Metformin has been demonstrated to attenuate hyperglycaemia by modulating the gut microbiota. However, the mechanisms through which the microbiome mediates metformin monotherapy failure (MMF) are unclear. Herein, in a prospective clinical cohort study of newly diagnosed type 2 diabetes mellitus (T2DM) patients treated with metformin monotherapy, metagenomic sequencing of faecal samples revealed that Phocaeicola vulgatus abundance was approximately 12 times higher in nonresponders than in responders. P. vulgatus rapidly hydrolysed taurine-conjugated bile acids, leading to ceramide accumulation and reversing the improvements in glucose intolerance conferred by metformin in high-fat diet-fed mice. Interestingly, C22:0 ceramide bound to mitochondrial fission factor to induce mitochondrial fragmentation and impair hepatic oxidative phosphorylation in P. vulgatus-colonized hyperglycaemic mice, which could be exacerbated by metformin. This work suggests that metformin may be unsuitable for P. vulgatus-rich T2DM patients and that clinicians should be aware of metformin toxicity to mitochondria. Suppressing P. vulgatus growth with cefaclor or improving mitochondrial function using adenosylcobalamin may represent simple, safe, effective therapeutic strategies for addressing MMF.

Objective:To develop a nomogram to predict vessels that encapsulate tumor cluster and/or microvascular invasion-positive hepatocellular carcinoma (VM-HCC) based on multiregional radiomics score derived from multisequence MRI.Methods:Clinical data of 209 patients with HCC undergoing radical liver resection at Affiliated Nantong Hospital 3 of Nantong University from January 2016 to December 2021 were retrospectively analyzed, including 149 males and 60 females, aged (58.5±9.2) years. Patients were divided into a training set ( n=146) and a testing set ( n=63). The patients in training set were further classified into two groups based on pathological results: the VM-HCC group ( n=76) and the non-VM-HCC group ( n=70). Radiomics features were extracted from the arterial phase and hepatobiliary phase images within the tumor, peritumor, and combined regions of interest. The arterial phase and hepatobiliary phase features from the same regions were integrated to obtain dual-sequence features. After feature selection, linear support vector machines (SVM) and linear regression machine learning classifiers were employed to construct radiomics models for different sequences and regions. The optimal radiomics model was selected based on the area under the receiver operating characteristic (ROC) curve from the testing set. Logistic regression analysis was performed to identify independent predictors of VM-HCC, and a visual nomogram was constructed using the results of the multivariate logistic regression analysis and the radiomics score of the optimal radiomics model. ROC curves were plotted, and area under curve (AUC) were calculated to evaluate the models’ discriminatory ability. Calibration curves and decision curve analysis (DCA) were utilized to assess the model’s calibration and clinical utility. Results:Among the radiomics models, the dual-sequence-combined region model based on the SVM classifier exhibited the best AUC in the testing set (AUC=0.764, 95% CI: 0.646-0.882). Multivariate logistic regression analysis indicated that HCC patients with protein induced by vitamin K absence or antagonist-II (PIVKA-II) levels >40 mAU/ml ( OR=4.266, 95% CI: 1.921-9.473, P<0.001) had a higher risk of VM-HCC. The nomogram combining PIVKA-II>40 mAU/ml and radiomics score achieved AUC of 0.806 (95% CI: 0.733-0.867) in the training set and 0.817 (95% CI: 0.699-0.903) in the testing set for predicting VM-HCC. The calibration curves of the nomogram showed good fit in both the training and testing sets. DCA indicated that the model possesses good clinical utility. Conclusion:The nomogram based on multiregional radiomics score derived from multisequence MRI demonstrates a good predictive performance for VM-HCC, which could facilitate the risk stratification of recurrence in HCC patients.

Objective To investigate the value of qualitative and quantitative characteristics of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced MRI in preoperative prediction of vessels encapsulating tumor clusters(VETC)pattern in hepatocellular carcinoma(HCC).Methods A total of 234 patients diagnosed with HCC by pathology were analyzed retrospectively.A total of 101 VETC-positive HCC patients and 133 VETC-negative HCC patients were included.All patients were divided into training group and validation group according to 7︰3.The training group data were used to construct a prediction model for VETC-positive HCC.Receiver operating characteristic(ROC)curve was drawn and the area under the curve(AUC)was calculated to verify the diagnostic efficiency of the model.Calibration curve was drawn to verify the calibration of the model.Results Multivariate logistic regression analysis predicted the independent risk factors for VETC-positive HCC:portal phase peripheral washout[odds ratio(OR)6.493],necrosis or severe ischemia(OR 4.756),targetoid transitional phase or hepatobiliary phase(OR 0.307),and lesion to liver signal intensity ratio(LLR)on arterial phase(OR 0.074).The AUC of the training group in predicting VETC-positive HCC was 0.790[95%confidence interval(CI)0.720-0.859].The AUC of the validation group in predicting VETC-positive HCC was 0.779(95%CI 0.668-0.889).The calibration curve diagram showed that the calibration curve(the slope was 0.91)almost coincides with the ideal curve,indicating that the prediction model had better calibration.Conclusion The qualitative and quantitative characteristics of Gd-EOB-DTPA enhanced MRI can be used to predict VETC-positive HCC preoperatively,the independent risk factors of VETC include portal phase peripheral washout,necrosis or severe ischemia,targetoid transitional phase or hepatobiliary phase,and LLR on arterial phase.

