Objective To evaluate the value of coronary CT angiography(CCTA)radiomics machine learning(ML)model combined with pericoronary fat attenuation index(FAI)for predicting coronary plaques progression.Methods Totally 194 patients with CCTA showing coronary plaques and received at least one CCTA review afterwards were retrospectively collected.The annual change value of total plaque burden(△TPB/y)was calculated based on the first and last CCTA to assess plaque progression.All patients were categorized into non-progressive(△TPB/y＜median △TPB/y)and progressive(△ TPB/y≥median △ TPB/y)groups.The patients were divided into training set(n=155)and validation set(n=39)at the ratio of 8∶2.Univariate and multivariate logistic regression analyses were used to screen clinical and primary CCTA related factors for plaque progression,and CCTA model was constructed.Radiomics features were extracted and screened based on primary CCTA to build ML models using random forest(RF),Gaussian process(GP),partial least squares discriminant analysis(PLS-DA),quadratic discriminant analysis(QDA)and support vector machine(SVM)algorithms.The effectiveness of all models was verified in validation set and the optimal ML model was selected.And its combination with CCTA model constructed combined model.The efficacy of each model for predicting coronary plaques progression was evaluated.Results Of 194 cases,97 were in progressive group and 97 were in non-progressive group.The training set included 77 cases of plaques progression and 78 of plaques non-progression,and the validation set included 20 of plaques progression and 19 of plaques non-progression.FAI was the independent predictor of plaque progression(OR=1.08,P＜0.001)and CCTA model was constructed.Ten optimal radiomics features based on training set were selected to build RF,GP,PLS-DA,QDA and SVM models.The area under the curve(AUC)of RF model in training set and validation set were both high,was considered as the optimal ML model.The AUC of CCTA,RF and combined models in training set was 0.684,0.847 and 0.861,respectively,while was 0.629,0.768 and 0.821 in validation set,respectively.Conclusion CCTA radiomics ML model combined with FAI could effectively predict coronary plaques progression.

Objective To evaluate the value of coronary CT angiography(CCTA)radiomics machine learning(ML)model combined with pericoronary fat attenuation index(FAI)for predicting coronary plaques progression.Methods Totally 194 patients with CCTA showing coronary plaques and received at least one CCTA review afterwards were retrospectively collected.The annual change value of total plaque burden(△TPB/y)was calculated based on the first and last CCTA to assess plaque progression.All patients were categorized into non-progressive(△TPB/y＜median △TPB/y)and progressive(△ TPB/y≥median △ TPB/y)groups.The patients were divided into training set(n=155)and validation set(n=39)at the ratio of 8∶2.Univariate and multivariate logistic regression analyses were used to screen clinical and primary CCTA related factors for plaque progression,and CCTA model was constructed.Radiomics features were extracted and screened based on primary CCTA to build ML models using random forest(RF),Gaussian process(GP),partial least squares discriminant analysis(PLS-DA),quadratic discriminant analysis(QDA)and support vector machine(SVM)algorithms.The effectiveness of all models was verified in validation set and the optimal ML model was selected.And its combination with CCTA model constructed combined model.The efficacy of each model for predicting coronary plaques progression was evaluated.Results Of 194 cases,97 were in progressive group and 97 were in non-progressive group.The training set included 77 cases of plaques progression and 78 of plaques non-progression,and the validation set included 20 of plaques progression and 19 of plaques non-progression.FAI was the independent predictor of plaque progression(OR=1.08,P＜0.001)and CCTA model was constructed.Ten optimal radiomics features based on training set were selected to build RF,GP,PLS-DA,QDA and SVM models.The area under the curve(AUC)of RF model in training set and validation set were both high,was considered as the optimal ML model.The AUC of CCTA,RF and combined models in training set was 0.684,0.847 and 0.861,respectively,while was 0.629,0.768 and 0.821 in validation set,respectively.Conclusion CCTA radiomics ML model combined with FAI could effectively predict coronary plaques progression.

