Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

Objective To evaluate the changes in postoperative plasma β-endorphin(β-EP)levels in patients who had received perioperative electroacupuncture(EA)treatment in 10 randomized controlled trials(RCTs)and examine the impact of EA on postoperative pain.Methods This meta-analysis evaluated the changes in plasma β-EP levels and visual analog scale(VAS)12,24 and 48 hours after surgery in patients receiving perioperative EA.It also assessed the changes in plasma serotonin(5-hydroxytryptamine,5-HT)and prostaglandin E2(PGE2)levels at 24 hours postsurgery.A comprehensive search was conducted in the China National Knowledge Infrastructure(CNKI),Wanfang,Chongqing VIP database,Chinese Biomedical Database(CBM),Web of Science,and PubMed databases.RCTs on perioperative EA and β-EP published from the inception of the websites up to July 25,2023,were retrieved.Effect size aggregation,literature quality assessment,and bias analysis were performed using RevMan 5.3 software,and sensitivity analysis was conducted via R 4.3.1.Results A total of 10 RCTs involving 706 patients were included.EA in conjunction with conventional anesthesia significantly increased plasma β-EP levels at 12 hours postsurgery[standard mean difference(SMD)=2.79,95%CI(1.85,3.72),Z=5.81,P＜0.00001],24hours postsurgery[SMD=1.87,95%CI(0.9,2.83),Z=3.79,P=0.0001],and 48 hours postsurgery[SMD=2.02,95%CI(1.49,2.54),Z=7.50,P＜0.00001].EA reduced plasma PGE2 levels at 24 hours postsurgery and plasma 5-HT levels at 24 hours postsurgery,and the VAS at 12,24 and 48 hours after surgery also decreased.Conclusion These findings suggest that perioperative EA markedly elevates plasma β-EP levels,reduces pain-inducing factors in plasma,and effectively alleviates acute postoperative pain.

OBJECTIVE: To explore the co-morbid influencing factors of postmenopausal osteoporosis(PMOP) and dyslipidemia, and to provide evidence-based basis for clinical co-morbidity management. METHODS: Based on the 2017 to 2018 Beijing community cross-sectional survey data, PMOP patients were included and divided into the dyslipidemia group and the uncomplicated dyslipidemia group according to whether they were comorbid with dyslipidemia. Demographic characteristics, living habits and disease history were collected through questionnaires, and bone mineral density and bone metabolism biomarkers (osteocalcin, blood calcium, serum typeⅠprocollagen N-terminal prepeptide, etc.) were detected on site. Co-morbidity risk factors were analyzed using binary logistic regression. RESULTS: Three hundred and twenty patients with PMOP were included, including the comorbid group (75 patients) and the uncomplicated group (245 patients). The results showed that history of cardiovascular disease [OR=1.801, 95%CI(1.003, 3.236), P=0.049], history of cerebrovascular disease [OR=2.923, 95%CI(1.460, 5.854), P=0.002], frying and cooking methods[OR=5.388, 95%CI(1.632, 17.793), P=0.006], OST results[OR=0.910, 95%CI(0.843, 0.983), P=0.016], and blood Ca results [OR=60.249, 95%CI(1.862, 1 949.926), P=0.021] were the influencing factors of PMOP complicated with dyslipidemia. CONCLUSION Focus should be placed on the influencing factors of PMOP and dyslipidemia co-morbidities, with emphasis on multidimensional assessment, combining lifestyle interventions with bone metabolism marker monitoring to optimize co-morbidity management.
Humans ; Dyslipidemias/epidemiology* ; Female ; Middle Aged ; Osteoporosis, Postmenopausal/metabolism* ; Aged ; Cross-Sectional Studies ; Risk Factors ; Bone Density

