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.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

ObjectiveTo investigate the effect of folic acid-modified crebanine polyethylene glycol-polylactic acid hydroxyacetic acid copolymer（PEG-PLGA） nanoparticles（FA-Cre@PEG-PLGA NPs， hereinafter referred to as NPs） combined with ultrasonic irradiation on subcutaneous tumor of liver cancer in Kunming（KM） mice. MethodsEighty-four healthy male KM mice were utilized to establish a subcutaneous tumor model of mouse hepatocellular carcinoma with H22 cells， then mice were randomly divided into model group， placebo group， hydroxycamptothecin group（8 mg∙kg^-1）， low， medium and high dose crebanine raw material groups（2， 2.5， 3 mg∙kg^-1， hereinafter referred to as the low， medium and high dose crebanine groups， respectively）， low， medium and high dose NPs groups（2， 2.5， 3 mg∙kg^-1）， and low， medium and high dose NPs combined with ultrasonic irradiation groups（2， 2.5， 3 mg∙kg^-1， hereinafter referred to as the low， medium and high dose combination groups， respectively）. The corresponding doses of drugs were administered via tail vein injection， the model group received no treatment， while the placebo group was injected with an equivalent amount of normal saline. Dosing was conducted for a total of 10 times on alternate days. The body mass of the mice was monitored， and parameters such as body mass change rate， thymus index， spleen index， tumor volume， tumor weight， relative tumor growth rate（T/C）， and tumor inhibition rate（TGI） were calculated. Pathological changes in liver and kidney tissues as well as the tumor were observed by hematoxylin-eosin（HE） staining. Additionally， the levels of aspartate aminotransferase（AST）， alanine aminotransferase（ALT）， blood urea nitrogen（BUN） and creatinine（CREA） in serum of mice were detected by biochemical method. Furthermore， the effect of ultrasound on the distribution of NPs in subcutaneous tumors of mouse hepatocellular carcinoma was observed by in vivo imaging technique. ResultsAmong different treatment methods， the combination of NPs and ultrasound irradiation had the best therapeutic effect. Compared with the model group， the body mass growth rates of mice in the medium and high combination groups decreased， while the thymus index and spleen index increased， but there was no statistically significant difference in serum AST， ALT， BUN and CREA levels， indicating that NPs combined with ultrasound irradiation had little effect on the normal physiological state of the body， oth groups had TGI>40% and T/C<60%， indicating a clear anti-tumor effect. Pathological analysis showed that compared with the NPs groups， the combination groups exhibited varying degrees of necrosis in tumor cells， accompanied by less damage to the liver and kidneys. In vivo imaging of small animals showed that compared with the high dose NPs group， the high dose combination group had stronger tumor targeting ability（P<0.01）. ConclusionNPs combined with ultrasonic irradiation can not only effectively targeted the drug to the tumor site， inhibit the subcutaneous tumor growth of mouse liver cancer， but also decrease damage to liver and kidney tissues.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective To investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients. Methods The data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, they were divided into a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistical differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and a nomogram model was constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. Results A total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of (59.0±10.3) years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of (56.8±10.3) years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS (P＜0.05). Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody positive (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant (P＜0.05), while the association between STAS and spiculation was not significant anymore (P=0.438). Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter non-small cell lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had a good prediction efficiency for STAS. The DCA plot showed that the model had a good clinically utility. Conclusion Male, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, and the nomogram model established in this study has a good predictive value and provides reference for preoperative planning of patients.

ObjectiveTo understand the epidemiological distribution and gene evolutionary variation of influenza A (H3N2) viruses in Fengxian District, Shanghai, in the surveillance year of 2023, and to provide a reference basis for influenza prevention and control. MethodsThe prevalence of influenza virus in Fengxian District in the 2023 influenza surveillance year (April 2023‒March 2024) was analyzed. The hemagglutinin (HA) gene, neuraminidase (NA) gene, and amino acid sequences of 75 strains of H3N2 influenza viruses were compared with the vaccine reference strain for similarity matching and phylogenetic evolutionary analysis, in addition to an analysis of gene characterization and variation. ResultsIn Fengxian District, there was a mixed epidemic of H3N2 and H1N1 in the spring of 2023, with H3N2 being the predominant subtype in the second half of the year, and Victoria B becoming the predominant subtype in the spring of 2024. A total of 75 influenza strains of H3N2 with HA and NA genes were distributed in the 3C.2a1b.2a.2a.2a.3a.1 and B.4 branches, with overall similarity to the reference strain of the 2024 vaccine higher than that of the reference strain of the 2022 and 2023 vaccine. Compared with the 2023 vaccine reference strain, three antigenic sites and one receptor binding site were changed in HA, with three glycosylation sites reduced and two glycosylation sites added; where as in NA seven antigenic sites and the 222nd resistance site changed with two glycosylation sites reduced. ConclusionThe risk of antigenic variation and drug resistance of H3N2 in this region is high, and it is necessary to strengthen the publicity and education on the 2024 influenza vaccine and long-term monitoring of influenza virus prevalence and variation levels.

