This study summarizes Professor Qin Zhenhua's clinical experience in treating cutaneous pruritus using a modified self-prescribed formula,Yinqiao Xingzi Decoction.Following the viewpoints from the classical Chinese medical literature and after years of clinical practice,Professor Qin proposes that the onset of cutaneous pruritus is often associated with the attack of exogenous pathogens,disharmony of qi and blood,or debility due to prolonged illness.The disease primarily involves the skin,with the fundamental pathogenesis of pathogens stagnating in the muscular superficies.Clinically,the treatment is frequently conducted from the perspective of fire-heat syndrome,and the therapeutic methods of clearing heat and removing toxins,releasing muscles and dispersing pathogens from the superficies,and dispelling wind to relieve itching are utilized.The approaches aim to cool heat in the blood,expel pathogens from the muscular layer,eliminate heat for stopping itching,and extinguish wind for calming the skin.The basic prescription,Yinqiao Xingzi Decoction(composed of Lonicerae Japonicae Flos,Forsythiae Fructus,Armeniacae Semen Amarum,Arnebiae Radix,Tribuli Fructus,Dictamni Cortex,Kochiae Fructus,and Glycyrrhizae Radix et Rhizoma),is used by modification depending on the predominance of pathogenic factors of wind,heat,dryness,or dampness-toxins,and according to the various syndromes like blood-heat,yin deficiency,or qi-blood deficiency.Yinqiao Xingzi Decoction is applicable to cutaneous pruritus with the most of clinical common syndrome types,but it is unsuitable for cases caused by yang deficiency or qi stagnation with blood stasis.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS/MS）， the combination of serum pharmacochemistry， response profile of absorbed components in serum， network pharmacology and drug-likeness prediction was used to screen the potential active ingredients of Yanghetang against breast cancer. MethodsUPLC-Q-TOF-MS/MS was used to identify the main components in different solvent extracts of Yanghetang， and serum pharmacochemistry was applied to analyze the absorbed components from the serum of female SD rats after 0.5， 1， 2 h of administration. Combined with the response characteristic values of serum drug components obtained from UNIFI 1.8.2， the absorbed prototype components and metabolites were screened to get the absorbed components of Yanghetang with a significant patterns of elimination and growth. Network pharmacology was applied to construct a drug-component-pathway-target-disease network， and molecular docking was performed between absorbed components and key targets of breast cancer， and the drug similarity was analyzed by SwissADME. ResultsForty-two compounds were identified in Yanghetang samples extracted with different solvents， of which 16 compounds were common to the three different extraction solvents（methanol， 50% methanol and water）. The results of drug-containing serum analysis showed that there were 16 absorbed components in serum， including 5 prototypes and 11 metabolites. Network pharmacology results showed that Yanghetang against breast cancer involved 15 key targets such as proto-oncogene tyrosine-protein kinase Src（SRC）， epidermal growth factor receptor（EGFR） and phosphoinositide 3 kinase catalytic alpha polypeptide（PIK3CA）. Molecular docking results showed that 16 potential active ingredients were well combined with the predicted targets. Combined with drug likenesses， 12 compounds in the absorbed components of Yanghetang were considered to have potential for anti-breast cancer activity， mainly including α-pinene and γ-eudesmol and their metabolites， of which one was from Ephedrae Herba， one was from Rehmanniae Radix， and eight were from Cinnamomi Cortex. ConclusionThe chemical components of Yanghetang mainly include polysaccharides， monoterpene glycosides and coumarins， and its prototype components mainly undergo oxidation， hydrolysis and acetylation after entering the blood. Its anti-breast cancer mechanism may be related to the regulation of signaling pathways such as the mitogen-activated protein kinase（MAPK） and phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）. The results of this study can lay a foundation for further exploration of Yanghetang in the treatment of breast cancer.

