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.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Ferroptosis has received great attention as an iron-dependent programmed cell death for efficient cancer therapy. However, with the accumulation of iron in tumor cells, the antioxidant system is activated by reducing glutathione (GSH) with glutathione peroxidase 4 (GPX4), which critically limits the ferroptosis therapeutic effect. Herein, an iron and GPX4 silencing siRNA (siGPX4) co-encapsulated ferritin nanocage (HFn@Fe/siGPX4) was developed to enhance ferroptosis by disruption of redox homeostasis and inhibition of antioxidant enzyme synergistically. The siGPX4 were loaded into the nanocages by pre-incubated with iron, which could significantly improve the loading efficiency of the gene drugs when compared with the reported gene drug loading strategy by ferritin nanocages. And more iron was overloaded into the ferritin through the diffusion method. When HFn@Fe/siGPX4 was taken up by human breast cancer cell MCF-7 in a TfR1-mediated pathway, the excess iron ions in the drug delivery system could for one thing induce ferroptosis by the production of reactive oxygen species (ROS), for another promote siGPX4 escaping from the lysosome to exert gene silencing effect more effectively. Both the in vitro and in vivo results demonstrated that HFn@Fe/siGPX4 could significantly inhibit tumor growth by synergistical ferroptosis. Thus, the developed HFn@Fe/siGPX4 afforded a combined ferroptosis strategy for ferroptosis-based antitumor as well as a novel and efficient gene drug delivery system.

OBJECTIVE: Traditional Chinese medicine (TCM) incorporates traditional diagnostic methods and several major treatment modalities including Chinese herbal medicine, Chinese patent medicine, and non-pharmacological methods such as acupuncture and tuina. Even though TCM is used daily by more than 70,000 healthcare facilities and over 700,000 clinical practitioners in China, there is a poor understanding of the extent to which TCM diagnostic methods are used, how different treatment modalities are deployed in general, and what major factors may affect the integration of TCM and Western medicine. This study aimed to fill this void in the literature. METHODS: In the 2021 National Healthcare Improvement Evaluation Survey, we included three questions gauging the perception and practices of TCM amongst physicians working in TCM-related facilities, investigating the frequency of their deployment of TCM diagnostic methods, and predominant TCM treatment methods. Our empirical analysis included descriptive statistics, intergroup chi-square analysis, and binary logistic regression to examine the association between different types of facilities and individual characteristics and TCM utilization patterns. RESULTS: A total of 7618 clinical physicians comprised our study sample. Among them, 84.27% have integrated TCM and Western medicine in their clinical practice, and 80.77% of TCM practitioners used the 4 diagnostic methods as a tool in their clinical practice. Chinese herbal medicine was the most widely utilized modality by Chinese TCM physicians (used by 88.49% of respondents), compared with the Chinese patent medicine and non-pharmacological TCM methods, which were used by 73.14%, and 69.39%, respectively. Herbal tea as an out-of-pocket health-maintenance intervention is also a notable practice, recommended by 29.43% of physicians. Significant variations exist across certain institutions, departments, and individual practitioners. CONCLUSION Given that most of the surveyed physicians integrated TCM with Western medicine in their clinical practices, the practice of "pure TCM" appears to be obsolete in China's tertiary healthcare institutions. Notably, remarkable variation exists in the use of different TCM modalities across institutions and among individuals, which might be related to and thus limited by the practitioners' experience. Future research focusing on the efficacy and safety of TCM interventions for specific diseases, the development of standardized clinical guidelines, and the enhancement of TCM education and training are called for to optimize TCM-Western medicine integration. Please cite this article as: Guo R, Zeng D, Zhao Q, Zhang XY, Zhang XK, Liu YL. How are different traditional Chinese medicine modalities deployed by clinical practitioners in China? Findings from a national survey. J Integr Med. 2025; 23(1): 36-45.
Medicine, Chinese Traditional/statistics & numerical data* ; Humans ; China ; Surveys and Questionnaires ; Female ; Male ; Physicians/statistics & numerical data* ; Practice Patterns, Physicians'/statistics & numerical data* ; Adult ; Middle Aged

Compared to traditional machine learning algorithms,which often suffer from low feature extraction efficiency,insufficient nonlinear pattern recognition capabilities and slow training speeds,the broad learning system(BLS)enhances the learning ability and efficiency by horizontally expanding the network structure.BLS offers advantages such as a simple structure,fast training speed,and strong generalization capabilities.While BLS has demonstrated potential in various fields,but its application in identification of complex samples has not been fully explored.This research investigated the feasibility of using BLS algorithm for identification of complex samples based on physicochemical indicators.Using the iris,wine,and breast cancer datasets,the length and width of petals and sepals of iris flowers,the physicochemical properties of wine,and the nuclear characteristics of breast cancer cells were used as input variables to establish BLS models for identifying iris species,wine varieties,and benign versus malignant nucleus.The model performance was evaluated by confusion matrices,accuracy,and runtime.Compared with partial least squares-discriminant analysis(PLS-DA),soft independent modeling of class analogies(SIMCA),and artificial neural networks(ANN),the results indicated that BLS demonstrated significant advantages in computational efficiency and recognition accuracy.Thus,BLS was an efficient and reliable method for identification of complex samples.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

Objective:To investigate the effect and safety of pancreatic extracorporeal shock wave lithotripsy (P-ESWL) in treating the chronic pancreatitis (CP) patients with main pancreatic duct (MPD) stones and to analyze the influencing factors of success of lithotripsy.Methods:Clinical data of 132 patients with CP complicated with MPD stones treated with P-ESWL in the Department of Gastroenterology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2022 to December 2023 were retrospectively analyzed, including 103 males and 29 females, aged (50.3±16.9) years. The times of P-ESWL, the success rate of stone fragmentation, the necessity of combining endoscopic retrograde cholangiopancreatograhy (ERCP), clearance rate of MPD stones, and incidence of post-P-ESWL complications (acute pancreatitis, abdominal hematoma, infection, steinstrasse, perforation, etc.) were evaluated. The factors influencing the success rate of lithotripsy were analyzed using univariate and multivariate logistic regression.Results:All patients underwent P-ESWL treatment, with (2.23±0.82) times of P-ESWL per person. The success rate of stone fragmentation was 87.1%(115/132). Of 107 CP patients (81.1%, 107/132) were treated with their first P-ESWL. Of 12 patients (9.1%, 12/132) underwent single P-ESWL, and 120 (90.9%, 120/132) underwent P-ESWL combined with ERCP. There were 95 cases (72.0%, 95/132) with effective removal of stones, and 62 (47.0%, 62/132) with complete removal of stones. Post-P-ESWL complications included eight cases (6.1%, 8/132) of acute pancreatitis, two (7.6%, 2/132) of steinstrasse complicated with acute pancreatitis and one (0.8%, 1/132) of abdominal hematoma. No infection or perforation occurred. Multivariate logistic regression analysis showed that the higher CT value of stones ( OR=1.239, 95% CI: 1.040-1.477, P=0.017) was associated with the lower success rate of stone fragmentation. Conclusion:P-ESWL is safe and effective in treating patients with CP complicated with MPD stones. The CT value of stones is a risk factor for the success rate of P-ESWL.