In recent years， traditional Chinese medicine （TCM） has achieved significant progress in the treatment of inflammatory bowel disease （IBD）. A comprehensive literature search was conducted covering the period from January 1， 2010， to December 30， 2024， across Chinese databases including China National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP China Science and Technology Journal Database， and the Chinese Biomedical Literature Service System， as well as international databases such as PubMed， Web of Science， and Embase. The clinical applications and mechanistic studies of TCM in IBD were systematically reviewed. The current status of TCM research on the etiology and pathogenesis of IBD， innovative clinical practices， and multimodal therapeutic approaches， including Chinese herbal formulas， single herbs or active compounds， acupuncture， herbal retention enema， and acupoint application， were summarized， together with their synergistic effects when combined with western medical treatments. The development and application of Chinese patent medicines for IBD are undergoing a profound transition from efficacy validation to mechanistic exploration. Mechanistic studies on the effects of TCM in IBD mainly focus on regulating gut microbiota homeostasis， repairing the intestinal mucosal barrier， and modulating intestinal immune balance. Furthermore， future research directions for TCM-based IBD management are proposed， including the establishment of TCM diagnostic and treatment models， expanding integrated applications of external and internal TCM therapies， innovating personalized treatment strategies， and advancing drug development. These efforts aim to provide insights for the standardized and precision-oriented development of TCM in the diagnosis and treatment of IBD.

OBJECTIVE To investigate the improvement effect and potential mechanism of Qingxue xiaozhi jiangtang formula on insulin resistance （IR） in type 2 diabetes mellitus （T2DM） rats. METHODS T2DM rat model was established by intraperitoneal injection of 30 mg/kg streptozotocin combined with high-fat and high-sugar diet. The rats were randomly divided into normal control group， model group， Qingxue xiaozhi jiangtang formula low-dose and high-dose groups （6.525， 13.05 g/kg， calculated by raw material） and metformin group （positive control， 0.18 g/kg）， with 8 rats in each group. Administration groups were given relevant medicine intragastrically； normal control group and model group were given constant volume of normal saline intragastrically， once a day， for consecutive 6 weeks. Body mass and fasting blood glucose （FBG） were determined， and oral glucose tolerance test was conducted. Serum fasting insulin （FINS） level was measured to calculate the insulin resistance index （HOMA-IR） and insulin sensitivity index （ISI）. Additionally， the level of serum lipids， liver function， oxidative stress indicators and inflammatory factors were assessed. The phosphorylation levels of kinase R-like endoplasmic reticulum kinase （PERK） and forkhead box O1 （FOXO1） protein in liver tissue of rats were determined. RESULTS Compared with model group， the body weight， ISI， the levels of high-density lipoprotein cholesterol and superoxide dismutase were increased significantly in Qingxue xiaozhi jiangtang formula high-dose group and metformin group （P＜0.05）； FBG， blood glucose level at 120 minutes of glucose loading， area under the curve of glucose， FINS， HOMA-IR， low-density lipoprotein cholesterol， total cholesterol， triglyceride， alanine transaminase， aspartate transaminase， alkaline phosphatase， malondialdehyde， interleukin-6， tumor necrosis factor-α， and C-reactive protein levels were significantly reduced （P＜ Δ0.05）； the pathological damage of liver tissue had significantlyimproved， and the phosphorylation levels of PERK and FOXO1 proteins in liver tissue were significantly decreased （P＜0.05）. CONCLUSIONS Qingxue xiaozhi jiangtang formula can regulate glucose and lipid metabolism， inflammation factor and oxidative stress levels， and alleviate insulin resistance in T2DM rats. Its mechanism of action may be related to the inhibition of the PERK/FOXO1 signaling pathway.

According to the work goals and tasks determined by edition outline of the Chinese Pharmacopoeia 2025 Edition, the Chinese Pharmacopoeia 2025 has been completed. Among them, 52 new pharmaceutical excipients monographs have been added, and the total number has reached 387. 245 pharmaceutical excipients monographs have been revised, of which 109 monographs have only textual revisions and 136 monographs have substantive revisions. This article focuses on the general framework and the main characteristics of the standards of pharmaceutical excipients in the Chinese Pharmacopoeia 2025, which can contribute to accurately understand and utilize the standards in Chinese Pharmacopoeia.

Pregnancy complicated by aortic root aneurysm in patients with Marfan syndrome is one of the main causes of termination of pregnancy or even death in pregnant women. A very small number of pregnant women require cardiac surgery to preserve pregnancy under extracorporeal circulation, and all surgeries use aortic root replacement. We reported a 30-year-old patient with severe aortic regurgitation combined with giant aortic root aneurysm and Marfan syndrome in mid-pregnancy. Valve-sparing root replacement using reimplantation technology was performed via a multidisciplinary cooperation model. This not only achieved the patient’s desire to continue pregnancy but also avoided the anticoagulation and bleeding complications brought by mechanical valve replacement, reduced pregnancy risks and improved long-term quality of life. Postoperative echocardiography showed a small amount of aortic valve regurgitation, aortic valve coaptation height of 0.6 cm, effective height of 1.1 cm, maximum aortic flow velocity of 1.4 m/s, mean transvalvular pressure gradient of 4.4 mm Hg, and satisfactory clinical results.

