vaccariae Semen were tested， analyzing the impact of formulation changes across different editions of Chinese Pharmacopoeia. The LC-MS was established for determining the changes in the ratio of toosendanin and isotoosendanin after water extraction of Toosendan Fructus. The contents of active components in different parts of Gleditsiae Spina were determined to identify the reason of the low contents of characteristic components in some enterprises. ResultsBased on the comprehensive analysis of the samples from different dosage forms， the contents of characteristic components of Vaccariae Semen and Gleditsiae Spina in tablets from manufacturer B and granules from manufacturer D were significantly higher than those in tablets from manufacturer A， and tablets and capsules from manufacturer C. The contents of tanshinones in some batches of products from manufacturer A were abnormally high， potentially linked to the use of 70% ethanol reflux during extraction of Salviae Miltiorrhizae Radix et Rhizoma. All samples from manufacturer C exhibited abnormally high proportions of salvianic acid A and 3，4-dihydroxybenzaldehyde（salvianolic acid degradation products） to the total seven phenolic acids， indicating a risk of blindly pursuing tanshinol content and neglecting more effective components. The extraction rate of the characteristic components from Vaccariae Semen by decocting with water was obviously higher than that by reflux extraction with 70% ethanol. However， using the stir-fried Vaccariae Semen could reduce the loss of ingredients. The content ratio of toosendanin and isotoosendanin decreased from the crude herb to the prepared medicine when Toosendan Fructus was prepared by water decoction. The reason for the low component content of Gleditsiae Spina may be attributed to manufacturers using excessive non-medicinal parts in their formulations. ConclusionIt is suggested that enterprises should ensure the quality of raw material inputs， especially those without quality-control items in the standard， reduce the use of non-medicinal parts， and prohibit arbitrary alterations to manufacturing methods or processes. It is also recommended that Vaccariae Semen in Rukuaixiao capsules and granules should be changed to the stir-fried processed products. Isotoosendanin should be taken into consideration in the drug supervision when Toosendan Fructus is prepared into medicine by water decoction. Salvianolic acid B should be set as a quality control index for Salviae Miltiorrhizae Radix et Rhizoma when revising the pharmacopoeia standard of Rukuaixiao preparations.

This study aims to explore the effects and mechanisms of the traditional Chinese medicine Cordyceps sinensis(CS) in ameliorating heart aging and injury in mice based on animal experiments and network pharmacology. A mouse model of heart aging was established by continuously subcutaneous injection of D-galactose(D-gal). Thirty mice were randomly assigned into a normal group, a model group, a low-dose CS(CS-L) group, a high-dose CS(CS-H) group, and a vitamin E(VE) group. Mice in these groups were administrated with normal saline, different doses of CS suspension, or VE suspension via gavage daily. After 60 days of treatment with D-gal and various drugs, all mice were euthanized, and blood and heart tissue samples were collected for determination of the indicators related to heart aging and injury in mice. Experimental results showed that both high and low doses of CS and VE ameliorated the aging phenotype, improved the heart index and myocardial enzyme spectrum, restored the expression levels of proteins associated with cell cycle arrest and senescence-associated secretory phenotypes(SASP), and alleviated the fibrosis and histopathological changes of the heart tissue in model mice. From the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP),259 active ingredients of CS were retrieved. From Gene Cards and OMIM, 2 568 targets related to heart aging were identified, and 133common targets shared by CS and heart aging were obtained. The Gene Ontology(GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes( KEGG) pathway enrichment revealed that the pathways related to heart aging involved oxidative stress,apoptosis, inflammation-related signaling pathways, etc. The animal experiment results showed that both high and low doses of CS and VE ameliorated oxidative stress and apoptosis in the heart tissue to varying degrees in model mice. Additionally, CS-H and VE activated the nuclear factor E2-related factor 2(Nrf2)/heme oxygenase-1(HO-1) pathway and inhibited the expression of key proteins in the nuclear factor-κB(NF-κB) pathway in the heart tissue of model mice. In conclusion, this study demonstrated based on network pharmacology and animal experiments that CS may alleviate heart aging and injury in aging mice by reducing oxidative stress,apoptosis, and inflammation in the heart via the Nrf2/HO-1/NF-κB pathway.
Animals ; Cordyceps/chemistry* ; Mice ; NF-E2-Related Factor 2/genetics* ; NF-kappa B/genetics* ; Aging/genetics* ; Male ; Signal Transduction/drug effects* ; Network Pharmacology ; Drugs, Chinese Herbal/pharmacology* ; Heme Oxygenase-1/genetics* ; Heart/drug effects* ; Humans ; Myocardium/metabolism* ; Membrane Proteins/genetics*