Objective To investigate the value of the liver imaging reporting and data system v2018(LI-RADS v2018)and other imaging features in predicting preoperative risk and postoperative prognosis of isolated macrotrabecular-massive hepatocellular carcinoma(MTM-HCC).Methods Patients with isolated hepatocellular carcinoma(HCC)confirmed by pathology after preoperative MRI examination were selected,and all patients were randomly assigned to a training group(n=146)and a validation group(n=62)in a 7∶3 ratio.Least absolute shrinkage and selection operator(LASSO)regression and multivariate logistic regression were used to screen independent prognostic factors of MTM-HCC and construct a nomogram.Patients were stratified into high-risk and low-risk subgroups based on the nomogram scores.Kaplan-Meier survival curves and Log-rank tests were used to compare the recurrence-free survival(RFS)among different subgroups of patients.Results Multivariate logistic regression analysis revealed that intratumoral vessels[odds ratio(OR)=3.480,95％confidence interval(CI)1.110-10.912,P=0.032],arterial phase hypovascular component ≥20％(OR=4.615,95％CI 1.728-12.321,P=0.002),and corona enhancement(OR=4.814,95％CI 1.816-12.766,P=0.002)were independent predictors of MTM-HCC.The nomogram constructed based on these indicators demonstrated area under the curve(AUC)of the receiver operating characteristic(ROC)curve was 0.834 and 0.764 for predicting MTM-HCC in the training and validation groups,respectively.The RFS predicted by the nomogram was significantly different between the high-risk and low-risk subgroups and both the pathologically confirmed MTM-HCC positive and negative groups(P＜0.05).Conclusion Intratumoral vessels,arterial phase hypovascular component ≥20％,and corona enhancement are independent predictors of MTM-HCC.The constructed nomogram based on these predictors demonstrates good diagnostic efficacy for MTM-HCC and has significant prognostic value for patients'RFS.

Objective To observe the value of the scoring model of MRI features for predicting proliferative hepatocellular carcinoma(HCC).Methods Data of 241 patients with pathologically confirmed HCC,including 90 cases of proliferative HCC and 151 cases of non-proliferative HCC were analyzed retrospectively.Univariate and multivariate logistic regression were used to compare the clinical and MRI findings evaluated according to liver imaging reporting and data system version 2018 between groups.The independent predictive factors of proliferative HCC were screened,and scores were assigned according to the weight,then a scoring model was constructed.Receiver operating characteristic(ROC)curve was drawn,and the area under the curves(AUC)were calculated to assess the predictive efficacy of this model.The patients were divided into high and low proliferation risk subgroups based on the optimal score thresholds.The recurrence free survival(RFS)rates and early RFS rates were compared between groups and subgroups.Results MRI showed tumor corona enhancement,arterial phase annular hyper-enhancement,intratumoral vessels,much focus parenchymal low enhancement and irregular tumor margins were all independent predictive factors for proliferative HCC(OR=3.287,2.362,4.542,2.997,2.379,all P＜0.05),which were then were scored with 7,5,9,7 and 5,respectively,with a total score of 0-33.AUC of the obtained scoring model for predicting proliferative HCC was 0.818.Taken 9 points as the optimal score thresholds,97 cases were assigned into high proliferation subgroup and 144 into low proliferation risk subgroups).Significant differences of RFS rates and early RFS rates were found between groups and subgroups(all P＜0.05).Conclusion MRI features scoring model could effectively predict proliferative HCC.

Objective:To develop a nomogram to predict vessels that encapsulate tumor cluster and/or microvascular invasion-positive hepatocellular carcinoma (VM-HCC) based on multiregional radiomics score derived from multisequence MRI.Methods:Clinical data of 209 patients with HCC undergoing radical liver resection at Affiliated Nantong Hospital 3 of Nantong University from January 2016 to December 2021 were retrospectively analyzed, including 149 males and 60 females, aged (58.5±9.2) years. Patients were divided into a training set ( n=146) and a testing set ( n=63). The patients in training set were further classified into two groups based on pathological results: the VM-HCC group ( n=76) and the non-VM-HCC group ( n=70). Radiomics features were extracted from the arterial phase and hepatobiliary phase images within the tumor, peritumor, and combined regions of interest. The arterial phase and hepatobiliary phase features from the same regions were integrated to obtain dual-sequence features. After feature selection, linear support vector machines (SVM) and linear regression machine learning classifiers were employed to construct radiomics models for different sequences and regions. The optimal radiomics model was selected based on the area under the receiver operating characteristic (ROC) curve from the testing set. Logistic regression analysis was performed to identify independent predictors of VM-HCC, and a visual nomogram was constructed using the results of the multivariate logistic regression analysis and the radiomics score of the optimal radiomics model. ROC curves were plotted, and area under curve (AUC) were calculated to evaluate the models’ discriminatory ability. Calibration curves and decision curve analysis (DCA) were utilized to assess the model’s calibration and clinical utility. Results:Among the radiomics models, the dual-sequence-combined region model based on the SVM classifier exhibited the best AUC in the testing set (AUC=0.764, 95% CI: 0.646-0.882). Multivariate logistic regression analysis indicated that HCC patients with protein induced by vitamin K absence or antagonist-II (PIVKA-II) levels >40 mAU/ml ( OR=4.266, 95% CI: 1.921-9.473, P<0.001) had a higher risk of VM-HCC. The nomogram combining PIVKA-II>40 mAU/ml and radiomics score achieved AUC of 0.806 (95% CI: 0.733-0.867) in the training set and 0.817 (95% CI: 0.699-0.903) in the testing set for predicting VM-HCC. The calibration curves of the nomogram showed good fit in both the training and testing sets. DCA indicated that the model possesses good clinical utility. Conclusion:The nomogram based on multiregional radiomics score derived from multisequence MRI demonstrates a good predictive performance for VM-HCC, which could facilitate the risk stratification of recurrence in HCC patients.

