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.

Objective This research was performed to identify rodent-borne pathogens in Hekou Port,Yunnan Province.Methods Rodents were captured using cages and dissected to collect their lungs,liver,spleen,and other viscera.Eight pathogens,including Yersinia pestis,Leptospira,Bartonella,and Anaplasmataceae,were identified using polymerase chain reaction amplification.Amplified pathogen sequences from positive samples were sequenced,and BLAST homology searches were conducted using GenBank to confirm pathogen identities.A phylogenetic tree of the identified pathogens was constructed using the neighbor joining method.Results The total of 31 rodents,identified as Rattus tanezumi,R.norvegicus,and Mus musculus,were captured.Among these,R.tanezumi was the dominant species,accounting for 64.52％of the total.Two pathogens,Leptospira interrogans and Neoehrlichia mikurensis,were detected,with positivity rates of 9.68％and 29.03％,respectively.No other pathogens were detected.The overall positivity rate for rodent-borne pathogens was 35.48％.Conclusions The single 16S rRNA gene fragment is insufficient for the molecular identification of all Neoehrlichia species.Accurate species identification should be based on a combined analysis of multiple genes.The prevalence of rodent-borne pathogens in Hekou Port indicates the necessity for enhanced surveillance of rodent-borne diseases and implementation of additional prevention and control measures in border ports.

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.

Objective:To investigate the value of gadoxetate disodium-enhanced MRI combined with T 1 mapping in preoperative prediction of cytokeratin 19 (CK19) and glypican-3 (GPC3) positive dual-phenotype hepatocellular carcinoma (DPHCC). Methods:This case-control study included retrospectively enrolled patients with pathologically confirmed HCC from Central People′s Hospital of Zhanjiang (training set, n=85; December 2020 to July 2022) and the Second Affiliated Hospital, School of Medicine, South China University of Technology (test set, n=35; April 2023 to April 2024). Patients were categorized into CK19 and GPC3 positive DPHCC group (training set=19, test set=11) and non-DPHCC group (training set=66, test set=24) based on postoperative immunohistochemical staining. All patients received preoperative MRI scans, including gadoxetate disodium-enhanced imaging and T 1 mapping. Clinical data were collected, qualitative MRI features were evaluated, and quantitative parameters were measured, including signal intensity, T 1 values, apparent diffusion coefficient (ADC), tumor-to-liver ADC ratio (rADC), tumor-to-liver signal intensity ratio, and T 1 relaxation time reduction rate (ΔT 1%). Statistical comparisons between groups were performed using independent t-tests, Mann-Whitney U tests, or χ2 tests. Multivariate logistic regression identified independent predictors of CK19 and GPC3 positive DPHCC, and a combined model was constructed. Predictive performance was evaluated using area under the receiver operating characteristic curve (AUC), with DeLong test comparing model performance. Results:Significant intergroup differences were observed in alpha-fetoprotein (AFP), total bilirubin, direct bilirubin, DWI target sign, rADC, hepatobiliary-phase T 1 (T 1HBP), and ΔT 1% ( P<0.05). Multivariate analysis identified AFP>20 ng/ml ( OR=5.835, 95% CI 1.019-33.397, P=0.048), DWI target sign ( OR=13.408, 95% CI 2.216-81.131, P=0.005), and ΔT1%≤31% ( OR=14.429, 95% CI 2.166-96.125, P=0.006) as independent predictors of DPHCC. The AUC values of the aforementioned three independent predictors and the combined model for predicting DPHCC were 0.641 (95% CI 0.530-0.742), 0.679 (95% CI 0.569-0.777), 0.740 (95% CI 0.634-0.829), and 0.886 (95% CI 0.799-0.945) in the training set, and 0.568 (95% CI 0.390-0.743), 0.669 (95% CI 0.490-0.818), 0.689 (95% CI 0.511-0.843), and 0.824 (95% CI 0.658-0.931) in the test set, respectively. The DeLong test results showed that in the training set, the diagnostic performance of the combined model was superior to those of the three individual features ( Z=3.68, P<0.001; Z=3.15, P=0.002; Z=3.15, P=0.002). In the test cohort, the combined model demonstrated better diagnostic performance than AFP>20 ng/ml and ΔT 1%≤31% ( Z=2.15, P=0.032; Z=2.12, P=0.034), while no statistically significant difference was observed compared with the DWI target sign ( Z=1.77, P=0.076). Conclusion:The integrated model incorporating clinical data, gadoxetate disodium-enhanced MRI, and T 1 mapping parameters effectively predicts CK19 and GPC3 positive DPHCC.

Insulin is an important protein hormone that participates in multiple metabolic pathways.Biosynthetic insulin has been widely used in the treatment of type 1 and type 2 diabetes.Currently,the number of reported cases of insulin overdose both at home and abroad is gradually increasing,and insulin homicide is no longer a means of"committing murder without leaving a trace".At present,there are no systematic protocols for the identification of insulin overdose in the field of forensic medi-cine in China.This article introduces the causes,toxicological characteristics,forensic examination,labo-ratory testing methods and indicator reference of insulin overdose.Based on the identification practice and research results and referring to relevant studies on insulin overdose at home and abroad,this pa-per aims to provide recommendations and references for the formulation of forensic identification guide-lines for insulin overdose cases.

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.