This study aimed to investigate the effect of Dahuang Zhechong Pills(DHZCP) in delaying heart aging(HA) and explore the potential mechanism. Network pharmacology and molecular docking were employed to explore the targets and potential mechanisms of DHZCP in delaying HA. Furthermore, in vitro experiments were conducted with the DHZCP-containing serum to verify key targets and pathways in D-galactose(D-gal)-induced aging of cardiomyocytes. Active components of DHZCP were searched against the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCSMP), and relevant targets were predicted. HA-related targets were screened from the GeneCards, Online Mendelian Inheritance in Man(OMIM), and DisGeNET. The common targets shared by the active components of DHZCP and HA were used to construct a protein-protein interaction network in STRING 12.0, and core targets were screened based on degree in Cytoscape 3.9.1. Metaspace was used for Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analyses of the core targets to predict the mechanisms. Molecular docking was performed in AutoDock Vina. The results indicated that a total of 774 targets of the active components of DHZCP and 4 520 targets related to HA were screened out, including 510 common targets. Core targets included B-cell lymphoma 2(BCL-2), serine/threonine kinase 1(AKT1), and hypoxia-inducible factor 1 subunit A(HIF1A). The GO and KEGG enrichment analyses suggested that DHZCP mainly exerted its effects via the phosphatidylinositol 3-kinase(PI3K)/AKT signaling pathway, HIF-1α signaling pathway, longevity signaling pathway, and apoptosis signaling pathway. Among the pathways predicted by GO and KEGG enrichment analyses, the PI3K/AKT/HIF-1α signaling pathway was selected for verification. The cell-counting kit 8(CCK-8) assay showed that D-gal significantly inhibited the proliferation of H9c2 cells, while DHZCP-containing serum increased the viability of H9c2 cells. SA-β-gal staining revealed a significant increase in the number of blue-green positive cells in the D-gal group, which was reduced by DHZCP-containing serum. TUNEL staining showed that DHZCP-containing serum decreased the number of apoptotic cells. After treatment with DHZCP-containing serum, the protein levels of Klotho, BCL-2, p-PI3K/PI3K, p-AKT1/AKT1, and HIF-1α were up-regulated, while those of P21, P16, BCL-2 associated X protein(Bax), and cleaved caspase-3 were down-regulated. The results indicated that DHZCP delayed HA via multiple components, targets, and pathways. Specifically, DHZCP may delay HA by reducing apoptosis via activating the PI3K/AKT/HIF-1α signaling pathway.
Proto-Oncogene Proteins c-akt/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Signal Transduction/drug effects* ; Apoptosis/drug effects* ; Myocytes, Cardiac/cytology* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Animals ; Rats ; Humans ; Molecular Docking Simulation ; Aging/metabolism* ; Protein Interaction Maps/drug effects* ; Heart/drug effects* ; Network Pharmacology

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.

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.

This study aims to explore the core connotation of the compatibility of Aconiti Lateralis Radix Praeparata(Fuzi)-Glycyrrhizae Radix et Rhizoma(Gancao) herb pair under physiological and pathological conditions. The biochemical indicators of serum/myocardial tissue, pathological changes of the myocardial tissue, and serum metabolic profiles of normal rats and heart failure model rats treated with Fuzi Decoction and Fuzi Gancao Decoction were determined. Network pharmacology and metabolomics were employed to establish the metabolite-target-pathway network for Glycyrrhizae Radix et Rhizoma in enhancing the efficacy and reducing the toxicity of Aconiti Lateralis Radix Praeparata, Western blotting was employed to verify the representative pathways in the network. The results showed that both decoctions lowered the levels of creatine kinase and other indicators and mitigate myocardial pathological injury in model rats. However, they caused the abnormal rises in creatine kinase and other indicators and myocardial pathological injury in normal rats. The results indicated that the compatibility reduced the toxicity in normal rats and enhanced the efficacy in model rats. The results of metabolomics showed that Fuzi Gancao Decoction recovered more metabolites in model rats and had weaker effect on interfe-ring with the metabolites in normal rats than Fuzi Decoction. The association analysis showed that the network of Glycyrrhizae Radix et Rhizoma enhancing the efficacy of Aconiti Lateralis Radix Praeparata involved 112 metabolites, 89 targets, and 15 pathways, including calcium and cAMP signaling pathways. The network of Glycyrrhizae Radix et Rhizoma reducing the cardiotoxicity of Aconiti Lateralis Radix Praeparata involved 36 metabolites, 59 targets, and 11 pathways, including adrenergic signaling and tricarboxylic acid cycle in cardiomyocytes. The experimental results of protein expression verified the reliability of the association analysis. This study demonstrated that the core connotation of the herb pair of Aconiti Lateralis Radix Praeparata-Glycyrrhizae Radix et Rhizoma changed under physio-logical and pathological states, and the compatibility results of enhancing efficacy and reducing toxicity were achieved with different metabolic pathways and biological processes.