By consulting herbal texts， medical records， formula collections， and other relevant literature from various historical periods， as well as modern and contemporary research materials， different aspects of the historical evolution of Zijingpi， including its name， origin， scientific name verification， medicinal part， genuine producing areas， harvesting， processing， and preparation， properties and flavors， and primary indications， were systematically reviewed and verified， providing a basis for the development of famous classical formula preparations containing this medicinal material. According to the textual research， Cercis chinensis was first recorded under the name "Zijingmu" in the Rihuazi Bencao from the Five Dynasties period. From the Song Dynasty to the Qing Dynasty， it was known by various names such as "Zijing"， "Zijingpi"， and "Zijingmupi". In modern and contemporary times， it has been officially named "Zijingpi"， with aliases such as "Mantiaohong"， "Zihuashu"， and "Qingminghua". Historically， the mainstream source of Zijingpi was the dried bark of Cercis chinensis Bunge， a species of the legume family. However， there were also instances of confusion with the Lythraceae plant Lagerstroemia indica L. The producing areas of Zijingpi have no special geographical limitation， and the plant is currently distributed throughout most parts of China. There were no special requirements for harvesting time in ancient times， while modern records indicate harvesting time in spring， summer， and autumn. Ancient processing methods were rarely recorded， with only mentions of stir-frying Zijingpi. Modern practice mostly uses the raw material medicinally. Modern standards prefer it to be "dry， long strips， and thick". The functions of Zijingpi， mainly to promote blood circulation， relieve strangury， and detoxify， have remained consistent from ancient to modern times. Based on the textual research findings， it is recommended that when developing and exploiting the famous classical formulas containing Zijingpi， the bark of C. chinensis should be selected as the source. The processing method should be chosen according to the formula requirements， and if no specific requirements are indicated， it is suggested to use the raw material medicinally.

OBJECTIVE To investigate the stability and compatibility of butorphanol， nicardipine， urapidil， and tirofiban. METHODS A micro-infusion pump was used to simulate the infusion process. Samples were collected in real time from the needle tip at 0， 2， 4， 6， and 8 h after mixing of the four drugs. The appearance， pH， and number of insoluble particles were examined. The contents of butorphanol， nicardipine， urapidil， and tirofiban were determined using the ultra-high-performance liquid chromatography method. RESULTS Within 8 hours， all mixed solutions remained clear and transparent， with no visible turbidity， precipitation， color change， or gas generation. The pH fluctuation ranged from 0.02 to 0.09， both within 0.1 pH units. The number of insoluble particles ≥10 μm in size in each compatibility solution was ≤9， and the number of insoluble particles ≥25 μm was ≤2， meeting the requirements of the 2025 edition of the Chinese Pharmacopoeia （Volume Ⅳ）. The relative percentage contents of butorphanol， nicardipine， urapidil， and tirofiban at 8 hours after compatibility mixing ranged from 92.38% to 113.40%. CONCLUSIONS Within 8 hours under simulated clinical micro-infusion pump infusion conditions， the stability and compatibility of the mixed solution containing butorphanol， nicardipine， urapidil， and tirofiban were satisfactory.

Submucosal angiomyolipoma(AML)of rectum is clinically rare.This article reports the endoscopic diagnosis and treatment process of a case of rectal AML.By reviewing the clinical data of this patient and combining with literature review,we aim to deepen the current understanding of AML in the digestive tract and avoid misdiagnosis and mistreatment in clinical practice.