OBJECTIVE To assess the scientific rigor， clarity and feasibility of the recommendations of the Guidelines for Evidence-based Use of Biological Agents for the Clinical Treatment of Osteoporosis （hereinafter referred to as the Guideline） through external review， in order to further revise and improve the Guideline recommendations. METHODS This study employed a cross-sectional survey research design， a convenience sampling method was adopted to select frontline medical workers in the field of osteoporosis （including clinical doctors， clinical pharmacists， and nurses） as well as patients or their family members. External review was conducted through a combination of closed-ended and open-ended electronic questionnaires to get feedback from them on the appreciation，clarity and feasibility of the 32 preliminary recommendations in the Guideline. RESULTS A total of 90 external review subjects from 15 hospitals were collected， including 45 clinical doctors， 15 clinical pharmacists， 15 nurses and 15 patients or their family members. The overall appreciation degree of recommendations was 99.38%， the overall clarity degree of recommendations was 98.92%， and the overall feasibility degree of recommendations was 99.65%. At the same time， 111 subjective suggestions were collected， which provided an important reference for the further improvement of the Guideline recommendations. Based on the above feedback， the Guideline steering committee and core expert group revised the wording of 12 draft recommendations without deletion， and finally determined 32 recommendations. CONCLUSIONS The external review provides an important basis for the final formation of the Guideline， further improves the scientific rigor， clarity and feasibility of the recommendations， and ensures the standardization， practicality and implementability of the Guideline.

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.

ObjectiveTo investigate the protective effect and mechanism of Shaoyaotang （SYD） on the lipopolysaccharide （LPS）-induced damage of tight junction proteins in the human colorectal adenocarcinoma （Caco-2） cell model of inflammation via the Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） pathway. MethodsCaco-2 cells were grouped as follows： Blank， model （LPS， 10 mg·L^-1）， SYD-containing serum （10%， 15%， and 20%）， and inhibitor （Fasudil， 25 μmol·L^-1）. After 24 hours of intervention， the cell viability in each group was examined by the cell-counting kit 8 （CCK-8） method. Enzyme-linked immunosorbent assay was employed to determine the levels of endothelin-1 （ET-1）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of RhoA， ROCK2， claudin-5， and zonula occludens-1 （ZO-1） in cells of each group. ResultsCompared with the blank group， the model group showcased a marked reduction in the cell viability （P<0.01）， elevations in the levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， declines in both mRNA and protein levels of ZO-1 and claudin-5 （P<0.01）， and rises in mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Compared with the model group， the Shaoyaotang-containing serum （10%， 15%， and 20%） groups had enhanced cell viability （P<0.01）， lowered levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， up-regulated mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and down-regulated mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Moreover， the inhibitor group and the 15% and 20% Shaoyaotang-containing serum groups had lower levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， higher mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and lower mRNA and protein levels of RhoA and ROCK2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can lower the levels of LPS-induced increases in levels of inflammatory cytokines and endothelin to ameliorate the damage of tight junction proteins of the Caco-2 cell model of inflammation by regulating the expression of proteins in the RhoA/ROCK pathway.

ObjectiveTo investigate the protective effect and mechanism of Shaoyaotang （SYD） on the lipopolysaccharide （LPS）-induced damage of tight junction proteins in the human colorectal adenocarcinoma （Caco-2） cell model of inflammation via the Ras homolog gene family member A （RhoA）/Rho-associated coiled-coil forming protein kinase （ROCK） pathway. MethodsCaco-2 cells were grouped as follows： Blank， model （LPS， 10 mg·L^-1）， SYD-containing serum （10%， 15%， and 20%）， and inhibitor （Fasudil， 25 μmol·L^-1）. After 24 hours of intervention， the cell viability in each group was examined by the cell-counting kit 8 （CCK-8） method. Enzyme-linked immunosorbent assay was employed to determine the levels of endothelin-1 （ET-1）， tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of RhoA， ROCK2， claudin-5， and zonula occludens-1 （ZO-1） in cells of each group. ResultsCompared with the blank group， the model group showcased a marked reduction in the cell viability （P<0.01）， elevations in the levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， declines in both mRNA and protein levels of ZO-1 and claudin-5 （P<0.01）， and rises in mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Compared with the model group， the Shaoyaotang-containing serum （10%， 15%， and 20%） groups had enhanced cell viability （P<0.01）， lowered levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.01）， up-regulated mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and down-regulated mRNA and protein levels of RhoA and ROCK2 （P<0.01）. Moreover， the inhibitor group and the 15% and 20% Shaoyaotang-containing serum groups had lower levels of ET-1， TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， higher mRNA and protein levels of ZO-1 and claudin-5 （P<0.05， P<0.01）， and lower mRNA and protein levels of RhoA and ROCK2 （P<0.05， P<0.01） than the 10% Shaoyaotang-containing serum group. ConclusionThe Shaoyaotang-containing serum can lower the levels of LPS-induced increases in levels of inflammatory cytokines and endothelin to ameliorate the damage of tight junction proteins of the Caco-2 cell model of inflammation by regulating the expression of proteins in the RhoA/ROCK pathway.