In 2025, significant breakthroughs were achieved in various aspects of liver transplantation, including xenotransplantation, machine perfusion, minimally invasive surgery, precise immune regulation and artificial intelligence, etc. The successful implementation of gene-modified pig-to-human assisted liver transplantation marked the official entry of xenotransplantation into the clinical transformation stage. The machine perfusion technology completed multiple large-scale clinical validations, significantly improving the transplantation outcomes of marginal donor livers and donor livers from donation after cardiac death, and pushing organ preservation into the era of dynamic functional assessment. Split liver transplantation and living donor liver transplantation continuously optimized in terms of donor-recipient matching, liver utilization and perioperative management. Robotic and laparoscopic technologies further promoted liver transplantation towards the direction of precision and minimally invasive surgery. Hepatocellular carcinoma liver transplantation gradually formed a precise management model centered on immunotherapy, bridge downgrade and recurrence risk prediction. At the same time, artificial intelligence and multi-omics technologies demonstrated significant application value in prognosis prediction, organ allocation and complication risk assessment. This article conducts a systematic review of the important research progress in the field of liver transplantation in 2025 and looks forward to the future development directions and challenges.

Objective To evaluate the advantages of a real-time computer endoscopy-assisted system(EndoAngel)for colorectal lesions detection in colonoscopy.Methods 2 000 patients who underwent EndoAngel assisted colonoscopy and conventional colonoscopy were selected for the study in a single-center,self-controlled study.According to different examination methods,the patients were divided into artificial intelligence(AI)group and traditional colonoscopy group,each with 1 000 cases.The results were statistically analyzed and compared with the polyp detection rate and adenoma detection rate of the two groups using pathological diagnosis as the gold standard.Further subgroup analysis will be conducted based on the seniority of the operating physicians.Results AI group's polyp detection rate was higher(39.3％)than conventional colonoscopy group polyp detection rate(29.0％),with statistically significant difference(x2=23.59,P=0.000).Of these,the detection rates of hyperplastic polyps and adenomatous polyps were 19.1％and 25.2％,which were significantly higher than those of 12.4％and 20.8％in the conventional colonoscopy group,and the differences were statistically significant(x2=16.92,P=0.000;x2=5.46,P=0.019).Further subgroup analysis of the two groups by physician seniority,the polyp detection rate of AI low seniority group(36.6％)was higher than that of conventional colonoscopy low seniority group(20.40％),with a statistically significant difference(x2=32.20,P=0.000).Among them,the detection rates of hyperplastic polyp(17.8％)and adenomatous polyp(23.6％)in AI low seniority group were higher than those in the conventional colonoscopy low seniority group(12.8％vs 13.6％),and the differences were significant(x2=4.82,P=0.028;x2=16.51,P=0.000).There were no significant differences in adenomatous polyp detection rates between the two groups of senior physicians.Conclusion EndoAngel assisted system can improve the polyp detection rate of colonoscopy,especially for the effect of low seniority physicians is more significant.

Objective To evaluate the advantages of a real-time computer endoscopy-assisted system(EndoAngel)for colorectal lesions detection in colonoscopy.Methods 2 000 patients who underwent EndoAngel assisted colonoscopy and conventional colonoscopy were selected for the study in a single-center,self-controlled study.According to different examination methods,the patients were divided into artificial intelligence(AI)group and traditional colonoscopy group,each with 1 000 cases.The results were statistically analyzed and compared with the polyp detection rate and adenoma detection rate of the two groups using pathological diagnosis as the gold standard.Further subgroup analysis will be conducted based on the seniority of the operating physicians.Results AI group's polyp detection rate was higher(39.3％)than conventional colonoscopy group polyp detection rate(29.0％),with statistically significant difference(x2=23.59,P=0.000).Of these,the detection rates of hyperplastic polyps and adenomatous polyps were 19.1％and 25.2％,which were significantly higher than those of 12.4％and 20.8％in the conventional colonoscopy group,and the differences were statistically significant(x2=16.92,P=0.000;x2=5.46,P=0.019).Further subgroup analysis of the two groups by physician seniority,the polyp detection rate of AI low seniority group(36.6％)was higher than that of conventional colonoscopy low seniority group(20.40％),with a statistically significant difference(x2=32.20,P=0.000).Among them,the detection rates of hyperplastic polyp(17.8％)and adenomatous polyp(23.6％)in AI low seniority group were higher than those in the conventional colonoscopy low seniority group(12.8％vs 13.6％),and the differences were significant(x2=4.82,P=0.028;x2=16.51,P=0.000).There were no significant differences in adenomatous polyp detection rates between the two groups of senior physicians.Conclusion EndoAngel assisted system can improve the polyp detection rate of colonoscopy,especially for the effect of low seniority physicians is more significant.