This article is based on modern psychology and TCM emotional theory,combined with facial expression recognition technology,to apply deep learning methods to the digital research of TCM emotions to more accurately capture and analyze patients'emotional states.A cross-disciplinary framework was established by synthesizing facial expression-emotion correlations from psychological and TCM perspectives.The methodology included:Data annotation of TCM-defined emotional expressions using standardized coding systems;Facial expression acquisition,spatiotemporal feature extraction and emotion classification through a 3D convolutional neural network(3D CNN).The framework achieved 91.43%accuracy in video-based emotion classification.High-arousal emotional states demonstrated superior recognition performance,with anger showing optimal recall(1.000 0)and F1-score(0.946 3),while surprise attained the highest precision(0.976 0).These findings aligned with TCM pathological characteristic of"anger induces qi ascending,surprise disrupts qi flow".The digital recognition framework for TCM emotional quantification based on facial expression recognition technology exhibits strong alignment with TCM observation diagnosis,providing clinicians with an objective tool to assess the"seven emotions"and elucidating emotion-facial correlations in classical TCM theory.Future research should focus on longitudinal validation across diverse populations and establish development pathways for AI-assisted TCM diagnostic systems.

BACKGROUND:The pathogenesis of osteoporosis is closely related to the immune system.A comprehensive and in-depth study of the relationship between immunity and osteoporosis is crucial for understanding and treating the disease.OBJECTIVE:To investigate the role of immune cells in osteoporosis using single-cell sequencing technology.METHODS:Femoral head tissue samples from osteoporosis and non-osteoporosis patients were downloaded from GEO database and analyzed using single-cell sequencing.Data analysis,including cell clustering,functional enrichment,pseudotime trajectory,and cell interaction analyses,was performed using R4.3.0 and software packages such as Seurat v.4.3,monocle(2.28.0),and CellChat.The femoral head tissues of patients with femoral neck fracture who underwent artificial hip replacement surgery were obtained,including two cases of osteoporosis patients and two cases of non-osteoporosis patients.Immunohistochemical staining was used to detect the protein expression of CCL13 and CCL18.qPCR was used to detect the immunoglobulin heavy constant γ-4,immunoglobulin λ constant 3,human class Ⅱ major histocompatibility complex DRβ1,and CD83 mRNA expression.Western blot was used to detect the protein expression of receptor-type tyrosine protein phosphatase C,CD22,and CD99.RESULTS AND CONCLUSION:Transcriptomic analysis identified 10 cell clusters,including osteoclasts,myeloid cells,T cells,osteoblasts,macrophages,monocytes,erythrocytes,B cells,bone marrow mesenchymal stem cells,and mast cells.There was an increase in the ratio of osteoclasts to T cells and a decrease in the ratio of osteoblasts to B cells in the femoral head tissue of the osteoporosis group.Among the B-cell subpopulations,the proportion of B-cells of taxa 1,3(BC1,BC3)in the femoral head tissue of the osteoporosis group was higher than that of the non-osteoporosis group,and the proportion of B-cells of taxa 2(BC2)was less than that of the non-osteoporosis group.BC1 was enriched significantly for labels such as regulation of adaptive immune response,somatic recombination of immune receptors,and modulation of lymphocyte-mediated immunity,while BC3 was enriched significantly for labels such as regulation of immunoglobulin production,response to type Ⅱ interferon,apoptotic processes involving cysteine endopeptidases,and cytotoxicity.The communication intensity between B-cell subtype BC1 and osteoblasts in the femoral head tissue of the osteoporosis group was higher than that of the non-osteoporosis group,while the communication intensity between BC3 and BC1 was also increased.The communication between BC3 and BC1 was significantly enriched in the CD22-receptor-type tyrosine protein phosphatase C pathway;the communication between BC1 and osteoblasts was mainly enriched in the CD99-CD99 pathway;and the communication between BC3 and osteoblasts was also highly enriched in the CD99-CD99 pathway.Protein expression of CCL13,CCL18,receptor-type tyrosine protein phosphatase C,CD22,CD99,immunoglobulin heavy constant γ-4,immunoglobulin λ constant 3,human class Ⅱ major histocompatibility complex DRβ1,and CD83 mRNA were higher in femoral tissues of the osteoporosis group than those of the non-osteoporosis group(P＜0.05).To conclude,specific B cell subpopulations can influence the differentiation and apoptosis of osteoblasts in the femoral tissue of osteoporosis patients.

