1.Pharmacological effects of Yindan Pinggan capsules in treating intrahepatic cholestasis
Shu-xin CAO ; Feng HUANG ; Fang WU ; Rong-rong HE
Acta Pharmaceutica Sinica 2025;60(2):417-426
This study aimed to investigate the therapeutic effect of Yindan Pinggan capsules (YDPG) on intrahepatic cholestasis (IHC) through animal experiments, while utilizing network pharmacology and molecular docking techniques to explore its potential mechanisms. Initially, the therapeutic effect of YDPG on an
2.Design, synthesis and anti-Alzheimer's disease activity evaluation of cinnamyl triazole compounds
Wen-ju LEI ; Zhong-di CAI ; Lin-jie TAN ; Mi-min LIU ; Li ZENG ; Ting SUN ; Hong YI ; Rui LIU ; Zhuo-rong LI
Acta Pharmaceutica Sinica 2025;60(1):150-163
19 cinnamamide/ester-triazole compounds were designed, synthesized and evaluated for their anti-Alzheimer's disease (AD) activity. Among them, compound
3.Brief introduction on the development of Chinese Pharmacopoeia 2025 Edition
HONG Xiaoxu ; SONG Zonghua ; MA Shuangcheng ; LAN Fen ; SHU Rong
Drug Standards of China 2025;26(1):001-010
The Pharmacopoeia of the People’s Republic of China 2025 edition is to be issued in March 2025. Chinese Pharmacopoeia is the basic requirements on the drug manufacture, drug testing, drug use and drug administration. The new edition Chinese Pharmacopoeia will be dramatically improved on the pharmacopoeia monographs included, establishing the standards system, standards conversion and application of drug quality control for the new technology, new method & new tool, drug control on the safety and effectiveness as well as the drug standard international harmonization. It will take important role on improving the drug quality, ensuring the safety of drugs for public use, strengthen technical support for drug administration, promoting the high-quality development of China’s medical and pharmaceutical industry. This paper introduces the development and revision of the Chinese Pharmacopoeia 2025 Edition,aim at helping the industries well understanding and implantation the new edition Chinese Pharmacopoeia.
4.The Mechanism of Blue Light in Inactivating Microorganisms and Its Applications in The Food and Medical Fields
Ruo-Hong BI ; Rong-Qian WU ; Yi LÜ ; Xiao-Fei LIU
Progress in Biochemistry and Biophysics 2025;52(5):1219-1228
Blue light inactivation technology, particularly at the 405 nm wavelength, has demonstrated distinct and multifaceted mechanisms of action against both Gram-positive and Gram-negative bacteria, offering a promising alternative to conventional antibiotic therapies. For Gram-positive pathogens such as Bacillus cereus, Listeria monocytogenes, and methicillin-resistant Staphylococcus aureus (MRSA), the bactericidal effects are primarily mediated by endogenous porphyrins (e.g., protoporphyrin III, coproporphyrin III, and uroporphyrin III), which exhibit strong absorption peaks between 400-430 nm. Upon irradiation, these porphyrins are photoexcited to generate cytotoxic reactive oxygen species (ROS), including singlet oxygen, hydroxyl radicals, and superoxide anions, which collectively induce oxidative damage to cellular components. Early studies by Endarko et al. revealed that (405±5) nm blue light at 185 J/cm² effectively inactivated L. monocytogenes without exogenous photosensitizers, supporting the hypothesis of intrinsic photosensitizer involvement. Subsequent work by Masson-Meyers et al. demonstrated that 405 nm light at 121 J/cm² suppressed MRSA growth by activating endogenous porphyrins, leading to ROS accumulation. Kim et al. further elucidated that ROS generated under 405 nm irradiation directly interact with unsaturated fatty acids in bacterial membranes, initiating lipid peroxidation. This process disrupts membrane fluidity, compromises structural integrity, and impairs membrane-bound proteins, ultimately causing cell death. In contrast, Gram-negative bacteria such as Salmonella, Escherichia coli, Helicobacter pylori, Pseudomonas aeruginosa, and Acinetobacter baumannii exhibit more complex inactivation pathways. While endogenous porphyrins remain central to ROS generation, studies reveal additional photodynamic contributors, including flavins (e.g., riboflavin) and bacterial pigments. For instance, H. pylori naturally accumulates protoporphyrin and coproporphyrin mixtures, enabling efficient 405 nm light-mediated inactivation without antibiotic resistance concerns. Kim et al. demonstrated that 405 nm light at 288 J/cm² inactivates Salmonella by inducing genomic DNA oxidation (e.g., 8-hydroxy-deoxyguanosine formation) and disrupting membrane functions, particularly efflux pumps and glucose uptake systems. Huang et al. highlighted the