Objective:To identify independent risk factors for early recurrence following curative resection of resectable pancreatic cancer and establish a nomogram prediction model.Methods:Clinical data from 405 patients with resectable pancreatic cancer treated at Renji Hospital, Shanghai Jiao Tong University School of Medicine from February 2010 to December 2020 were retrospectively reviewed. Patients were stratified into a training cohort (265 patients form February 2010 to December 2018) and a validation cohort (140 patients from January 2019 to December 2020) based on surgery dates. Optimal cutoff values for clinical variables were determined using X-tile software. Independent risk factors were identified through univariate and multivariate Cox proportional hazards regression analyses. Kaplan-Meier curves for recurrence-free survival (RFS) were generated across subgroups, and a nomogram was developed to predict early recurrence (within 1 year post-surgery). Time-dependent receiver operating characteristic (tROC) curves was drawn and area under the curve (AUC) metrics were utilized to evaluate predictive accuracy, while model reliability was assessed by calibration curves. Individualized risk scores derived from the nomogram were stratified into high- and low-risk groups using X-tile-derived cutoff values. Survival differences between groups were analyzed via log-rank tests. The clinical application value was judged by decision curve analysis (DCA) compared to TNM staging. Results:In the training cohort, 139 patients (52.45%) experienced early recurrence, with a median RFS of 11.1 months [interquartile range ( IQR): 6.0-26.0]. The validation cohort reported 70 early recurrences (50.00%) and a median RFS of 11.8 months ( IQR: 4.9-21.4). Univariate analysis revealed significant associations between early recurrence and tumor diameter, carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), systemic immune-inflammation index (SⅡ), and prognostic nutritional index (PNI). Multivariate analysis identified tumor diameter ≥3.75 cm ( HR=1.718, 95% CI 1.223-2.412, P=0.002), CA19-9≥218 U/ml ( HR=1.567, 95% CI 1.107-2.220, P=0.011), CA125≥20.98 U/ml ( HR=2.501, 95% CI 1.768-3.539, P<0.001), SⅡ≥388.28 ( HR=1.708, 95% CI 1.096-2.662, P=0.018), and PNI<53.18 ( HR=0.596, 95% CI 0.404-0.879, P=0.009) as independent risk factors for early recurrence. The nomogram achieved AUC values of 0.771 and 0.708 in the training and validation cohorts, respectively. Calibration curves demonstrated strong agreement between predicted and observed survival probabilities. Kaplan-Meier analysis revealed significantly lower 1-year RFS rates in high-risk versus low-risk groups for both cohorts (training: HR=3.65, 95% CI 2.45-5.44, P<0.001; validation: HR=2.37, 95% CI 1.39-4.06, P=0.001). DCA indicated superior net benefit of the nomogram over TNM staging across threshold probabilities of 0.2-0.9. Conclusions:The proposed nomogram effectively integrates clinical and serological biomarkers to preoperatively assess early recurrence risk in resectable pancreatic cancer patients, offering enhanced precision for clinical decision-making.