Objective:To explore the application effect of 3D technology-assisted teaching based on "four-in-one" flipped classroom in clinical teaching of neurosurgery, and provide a basis for optimizing the medical education mode.Methods:A total of 50 students from the Second Clinical College were selected between June 2020 and June 2024, including eight-year program medical students and postgraduate neurosurgery students. The control group ( n=25) received the conventional teaching mode. The experimental group ( n=25) was taught using the "four-in-one" flipped classroom combined with 3D technology, including characteristic textbooks with 3D model drawings, Internet platforms (video libraries and virtual simulation modules), mobile interactive terminals (real-time question and answer), and virtual simulation technology. Effectiveness was evaluated through theoretical assessment (e.g., neuroanatomy and clinical application ability, with a total score of 100 points), operational assessment (e.g., surgical design and aseptic concept, with a total score of 100 points), and a teaching quality questionnaire. Independent samples t-test was conducted using SPSS 22.0. Results:The total score of theoretical assessment was higher in the experimental group than that in the control group [(86.52±5.21) vs. (73.56±6.32), P<0.001], with the largest difference observed in case analysis questions [(26.03±3.65) vs. (22.22±3.50), P=0.001]. In the operational assessment, the experimental group performed better in "surgical process design" [(26.30±4.14) vs. (21.44±3.45), P<0.001] and "aseptic concept" [(8.18±0.98) vs. (6.64±0.79), P<0.001]. The teaching quality questionnaire showed that the experimental group scored higher in "clinical practice skill enhancement" [(23.13±1.39) vs. (21.45±1.86), P=0.001] and "self-directed learning motivation" [(21.84±1.60) vs. (19.75±1.45), P<0.001]. Conclusions:The combination of "four-in-one" flipped classroom and 3D technology can significantly improve the teaching effectiveness of neurosurgery, especially in the cultivation of clinical thinking and practical abilities. This approach is worth promoting.

BACKGROUND:The pathogenesis of osteoporosis is closely related to the immune system.A comprehensive and in-depth study of the relationship between immunity and osteoporosis is crucial for understanding and treating the disease.OBJECTIVE:To investigate the role of immune cells in osteoporosis using single-cell sequencing technology.METHODS:Femoral head tissue samples from osteoporosis and non-osteoporosis patients were downloaded from GEO database and analyzed using single-cell sequencing.Data analysis,including cell clustering,functional enrichment,pseudotime trajectory,and cell interaction analyses,was performed using R4.3.0 and software packages such as Seurat v.4.3,monocle(2.28.0),and CellChat.The femoral head tissues of patients with femoral neck fracture who underwent artificial hip replacement surgery were obtained,including two cases of osteoporosis patients and two cases of non-osteoporosis patients.Immunohistochemical staining was used to detect the protein expression of CCL13 and CCL18.qPCR was used to detect the immunoglobulin heavy constant γ-4,immunoglobulin λ constant 3,human class Ⅱ major histocompatibility complex DRβ1,and CD83 mRNA expression.Western blot was used to detect the protein expression of receptor-type tyrosine protein phosphatase C,CD22,and CD99.RESULTS AND CONCLUSION:Transcriptomic analysis identified 10 cell clusters,including osteoclasts,myeloid cells,T cells,osteoblasts,macrophages,monocytes,erythrocytes,B cells,bone marrow mesenchymal stem cells,and mast cells.There was an increase in the ratio of osteoclasts to T cells and a decrease in the ratio of osteoblasts to B cells in the femoral head tissue of the osteoporosis group.Among the B-cell subpopulations,the proportion of B-cells of taxa 1,3(BC1,BC3)in the femoral head tissue of the osteoporosis group was higher than that of the non-osteoporosis group,and the proportion of B-cells of taxa 2(BC2)was less than that of the non-osteoporosis group.BC1 was enriched significantly for labels such as regulation of adaptive immune response,somatic recombination of immune receptors,and modulation of lymphocyte-mediated immunity,while BC3 was enriched significantly for labels such as regulation of immunoglobulin production,response to type Ⅱ interferon,apoptotic processes involving cysteine endopeptidases,and cytotoxicity.The communication intensity between B-cell subtype BC1 and osteoblasts in the femoral head tissue of the osteoporosis group was higher than that of the non-osteoporosis group,while the communication intensity between BC3 and BC1 was also increased.The communication between BC3 and BC1 was significantly enriched in the CD22-receptor-type tyrosine protein phosphatase C pathway;the communication between BC1 and osteoblasts was mainly enriched in the CD99-CD99 pathway;and the communication between BC3 and osteoblasts was also highly enriched in the CD99-CD99 pathway.Protein expression of CCL13,CCL18,receptor-type tyrosine protein phosphatase C,CD22,CD99,immunoglobulin heavy constant γ-4,immunoglobulin λ constant 3,human class Ⅱ major histocompatibility complex DRβ1,and CD83 mRNA were higher in femoral tissues of the osteoporosis group than those of the non-osteoporosis group(P＜0.05).To conclude,specific B cell subpopulations can influence the differentiation and apoptosis of osteoblasts in the femoral tissue of osteoporosis patients.

