1.In Vitro and in vivo Component Analysis of Total Phenolic Acids from Gei Herba and Its Effect on Promoting Acute Wound Healing and Inhibiting Scar Formation
Xixian KONG ; Guanghuan TIAN ; Tong WU ; Shaowei HU ; Jie ZHAO ; Fuzhu PAN ; Jingtong LIU ; Yong DENG ; Yi OUYANG ; Hongwei WU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(3):156-167
ObjectiveBased on ultra performance liquid chromatography-quadrupole-electrostatic field orbital trap high-resolution mass spectrometry(UPLC-Q-Orbitrap-MS), to identify the in vivo and in vitro chemical components of total phenolic acids in Gei Herba(TPAGH), and to clarify the pharmacological effects and potential mechanisms of the effective part in promoting acute wound healing and inhibiting scar formation. MethodsUPLC-Q-Orbitrap-MS was used to identify the chemical components of TPAGH and ingredients absorbed in vivo after topical administration. A total of 120 ICR mice were randomly divided into the model group, recombinant human epidermal growth factor(rhEGF) group(4 mg·kg-1), and low, medium, and high dose groups of TPAGH(3.5, 7, 14 mg·kg-1), with 24 mice in each group. A full-thickness skin excision model was constructed, and each administration group was coated with the drug at the wound site, and the model group was treated with an equal volume of normal saline, the treatment was continued for 30 days, during which 8 mice from each group were sacrificed on days 6, 12, and 30. The healing of the wounds in the mice was observed, and histopathological changes in the skin tissues were dynamically observed by hematoxylin-eosin(HE), Masson, and Sirius red staining, and enzyme-linked immunosorbent assay(ELISA) was used to dynamically measure the contents of interleukin-6(IL-6), tumor necrosis factor-α(TNF-α), vascular endothelial growth factor A(VEGFA), matrix metalloproteinase(MMP)-3 and MMP-9 in skin tissues. Network pharmacology was used to predict the targets related to the promotion of acute wound healing and the inhibition of scar formation by TPAGH, and molecular docking of key components and targets was performed. Gene Ontology(GO) biological process analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were carried out for the related targets, so as to construct a network diagram of herbal material-compound-target-pathway-pharmacological effect-disease for further exploring its potential mechanisms. ResultsA total of 146 compounds were identified in TPAGH, including 28 phenylpropanoids, 31 tannins, 23 triterpenes, 49 flavonoids, and 15 others, and 16 prototype components were found in the serum of mice. Pharmacodynamic results showed that, compared with the model group, the TPAGH groups showed a significant increase in relative wound healing rate and relative scar inhibition rate(P<0.05), and the number of new capillaries, number of fibroblasts, number of new skin appendages, epidermal regeneration rate, collagen deposition ratio, and Ⅲ/Ⅰ collagen ratio in the tissue were significantly improved(P<0.05, 0.01), the levels of IL-6, TNF-α, MMP-3 and MMP-9 in the skin tissues were reduced to different degrees, while the level of VEGFA was increased. Network pharmacology analysis screened 10 core targets, including tumor protein 53(TP53), sarcoma receptor coactivator(SRC), protein kinase B(Akt)1, signal transducer and activator of transcription 3(STAT3), epidermal growth factor receptor(EGFR) and so on, participating in 75 signaling pathways such as advanced glycation end-products(AGE)-receptor for AGE(AGE/RAGE) signaling pathway, phosphatidylinositol 3-kinase(PI3K)/Akt signaling pathway, mitogen-activated protein kinase(MAPK) signaling pathway. Molecular docking confirmed that the key components genistein, geraniin, and casuariin had good binding ability to TP53, SRC, Akt1, STAT3 and EGFR. ConclusionThis study comprehensively reflects the chemical composition of TPAGH and the absorbed components after topical administration through UPLC-Q-Orbitrap-MS. TPAGH significantly regulates key indicators of skin healing and tissue reconstruction, thereby clarifying its role in promoting acute wound healing and inhibiting scar formation. By combining in vitro and in vivo component identification with network pharmacology, the study explores how key components may bind to targets such as TP53, Akt1 and EGFR, exerting therapeutic effects through related pathways such as immune inflammation and vascular regeneration.
