To introduce the general thinking, guidelines, work objectives and elaboration process of the general technical requirements adopted by volume Ⅳ of the Chinese Pharmacopoeia 2025 Edition, and to summarize and figure out the main characteristics on dosage forms, physico-chemical testing, microbial and biological testing, reference standards and guidelines The newly revised general chapters of pharmacopoeia give full play to the normative and guiding role of the Chinese Pharmacopoeia standard, track the frontier dynamics of international drug regulatory science and the elaboration of monographs, expand the application of state-of-the-art technologies, and steadily promote the harmonization and unification with the ICH guidelines； further enhance the overall capacity of TCM quality control, actively implement the 3 R principles on animal experiments, and practice the concept of environmental-friendly； replace and/or reduce the use of toxic and hazardous reagents, strengthen the requirements of drug safety control This paper aims to provide a full-view perspective for the comprehensive, correct understanding and accurate implementation of general technical requirements included in the Chinese Pharmacopoeia 2025 Edition.

ObjectiveTo establish the fingerprints of 15 batches of Hengzhi Kechuan capsules， to quantitatively analyze 10 index components， and to evaluate the quality uniformity of samples from different batches. MethodsThe fingerprints and quantitative analysis of Hengzhi Kechuan capsules were established by a combination method of high performance liquid chromatography coupled with diode array detector and charged aerosol detector（HPLC-DAD-CAD）， adenosine， guanosine， vanillic acid， safflomin A， agarotetrol， naringin， hesperidin， militarine， ginsenoside Rb₁， and glycyrrhizic acid were selected as quality attribute indexes. A total of 15 batches of Hengzhi Kechuan capsules from 2022 to 2024（3 boxes per batch） were qualitatively and quantitatively analyzed， and the quality uniformity level of the manufacturers was characterized by parameters of intra-batch consistency（P_A） and inter-batch consistency（P_B）. The homogeneity and difference of quality attribute indexes of samples from different years were analyzed by heatmap clustering analysis. ResultsHPLC fingerprints and quantitative method of Hengzhi Kechuan capsules were established， and the methods could be used for qualitative and quantitative analysis of this preparation， which was found to be stable and reliable by method validation. The similarity of fingerprints of 15 batches of samples was 0.887-0.975， a total of 13 common peaks were calibrated， and 10 common peaks were designated， all of which were quality attribute index components. The results of quantitative analysis showed that the contents of the above 10 ingredients in the samples were 0.038-0.078， 0.115-0.251， 0.007-0.018， 0.291-0.673， 0.122-0.257， 0.887-1.905， 1.841-3.364， 1.412-2.450， 2.207-3.112， 0.650-1.161， respectively. And the contents of ginsenoside Rb₁ and glycyrrhizic acid met the limit requirements in the 2020 edition of Chinese Pharmacopoeia. For the samples from 15 batches， the P_A values of the 10 index components were all <10%， indicating good intra-batch homogeneity， and the P_B values ranged from 33.86% to 92.97%， suggesting that the inter-batch homogeneity was poor. Heatmap clustering analysis showed that the samples from different years were clustered into separate categories， and adenosine， guanosine， safflomin A， naringin， hesperidin and agarotetrol were the main differential components. ConclusionThe intra-annual quality uniformity of Hengzhi Kechuan capsules is good and the inter-annual quality uniformity is insufficient， which may be related to the quality difference of Pinellinae Rhizoma Praeparatum， Carthami Flos， Citri Sarcodactylis Fructus， Citri Reticulatae Pericarpium， Aquilariae Lignum Resinatum， Citri Fructus， etc. In this study， the fingerprint and multi-indicator determination method of Hengzhi Kechuan capsules was established， which can be used for more accurate and efficient quality control and standardization enhancement.

Objective: To explore the causal association between dietary components (carbohydrate, fat, protein, and sugar) and 119 genera of known gut microbiota using Mendelian randomization (MR) methods. Methods: Genome-wide association study (GWAS) data for dietary components were collected from the DietGen, while GWAS data for gut microbiota were collected from the MiBioGen. Single nucleotide polymorphism (SNP) loci associated with the four dietary components were used as instrumental variables, and 119 known gut microbiota genera were used as the outcomes. MR analysis was performed using inverse variance weighted (IVW) method. Heterogeneity was evaluated using Cochran's Q test, horizontal pleiotropy and exclude outliers were tested using MR-Egger regression and MR-PRESSO test. Common genetic pleiotropic genes between dietary components and gut microbiota were identified by MAGMA and PLACO analyses. Results: The MR analysis revealed causal associations between carbohydrates and 4 gut microbiota genera, fats and 14 genera, proteins and 14 genera, and sugars and 11 genera (all P<0.05). The MR-Egger regression analysis showed no horizontal pleiotropy among the selected SNPs, and the MR-PRESSO test did not identify any outliers (all P>0.05). The MAGMA and PLACO analyses revealed that 74.42% (32/43) of the causal associations had pleiotropic genes, with 1 to 10 pleiotropic genes identified. Multiple causal association groups shared the same pleiotropic genes. Conclusion There are potential genetic and causal associations between dietary components and gut microbiota.