Objective:To analyze the population structure, quantity of rodents, fleas and epidemiological characteristics of animal plague in the plague foci of Erenhot in Inner Mongolia Autonomous Region, and to provide a basis for scientific prevention and control of plague.Methods:The descriptive epidemiological method was used to analyze the surveillance and epidemic data of plague in Erenhot from 2013 to 2023 (from the plague prevention and control management information system of the Chinese Center for Disease Control and Prevention, and the summary of plague surveillance data in Inner Mongolia Autonomous Region from 2013 to 2023), including rat density, nocturnal rat capture, flea infection of rodents, bacteriological and serological detection, etc.Results:From 2013 to 2023, a total of 418 hm 2 of plague foci were investigated in Erenhot, 1 054 rats were caught, and the density of rats was 2.52/hm 2, among which Meriones unguiculatus was the dominant species ( n = 480), and the density was 1.15/hm 2. The capture rate of nocturnal rodents was 6.38% (1 291/20 250). The flea infestation rate of rodents was 35.53% (1 491/4 197), with a flea index of 1.25. Xenopsylla conformity is the dominant flea species ( n = 1 886). Animal plague outbreaks occurred in 7 years, with 11 positive rodents and 10 groups of positive fleas identified by the bacteriology tests, and a total of 21 strains of Yersinia pestis isolated. Eleven positive sera samples were detected by serology. Conclusion:The rodent density in the plague foci of Erenhot is relatively low, but the flea index is high, the animal epidemic is active, facing a significant risk of imported human and animal plague epidemics.

This article summarizes current research and real-world evidence on the combined use of 5-aminosalicylates acid (5-ASA) with biologic agents in ulcerative colitis (UC) patients undergoing step-up therapy. Furthermore, it explores the potential value of whether combination therapy or not in different clinical scenarios. The findings provide insights for personalized UC treatment strategies and suggest directions for future research.

Objective:To explore the clinical features, histopathological morphology, and differential diagnosis of lymphoepithelioma-like carcinoma with abnormal expression of follicular dendritic cell markers.Methods:From 2020 to 2021, 4 cases of lymphoepithelioma-like carcinoma with abnormal expression of follicular dendritic cell markers diagnosed in Fujian Cancer Hospital (2 cases) and the Second Affiliated Hospital of Fujian Medical University (2 cases) were collected. Different ancillary procedures such as HE, special stains, immunohistochemistry, and in situ hybridization techniques were used to assess the histopathological features and immunophenotypes. The clinical data were collected and literature was reviewed.Results:All 4 cases of lymphoepithelioma-like carcinoma with abnormal expression of follicular dendritic cell markers were male. They were 32, 45, 67 and 39 years old, respectively. The main clinical manifestations were bloody phlegm, abdominal pain, fatigue and anorexia. The clinical stages at diagnosis were stage Ⅳ (3 cases) and stage Ⅱ (1 case). Cases 2 and 3 had two pathological examinations at different sites, with a total of six pathological examinations. The histomorphology showed singly scattered or nests of tumor cells in a background of abundant small lymphocytes. The tumor cells were enlarged and pleomorphic, some appeared polygonal with inconspicuous cell borders, and they were arranged in a syncytial pattern. There were megakaryocytes, multinucleated tumor cells, and a few spindle-shaped cells seen. Atypical mitosis was commonly noted. By immunohistochemistry, the tumor cells were positive for CKpan(5/6), CK8/18(4/4), CAM5.2(2/5), CK-H(0/4), CK-L(3/4), EMA(4/5), CK5/6(3/6), p63(1/6), p40(1/6), E-cadherin (4/6), SSTR2(6/6), PD-L1(5/5), LCA(0/6), vimentin(5/6), CD2 (6/6), CD23(6/6), CD35(5/6), CXCL-13(4/5) and D2-40(1/5). The Ki-67 proliferative index was 60%-95%. In situ hybridization for EBER were all positive (6/6). Special stain for reticulin showed positive staining surrounding nests of tumor cells.Conclusions:The expression of follicular dendritic cell markers in lymphoepithelioma-like carcinoma is very rare, which may be related to EBV infection. Occasionally, it can overlap with follicular dendritic cell sarcoma by morphology and immunophenotype, which can lead to misdiagnosis. Only by combining clinical information, morphological characteristics and immunophenotype can an appropriate diagnosis be made.