Objective:To investigate the effects of hepatic fatty acid transporter 5 (FATP5) gene expression on the levels of free long-chain fatty acid (LCFA) in mice with metabolic associated fatty liver disease (MAFLD).Methods:From June to December 2022, a prospective study was conducted with three experimental groups: wild-type (WT) group, FATP5 gene expression negative (FATP5 -) group, and human FATP5 gene expression positive (hFATP5 +) group, with 10 mice in each group. Each group of mice was fed a high-fat diet for 16 weeks to establish a model of MAFLD. Hepatic tissue changes were observed using hematoxylin-eosin staining. The liver mass and liver coefficient of the mice were measured. Total cholesterol (TC), triglycerides (TG), aspartate aminotransferase (AST), alanine aminotransferase (ALT), uric acid (UA), and LCFA levels were determined using an automatic biochemical analyzer. Blood glucose (Glu) levels were measured using a blood glucose analyzer. The liver mass and liver coefficient, TC and TG levels, AST and ALT levels, Glu and UA levels, and LCFA levels were compared among the three groups. Results:In the WT group, there was significant inflammatory cell infiltration within the hepatocytes and a large amount of fat accumulation. In the FATP5 - group, the inflammatory cell infiltration in the hepatocytes was mild with slight fat accumulation. In the hFATP5 + group, the inflammatory cell infiltration in the hepatocytes was severe, with great fat accumulation. The liver mass [(1.27 ± 0.25) g], liver coefficient (2.38 ± 0.19), TC [(1.82 ± 0.26) mmol/L], TG [(0.93 ± 0.24) mmol/L], AST [(169.95 ± 37.73) U/L], ALT [(95.36 ± 21.49) U/L], Glu [(8.34 ± 1.52) mmol/L], and UA [(74.32 ± 15.52) μmol/L] in the FATP5 - group were all significantly lower than those in the WT group [(1.61 ± 0.23) g, (2.71 ± 0.20), (2.31 ± 0.28) mmol/L, (1.34 ± 0.21) mmol/L, (278.31 ± 43.24) U/L, (147.32 ± 28.81) U/L, (10.52 ± 1.24) mmol/L, (96.28 ± 17.43) μmol/L], while the LCFA level [(3.57 ± 0.48) mg/L] in the FATP5 - group was significantly higher than that in the WT group [(2.63 ± 0.56) mg/L] ( t = 3.17, 3.78, 4.06, 4.07, 5.97, 4.57, 3.51, 2.98, 4.03, all P < 0.05). In the hFATP5 + group, the liver mass [(1.92 ± 0.30) g], liver coefficient (2.95 ± 0.23), TC [(2.59 ± 0.24) mmol/L], TG [(1.76 ± 0.35) mmol/L], AST [(341.22 ± 48.98) U/L], ALT [(189.45 ± 17.97) U/L], Glu [(13.21 ± 1.98) mmol/L], and UA [(117.74 ± 18.38) μmol/L] were all significantly higher than those in the WT group, while the LCFA level [(3.57 ± 0.48) mg/L] in the FATP5 + group was significantly lower than that in the WT group ( t = 2.59, 2.49, 2.40, 3.25, 3.04, 3.92, 3.64, 2.68, 3.19, all P < 0.05). Conclusions:The absence of FATP5 in the liver can elevate blood levels of LCFA in mice with MAFLD, reduce food intake, and help alleviate the symptoms of MAFLD.

The traditional Chinese medicine(TCM) industry is a crucial part of China's pharmaceutical sector and plays a strategic role in ensuring public health and promoting economic and social development. In response to the practical demand for high-quality development of the TCM industry, this paper focused on the bottlenecks encountered during the digital and intelligent transformation of TCM production systems. Specifically, it explored technical strategies and methodologies for constructing the best TCM production mode. An innovative artificial intelligence(AI)-centered technical architecture for TCM production was proposed, focusing on key aspects of production management including process modeling, state evaluation, and decision optimization. Furthermore, a series of critical technologies were developed to realize the best TCM production mode. Finally, a novel AI-driven TCM production mode characterized by a closed-loop system of "measurement-modeling-decision-execution" was presented through engineering case studies. This study is expected to provide a technological pathway for developing new quality productive forces within the TCM industry.
Artificial Intelligence ; Drugs, Chinese Herbal ; Medicine, Chinese Traditional/methods* ; Humans

Panax ginseng as a perennial herb of Araliaceae, exhibits pharmacological effects such as central nervous system stimulation, anti-tumor properties, and cardiovascular and cerebrovascular protection. The B3 gene family plays a crucial role in growth and development, antioxidant activity, stress resistance, and secondary metabolism regulation of plants and has been extensively studied in various plants. However, the identification and analysis of the B3 gene family in P. ginseng have not been reported. In this study, a total of 145 B3 genes(PgB3s) with complete open reading frames(ORF) were identified from P. ginseng and classified into five subfamilies based on domain types. Through correlation analysis with ginsenoside content, SNP/InDels analysis, and interaction analysis with key enzyme genes, 15 PgB3 transcripts were found to be significantly correlated with ginsenoside content and exhibited a close interaction network with key enzyme genes involved in ginsenoside biosynthesis, which indicated that these genes may participate in the regulation of ginsenoside biosynthesis. Additionally, this study found that PgB3 genes exhibited induced expression in response to methyl jasmonate(MeJA) stress, which aligned with the presence of abundant stress response elements in their promoters, confirming the important role of the B3 gene family in P. ginseng in stress resistance. The results of this study revealed the potential functions of PgB3 genes in ginsenoside biosynthesis and stress response, providing a significant theoretical basis for further research on the functions of PgB3 genes and their regulatory mechanisms.
Panax/metabolism* ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Ginsenosides/biosynthesis* ; Multigene Family ; Phylogeny