Objective:To compare the effectiveness and safety profile of tenofovir amibufenamide (TMF) and tenofovir alafenamide (TAF), especially the effects on lipid metabolism in the treatment of chronic hepatitis B.Methods:A retrospective study was conducted on the virological response rate, biochemical response rate, renal function indicators, and lipid metabolism status of 159 cases with chronic hepatitis B (72 cases with TMF and 87 cases with TAF) after 48 weeks of antiviral treatment. The effects of the two drugs on lipid metabolism were further explored through cell and animal experiments.Results:There were no statistically significant differences in baseline age, gender ratio, treatment-na?ve and treatment-experienced proportions, hepatitis B virus (HBV) DNA and aminotransferase levels, renal function indicators, and serum lipid levels between the two groups. The levels of HBV DNA and transaminase were significantly reduced after 48 weeks of treatment in both groups. However, there were no statistically significant differences in virological response (84.2% vs. 75.8%, χ2=0.733, P=0.392) and biochemical response rate (86.1% vs. 85.1%, χ2=0.035, P=0.851) between the two groups. There was no significant change in the renal function index levels before and after treatment between the two groups of patients. Triglyceride [TG, 1.30 (0.93, 1.81) mmol/L vs. 1.30 (0.82, 1.84) mmol/L, Z=-0.196, P=0.844], total cholesterol [TC, 4.53 (3.91, 5.15) mmol/L vs. 4.55 (3.88, 5.24) mmol/L, Z=-1.131, P=0.258], high-density lipoprotein [HDL-C, 1.04 (0.90, 1.3) mmol/L vs. 1.08 (0.94, 1.30) mmol/L, Z=-0.811, P=0.417], low-density lipoprotein [LDL-C, 2.68 (2.04, 3.29) mmol/L vs. 2.57 (1.99, 3.49) mmol/L, Z=-1.716, P=0.086] and the ratio of total cholesterol to high-density lipoprotein [TC/HDL-C, 4.52 (3.10, 5.23) vs. 4.30 (3.27, 5.01), Z=-0.410, P=0.682] had not statistically significant differences in the TMF group before and after treatment. TG [1.24(0.95, 1.98) mmol/L vs. 1.42(1.09, 2.21) mmol/L, Z=-2.895, P=0.004], TC [4.44(3.74, 5.26) mmol/L vs. 4.68(4.07), 5.46) mmol/L, Z=-2.825, P=0.005], low-density lipoprotein (LDL-C) [2.74 (2.05, 3.58) mmol/L vs. 2.87 (2.34, 3.50) mmol/L, Z=-2.419, P=0.016] , and TC/HDL-C [3.89(3.13, 4.82) vs. 4.39(3.70, 5.40), Z=-4.478, P<0.001] levels were increased after TAF treatment, while HDL-C levels were decreased [1.19 (0.98, 1.35) mmol/L vs. 1.04 (0.90, 1.33) mmol/L, Z=-3.070, P=0.002]. The absolute values comparison changes had no statistically significant differences in TG [-0.04(-0.37, 0.46) mmol/L and 0.18 (-0.14, 0.46) mmol/L, Z=-1.853, P=0.064], TC [0.06(-0.38, 0.63) mmol/L vs. 0.23(-0.21, 0.65) mmol/L, Z=-1.010, P=0.312] and LDL-C level [-0.19(-0.33, 0.18) mmol/L vs. 0.18 (-0.13, 0.58) mmol/L, Z=-0.523, P=0.601] before and after treatment between the two groups of patients. The TMF group had higher HDL-C [0.06 (-0.16, 1.84) mmol/L vs. -0.12 (-0.26,0.04) mmol/L, Z=-2.890, P=0.004], but lower TC/HDL-C [-0.04(-0.67, 0.44) vs. 0.40(-0.14, 1.33), Z=-3.959, P<0.001] than the TAF group. HepG2 cells were interfered with 10 μg/ml TMF and TAF for 72 hours, respectively. Microscopic examination revealed that in the TMF group [12 196 (10 740, 14 345) vs. 4 029 (3 086, 