In recent years, cancer treatment methods and means are becoming more and more diversified, and single treatment methods often have limited efficacy, while the synergistic effect of immunity combined with chemotherapy can inhibit tumor growth more effectively. Based on this, we constructed a sodium alginate hydrogel composite system loaded with chemotherapeutic agents and tumor vaccines (named SA-DOX-NA) with a view to the combined use of chemotherapeutic agents and tumor vaccines. Firstly, the tumor vaccine (named NA) degradable under acidic conditions was constructed by in situ polymerization using chicken ovalbumin (OVA), acrylamide (AAM) and 2-(dimethylamino) ethyl methacrylate (DMAEMA) monomer. Then a hydrogel composite system SA-DOX-NA co-loaded with chemotherapeutic drug doxorubicin (DOX) and NA was prepared using sodium alginate as a matrix. The results showed that SA-DOX-NA had good in situ gel-forming ability and formed a mesh structure that could realize the co-loading of DOX and NA as well as the slow drug release. The electron microscopy results showed that SA-DOX-NA had good in situ gel-forming ability with good internal connectivity, and the three-dimensional mesh structure could realize the co-loading of DOX and NA as well as the slow drug release. The antitumor and immunomodulatory results showed that SA-DOX-NA both effectively inhibited the growth of tumor cells and efficiently promoted the proliferation and activation of DC2.4 dendritic cells without additional adjuvant. In summary, SA-DOX-NA exerts the dual efficacy of chemotherapy and immunotherapy for tumor treatment, and has a good application prospect in local tumor treatment.

ObjectiveTo improve the therapeutic effect of Buyang Huanwutang（BYHW） on diabetic kidney disease （DKD） and explore new methods for developing new Chinese medicine decoctions，we utilized 5-hydroxymethylcytosine （5hmC）-Seal sequencing technology and network pharmacology to modify BYHW. MethodsWe selected 14 diabetes mellitus （DM） patients and 15 DKD patients hospitalized in the Department of Endocrinology of Peking University Third Hospital in 2021. Circulating free DNA （cfDNA） in the patients’ plasma was sequenced. After data processing and screening， we performed temporal clustering analysis to select a DKD 5hmC gene set， which was then cross-validated with a DKD database gene set to obtain the DKD gene set. We retrieved target genes of the seven herbal components of BYHW from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP） and the Encyclopedia of Traditional Chinese Medicine （ETCM）， and performed cross-analysis with the DKD gene set to identify common genes shared by the disease and the Chinese medicines. A protein-protein interaction （PPI） network was constructed for the common genes to screen out the key genes. Chinese medicines targeting these key genes were searched against ETCM to identify removable Chinese medicines. Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis was performed on non-common DKD genes， and key genes in DKD-related pathways were selected based on machine learning. The GSE30529 dataset was used to verify the expression trends of 5hmC-modified genes and the feasibility of target genes as drug targets. TCMBank was used to search for target genes and obtain compounds targeting these genes and the corresponding Chinese medicines to construct a "key target-compound-Chinese medicine" network. Molecular docking was employed to verify the binding affinity of compounds with key targets. TCMSP and ETCM were used to search and count the candidate Chinese medicines targeting DKD-related genes， and a new decoction was formed by adding the selected Chinese medicines. A mouse model of DKD was established to examine the efficacy of the new decoction based on the mouse body mass， random blood glucose， urinary microalbumin （mALB）， serum creatinine （Scr）， and blood urea nitrogen （BUN） and by hematoxylin-eosin staining， periodic acid-Schiff staining， Masson staining， immunofluorescence assay， and Real-time PCR. ResultsThe cross-analysis results showed that the DKD gene set included 507 genes， of which 30 were target genes of BYHW. The PPI analysis indicated that the top 15% target genes regarding the degree were interleukin-6 （IL-6）， Toll-like receptor 4 （TLR4）， lactotransferrin （LTF）， lipoprotein lipase （LPL）， and sterol regulatory element-binding transcription factor 1 （SREBF1）. Persicae Semen and Pheretima in BYHW were unrelated to key genes and removed. Machine learning identified 10 potential target genes， among which TBC1 domain family member 5 （TBC1D5）， RAD51 paralog B （RAD51B）， and proteasome 20S subunit alpha 6 （PSMA6） had expression trends consistent with the GSE30529 dataset and could serve as drug targets. The "key target-compound-Chinese medicine" network and molecular docking results indicated that the compounds with good binding affinity to target proteins were arginine， glycine， myristicin， serine， and tyrosine， corresponding to 121 Chinese medicines. The top 10 Chinese medicines targeting DKD-related genes were Lycii Fructus， Ginseng Radix et Rhizoma， Dioscoreae Rhizoma， Rehmanniae Radix Praeparata， Isatidis Radix， Glehniae Radix， Ophiopogonis Radix， Allii Sativi Bulbus， Isatidis Folium， and Bolbostemmatis Rhizoma. Based on traditional Chinese medicine theory， the new decoction was obtained after removal of Persicae Semen and Pheretima and addition of Rehmanniae Radix Praeparata and Dioscoreae Rhizoma. Animal experiment results indicated that the modified BYHW improved the kidney function and inhibited renal fibrosis in DKD mice， with better effects than the original decoction. ConclusionThe BYHW modified based on 5hmC-Seal sequencing demonstrates better performance in inhibiting fibrosis and ameliorating DKD than the original decoction. This elucidates the biomedical theory behind the epigenetic modification of traditional Chinese medicine prescriptions， potentially offering new perspectives for the exploration of these prescriptions

