Hepatic fibrosis is a reversible pathological process in various chronic liver diseases and is closely associated with the development and progression of severe liver diseases such as liver cirrhosis and hepatocellular carcinoma， and it has emerged as a significant global health challenge. In recent years， studies have shown that histone lactylation， a newly discovered epigenetic modification， actively participates in regulating the progression of hepatic fibrosis. This article systematically reviews the core regulatory effect of histone lactylation modification in the interaction between inflammatory microenvironment and hepatic fibrosis， in order to clarify the cascade regulatory mechanism of “inflammation-hepatic fibrosis” and provide new insights for early diagnosis， targeted intervention， and prevention of malignant transformation in hepatic fibrosis.

Liver fibrosis is a critical pathological process in the progression of chronic liver diseases and is mainly driven by the activation of hepatic stellate cells， and it is characterized by excessive deposition of extracellular matrix. Programmed cell death is widely observed in liver fibrosis and plays diverse roles in different types of cells. It is not only a mechanism for maintaining cellular homeostasis through metabolism， but it can also regulate the development and progression of diseases. Ferroptosis has recently emerged as a research focus due to its close association with lipid metabolism. This article systematically reviews the related concepts of lipid metabolism， ferroptosis， and liver fibrosis， analyzes the bridging role and dual regulatory function of ferroptosis in lipid metabolism and liver fibrosis， and further highlights the clinical application value of targeting ferroptosis in hepatic stellate cells for the treatment of liver fibrosis， in order to provide new perspectives for the mechanistic studies on liver fibrosis and the optimization of related clinical intervention strategies.

Objective:To compare the differences among four routine lipid testing systems in detecting high triglyceride (TG) serum samples and evaluate the accuracy and consistency of the four homogeneous low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) reagents using vertical auto profile (VAP) as the reference method.Methods:A retrospective study was conducted on 249 serum samples with elevated TG levels collected from the Department of Laboratory Medicine at the Second Xiangya Hospital of Central South University between January and October 2024. TG, total cholesterol (TC), LDL-C, and HDL-C were measured using four homogeneous detection systems: Beckman Coulter (USA), Wako Pure Chemical Industries (Japan), Mindray (China), and Roche Diagnostics (Germany). VAP was used to analyze lipoprotein subfractions, including very-low-density lipoprotein cholesterol (VLDL-C), intermediate-density lipoprotein cholesterol (IDL-C), LDL-C, lipoprotein(a) cholesterol [Lp(a)-C], and HDL-C. The mean coefficient of variation ( CV) across the four systems was calculated for each parameter. Pearson correlation and ordinal logistic regression (OLR) were used to assess correlations between the four HDL-C/LDL-C systems and VAP. Bland-Altman plots were generated to evaluate biases, and deviations were calculated. For parameters with significant deviations, multivariate linear regression and standardized coefficients were used to analyze correlations between biases and lipoprotein subfractions. Based on the Chinese Guidelines for Lipid Management (2023), LDL-C and non-HDL-C treatment goals were categorized into five risk levels (ultra-high, high, moderate, high-risk, and low-risk). VAP results defined LDL-C/non-HDL-C intervals, and the four systems′ concordance in risk classification was evaluated. Samples were grouped into A, B, C, D ( n=63, 62, 62, 62) by TG concentration, and ANOVA, chi-square, and Fisher exact tests assessed intergroup differences. Results:The mean CVs across systems for TG, TC, LDL-C, HDL-C, and non-HDL-C were 2.98%, 1.76%, 18.10%, 5.60%, 2.58%, respectively. Pearson correlations between LDL-C results (Beckman, Wako, Mindray, Roche) and VAP were 0.889, 0.854, 0.899, and 0.973; mean relative deviations were 54.8%, 41.0%, 49.3%, and 3.6%; classification accuracies were 6.0% (15/249), 21.3% (53/249), 9.2% (23/249), and 76.7% (191/249). HDL-C deviations were 18.7%, 15.1%, 11.1%, and 8.7%, with correlations ( r) of 0.883, 0.911, 0.959, and 0.950 (all P<0.001). LDL-C means showed no intergroup differences (A-D), but CV increased with TG levels ( P<0.001). HDL-C means and CVs showed no significant intergroup differences. Beckman, Wako, and Mindray LDL-C results exhibited significant positive biases correlated with TG and VLDL-C (multivariate regression; P<0.05); VLDL-C had the strongest influence (standardized coefficients: 0.820, 0.394, 0.813; P<0.001). Non-HDL-C classifications matched VAP in 92.4% (Beckman), 85.9% (Wako), 94.0% (Mindray), and 93.2% (Roche), with no intergroup differences. Conclusion:For high-TG sera, Beckman, Wako, and Mindray LDL-C exhibited significant positive biases correlated with TG and VLDL-C, while Roche LDL-C showed minimal deviation. TG, TC, HDL-C, and non-HDL-C results showed minimal variation across the four systems. All systems demonstrated comparable accuracy for non-HDL-C compared to VAP. The non-HDL-C measured by the four detection systems demonstrates high accuracy and consistency in atherosclerotic cardiovascular disease risk stratification and lipid-lowering goal assessment, and it is unaffected by TG levels.

Blood lipid testing serves as the foundation for clinical lipid management. Ensuring the accuracy of blood lipid test results, particularly the precision and stability of low low-density lipoprotein cholesterol (LDL-C) values, is crucial for evaluating therapeutic effects among individuals undergoing lipid management and developing subsequent effective lipid-modulatoring strategies. Clinical laboratories should not only focus on quality control measures during the pre-analytical, analytical, and post-analytical phases of testing but also pay attention to variations in laboratory indicators and cutoff values for high, moderate, and low-risk population stratification based on clinical guidelines. Additionally, it is essential to understand the impact of high triglyceride levels on LDL-C testing and provide relevant education to both doctors and patients. By revamping the traditional format of blood lipid test reports to align with the concepts and requirements of lipid management guidelines, laboratories can make a substantial valuable contribution to individual lipid management in the modern era of lipid detection and monitoring.