Objective:To identify independent risk factors for early recurrence following curative resection of resectable pancreatic cancer and establish a nomogram prediction model.Methods:Clinical data from 405 patients with resectable pancreatic cancer treated at Renji Hospital, Shanghai Jiao Tong University School of Medicine from February 2010 to December 2020 were retrospectively reviewed. Patients were stratified into a training cohort (265 patients form February 2010 to December 2018) and a validation cohort (140 patients from January 2019 to December 2020) based on surgery dates. Optimal cutoff values for clinical variables were determined using X-tile software. Independent risk factors were identified through univariate and multivariate Cox proportional hazards regression analyses. Kaplan-Meier curves for recurrence-free survival (RFS) were generated across subgroups, and a nomogram was developed to predict early recurrence (within 1 year post-surgery). Time-dependent receiver operating characteristic (tROC) curves was drawn and area under the curve (AUC) metrics were utilized to evaluate predictive accuracy, while model reliability was assessed by calibration curves. Individualized risk scores derived from the nomogram were stratified into high- and low-risk groups using X-tile-derived cutoff values. Survival differences between groups were analyzed via log-rank tests. The clinical application value was judged by decision curve analysis (DCA) compared to TNM staging. Results:In the training cohort, 139 patients (52.45%) experienced early recurrence, with a median RFS of 11.1 months [interquartile range ( IQR): 6.0-26.0]. The validation cohort reported 70 early recurrences (50.00%) and a median RFS of 11.8 months ( IQR: 4.9-21.4). Univariate analysis revealed significant associations between early recurrence and tumor diameter, carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), systemic immune-inflammation index (SⅡ), and prognostic nutritional index (PNI). Multivariate analysis identified tumor diameter ≥3.75 cm ( HR=1.718, 95% CI 1.223-2.412, P=0.002), CA19-9≥218 U/ml ( HR=1.567, 95% CI 1.107-2.220, P=0.011), CA125≥20.98 U/ml ( HR=2.501, 95% CI 1.768-3.539, P<0.001), SⅡ≥388.28 ( HR=1.708, 95% CI 1.096-2.662, P=0.018), and PNI<53.18 ( HR=0.596, 95% CI 0.404-0.879, P=0.009) as independent risk factors for early recurrence. The nomogram achieved AUC values of 0.771 and 0.708 in the training and validation cohorts, respectively. Calibration curves demonstrated strong agreement between predicted and observed survival probabilities. Kaplan-Meier analysis revealed significantly lower 1-year RFS rates in high-risk versus low-risk groups for both cohorts (training: HR=3.65, 95% CI 2.45-5.44, P<0.001; validation: HR=2.37, 95% CI 1.39-4.06, P=0.001). DCA indicated superior net benefit of the nomogram over TNM staging across threshold probabilities of 0.2-0.9. Conclusions:The proposed nomogram effectively integrates clinical and serological biomarkers to preoperatively assess early recurrence risk in resectable pancreatic cancer patients, offering enhanced precision for clinical decision-making.

Objective:To establish HPLC fingerprints of Aristolochia contorta and honey-processed Aristolochia contorta; To analyze the changes of chemical components before and after honey processing with multivariate statistics; To provide a reference for the study on the toxicity reduction of Aristolochia contorta.Methods:The fingerprints of 11 batches of Aristolochia contorta and honey-processed Aristolochia contorta were established through HPLC. Clustering analysis (HCA), principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and independent sample t-test were used to compare the changes of chemical components of Aristolochia contorta before and after honey processing.Results:The results showed that there were 14 common peaks in the fingerprints of Aristolochia contorta and Aristolochia contorta. 7 common peaks were identified. Both HCA and PCA could clearly distinguish the samples of Aristolochia contorta before and after honey processing. OPLS-DA found and screened 7 differential markers, and the order of difference significance was peak 3 > peak 7 (7-hydroxy aristolochic acid A) > peak 5 (aristolochic acid C)> peak 8 (aristolochic acid D) > peak 6 > peak 2 (Magnolia alkaloid) > peak 14 (aristolochic acid Ⅰ). After honey processing, the content of chemical components represented by peaks 2, 3, 5, 6, 7, 8 and 14 decreased ( P<0.05). Conclusion:This method is simple and specific, which can be used for the fingerprint analysis of Aristolochia contorta and honey-processed Aristolochia contorta, and can effectively distinguish Aristolochia contorta and honey-processed Aristolochia contorta, and provide a reference for the processing research of toxicity reduction of Aristolochia contorta honey processing.

