ObjectiveTo observe the changes in the levels of different subtypes of epidermal growth factor receptor （ErbB）， namely ErbB1， ErbB2， ErbB3， and ErbB4， in the spinal dorsal horn of inflammatory pain model rats， and to explore their mechanism of mediating hyperalgesia as well as the intervention mechanism of electroacupuncture at "Zusanli （ST 36）" and "Kunlun （BL 60）". MethodsThe study was divided into five parts. In experiment 1， 14 Sprague Dawley （SD） rats were randomly divided into control and inflammatory pain group （7 rats each group） to observe the pain behavior and the protein expression of different ErbB receptor subtypes in the spinal dorsal horn. In experiment 2， 30 rats were randomly divided into control group 1， inflammatory pain group 1， and low-， medium-， and high-concentration TX1-85-1 groups， with 6 rats in each group， to observe the effect of inhibiting spinal ErbB3 on inflammatory pain. In experiment 3， 12 rats were randomly divided into control virus group and ErbB3 knockdown virus group， with 6 rats in each group， to observe the effect of knocking down ErbB3 in the spinal dorsal horn on inflammatory pain. In experiment 4， 44 rats were randomly divided into control group 2， inflammatory pain group 2， electroacupuncture group， and sham electroacupuncture group， with 11 rats in each group， to observe the effect of electroacupuncture. In experiment 5， 40 rats were randomly divided into control group 3， inflammatory pain group 3， electroacupuncture group 1， and electroacupuncture + NRG1 group， with 10 rats in each group， to observe the effect of activating ErbB3 on electroacupuncture. A rat model of inflammatory pain was established by subcutaneous injection of 100 μl of complete Freund's adjuvant into the sole of the unilateral hind foot of SD rats. Rats in the low-， medium-， and high-concentration TX1-85-1 groups were intrathecally injected with ErbB3 inhibitor TX1-85-1 on day 5 to day 7 after modeling. Rats in the ErbB3 knockdown virus group were injected with ErbB3 knockdown virus packaged with adenovirus vector-based short hairpin RNA （shRNA） into the spinal dorsal horn in situ 3 weeks before modeling. Rats in each electroacupuncture group received electroacupuncture at bilateral "Zusanli （ST 36）" and "Kunlun （BL 60）" from day 1 to day 7 after modeling， with dense-sparse waves at a frequency of 2 Hz/100 Hz and a current of 0.5-1.5 mA for 30 minutes once a day. Rats in the electroacupuncture + NRG1 group were intrathecally injected with ErbB3 ligand recombinant human neuregulin-1 （NRG1） after electroacupuncture intervention from day 5 to day 7 after modeling. The mechanical withdrawal threshold and thermal withdrawal latency of rats were measured on day 1， 3， 5， and 7 after modeling to evaluate behavior， and Western Blot was used to detect the protein and phosphorylation levels of each ErbB subtype in the spinal dorsal horn. ResultsCompared with the control group， rats in the inflammatory pain group showed decreased mechanical withdrawal threshold and thermal withdrawal latency of rats， and increased expression of phosphorylated ErbB3 （p-ErbB3） protein in the spinal dorsal horn on days 1， 3， 5， and 7 after modeling （P＜0.01）. On day 5 and day 7 after modeling， compared with the inflammatory pain group 1， the mecha-nical withdrawal threshold and thermal withdrawal latency of rats in the medium- and high-concentration TX1-85-1 groups increased， and the expression of p-ErbB3 protein decreased （P＜0.05）. On day 1， 3， 5， and 7 after modeling， compared with the control virus group， the mechanical withdrawal threshold and thermal withdrawal latency of rats in the ErbB3 knockdown virus group increased （P＜0.05）. On day 5 and day 7 after modeling， compared with the inflammatory pain group 2 and the sham electroacupuncture group， the mechanical withdrawal threshold and thermal withdrawal latency of rats in the electroacupuncture group increased， and the expression of p-ErbB3 protein decreased （P＜0.05）. On day 5 and day 7 after modeling， compared with the electroacupuncture + NRG1 group， the mechanical withdrawal threshold and thermal withdrawal latency of rats in the electroacupuncture group 1 increased （P＜0.05）. ConclusionThe p-ErbB3 in the spinal dorsal horn involved in hyperalgesia in rats with inflammatory pain， and electroacupuncture at "Zusanli （ST 36）" and "Kunlun （BL 60）" can alleviate inflammatory pain by inhibiting the expression of p-ErbB3 protein in the spinal dorsal horn of rats.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

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.

