Hepatocellular carcinoma （HCC） is a common malignant tumor with a high mortality rate， an insidious onset， and complex pathological mechanisms. In the tumor microenvironment， tumor-promoting immune cells protect tumor cells from immune attacks， while dysfunction of anti-tumor immune cells causes the inhibition of immune response， thereby leading to the continuous deterioration of cancer. In recent years， traditional Chinese medicine has shown good efficacy in the treatment of HCC， and it can inhibit the proliferation and metastasis of cancer cells by regulating immune cells. By analyzing related articles in China and globally， this article summarizes how immune cells affect the progression of HCC through the immunosuppressive pathway and how traditional Chinese medicine exerts an anti-HCC effect by regulating immune cells， in order to provide theoretical basis and reference for optimizing the treatment of HCC.

[Objective] To explore the clinical significance and application value of establishing a database for red blood cell alloantibody detection. [Methods] Patients who were scheduled for blood transfusion in our hospital from January 1, 2020 to May 1, 2024 were selected as the research subjects. A red blood cell alloantibody detection database was established using Microsoft Office Excel software to register the detection data of patients' alloantibodies and antibodies of undetermined specificity (AUS). A retrospective analysis was conducted on the clinical characteristics, antibody distribution, antibody decay and repeat positivity of the patients in the database. The LISS-IAT method was routinely used for antibody screening and identification. [Results] Among the alloantibodies, the Rh blood group system had the highest detection rate, followed by antibodies of the MNS blood group system and the Lewis blood group system. The predominant antibody in the Rh blood group system was anti-E. In the univariate analysis, the positivity of antibody was significantly associated with the patient's gender, age, blood transfusion history, pregnancy history and type of disease (all P<0.001). In the database, 48 patients experienced antibody decay, accounting for 15.24%(48/315), with an average time span of antibody decay ranging from 22 to 1 324 days. Six cases showed repeat positivity after decay, which were related to blood transfusions. The shortest interval between blood transfusions that led to antibody repeat positivity was 3 days, and the longest interval was 427 days. Among 58 cases with AUS, 3 converted into alloantibodies, among which 2 were anti-E and 1 was anti-Lea. [Conclusion] Establishing a red blood cell alloantibody detection database is an effective way to guide ambiguous cross-matching in clinical practice and is also an effective measure for the management of transfusion risks.

BACKGROUND:We have successfully established an animal model of small ear pig in southern Yunnan province with internal tension relieving technique combined with autologous Achilles tendon for anterior cruciate ligament reconstruction,and verified the stability and reliability of the model.However,whether internal tension relieving technique can promote the ligamentalization process of autologous Achilles tendon graft has not been studied. OBJECTIVE:To investigate the differences in the process of ligamentalization between conventional reconstruction and internal reduction reconstruction of the anterior cruciate ligament by gross view,histology and electron microscopy. METHODS:Thirty adult female small ear pigs in southern Yunnan province were selected.Anterior cruciate ligament reconstruction was performed on the left knee joint with the ipsilateral knee Achilles tendon(n=30 in the normal group),and anterior cruciate ligament reconstruction was performed on the right knee joint with the ipsilateral knee Achilles tendon combined with the internal relaxation and enhancement system(n=30 in the relaxation group).The autogenous right forelimb was used as the control group;the anterior cruciate ligament was exposed but not severed or surgically treated.At 12,24,and 48 weeks after surgery,10 animals were sacrificed,respectively.The left and right knee joint specimens were taken for gross morphological observation to evaluate the graft morphology.MAS score was used to evaluate the excellent and good rate of the ligament at each time point.Hematoxylin-eosin staining was used to evaluate the degree of ligament graft vascularization.Collagen fibers and nuclear morphology were observed,and nuclear morphology was scored.Ultrastructural remodeling was evaluated by scanning electron microscopy and transmission electron microscopy. RESULTS AND CONCLUSION:(1)The ligament healing shape of the relaxation group was better at various time points after surgery,and the excellent and good rate of MAS score was higher(P<0.05).Moreover,the relaxation group could obtain higher ligament vascularization score(P<0.05).(2)The arrangement of collagen bundles and fiber bundles in the two groups gradually tended to be orderly,and the transverse fiber connections between collagen gradually increased and thickened,suggesting that the strength and shape degree of the grafts were gradually improved,but the ligament remodeling in the relaxation group was always faster than that in the normal group at various time points after surgery.(3)The diameter,distribution density,and arrangement degree of collagen fibers in the relaxation group were better than those in the normal group at all time points,especially in the comparison of collagen fiber diameter between and within the relaxation group(P<0.05).