Objective:To explore the application effect of 3D technology-assisted teaching based on "four-in-one" flipped classroom in clinical teaching of neurosurgery, and provide a basis for optimizing the medical education mode.Methods:A total of 50 students from the Second Clinical College were selected between June 2020 and June 2024, including eight-year program medical students and postgraduate neurosurgery students. The control group ( n=25) received the conventional teaching mode. The experimental group ( n=25) was taught using the "four-in-one" flipped classroom combined with 3D technology, including characteristic textbooks with 3D model drawings, Internet platforms (video libraries and virtual simulation modules), mobile interactive terminals (real-time question and answer), and virtual simulation technology. Effectiveness was evaluated through theoretical assessment (e.g., neuroanatomy and clinical application ability, with a total score of 100 points), operational assessment (e.g., surgical design and aseptic concept, with a total score of 100 points), and a teaching quality questionnaire. Independent samples t-test was conducted using SPSS 22.0. Results:The total score of theoretical assessment was higher in the experimental group than that in the control group [(86.52±5.21) vs. (73.56±6.32), P<0.001], with the largest difference observed in case analysis questions [(26.03±3.65) vs. (22.22±3.50), P=0.001]. In the operational assessment, the experimental group performed better in "surgical process design" [(26.30±4.14) vs. (21.44±3.45), P<0.001] and "aseptic concept" [(8.18±0.98) vs. (6.64±0.79), P<0.001]. The teaching quality questionnaire showed that the experimental group scored higher in "clinical practice skill enhancement" [(23.13±1.39) vs. (21.45±1.86), P=0.001] and "self-directed learning motivation" [(21.84±1.60) vs. (19.75±1.45), P<0.001]. Conclusions:The combination of "four-in-one" flipped classroom and 3D technology can significantly improve the teaching effectiveness of neurosurgery, especially in the cultivation of clinical thinking and practical abilities. This approach is worth promoting.

This article is based on modern psychology and TCM emotional theory,combined with facial expression recognition technology,to apply deep learning methods to the digital research of TCM emotions to more accurately capture and analyze patients'emotional states.A cross-disciplinary framework was established by synthesizing facial expression-emotion correlations from psychological and TCM perspectives.The methodology included:Data annotation of TCM-defined emotional expressions using standardized coding systems;Facial expression acquisition,spatiotemporal feature extraction and emotion classification through a 3D convolutional neural network(3D CNN).The framework achieved 91.43%accuracy in video-based emotion classification.High-arousal emotional states demonstrated superior recognition performance,with anger showing optimal recall(1.000 0)and F1-score(0.946 3),while surprise attained the highest precision(0.976 0).These findings aligned with TCM pathological characteristic of"anger induces qi ascending,surprise disrupts qi flow".The digital recognition framework for TCM emotional quantification based on facial expression recognition technology exhibits strong alignment with TCM observation diagnosis,providing clinicians with an objective tool to assess the"seven emotions"and elucidating emotion-facial correlations in classical TCM theory.Future research should focus on longitudinal validation across diverse populations and establish development pathways for AI-assisted TCM diagnostic systems.