Objective:To establish the ultra-high performance liquid chromatography (UPLC) fingerprint and high performance liquid chromatography (HPLC) content determination method of Curcumae Radix standard decoction; To predict the quality markers of Curcumae Radix standard decoction combined with network pharmacology.Methods:UPLC method was used to establish the fingerprint of Curcumae Radix standard decoction, and the common peaks were determined. Combined with chemical pattern recognition techniques such as similarity analysis and clustering analysis, Curcumae Radix standard decoction from different producing areas was studied, and curcumol was used as an index to determine the content of 24 batches of Curcumae Radix standard decoction. At the same time, network pharmacology was used to predict potential of curcumol and (1S, 6β)-1β-Methyl-4-(1-methylethylidene)-7β-(3-oxobutyl) bicyclo [4.1.0] heptan-3-one.Results:A total of 24 batches of Curcumae Radix standard decoction from different habitats were compared and analyzed, and 10 common peaks were calibrated. The similarity of 24 batches of samples ranged from 0.982 to 0.999. Clustering analysis and principal component analysis divided them into three categories. Heat map analysis showed that peak 8 (curcumol) and peak 9 ((1S, 6β)-1β-Methyl-4-(1-methylethylidene)-7β-(3-oxobutyl) bicyclo [4.1.0] heptan-3-one) were the main components. The content of curcumol in 24 batches of Curcumae Radix standard decoction was 0.69-1.87 mg/g; curcumol and (1S, 6β)-1β-Methyl-4-(1-methylethylidene)-7β- (3-oxobutyl) bicyclo [4.1.0] heptan-3-one may regulate the neuroactive ligand-receptor interaction signaling pathway, calcium signaling, and excitation by regulating neuroactive ligand-receptor interaction signaling pathway, calcium signaling, and excitation. It was preliminarily predicted that curcumol and (1S, 6β)-1β-Methyl-4-(1-methylethylidene)-7β-(3-oxobutyl) bicyclo [4.1.0] heptan-3-one were potential quality markers of Curcumae Radix.Conclusion:Curcumol and (1S, 6β)-1β-Methyl-4-(1-methylethylidene)-7β-(3-oxobutyl) bicyclo [4.1.0] heptan-3-one are potential quality markers of Curcumae Radix standard decoction, and the established fingerprint can be used for the quality control of Curcumae Radix standard decoction.

Objective:To investigate the expression pattern,clinical significance,and the regulatory role of 2',5'-oligoadenylate synthetase 1(OAS1)in the proliferation of pancreatic ductal adenocarcinoma(PDAC)cells.Methods:Public databases such as Gene Expression Omnibus(GEO)and The Cancer Genome Atlas(TCGA)were used to analyze the expression of OAS1 in pancreatic cancer tissues.Immunohistochemical staining was applied to validate the expression level of OAS1 in PDAC tissue microarrays,and the association between OAS1 expression level and the prognosis of patients was analyzed.Real-time fluorescence quantitative PCR was performed to examine the expression level of OAS1 mRNA in different PDAC cell lines.CCK-8 assay and colony formation assay was used to assess the effect of OAS1 on the proliferation of PDAC cells after OAS1 silencing in Patu-8988 and PDC0034 cells by siRNA treatment.Further,Gene Set enrichment analysis(GSEA)was performed to screen for possible molecular mechanism of the regulatory role of OAS1 in PDAC.Cell viability and cholesterol level was analyzed after treatment with mTOR signaling activator MHY1485 in OAS1-silenced Patu-8988 and PDC0034 cells in order to verify the underlying mechanism of the regulatory role of OAS1 in PDAC cell proliferation.Results:Database analysis showed significant upregulation of OAS1 expression in pancreatic cancer tissues(P<0.05).Immunohistochemical staining results from PDAC tissue microarray showed that OAS1 expression was significantly upregulated in PDAC tissues compared with the paired paracancerous tissues,and high OAS1 expression was associated with poor prognosis(P<0.05).Real-time fluorescence quantitative PCR and Western blotting analysis show that OAS1 expression was higher in PDAC cells lines compared with normal ductal cells of the pancreas.The proliferative activity of PDAC cells decreased significantly after OAS1 silencing in Patu-8988 and PDC0034 cells(P<0.001).GSEA results indicated that OAS1 may affect PDAC cell proliferation through mTOR signaling pathway and cholesterol metabolism associated pathway.The mTOR signaling pathway may be inhibited and the total cellular cholesterol decreased after OAS1 silencing.Treatment with mammalian target of rapamycin(mTOR)activator MHY1485 partially reversed the inhibitory effect of OAS1 silencing on the proliferation and cholesterol metabolism of PDAC cells.Conclusion:OAS1 expression is upregulated in PDAC tumor tissues and cells and is associated with poor prognosis.OAS1 may promote the proliferation of pancreatic cancer cells by enhancing cholesterol metabolism through activation of the mTOR signaling pathway.