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

Objective:To construct and evaluate a radiomics model for predicting perineural invasion in patients with intrahepatic cholangiocarcinoma (ICC).Methods:Clinical data of 144 patients with ICC undergoing surgery in the People’s Hospital of Zhengzhou University ( n=113) and the Affiliated Cancer Hospital of Zhengzhou University ( n=31) from January 2018 to June 2023 were retrospectively analyzed, including 80 males and 64 females, aged (58.8±10.1) years. The patients were randomly divided into a training set ( n=100) and a test set ( n=44) at a ratio of 7: 3. The former set was used to build the model for predicting perineural invasion, and the latter was used to evaluate the model. Enhanced CT images and clinical data of the patients were collected, and features related to perineural invasion were screened. A light gradient boosting machine was used to construct an imaging genomics model. The model was evaluated using the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results:Univariate and multivariate logistic regression analysis showed that none of the clinical features were associated with neural invasion in ICC patients (all P>0.05). Six, 25, 32, and 37 radiomics features were obtained by screening the intratumoral, 2 mm peritumoral, 5 mm peritumoral, and 8 mm peritumoral regions, respectively. The area under the ROC curve for predicting perineural invasion in ICC patients was 0.849 (95% CI: 0.774-0.923) in the training set and 0.745 (95% CI: 0.597-0.894) in the test set for the intratumoral model, 0.966 (95% CI: 0.938-0.995) and 0.750 (95% CI: 0.604-0.896) for the 5mm peritumoral model, 0.936 (95% CI: 0.892-0.980) and 0.792 (95% CI: 0.644-0.939) for the 2mm peritumoral model, and 0.961 (95% CI: 0.929-0.992) and 0.689 (95% CI: 0.526-0.853) for the 8mm peritumoral model. The area under the ROC curve, accuracy, sensitivity, and specificity of the combined intratumoral and 5mm peritumoral model for predicting perineural invasion were 0.927 (95% CI: 0.878-0.976), 88.0%, 84.5%, and 89.8% in the training set, and 0.849 (95% CI: 0.737-0.960), 77.3%, 85.2%, and 72.0% in the test set, respectively. The calibration curve showed a deviation between the calibration curve of the combined intratumoral and 5mm peritumoral model and the ideal line, but it could achieve basic consistency. DCA showed that when the threshold was between 0.18 and 0.70, the combined intratumoral and 5mm peritumoral model could bring clinical net benefit to patients when predicting neural invasion. Conclusion:The intratumoral and 5mm peritumoral imaging genomics model based on enhanced CT features can effectively predict neural invasion and offer clinical benefits in patients with ICC.

Objective To optimize the platelet enrichment method,and to analyze the concentration changes of key molecules in platelet-rich plasma(PRP)before and after activation,as well as the impact of its activated products on the proliferation of rat endothelial progenitor cells.Methods The tube double-centrifu-gation method was employed to optimize platelet enrichment,and the platelet count in the enriched PRP was measured.ELISA was used to detect the concentration changes of vascular endothelial growth factor(VEGF),endostatin(ES),and P-selectin(CD62P)in PRP before and after activation.The PRP was activated by using liquid nitrogen freeze-thaw method,and the effect of its activated products on the proliferation of rat endothelial progenitor cells was evaluated by using the methyl thiazolyl tetrazolium(MTT)assay.Results The optimal enrichment coefficient of platelets achieved by the double-centrifugation method was 4.63.After low-speed,long-duration double centrifugation,the platelet count was highest in the upper layer of the buffy coat.For PRP with a platelet count of 500× 109/L obtained by machine collection,the VEGF con-centrations before and after activation were(3 418.12±488.80)pg/mL and(4 530.04±308.30)pg/mL,re-spectively,the ES concentrations were(6 168.98±253.22)pg/mL and(6 594.65±82.47)pg/mL,respec-tively,the CD62P concentrations were(6 678.23±324.15)pg/mL and(17 630.53±746.24)pg/mL,respec-tively,statistically significant differences were observed in the above indicators before and after activation(P＜0.01).The activated PRP was diluted in a gradient manner by using a specialized culture medium for en-dothelial progenitor cells.MTT assay results indicated that,in the basal medium,the optimal volume fraction for promoting endothelial progenitor cell proliferation was 0.25％after 48 hours of culture;in the complete medium,the optimal volume fractions for promoting endothelial progenitor cell proliferation were 0.062 5％after 24 hours and 0.125％after 48 hours.Conclusion The concentrations of VEGF,ES,and CD62P in the optimized,enriched PRP exhibited significant changes before and after activation.The optimal volume fraction for promoting endothelial progenitor cell proliferation in the basal medium was 0.25％.