2.Mechanism of Xuefu Zhuyutang in Intervening in Ferroptosis in Rats with Coronary Heart Disease with Blood Stasis Syndrome Based on ACSL4 Signalling Pathway
Yi LIU ; Yang YANG ; Chang SU ; Peng TIAN ; Mingyun WANG ; Ruqian ZHONG ; Xuejiao XIE ; Qing YAN ; Qinghua PENG ; Qiuyan ZHANG
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(6):27-38
ObjectiveTo investigate the mechanism of ferroptosis mediated by long-chain acyl-CoA synthetase 4 (ACSL4) signalling pathway in rats with coronary heart disease with blood stasis syndrome and the intervention effect of Xuefu Zhuyutang. MethodsSPF male SD rats were randomly divided into normal group, sham-operation group, model group, trimetazidine group (5.4 mg·kg-1), low-, medium-, and high-dose group (3.51, 7.02,14.04 g·kg-1) of Xuefu Zhuyutang. The coronary artery left anterior descending ligation method was used to prepare a model of coronary heart disease with blood stasis syndrome, and continuous treatment for 7 d was conducted, while the sham-operation group was only threaded and not ligated. The general macroscopic symptoms of the rats were observed, and indicators such as electrocardiogram, echocardiography, and blood rheology were detected. The pathological morphology of myocardial tissue was observed by hematoxylin-eosin (HE) staining, and the changes in mitochondria in myocardial tissue were observed by transmission electron microscopy. The level of iron deposition in myocardial tissue was observed by Prussian blue staining. The levels of 12-hydroxyeicosatetraenoic acid (12-HETE) and 15-HETE were detected in serum by enzyme-linked immunosorbent assay. A biochemical colourimetric assay was used to detect the levels of Fe2+, lipid peroxidation (LPO), glutathione (GSH), and T-GSH/glutathione disulfide (GSSG) in myocardial tissue. DCFH-DA fluorescence quantitative assay was employed to detect the levels of reactive oxygen species (ROS). Western blot and Real-time fluorescence quantitative polymerase chain reaction (Real-time PCR) was adopted to detect the protein and mRNA expressions of glutathione peroxidase 4 (GPX4), ferritin heavy chain 1 (FTH1), ACSL4, and ly-sophosphatidylcholine acyltransferase3 (LPCAT3) in myocardial tissue. ResultsCompared with those in the normal group, the rats in the model group were poor in general macroscopic symptoms. The electrocardiogram showed widened QRS wave amplitude and increased voltage, bow-back elevation of the ST segments, elevated T waves, J-point elevation, and accelerated heart rate. Echocardiography showed a significant reduction in left ventricular ejection fraction (LVEF) and left ventricular fraction shortening (LVFS) (P<0.01). Blood rheology showed that the viscosity of the whole blood (low, medium, and high rate of shear) was significantly increased (P<0.01). HE staining showed an abnormal structure of myocardial tissue. There was a large area of myocardial necrosis and inflammatory cell infiltration and a large number of connective tissue between myocardial fibers. Transmission electron microscopy showed that the mitochondria were severely atrophy or swelling. The cristae were reduced or even broken, and the matrix was flocculent or even vacuolated. Prussian blue staining showed that there were a large number of iron-containing particles, and the iron deposition was obvious. The content of 12-HETE and 15-HETE in the serum was significantly increased (P<0.01). The content of Fe2+, LPO, and ROS in myocardial tissue was significantly increased (P<0.01). The content of GSH was significantly decreased (P<0.01), and T-GSH/GSSG was decreased (P<0.01). The protein and mRNA expressions of GPX4 and FTH1 in myocardial tissue were both significantly decreased (P<0.05, P<0.01), while those of ACSL4 and LPCAT3 increased significantly (P<0.01). Compared with the model group, the general macroscopic symptoms and electrocardiogram results of rats in low-, medium- and high-dose groups of Xuefu Zhuyutang were alleviated, and the differences in LVEF/LVFS ratios were all significantly increased (P<0.05, P<0.01). The differences in whole-blood viscosity (low, medium, and high rate of shear) were all significantly decreased (P<0.01). The results of HE staining and transmission electron microscopy showed that the morphology, structure, and mitochondria of cardiomyocytes were improved. The content of 12-HETE and 15-HETE in serum was reduced to different degrees in low-, medium-, and high-dose groups of Xuefu Zhuyutang (P<0.05, P<0.01). The content of Fe2+, LPO, and ROS was significantly reduced in the medium- and high-dose groups of Xuefu Zhuyutang (P<0.05, P<0.01), and the content of GSH and T-GSH/GSSG was significantly increased (P<0.05, P<0.01). The protein and mRNA expressions of GPX4 and FTH1 were significantly increased to varying degrees in the medium- and high-dose groups of Xuefu Zhuyutang (P<0.05, P<0.01), and ACSL4 and LPCAT3 were decreased to different degrees in the low-, medium-, and high-dose groups of Xuefu Zhuyutang (P<0.05, P<0.01). ConclusionXuefu Zhuyutang can regulate iron metabolism and anti-lipid oxidation reaction to mediate ferroptosis through the ACSL4 signalling pathway, thus exerting a protective effect on rats with coronary heart disease with blood stasis syndrome.