It is believed that the endoscopic manifestations of interstitial cystitis/bladder pain syndrome （IC/BPS） such as extensive bleeding and Hunner's ulcers as well as its recurrent and prolonged condition are in line with the characteristics of sores and ulcers in traditional Chinese medicine （TCM）， and the treatment can be referred to TCM theory of sores and ulcers. The mechanism of IC/BPS is characterized by root deficiency and branch excess. The root cause is deficiency of the spleen and kidney qi， while the manifesting factors are dampness-heat and blood stasis. The treatment is based on the principles of promoting and supplementing， combining with resolving therapy， so that the symptoms could be relieved by promoting blood circulation and clearing heat， unblocking the collaterals and relieve pain. In clinical practice， modified Neituo Shengji Powder （内托生肌散） was commonly used to boost qi and invigorate blood， expel swollen sore and express toxin； combining with Sijunzi Decoction （四君子汤） or Suoquan Pill （缩泉丸） based on specific symptoms to strengthen the spleen and kidneys， thereby reinforcing healthy qi； according to concurrent symptoms like blood stasis， dampness heat， prescription with Sanleng （Cyperus rotundus）， Ezhu （Curcuma aromatica Salisb） to invigorate blood and dissolve stasis， or Yiyiren （Coix lacryma-jobi）， Zexie （Alisma plantago-aquatica） to clear heat and drain dampness.

BACKGROUND:Establishing a nomogram prediction model for postoperative pulmonary infection in hip fractures and taking early intervention measures is crucial for improving patients'quality of life and reducing medical costs. OBJECTIVE:To construct a nomogram risk prediction model of postoperative pulmonary infection in elderly patients with hip fracture,and provide theoretical basis for feasible prevention and early intervention. METHODS:Case data of 305 elderly patients with hip fractures who underwent surgical treatment at Wuxi Traditional Chinese Medicine Hospital Affiliated to Nanjing University of Chinese Medicine between January and October 2020(training set)were retrospectively analyzed.Using univariate and multivariate logistic regression analysis and Hosmer-Lemeshow goodness of fit test,receiver operating characteristic curve was utilized to analyze the diagnostic predictive efficacy of independent risk factors and joint models for postoperative pulmonary infections.Tools glmnet,pROC,and rms in R Studio software were applied to construct a nomogram model for predicting the risk of postoperative pulmonary infection in elderly patients with hip fractures,and calibration curves were further drawn to verify the predictive ability of the nomogram model.Receiver operating characteristic curves,calibration curves,and decision curves were analyzed for 133 elderly patients with hip fractures(validation set)receiving surgery at the same hospital from November 2022 to March 2023 to further predict the predictive ability of the nomogram model. RESULTS AND CONCLUSION:(1)The postoperative pulmonary infection rate in elderly patients with hip fractures in this group was 9.18%(28/305).(2)Single factor and multivariate analysis,as well as forest plots,showed that preoperative hospitalization days,leukocyte count,hypersensitive C-reactive protein,and serum sodium levels were independent risk factors(P<0.05).The Hosmer-Lemeshow goodness of fit test showed good fit(χ2=4.57,P=0.803).Receiver operating characteristic curve analysis was conducted on the independent risk factors and their joint models mentioned above,and the differentiation of each independent risk factor and joint model was good,with statistical significance(P<0.05).(3)The graphical calibration method,C-index,and decision curve were used to validate the nomogram prediction model.The predicted calibration curve was located between the standard curve and the acceptable line,and the predicted risk of the nomogram model was consistent with the actual risk.(4)The validation set used receiver operating characteristic curve,graphic calibration method,and decision curve to validate the prediction model.The results showed good consistency with clinical practice,indicating that the model had a good fit.The nomogram risk prediction model constructed for postoperative pulmonary infection in elderly patients with hip fractures has good predictive performance.The use of the nomogram risk prediction model can screen high-risk populations and provide a theoretical basis for early intervention.