enhanced efficacy of pulsed 405 nm light over continuous irradiation for E. coli, attributing this to increased membrane damage and optimized ROS generation through frequency-dependent photodynamic effects. Environmental factors such as temperature, pH, and osmotic stress further modulate susceptibility, sublethal stress conditions (e.g., high salinity or acidic environments) weaken bacterial membranes, rendering cells more vulnerable to subsequent ROS-mediated damage. The 405 nm blue light inactivates drug-resistant Pseudomonas aeruginosa through endogenous porphyrins, pyocyanin, and pyoverdine, with the inactivation efficacy influenced by bacterial growth phase and culture medium composition. Intriguingly, repeated 405 nm exposure (20 cycles) failed to induce resistance in A. baumannii, with transient tolerance linked to transient overexpression of antioxidant enzymes (e.g., superoxide dismutase) or stress-response genes (e.g., oxyR). For Gram-positive bacteria, porphyrin abundance dictates sensitivity, whereas in Gram-negative species, membrane architecture and accessory pigments modulate outcomes. Critically, ROS-mediated damage is nonspecific, targeting DNA, proteins, and lipids simultaneously, thereby minimizing resistance evolution. The 405 nm blue light technology, as a non-chemical sterilization method, shows promise in medical and food industries. It enhances infection control through photodynamic therapy and disinfection, synergizing with red light for anti-inflammatory treatments (e.g., acne). In food processing, it effectively inactivates pathogens (e.g., E. coli, S. aureus) without altering food quality. Despite efficacy against multidrug-resistant A. baumannii, challenges include device standardization, limited penetration in complex materials, and optimization of photosensitizers/light parameters. Interdisciplinary research is needed to address these limitations and scale applications in healthcare, food safety, and environmental decontamination.
5.Healing Through Loss: Exploring Nurses’ Post-Traumatic Growth After Patient Death
YongHan KIM ; Joon-Ho AHN ; Jangho PARK ; Young Rong BANG ; Jin Yong JUN ; Youjin HONG ; Seockhoon CHUNG ; Junseok AHN ; C. Hyung Keun PARK
Psychiatry Investigation 2025;22(1):40-46
Objective:
This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required.
Methods:
An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed.
Results:
PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator.
Conclusion
PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.
6.Healing Through Loss: Exploring Nurses’ Post-Traumatic Growth After Patient Death
YongHan KIM ; Joon-Ho AHN ; Jangho PARK ; Young Rong BANG ; Jin Yong JUN ; Youjin HONG ; Seockhoon CHUNG ; Junseok AHN ; C. Hyung Keun PARK
Psychiatry Investigation 2025;22(1):40-46
Objective:
This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required.
Methods:
An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed.
Results:
PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator.
Conclusion
PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.
7.Healing Through Loss: Exploring Nurses’ Post-Traumatic Growth After Patient Death
YongHan KIM ; Joon-Ho AHN ; Jangho PARK ; Young Rong BANG ; Jin Yong JUN ; Youjin HONG ; Seockhoon CHUNG ; Junseok AHN ; C. Hyung Keun PARK
Psychiatry Investigation 2025;22(1):40-46
Objective:
This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required.
Methods:
An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed.
Results:
PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator.
Conclusion
PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.
8.Healing Through Loss: Exploring Nurses’ Post-Traumatic Growth After Patient Death
YongHan KIM ; Joon-Ho AHN ; Jangho PARK ; Young Rong BANG ; Jin Yong JUN ; Youjin HONG ; Seockhoon CHUNG ; Junseok AHN ; C. Hyung Keun PARK
Psychiatry Investigation 2025;22(1):40-46
Objective:
This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required.
Methods:
An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed.
Results:
PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator.
Conclusion
PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.
9.Healing Through Loss: Exploring Nurses’ Post-Traumatic Growth After Patient Death
YongHan KIM ; Joon-Ho AHN ; Jangho PARK ; Young Rong BANG ; Jin Yong JUN ; Youjin HONG ; Seockhoon CHUNG ; Junseok AHN ; C. Hyung Keun PARK
Psychiatry Investigation 2025;22(1):40-46
Objective:
This study aimed to identify the factors contributing to post-traumatic growth (PTG) among nurses who experienced patient death during the coronavirus disease-2019 (COVID-19) pandemic and to evaluate the necessity of grief support is required.