ObjectiveTo understand the epidemiological distribution and gene evolutionary variation of influenza A (H3N2) viruses in Fengxian District, Shanghai, in the surveillance year of 2023, and to provide a reference basis for influenza prevention and control. MethodsThe prevalence of influenza virus in Fengxian District in the 2023 influenza surveillance year (April 2023‒March 2024) was analyzed. The hemagglutinin (HA) gene, neuraminidase (NA) gene, and amino acid sequences of 75 strains of H3N2 influenza viruses were compared with the vaccine reference strain for similarity matching and phylogenetic evolutionary analysis, in addition to an analysis of gene characterization and variation. ResultsIn Fengxian District, there was a mixed epidemic of H3N2 and H1N1 in the spring of 2023, with H3N2 being the predominant subtype in the second half of the year, and Victoria B becoming the predominant subtype in the spring of 2024. A total of 75 influenza strains of H3N2 with HA and NA genes were distributed in the 3C.2a1b.2a.2a.2a.3a.1 and B.4 branches, with overall similarity to the reference strain of the 2024 vaccine higher than that of the reference strain of the 2022 and 2023 vaccine. Compared with the 2023 vaccine reference strain, three antigenic sites and one receptor binding site were changed in HA, with three glycosylation sites reduced and two glycosylation sites added; where as in NA seven antigenic sites and the 222nd resistance site changed with two glycosylation sites reduced. ConclusionThe risk of antigenic variation and drug resistance of H3N2 in this region is high, and it is necessary to strengthen the publicity and education on the 2024 influenza vaccine and long-term monitoring of influenza virus prevalence and variation levels.

OBJECTIVE To understand the development status and existing problems of traditional Chinese medicine（TCM） pharmacists in public TCM hospitals in China， aiming to provide suggestions for the competent departments to formulate management policies for TCM pharmacists and promote the healthy development of TCM. METHODS The data on the number and professional titles of TCM pharmacists in public TCM hospitals in China from 2019 to 2023 were collected. Descriptive analysis was employed to analyze the number， distribution and professional titles of TCM pharmacists in public TCM hospitals across the country， and to measure the quantity shortfalls of the number of TCM pharmacists in these hospitals. RESULTS From 2019 to 2023， the number of TCM pharmacists in public TCM hospitals in China grew slowly， with an average annual growth rate of 2.56%. However， the proportion of TCM pharmacists to the total number of pharmacists in public TCM hospitals gradually decreased， with an average annual growth rate of －0.65%. In terms of hospital grades， the number of TCM pharmacists in tertiary public TCM hospitals showed positive growth， while those in secondary and primary public TCM hospitals showed negative growth. In terms of hospital types， the average annual growth rate of TCM pharmacists in TCM hospitals was 2.22%， in integrated Chinese and Western medicine hospitals it was 7.97%， and in ethnic minority medicine hospitals it was 2.74%. The development of TCM pharmacists in different provinces was uneven. The annual growth rate of TCM pharmacists in Guizhou exceeded 10%， while the growth rate in Hunan and Heilongjiang was negative. In 2023， the number of TCM pharmacists per thousand population in public TCM hospitals was 0.03， indicating a relatively low staffing level. The professional titles of TCM pharmacists in public TCM hospitals were mainly primary and E-mail：601907549@qq.com intermediate， with a total of 67.33%. According to the calculation that the proportion of TCM pharmacists to pharmacists was not less than 60%， public TCM hospitals and hospitals of integrated TCM and Western medicine should be reconfigured with TCM pharmacists 6 212 and 1 288 people， respectively. CONCLUSIONS The number of TCM pharmacists in public TCM hospitals is growing slowly， with insufficient staffing levels， relatively low professional titles， and uneven distribution and development across provinces. It is suggested that relevant competent departments strengthen policy guidance， increase the attention given by the state level to TCM pharmacists， strengthen the construction of the talent team for TCM pharmacists， improve the quality and optimize the allocation of TCM pharmacist talents in order to promote the high-quality development of TCM services.