Objective To establish an ultra-high performance liquid chromatography(UPLC)fingerprint and multi-index content determination method of Siraitiae fructus standard decoction.Methods 15 batches of Siraitiae fructus from different producing areas were collected,Siraitiae fructus standard decoction was prepared according to Technical Requirements for Quality Control and Standardization of Traditional Chinese Medicine Formula Granules,and the extract rate was calculated.UPLC was used to establish the fingerprint of 15 batches of Siraitiae fructus standard decoction and determine the contents of 11-O-mogroside V,kaempferitrin and mogroside V,which were the main effective components.The chemometrics analysis was used to evaluate the quality of Siraitiae fructus standard decoction and find possible quality markers.Results The extraction rate of 15 batches Siraitiae fructus standard decoction ranged from 24.79％to 34.95％.There were 16 common peaks in the fingerprint,and 4 components were identified.The Siraitiae fructus standard decoction was divided into 2 categories by chemometrics analysis,among which samples from Liuzhou,Guangxi were in one category and samples from Guilin,Guangxi were in another category.Seven differential markers were screened out under the condition of variable importance projection value,and the order was as follows:peak 8＞peak 7＞peak 5＞peak 12(kaempferitrin)＞peak 1＞peak 13＞peak 4.The contents of kaempferitrin,11-O-mogroside V and mogroside V in samples from Guilin,Guangxi were slightly higher than those in samples from Liuzhou,Guangxi.Conclusion The UPLC fingerprint and content determination method established in this study are feasible,which can provide a basis for the quality evaluation of Siraitiae fructus.The results of principal component analysis show that kaempferol is likely to become a quality marker of Siraitiae fructus.

Objective:To establish UPLC fingerprint method and 2 contents determination methods of Buddleja officinalis; To provide a reference for improving the quality control standard and evaluation of Buddleja officinalis from different habitats.Methods:UPLC method was used to establish the fingerprints of 17 batches of Buddleja officinalis. The similarity evaluation, clustering analysis, principal component analysis and orthogonal partial least squares discriminant analysis were used to compare the quality differences of Buddleja officinalis from different habitats. The contents of acteoside and linarin in Buddleja officinalis were determined.Results:There were 12 common peaks in UPLC fingerprints of Buddleja officinalis, six of which were identified as echinacoside, acteoside, cynaroside, isoacteoside, linarin, and apigenin. The fingerprint similarity of 17 batches of Buddleja officinalis was more than 0.9; Buddleja officinalis from different habitats were classified into 2 groups. Five differential markers were determined by OPLS-DA analysis. The order of significance was acteoside > peak 3 > echinacoside > isoacteoside > linarin. Edgeworthia chrysantha was identified by the method of fingerprint as counterfeit. The results of content determination showed that the content of Buddleja officinalis in Hubei and Sichuan was the high and stable.Conclusion:The method can effectively analyze the differences of Buddleja officinalis from different habitats, and provide reference for the quality control of Buddleja officinalis.