5 425) cells, Z=-4.815, P<0.001] and TAF group [12 484 (11 176, 15 824) vs. 4 029 (3 086, 5 425), Z=-4.815, P<0.001], the number of intracellular lipid droplets was higher than that in the control group after Oil Red O staining, but the difference between the two groups was not statistically significant. Ten-week-old C57/BL6J male mice were given 3.8 mg/kg TMF or TAF by continuous gavage for 12 weeks. The liver tissue was stained with Oil Red O. The number of lipid droplets was higher in the liver tissue of mice in the TAF group than that of the control group [30 647 (28 050, 34 821) and 27 614 (25 214, 29 176), Z=-2.529, P=0.011], while the difference between the TMF group and control group was not statistically significant. The serum TG levels were higher in the TAF group mice [1.17 (1.11, 1.19) μmol/L vs. 1.06 (1.04, 1.09) μmol/L, Z=-2.060, P=0.039], TC [2.58 (2.55, 2.80) μmol/L L vs. 2.33 (2.18, 2.54) μmol/L, Z=-2.084, P=0.037] than those of the control group after drug administration, while HDL-C levels were lower than those of the control group [1.14 (1.13, 1.16) μmol/L vs. 1.29 (1.28, 1.32) μmol/L, Z=-2.313, P=0.021] and TMF group [1.14 (1.13, 1.16) μmol/L vs. 1.30 (1.28, 1.38) μmol/L, Z=-2.795, P=0.005]. However, there was no statistically significant difference in TG, TC, and HDL-C levels between the TMF and the control group. Conclusion:Both TMF and TAF can effectively inhibit HBV replication and promote liver function recovery, with no significant impact on renal function. However, TAF may generate an adverse effect on lipid metabolism in the body, while TMF has no obvious effect.

Objective:To compare the effectiveness and safety profile of tenofovir amibufenamide (TMF) and tenofovir alafenamide (TAF), especially the effects on lipid metabolism in the treatment of chronic hepatitis B.Methods:A retrospective study was conducted on the virological response rate, biochemical response rate, renal function indicators, and lipid metabolism status of 159 cases with chronic hepatitis B (72 cases with TMF and 87 cases with TAF) after 48 weeks of antiviral treatment. The effects of the two drugs on lipid metabolism were further explored through cell and animal experiments.Results:There were no statistically significant differences in baseline age, gender ratio, treatment-na?ve and treatment-experienced proportions, hepatitis B virus (HBV) DNA and aminotransferase levels, renal function indicators, and serum lipid levels between the two groups. The levels of HBV DNA and transaminase were significantly reduced after 48 weeks of treatment in both groups. However, there were no statistically significant differences in virological response (84.2% vs. 75.8%, χ2=0.733, P=0.392) and biochemical response rate (86.1% vs. 85.1%, χ2=0.035, P=0.851) between the two groups. There was no significant change in the renal function index levels before and after treatment between the two groups of patients. Triglyceride [TG, 1.30 (0.93, 1.81) mmol/L vs. 1.30 (0.82, 1.84) mmol/L, Z=-0.196, P=0.844], total cholesterol [TC, 4.53 (3.91, 5.15) mmol/L vs. 4.55 (3.88, 5.24) mmol/L, Z=-1.131, P=0.258], high-density lipoprotein [HDL-C, 1.04 (0.90, 1.3) mmol/L vs. 1.08 (0.94, 1.30) mmol/L, Z=-0.811, P=0.417], low-density