Objective::Data comparing the outcomes of MiStent (Micell Technologies, Durham, North Carolina, USA) microcrystalline biodegradable polymer (BP) drug-eluting stent (DES) and those of another post-marketing BP-DES, TIVOLI (EssenTech, Beijing, China) are rare. This study sought to compare the angiographic efficacy and clinical outcomes of the microcrystalline BP sirolimus-eluting stent (SES) system MiStent and those of TIVOLI BP-SES.Methods::The DESSOLVE-C trial was a prospective, single-blinded, multicenter, randomized trial (NCT02448524), which randomly assigned patients with de novo coronary lesions to receive MiStent or TIVOLI BP-SES by a 1:1 ratio. The primary endpoint was a non-inferiority comparison of in-stent late lumen loss (LLL) by quantitative coronary angiography at 9 months. The secondary endpoint was device-related clinical cardiovascular composite events (target lesion failure (TLF), composite of cardiac death, target vessel myocardial infarction (MI), and clinically driven target lesion revascularization) and 1-year outcomes. Results::A total of 428 patients (216 patients in the MiStent group and 212 patients in the TIVOLI group) were enrolled and included in an intention-to-treat analysis. MiStent was not only non-inferior but superior to TIVOLI for in-stent LLL at 9 months ((0.23 ± 0.37) mm vs. (0.34 ± 0.48) mm, P for non-inferiority <0.001, P for superiority = 0.02). Although without significant difference, the rate of TLF in MiStent was quantitatively lower than that in TIVOLI (3.70% vs. 6.60%; P = 0.17). Conclusion::Compared with TIVOLI BP-SES, the MiStent system was superior in in-stent LLL at 9 months and had a comparable clinical benefit at 1 year in de novo coronary lesions.

Objective::Data comparing the outcomes of MiStent (Micell Technologies, Durham, North Carolina, USA) microcrystalline biodegradable polymer (BP) drug-eluting stent (DES) and those of another post-marketing BP-DES, TIVOLI (EssenTech, Beijing, China) are rare. This study sought to compare the angiographic efficacy and clinical outcomes of the microcrystalline BP sirolimus-eluting stent (SES) system MiStent and those of TIVOLI BP-SES.Methods::The DESSOLVE-C trial was a prospective, single-blinded, multicenter, randomized trial (NCT02448524), which randomly assigned patients with de novo coronary lesions to receive MiStent or TIVOLI BP-SES by a 1:1 ratio. The primary endpoint was a non-inferiority comparison of in-stent late lumen loss (LLL) by quantitative coronary angiography at 9 months. The secondary endpoint was device-related clinical cardiovascular composite events (target lesion failure (TLF), composite of cardiac death, target vessel myocardial infarction (MI), and clinically driven target lesion revascularization) and 1-year outcomes. Results::A total of 428 patients (216 patients in the MiStent group and 212 patients in the TIVOLI group) were enrolled and included in an intention-to-treat analysis. MiStent was not only non-inferior but superior to TIVOLI for in-stent LLL at 9 months ((0.23 ± 0.37) mm vs. (0.34 ± 0.48) mm, P for non-inferiority <0.001, P for superiority = 0.02). Although without significant difference, the rate of TLF in MiStent was quantitatively lower than that in TIVOLI (3.70% vs. 6.60%; P = 0.17). Conclusion::Compared with TIVOLI BP-SES, the MiStent system was superior in in-stent LLL at 9 months and had a comparable clinical benefit at 1 year in de novo coronary lesions.

Ferroptosis is a non-apoptotic regulated cell death caused by iron accumulation and subsequent lipid peroxidation. Currently, the therapeutic role of ferroptosis on cancer is gaining increasing interest. Baicalin an active component in

Combined with work experience, this paper described the project process of clinical research pro-jects and ethical review points, and pointed out that clinical research projects should be submitted to peer reviewers prior to ethical review. The ethics committee would review the projects in accordance with legality, scientificity, feasibility, ethics, and other points in detail. Accurately grasp of the balance between innovations and ethics ensure the standardized development of clinical research.