ObjectiveTo improve the therapeutic effect of Buyang Huanwutang（BYHW） on diabetic kidney disease （DKD） and explore new methods for developing new Chinese medicine decoctions，we utilized 5-hydroxymethylcytosine （5hmC）-Seal sequencing technology and network pharmacology to modify BYHW. MethodsWe selected 14 diabetes mellitus （DM） patients and 15 DKD patients hospitalized in the Department of Endocrinology of Peking University Third Hospital in 2021. Circulating free DNA （cfDNA） in the patients’ plasma was sequenced. After data processing and screening， we performed temporal clustering analysis to select a DKD 5hmC gene set， which was then cross-validated with a DKD database gene set to obtain the DKD gene set. We retrieved target genes of the seven herbal components of BYHW from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP） and the Encyclopedia of Traditional Chinese Medicine （ETCM）， and performed cross-analysis with the DKD gene set to identify common genes shared by the disease and the Chinese medicines. A protein-protein interaction （PPI） network was constructed for the common genes to screen out the key genes. Chinese medicines targeting these key genes were searched against ETCM to identify removable Chinese medicines. Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis was performed on non-common DKD genes， and key genes in DKD-related pathways were selected based on machine learning. The GSE30529 dataset was used to verify the expression trends of 5hmC-modified genes and the feasibility of target genes as drug targets. TCMBank was used to search for target genes and obtain compounds targeting these genes and the corresponding Chinese medicines to construct a "key target-compound-Chinese medicine" network. Molecular docking was employed to verify the binding affinity of compounds with key targets. TCMSP and ETCM were used to search and count the candidate Chinese medicines targeting DKD-related genes， and a new decoction was formed by adding the selected Chinese medicines. A mouse model of DKD was established to examine the efficacy of the new decoction based on the mouse body mass， random blood glucose， urinary microalbumin （mALB）， serum creatinine （Scr）， and blood urea nitrogen （BUN） and by hematoxylin-eosin staining， periodic acid-Schiff staining， Masson staining， immunofluorescence assay， and Real-time PCR. ResultsThe cross-analysis results showed that the DKD gene set included 507 genes， of which 30 were target genes of BYHW. The PPI analysis indicated that the top 15% target genes regarding the degree were interleukin-6 （IL-6）， Toll-like receptor 4 （TLR4）， lactotransferrin （LTF）， lipoprotein lipase （LPL）， and sterol regulatory element-binding transcription factor 1 （SREBF1）. Persicae Semen and Pheretima in BYHW were unrelated to key genes and removed. Machine learning identified 10 potential target genes， among which TBC1 domain family member 5 （TBC1D5）， RAD51 paralog B （RAD51B）， and proteasome 20S subunit alpha 6 （PSMA6） had expression trends consistent with the GSE30529 dataset and could serve as drug targets. The "key target-compound-Chinese medicine" network and molecular docking results indicated that the compounds with good binding affinity to target proteins were arginine， glycine， myristicin， serine， and tyrosine， corresponding to 121 Chinese medicines. The top 10 Chinese medicines targeting DKD-related genes were Lycii Fructus， Ginseng Radix et Rhizoma， Dioscoreae Rhizoma， Rehmanniae Radix Praeparata， Isatidis Radix， Glehniae Radix， Ophiopogonis Radix， Allii Sativi Bulbus， Isatidis Folium， and Bolbostemmatis Rhizoma. Based on traditional Chinese medicine theory， the new decoction was obtained after removal of Persicae Semen and Pheretima and addition of Rehmanniae Radix Praeparata and Dioscoreae Rhizoma. Animal experiment results indicated that the modified BYHW improved the kidney function and inhibited renal fibrosis in DKD mice， with better effects than the original decoction. ConclusionThe BYHW modified based on 5hmC-Seal sequencing demonstrates better performance in inhibiting fibrosis and ameliorating DKD than the original decoction. This elucidates the biomedical theory behind the epigenetic modification of traditional Chinese medicine prescriptions， potentially offering new perspectives for the exploration of these prescriptions

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.

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.

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.