3.Breakthrough cases of mumps in Ningbo City
TIAN Haiyan ; LI Baojun ; CHEN Yi
Journal of Preventive Medicine 2025;37(3):292-295
Objective:
To investigate the characteristics of the breakthrough cases of mumps in Ningbo City, Zhejiang Province from 2018 to 2023, so as to provide insights into improving prevention and control measures for mumps.
Methods:
Data of mumps cases and mumps containing vaccine (MuCV) vaccination in Ningbo City from 2018 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System and Zhejiang Immunization Planning Information System. The population distribution characteristics and MuCV immunization history of mumps breakthrough cases were described. The impacts of the final immunization age and immunization interval on the age of onset were analyzed.
Results:
A total of 6 643 mumps cases were reported in Ningbo City from 2018 to 2023, with an average incidence rate of 11.72/105. There were 5 142 breakthrough cases (77.40%), including 3 173 males (61.71%) and 1 969 females (38.29%). The median age of onset was 6.00 (interquartile range, 4.00) years. There were 2 487 cases in preschool children (48.37%) and 2 232 cases in students (43.41%). There were 4 736 one-dose breakthrough cases (92.10%) and 406 two-dose breakthrough cases (7.90%). The proportion of two-dose breakthrough cases among all mumps cases increased from 1.00% in 2018 to 25.32% in 2023. Among individuals born after December 2018, the median age of onset of two-dose breakthrough cases was 3.00 (interquartile range, 1.00) years, which was older than that of one-dose breakthrough cases at 1.00 (interquartile range, 2.00) year (P<0.05). The ages of onset of mumps breakthrough cases differed significantly with varying final immunization ages and immunization intervals (both P<0.05).
Conclusions
The breakthrough cases of mumps in Ningbo City from 2018 to 2023 were mainly males, preschool children and students. The proportion of two-dose breakthrough cases increased, and the age of onset delayed.
4.Study of adsorption of coated aldehyde oxy-starch on the indexes of renal failure
Qian WU ; Cai-fen WANG ; Ning-ning PENG ; Qin NIE ; Tian-fu LI ; Jian-yu LIU ; Xiang-yi SONG ; Jian LIU ; Su-ping WU ; Ji-wen ZHANG ; Li-xin SUN
Acta Pharmaceutica Sinica 2025;60(2):498-505
The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure
5.Mitochondria: The Target of Ionizing Radiation Damage
Lian-Chen TIAN ; Ya-Yi YUAN ; Xu-Hong DANG
Progress in Biochemistry and Biophysics 2025;52(4):836-844
In recent years, due to the development of radiotherapy technology and nuclear energy, people have paid more and more attention to the various effects of ionizing radiation on organisms. Ionizing radiation can induce protein, DNA and other biological macromolecules to damage, resulting in apoptosis, senescence, cancer and a series of changes. For a long time, it has been believed that the main target of ionizing radiation damage is DNA in the nucleus. However, it has been reported in recent years that ionizing radiation has both direct and indirect effects, and the theory of ROS damage in the indirect effects believes that ionizing radiation has target uncertainty, so it is not comprehensive enough to evaluate only the DNA damage in the nucleus. It has been reported that ionizing radiation can cause damage to organelles as well as damage to cells. Mitochondria are important damaged organelles because mitochondria occupy as much as 30% of the entire cell volume in the cytoplasm, which contains DNA and related enzymes that are closely related to cellular ATP synthesis, aerobic respiration and other life activities. What is more noteworthy is that mitochondria are the only organelles in which DNA exists in the human body, which makes researchers pay attention to various damage to mitochondrial DNA caused by ionizing radiation (such as double-strand breaks, base mismatching, and fragment loss). Although these damages also occur in the nucleus, mitochondrial DNA is more severely damaged than nuclear DNA due to its lack of histone protection, so mitochondria are important targets of ionizing radiation damage in addition to the nucleus. Mitochondrial DNA is not protected by histones and has little repair ability. When exposed to ionizing radiation, common deletions occur at an increased frequency and are passed on to offspring. For large-scale mitochondrial DNA damage, mitochondria indirectly compensate for the amount of damaged DNA by increasing the number of DNA copies and maintaining the normal function of mitochondrial DNA. Mitochondria are in a state of oxidative stress after exposure to ionizing radiation, and this oxidative stress will promote the change in mitochondrial function. When mitochondria are damaged, the activity of proteins related to aerobic respiration decreases, and oxidative respiration is inhibited to a certain extent. At the same time, a large amount of active superoxide anions are continuously produced to stimulate mitochondrial oxidative stress, and the signal of such damage is transmitted to the surrounding mitochondria, resulting in a cascade of damage reaction, which further activates the signalling pathway between mitochondria and nucleus. The cell nucleus is also in a state of oxidative stress, and finally, the level of free radicals is high, causing secondary damage to the genetic material DNA of mitochondria and nucleus. In this paper, the damage effects of ionizing radiation on mitochondria are reviewed, to provide a new idea for radiation protection.