Objective To explore and verify the prognostic value of endothelial cells in glioblastoma. Methods Through bioinformatics analysis of the TCGA and CGGA databases, we screened endothelial cell-related markers in GBM single-cell data according to a series of criteria. Moreover, univariate Cox regression analysis was performed to obtain and screen endothelial cell prognosis-related markers and construct endothelial cell-related prognostic risk score. qPCR experiments was used to verify the differences in the expression of prognostic markers in GBM tissues and peritumoral normal brain tissues. Kaplan-Meier method was used to construct the survival curve to identify the prognostic efficacy of the prognostic risk score. Results A total of 2 115 prognostic genes of glioblastoma (GBM) were screened. Among them, 1 494 was upregulated and 621 was downregulated. Seven groups of cells were obtained after GBM single-cell sequencing analysis, including AC-like tumor cells, endothelial cells, monocytes/macrophages, NB-like tumor cells, neurons, OC-like tumor cells, and OPC-like tumor cells. According to the differential genes of endothelial cells and the corresponding screening criteria, four genes (DUSP6, STC1, VWA1, and TM4SF1) were screened for risk-score construction. The expression of the target gene in GBM tissues and normal brain tissues around the tumor was significantly up-regulated detected by qPCR. The risk score=0.171*DUSP6+0.144*STC1+0.041*VWA1−0.004*TM4SF1. Conclusion The glioblastoma endothelial cells’ risk score determined in this study can preferably predict the prognosis of patients.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

ObjectiveTo explore quality difference factors of Perillae Caulis based on the contents of multiple chemical components and comprehensively evaluate the quality. MethodsA total of 32 batches of Perillae Caulis samples were collected from 12 producing areas such as Hebei， Anhui and Guangdong， and their diameter range， epidermis color and producing areas were recorded. Total flavonoids， total phenols， volatile oils， 5 active components and 84 volatile components in 32 batches of samples were quantitatively or semi-quantitatively determined by colorimetry， ultra performance liquid chromatography-photodiode array detector（UPLC-PDA） and gas chromatography-mass spectrometry（GC-MS）. Then the differences between the contents of these components were analyzed by principal component analysis（PCA） and non-parametric test. According to the weights of the index components determined by PCA model， entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） model was constructed to evaluate the quality of Perillae Caulis with different characters and origins. ResultsThere were significant differences in the composition of Perillae Caulis with different diameters， epidermis colors and producing areas， and 9 differential components were screened out， including 6 index constituents（total flavonoids， total phenols， caffeic acid， scutellarin， rosmarinic acid and luteolin） and 3 volatile components（caryophyllene oxide， （-）-humulene epoxide Ⅱ， 14-hydroxycaryophyllene）， of which 6 index constituents were higher in samples with small diameter， purple-brown epidermis and southern origin， while the contents of 3 volatile components were higher in samples with large diameter， dark-brown epidermis and northern origin. A significant difference was shown in the model scores of different diameters， epidermis colors and origins（P<0.05）， and the scores of Perillae Caulis with small diameter and purple-brown epidermis from southern area， especially Guangdong， had a high score. ConclusionThere are significant differences in the composition and content of chemical constituents between different diameters， epidermal colors and production areas of Perillae Caulis， samples showing small diameter， owing purple-brown epidermis， and originating from Guangdong were of higher-quality due to their higher content of 8 key indices.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Cholelithiasis is a common biliary system disease with a high incidence worldwide. Abnormal lipid metabolism has been shown to play a key role in the mechanism of gallstones. Therefore, recent research literature on the genes, proteins, and molecular substances involved in lipid metabolism during the pathogenesis of gallstones has been conducted. This study aimed to determine the role of lipid metabolism in the pathogenesis of gallstones and provide insights for future studies using previous research in genomics, metabolomics, transcriptomics, and other fields.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.