lipoprotein [LDL-C, 2.68 (2.04, 3.29) mmol/L vs. 2.57 (1.99, 3.49) mmol/L, Z=-1.716, P=0.086] and the ratio of total cholesterol to high-density lipoprotein [TC/HDL-C, 4.52 (3.10, 5.23) vs. 4.30 (3.27, 5.01), Z=-0.410, P=0.682] had not statistically significant differences in the TMF group before and after treatment. TG [1.24(0.95, 1.98) mmol/L vs. 1.42(1.09, 2.21) mmol/L, Z=-2.895, P=0.004], TC [4.44(3.74, 5.26) mmol/L vs. 4.68(4.07), 5.46) mmol/L, Z=-2.825, P=0.005], low-density lipoprotein (LDL-C) [2.74 (2.05, 3.58) mmol/L vs. 2.87 (2.34, 3.50) mmol/L, Z=-2.419, P=0.016] , and TC/HDL-C [3.89(3.13, 4.82) vs. 4.39(3.70, 5.40), Z=-4.478, P<0.001] levels were increased after TAF treatment, while HDL-C levels were decreased [1.19 (0.98, 1.35) mmol/L vs. 1.04 (0.90, 1.33) mmol/L, Z=-3.070, P=0.002]. The absolute values comparison changes had no statistically significant differences in TG [-0.04(-0.37, 0.46) mmol/L and 0.18 (-0.14, 0.46) mmol/L, Z=-1.853, P=0.064], TC [0.06(-0.38, 0.63) mmol/L vs. 0.23(-0.21, 0.65) mmol/L, Z=-1.010, P=0.312] and LDL-C level [-0.19(-0.33, 0.18) mmol/L vs. 0.18 (-0.13, 0.58) mmol/L, Z=-0.523, P=0.601] before and after treatment between the two groups of patients. The TMF group had higher HDL-C [0.06 (-0.16, 1.84) mmol/L vs. -0.12 (-0.26,0.04) mmol/L, Z=-2.890, P=0.004], but lower TC/HDL-C [-0.04(-0.67, 0.44) vs. 0.40(-0.14, 1.33), Z=-3.959, P<0.001] than the TAF group. HepG2 cells were interfered with 10 μg/ml TMF and TAF for 72 hours, respectively. Microscopic examination revealed that in the TMF group [12 196 (10 740, 14 345) vs. 4 029 (3 086, 5 425) cells, Z=-4.815, P<0.001] and TAF group [12 484 (11 176, 15 824) vs. 4 029 (3 086, 5 425), Z=-4.815, P<0.001], the number of intracellular lipid droplets was higher than that in the control group after Oil Red O staining, but the difference between the two groups was not statistically significant. Ten-week-old C57/BL6J male mice were given 3.8 mg/kg TMF or TAF by continuous gavage for 12 weeks. The liver tissue was stained with Oil Red O. The number of lipid droplets was higher in the liver tissue of mice in the TAF group than that of the control group [30 647 (28 050, 34 821) and 27 614 (25 214, 29 176), Z=-2.529, P=0.011], while the difference between the TMF group and control group was not statistically significant. The serum TG levels were higher in the TAF group mice [1.17 (1.11, 1.19) μmol/L vs. 1.06 (1.04, 1.09) μmol/L, Z=-2.060, P=0.039], TC [2.58 (2.55, 2.80) μmol/L L vs. 2.33 (2.18, 2.54) μmol/L, Z=-2.084, P=0.037] than those of the control group after drug administration, while HDL-C levels were lower than those of the control group [1.14 (1.13, 1.16) μmol/L vs. 1.29 (1.28, 1.32) μmol/L, Z=-2.313, P=0.021] and TMF group [1.14 (1.13, 1.16) μmol/L vs. 1.30 (1.28, 1.38) μmol/L, Z=-2.795, P=0.005]. However, there was no statistically significant difference in TG, TC, and HDL-C levels between the TMF and the control group. Conclusion:Both TMF and TAF can effectively inhibit HBV replication and promote liver function recovery, with no significant impact on renal function. However, TAF may generate an adverse effect on lipid metabolism in the body, while TMF has no obvious effect.