AIM:This study aims to investigate the regulatory effects of caffeic acid phenethyl ester(CAPE)on metabotropic glutamate receptor 5(mGluR5)and tyrosine kinase Fyn,and to explore its role in alleviating neuroinflam-mation and pathological features of Alzheimer disease(AD).METHODS:In vitro,the murine neuroblastoma N2a cell line was treated with amyloid β-protein 42 oligomers(Aβ42Os;10 nmol/L to 10 μmol/L)for 24 h.Cell viability was as-sessed by MTT assay.Western blot analyzed mGluR5 expression and Fyn phosphorylation(Tyr416).Pharmacological modulators(CHPG/MPEP)were used to evaluate mGluR5-mediated inflammatory cytokine regulation(qPCR)and Fyn ac-tivation.In vivo,wild-type(WT)and 5×FAD mice(WT,WT+CAPE,5×FAD and 5×FAD+CAPE)were analyzed for AD-related proteins,neuroinflammation(ELISA),glial activation(GFAP/Iba-1 immunofluorescence),and β-amyloid deposi-tion(thioflavin S).RESULTS:(1)Treatment with 1 μmol/L Aβ42Os increased mGluR5 expression(P<0.01)and Fyn phosphorylation(P<0.01)without affecting N2a cell viability.Intracerebral Aβ42Os injection similarly up-regulated hip-pocampal mGluR5 and Fyn(P<0.01).(2)MPEP reduced mGluR5 expression(P<0.01)and Fyn phosphorylation(P<0.01),while suppressing tumor necrosis factor-α(TNF-α)and interleukin-6(IL-6)mRNA levels(P<0.01).(3)CAPE decreased mGluR5-Fyn activation in N2a cells,neurons,and 5×FAD mice(P<0.01).(4)CAPE-treated 5×FAD mice exhibited reduced neuroinflammation markers(GFAP,Iba-1,TNF-α,IL-1β,and IL-6),Aβ plaques,and p-APP levels(P<0.01).CONCLUSION:Treatment with CAPE inhibits Aβ42Os-induced mGluR5-Fyn signaling activation,thereby attenuating neuroinflammation and the pathology associated with AD.

Objective:To explore the clinical features, histopathological morphology, and differential diagnosis of lymphoepithelioma-like carcinoma with abnormal expression of follicular dendritic cell markers.Methods:From 2020 to 2021, 4 cases of lymphoepithelioma-like carcinoma with abnormal expression of follicular dendritic cell markers diagnosed in Fujian Cancer Hospital (2 cases) and the Second Affiliated Hospital of Fujian Medical University (2 cases) were collected. Different ancillary procedures such as HE, special stains, immunohistochemistry, and in situ hybridization techniques were used to assess the histopathological features and immunophenotypes. The clinical data were collected and literature was reviewed.Results:All 4 cases of lymphoepithelioma-like carcinoma with abnormal expression of follicular dendritic cell markers were male. They were 32, 45, 67 and 39 years old, respectively. The main clinical manifestations were bloody phlegm, abdominal pain, fatigue and anorexia. The clinical stages at diagnosis were stage Ⅳ (3 cases) and stage Ⅱ (1 case). Cases 2 and 3 had two pathological examinations at different sites, with a total of six pathological examinations. The histomorphology showed singly scattered or nests of tumor cells in a background of abundant small lymphocytes. The tumor cells were enlarged and pleomorphic, some appeared polygonal with inconspicuous cell borders, and they were arranged in a syncytial pattern. There were megakaryocytes, multinucleated tumor cells, and a few spindle-shaped cells seen. Atypical mitosis was commonly noted. By immunohistochemistry, the tumor cells were positive for CKpan(5/6), CK8/18(4/4), CAM5.2(2/5), CK-H(0/4), CK-L(3/4), EMA(4/5), CK5/6(3/6), p63(1/6), p40(1/6), E-cadherin (4/6), SSTR2(6/6), PD-L1(5/5), LCA(0/6), vimentin(5/6), CD2 (6/6), CD23(6/6), CD35(5/6), CXCL-13(4/5) and D2-40(1/5). The Ki-67 proliferative index was 60%-95%. In situ hybridization for EBER were all positive (6/6). Special stain for reticulin showed positive staining surrounding nests of tumor cells.Conclusions:The expression of follicular dendritic cell markers in lymphoepithelioma-like carcinoma is very rare, which may be related to EBV infection. Occasionally, it can overlap with follicular dendritic cell sarcoma by morphology and immunophenotype, which can lead to misdiagnosis. Only by combining clinical information, morphological characteristics and immunophenotype can an appropriate diagnosis be made.