Methods:
An online survey was conducted to assess the experiences of nurses at Ulsan University Hospital who lost patients during the past year of the pandemic. In total, 211 nurses were recruited. We obtained information on the participants’ demographic and clinical characteristics. For symptoms rating, we used the following scales: the Post-traumatic Growth Inventory (PTGI), Stress and Anxiety to Viral Epidemic-9 (SAVE-9), Patient Health Questionnaire (PHQ-9), Pandemic Grief Scale (PGS), and Utrecht Grief Rumination Scale (UGRS), and Grief Support in Healthcare Scale (GSHCS). Pearson’s correlation coefficients, linear regression, and mediation analysis were employed.
Results:
PTGI scores were significantly correlated with the SAVE-9 (r=0.31, p<0.01), PHQ-9 (r=0.31, p<0.01), PGS (r=0.28, p<0.01), UGRS (r=0.45, p<0.01), and GSHCS scores (r=0.46, p<0.01). The linear regression analysis revealed the factors significantly associated with PTGI scores: SAVE-9 (β=0.16, p=0.014), UGRS (β=0.29, p<0.001), and GSHCS (β=0.34, p<0.001). The mediation analysis revealed that nurses’ stress and anxiety about COVID-19 and grief rumination had a direct impact on PTG, with grief support serving as a significant mediator.
Conclusion
PTG was promoted by increases in the medical staff’s anxiety and stress related to COVID-19, grief rumination, and grief support. For the medical staff’s experience of bereavement to result in meaningful personal and professional growth, family members, colleagues, and other associates should provide thoughtful support.
10.Danggui Shaoyaosan Combined with Yinchenhaotang Regulates Lipid Metabolism to Ameliorate Type 2 Diabetes Mellitus Complicated with Metabolic Dysfunction-associated Steatotic Liver Disease
Yilin XU ; Liu LI ; Junju ZOU ; Hong LI ; Rong YU
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(15):38-47
ObjectiveTo explore the regulatory effect and mechanism of Danggui Shaoyaosan combined with Yinchenhaotang on lipid metabolism in the mouse model of type 2 diabetes mellitus (T2DM) complicated with metabolic dysfunction-associated steatotic liver disease (MASLD) based on network pharmacology and animal experiments. MethodsTwenty-four MKR transgenic diabetic mice were randomly allocated into 4 groups: Model, low-dose (12.6 g·kg-1) Chinese medicine (concentrated decoction of Danggui Shaoyaosan combined with Yinchenhaotang), high-dose (25.2 g·kg-1) Chinese medicine, and Western medicine (metformin, 0.065 g·kg-1). Six FVB mice were used as the normal group. All groups were treated for 6 consecutive weeks. The mice in the drug treatment groups were administrated with corresponding agents by gavage, and those in the normal group and model group received the same volume of distilled water. Fasting blood glucose, body weight, liver weight, glucose tolerance, liver function indicators, blood lipid levels, and pathological changes in the liver were evaluated for each group. Network pharmacology was employed to analyze the targets and pathways of Danggui Shaoyaosan combined with Yinchenhaotang in the treatment of T2DM complicated with MASLD. Molecular biological techniques were used to verify the enriched key targets. ResultsCompared with the model group, each treatment group showed reduced fasting blood glucose, body weight, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and liver weight (P<0.01). The high-dose Chinese medicine group was superior to the low-dose group in reducing low-density lipoprotein (LDL), increasing high-density lipoprotein (HDL), and recovering glucose tolerance (AUC) and ALT (P<0.05), with the effect similar to that of the Western medicine group. Morphologically, Chinese medicine groups showed reduced lipid accumulation and alleviated pathological damage in the liver tissue, with the high-dose group demonstrating more significant changes. Network pharmacology results showed that Danggui Shaoyaosan combined with Yinchenhaotang may exert therapeutic effects through multiple targets such as fatty acid synthase (FAS), acetyl-CoA carboxylase (ACC), B-cell lymphoma-2 (Bcl-2), MYC oncogene (MYC), and interleukin-1β (IL-1β). Western blot showed that compared with the model group, the treatment groups demonstrated down-regulated protein levels of FAS and ACC (P<0.01) and up-regulated protein levels of peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) and UCP1 (P<0.01). Compared with the low-dose Chinese medicine group, the high-dose Chinese medicine group exhibited down-regulated protein levels of FAS and ACC and up-regulated protein levels of PGC-1α and UCP1 (P<0.05). ConclusionDanggui Shaoyaosan combined with Yinchenhaotang has the effect of ameliorating T2DM complicated with MASLD and can improve the liver lipid metabolism by up-regulating the protein levels of Fas and ACC and down-regulating the protein levels of PGC-1α and UCP1.

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