Macrophages are innate immune cells connected with the development of inflammation. Retinoic acid has previously been proved to have anti-inflammatory and anti-arthritic properties. However, the exact mechanism through which retinoic acid modulates arthritis remains unclear. This study aimed to investigate whether retinoic acid ameliorates rheumatoid arthritis by modulating macrophage polarization. This study used retinoic acid to treat mice with adjuvant arthritis and evaluated anti-inflammatory effects by arthritis score, thermal nociceptive sensitization test, histopathologic examination and immunofluorescence assays. In addition, its specific anti-arthritic mechanism was investigated by flow cytometry, cell transfection and inflammatory signaling pathway assays in RAW264.7 macrophages in vitro. Retinoic acid significantly relieved joint pain and attenuated inflammatory cell infiltration in mice. Furthermore, this treatment modulated peritoneal macrophage polarization, increased levels of arginase 1, as well as decreased inducible nitric oxide synthase expression. In vitro, we verified that retinoic acid promotes macrophage transition from the M1 to M2 type by upregulating mitogen-activated protein kinase (MAPK) phosphatase 1 (MKP-1) expression and inhibiting P38, JNK and ERK phosphorylation in lipopolysaccharide-stimulated RAW264.7 cells. Notably, the therapeutic effects of retinoic acid were inhibited by MKP-1 knockdown. Retinoic acid exerts a significant therapeutic effect on adjuvant arthritis in mice by regulating macrophage polarization through the MKP-1/MAPK pathway, and play an important role in the treatment of rheumatic diseases.

The Chinese Pharmacopoeia is the legal technical standard which should be followed during the research, production, use, and administration of drugs. At present, the new edition of the Chinese Pharmacopoeia is planned to be promulgated and implemented. This article summarizes and analyzes the main characteristics and the content of updates and amendments of the Chinese Pharmacopoeia 2025 Edition(Volume Ⅰ), to provide a reference for the correct understanding and accurate implementation the new edition of the pharmacopoeia.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

Direct compression is an ideal method for tablet preparation, but it requires the powder's high functional properties. The functional properties of the powder during compression directly affect the quality of the tablet. 15 parameters such as Py, FES-8KN, FES-12KN, FES-16KN, CR-8KN, CR-12KN, and CR-16KN were used as the characteristic variables in this paper. Unsupervised learning methods like principal component analysis, cluster analysis, and factor analysis were applied to analyze and classify the compression behavior data of 36 traditional Chinese medicine powders. The results showed that both different dimensionality reduction classification methods could effectively differentiate the compression behavior characteristics of 36 traditional Chinese medicine compound powders. The hierarchical cluster analysis results showed a better agreement with the actual compression phenomena of the powders, where group 1 was high elasticity and low compressibility, group 2 was easily compressed and hard to break, group 3 was excellent compressibility and compactibility. This study is expected to provide references and ideas for predicting the behavior of traditional Chinese medicine powders and the screening of tablet formulations.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

OBJECTIVE To explore the construction of selection system for drug directory of the county-level medical community based on multi-criteria decision analysis， and provide decision-making basis for the selection of drug directory of medical community. METHODS Taking county-level medical community in Chongqing as an example，Delphi method and analytic hierarchy process were employed to construct the selection system for drug directory of the county-level medical community. Selected drugs were quantitatively scored based on the constructed index system， and the drug directory was selected according to the drug’s comprehensive score. The implementation effect of the directory was then evaluated through questionnaire surveys one year after the implementation of the directory. RESULTS The expert authority coefficients of the two rounds of consultation were＞ 0.8， with Kendall’s W values of 0.213 and 0.196， respectively （P＜0.001）. Finally， the selection system for drug directory of the medical community was determined to include five evaluation dimensions： safety， effectiveness， economy， accessibility， and innovation， along with eight evaluation indicators. In the drug directory selected according to the above method， the proportions of centrally procured drugs， medical insurance drugs， and essential drugs had all increased compared to before the selection； the comprehensive scores of chemical drugs ranged from 50.25 to 96.31 scores， and the proportion of drugs scoring between 70 and 100 scores had increased from 78.06% before selection to 85.82%. Among them， antiparasitic drugs had the highest comprehensive scores， while drugs for the digestive tract and metabolism were the most numerous. The evaluation scores of each indicator and the comprehensive scores of drugs in the drug directory after the selection process increased significantly than before selection （P＜ 0.05）. CONCLUSIONS The selection system for drug directory of the county-level medical community constructed in this study is scientific， objective and operable. This process facilitates the promotion of standardized and unified management of drugs in the medical community.

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.