Abstract Traditional Chinese medicine (TCM) auscultation has a long history, and with advancements in equipment and analytical methods, the quantitative analysis of auscultation parameters has determined. However, the complexity and diversity of auscultation, along with variations in devices, analytical methods, and applications, bring challenges to its standardization and deeper application. This review presents the advancements in auscultation equipment and systems, auscultation characteristic parameters, and their application in the diagnosis of pulmonary diseases and syndromes over the past 10 years, while also exploring the progress and challenges of current digital research of auscultation. This review also proposes the establishment of standardized protocols for the collection and analysis of auscultation data, the incorporation of advanced artificial intelligence (AI) auscultation analysis methods, and an exploration of the diagnostic utility of auscultatory features in pulmonary diseases and syndromes, so as to provide more precise decision support for intelligent diagnosis of pulmonary diseases and syndromes

Objective: To explore the feasibility of constructing a lung cancer early-warning risk model based on facial image features, providing novel insights into the early screening of lung cancer. Methods: This study included patients with pulmonary nodules diagnosed at the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 1, 2019 to December 31, 2024, as well as patients with lung cancer diagnosed in the Oncology Departments of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine and Longhua Hospital during the same period. The facial image information of patients with pulmonary nodules and lung cancer was collected using the TFDA-1 tongue and facial diagnosis instrument, and the facial diagnosis features were extracted from it by deep learning technology. Statistical analysis was conducted on the objective facial diagnosis characteristics of the two groups of participants to explore the differences in their facial image characteristics, and the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables. Based on the screened feature variables, four machine learning methods: random forest, logistic regression, support vector machine (SVM), and gradient boosting decision tree (GBDT) were used to establish lung cancer classification models independently. Meanwhile, the model performance was evaluated by indicators such as sensitivity, specificity, F1 score, precision, accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), and the area under the precision-recall curve (AP). Results: A total of 1 275 patients with pulmonary nodules and 1 623 patients with lung cancer were included in this study. After propensity score matching (PSM) to adjust for gender and age, 535 patients were finally included in the pulmonary nodule group and the lung cancer group, respectively. There were significant differences in multiple color space metrics (such as R, G, B, V, L, a, b, Cr, H, Y, and Cb) and texture metrics [such as gray-levcl co-occurrence matrix (GLCM)-contrast (CON) and GLCM-inverse different moment (IDM)] between the two groups of individuals with pulmonary nodules and lung cancer (P < 0.05). To construct a classification model, LASSO regression was used to select 63 key features from the initial 136 facial features. Based on this feature set, the SVM model demonstrated the best performance after 10-fold stratified cross-validation. The model achieved an average AUC of 0.8729 and average accuracy of 0.799 0 on the internal test set. Further validation on an independent test set confirmed the model’s robust performance (AUC = 0.823 3, accuracy = 0.729 0), indicating its good generalization ability. Feature importance analysis demonstrated that color space indicators and the whole/lip Cr components (including color-B-0, wholecolor-Cr, and lipcolor-Cr) were the core factors in the model’s classification decisions, while texture indicators [GLCM-angular second moment (ASM)_2, GLCM-IDM_1, GLCM-CON_1, GLCM-entropy (ENT)_2] played an important auxiliary role. Conclusion The facial image features of patients with lung cancer and pulmonary nodules show significant differences in color and texture characteristics in multiple areas. The various models constructed based on facial image features all demonstrate good performance, indicating that facial image features can serve as potential biomarkers for lung cancer risk prediction, providing a non-invasive and feasible new approach for early lung cancer screening.