6.Inhibition of HDAC3 Promotes Psoriasis Development in Mice Through Regulating Th17
Fan XU ; Xin-Rui ZHANG ; Yang-Chen XIA ; Wen-Ting LI ; Hao CHEN ; An-Qi QIN ; Ai-Hong ZHANG ; Yi-Ran ZHU ; Feng TIAN ; Quan-Hui ZHENG
Progress in Biochemistry and Biophysics 2025;52(4):1008-1017
ObjectiveTo investigate the influence of histone deacetylase 3 (HDAC3) on the occurrence, development of psoriasis-like inflammation in mice, and the relative immune mechanisms. MethodsHealthy C57BL/6 mice aged 6-8 weeks were selected and randomly divided into 3 groups: control group (Control), psoriasis model group (IMQ), and HDAC3 inhibitor RGFP966-treated psoriasis model group (IMQ+RGFP966). One day prior to the experiment, the back hair of the mice was shaved. After a one-day stabilization period, the mice in Control group was treated with an equal amount of vaseline, while the mice in IMQ group was treated with imiquimod (62.5 mg/d) applied topically on the back to establish a psoriasis-like inflammation model. The mice in IMQ+RGFP966 group received intervention with a high dose of the HDAC3-selective inhibitor RGFP966 (30 mg/kg) based on the psoriasis-like model. All groups were treated continuously for 5 d, during which psoriasis-like inflammation symptoms (scaling, erythema, skin thickness), body weight, and mental status were observed and recorded, with photographs taken for documentation. After euthanasia, hematoxylin-eosin (HE) staining was used to assess the effect of RGFP966 on the skin tissue structure of the mice, and skin thickness was measured. The mRNA and protein expression levels of HDAC3 in skin tissues were detected using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot (WB), respectively. Flow cytometry was employed to analyze neutrophils in peripheral blood and lymph nodes, CD4+ T lymphocytes, CD8+ T lymphocytes in peripheral blood, and IL-17A secretion by peripheral blood CD4+ T lymphocytes. Additionally, spleen CD4+ T lymphocyte expression of HDAC3, CCR6, CCR8, and IL-17A secretion levels were analyzed. Immunohistochemistry was used to detect the localization and expression levels of HDAC3, IL-17A, and IL-10 in skin tissues. ResultsCompared with the Control group, the IMQ group exhibited significant psoriasis-like inflammation, characterized by erythema, scaling, and skin wrinkling. Compared with the IMQ group, RGFP966 exacerbated psoriasis-like inflammatory symptoms, leading to increased hyperkeratosis. The psoriasis area and severity index (PASI) skin symptom scores were higher in the IMQ group than those in the Control group, and the scores were further elevated in the IMQ+RGFP966 group compared to the IMQ group. Skin thickness measurements showed a trend of IMQ+RGFP966>IMQ>Control. The numbers of neutrophils in the blood and lymph nodes increased sequentially in the Control, IMQ, and IMQ+RGFP966 groups, with a similar trend observed for CD4+ and CD8+ T lymphocytes in the blood. In skin tissues, compared with the Control group, the mRNA and protein levels of HDAC3 decreased in the IMQ group, but RGFP966 did not further reduce these expressions. HDAC3 was primarily located in the nucleus. Compared with the Control group, the nuclear HDAC3 content decreased in the skin tissues of the IMQ group, and RGFP966 further reduced nuclear HDAC3. Compared with the Control and IMQ groups, RGFP966 treatment decreased HDAC3 expression in splenic CD4+ and CD8+ T cells. RGFP966 treatment increased the expression of CCR6 and CCR8 in splenic CD4+ T cells and enhanced IL-17A secretion by peripheral blood and splenic CD4+ T lymphocytes. Additionally, compared with the IMQ group, RGFP966 reduced IL-10 protein levels and upregulated IL-17A expression in skin tissues. ConclusionRGFP966 exacerbates psoriatic-like inflammatory responses by inhibiting HDAC3, increasing the secretion of the cytokine IL-17A, and upregulating the expression of chemokines CCR8 and CCR6.
7.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
Objective:
Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.
Methods:
Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).
Results:
LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.
Conclusion
Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.
8.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
Objective:
Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.
Methods:
Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).
Results:
LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.
Conclusion
Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.
9.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
Objective:
Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.
Methods:
Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).
Results:
LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.
Conclusion
Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.
10.Comparison of Logistic Regression and Machine Learning Approaches in Predicting Depressive Symptoms: A National-Based Study
Xing-Xuan DONG ; Jian-Hua LIU ; Tian-Yang ZHANG ; Chen-Wei PAN ; Chun-Hua ZHAO ; Yi-Bo WU ; Dan-Dan CHEN
Psychiatry Investigation 2025;22(3):267-278
Objective:
Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic.
Methods:
Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC).
Results:
LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models.
Conclusion
Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.


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