ObjectiveTo investigate the protective effect and mechanism of Shaoyaotang （SYD） on the lipopolysaccharide （LPS）-induced damage of tight junction proteins in the human colorectal adenocarcinoma （Caco-2） cell model of inflammation via the Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） pathway. MethodsCaco-2 cells were grouped as follows： Blank， model （LPS， 10 mg·L^-1）， SYD-containing serum （10%， 15%， and 20%）， and inhibitor （Fasudil， 25 μmol·L^-1）. After 24 hours of intervention， the cell viability in each group was examined by the cell-counting kit 8 （CCK-8） method. Enzyme-linked immunosorbent assay was employed to determine the levels of endothelin-1 （ET-1）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of RhoA， ROCK2， claudin-5， and zonula occludens-1 （ZO-1） in cells of each group. ResultsCompared with the blank group， the model group showcased a marked reduction in the cell viability （P<0.01）， elevations in the levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， declines in both mRNA and protein levels of ZO-1 and claudin-5 （P<0.01）， and rises in mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Compared with the model group， the Shaoyaotang-containing serum （10%， 15%， and 20%） groups had enhanced cell viability （P<0.01）， lowered levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， up-regulated mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and down-regulated mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Moreover， the inhibitor group and the 15% and 20% Shaoyaotang-containing serum groups had lower levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， higher mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and lower mRNA and protein levels of RhoA and ROCK2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can lower the levels of LPS-induced increases in levels of inflammatory cytokines and endothelin to ameliorate the damage of tight junction proteins of the Caco-2 cell model of inflammation by regulating the expression of proteins in the RhoA/ROCK pathway.

ObjectiveTo investigate the protective effect and mechanism of Shaoyaotang （SYD） on the lipopolysaccharide （LPS）-induced damage of tight junction proteins in the human colorectal adenocarcinoma （Caco-2） cell model of inflammation via the Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） pathway. MethodsCaco-2 cells were grouped as follows： Blank， model （LPS， 10 mg·L^-1）， SYD-containing serum （10%， 15%， and 20%）， and inhibitor （Fasudil， 25 μmol·L^-1）. After 24 hours of intervention， the cell viability in each group was examined by the cell-counting kit 8 （CCK-8） method. Enzyme-linked immunosorbent assay was employed to determine the levels of endothelin-1 （ET-1）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of RhoA， ROCK2， claudin-5， and zonula occludens-1 （ZO-1） in cells of each group. ResultsCompared with the blank group， the model group showcased a marked reduction in the cell viability （P<0.01）， elevations in the levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， declines in both mRNA and protein levels of ZO-1 and claudin-5 （P<0.01）， and rises in mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Compared with the model group， the Shaoyaotang-containing serum （10%， 15%， and 20%） groups had enhanced cell viability （P<0.01）， lowered levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， up-regulated mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and down-regulated mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Moreover， the inhibitor group and the 15% and 20% Shaoyaotang-containing serum groups had lower levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， higher mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and lower mRNA and protein levels of RhoA and ROCK2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can lower the levels of LPS-induced increases in levels of inflammatory cytokines and endothelin to ameliorate the damage of tight junction proteins of the Caco-2 cell model of inflammation by regulating the expression of proteins in the RhoA/ROCK pathway.

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.

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.

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.