Objective:To compare the differences among four routine lipid testing systems in detecting high triglyceride (TG) serum samples and evaluate the accuracy and consistency of the four homogeneous low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) reagents using vertical auto profile (VAP) as the reference method.Methods:A retrospective study was conducted on 249 serum samples with elevated TG levels collected from the Department of Laboratory Medicine at the Second Xiangya Hospital of Central South University between January and October 2024. TG, total cholesterol (TC), LDL-C, and HDL-C were measured using four homogeneous detection systems: Beckman Coulter (USA), Wako Pure Chemical Industries (Japan), Mindray (China), and Roche Diagnostics (Germany). VAP was used to analyze lipoprotein subfractions, including very-low-density lipoprotein cholesterol (VLDL-C), intermediate-density lipoprotein cholesterol (IDL-C), LDL-C, lipoprotein(a) cholesterol [Lp(a)-C], and HDL-C. The mean coefficient of variation ( CV) across the four systems was calculated for each parameter. Pearson correlation and ordinal logistic regression (OLR) were used to assess correlations between the four HDL-C/LDL-C systems and VAP. Bland-Altman plots were generated to evaluate biases, and deviations were calculated. For parameters with significant deviations, multivariate linear regression and standardized coefficients were used to analyze correlations between biases and lipoprotein subfractions. Based on the Chinese Guidelines for Lipid Management (2023), LDL-C and non-HDL-C treatment goals were categorized into five risk levels (ultra-high, high, moderate, high-risk, and low-risk). VAP results defined LDL-C/non-HDL-C intervals, and the four systems′ concordance in risk classification was evaluated. Samples were grouped into A, B, C, D ( n=63, 62, 62, 62) by TG concentration, and ANOVA, chi-square, and Fisher exact tests assessed intergroup differences. Results:The mean CVs across systems for TG, TC, LDL-C, HDL-C, and non-HDL-C were 2.98%, 1.76%, 18.10%, 5.60%, 2.58%, respectively. Pearson correlations between LDL-C results (Beckman, Wako, Mindray, Roche) and VAP were 0.889, 0.854, 0.899, and 0.973; mean relative deviations were 54.8%, 41.0%, 49.3%, and 3.6%; classification accuracies were 6.0% (15/249), 21.3% (53/249), 9.2% (23/249), and 76.7% (191/249). HDL-C deviations were 18.7%, 15.1%, 11.1%, and 8.7%, with correlations ( r) of 0.883, 0.911, 0.959, and 0.950 (all P<0.001). LDL-C means showed no intergroup differences (A-D), but CV increased with TG levels ( P<0.001). HDL-C means and CVs showed no significant intergroup differences. Beckman, Wako, and Mindray LDL-C results exhibited significant positive biases correlated with TG and VLDL-C (multivariate regression; P<0.05); VLDL-C had the strongest influence (standardized coefficients: 0.820, 0.394, 0.813; P<0.001). Non-HDL-C classifications matched VAP in 92.4% (Beckman), 85.9% (Wako), 94.0% (Mindray), and 93.2% (Roche), with no intergroup differences. Conclusion:For high-TG sera, Beckman, Wako, and Mindray LDL-C exhibited significant positive biases correlated with TG and VLDL-C, while Roche LDL-C showed minimal deviation. TG, TC, HDL-C, and non-HDL-C results showed minimal variation across the four systems. All systems demonstrated comparable accuracy for non-HDL-C compared to VAP. The non-HDL-C measured by the four detection systems demonstrates high accuracy and consistency in atherosclerotic cardiovascular disease risk stratification and lipid-lowering goal assessment, and it is unaffected by TG levels.

Blood lipid testing serves as the foundation for clinical lipid management. Ensuring the accuracy of blood lipid test results, particularly the precision and stability of low low-density lipoprotein cholesterol (LDL-C) values, is crucial for evaluating therapeutic effects among individuals undergoing lipid management and developing subsequent effective lipid-modulatoring strategies. Clinical laboratories should not only focus on quality control measures during the pre-analytical, analytical, and post-analytical phases of testing but also pay attention to variations in laboratory indicators and cutoff values for high, moderate, and low-risk population stratification based on clinical guidelines. Additionally, it is essential to understand the impact of high triglyceride levels on LDL-C testing and provide relevant education to both doctors and patients. By revamping the traditional format of blood lipid test reports to align with the concepts and requirements of lipid management guidelines, laboratories can make a substantial valuable contribution to individual lipid management in the modern era of lipid detection and monitoring.

Objective:Bone morphogenetic protein-4(BMP4)has been proved to be an important regulatory factor for the pathological process of atherosclerosis(AS).However,there are few related clinical studies.This study aims to investigate the levels of plasma BMP4 in patients suffering from the arterial occlusive diseases(ACD)characterized by AS,and further to test the relationship between BMP4 and inflammation and vascular injury. Methods:A total of 38 ACD patients(the ACD group)and 38 healthy people for the physical examination(the control group)were enrolled.The plasma in each subject from both groups was obtained to test the levels of BMP4,tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β),IL-10,and vascular endothelial cadherin(VE-cadherin),and the relationship between BMP4 and the detected indicators above were further analyzed. Results:Compared with the control group,the patients in the ACD group displayed significant elevations in the neutrophil to lymphocyte ratio[NLR,1.63(1.26,1.91)vs 3.43(2.16,6.61)]and platelet to lymphocyte ratio[PLR,6.37(5.26,7.74)vs 15.79(7.97,20.53)],while decrease in the lymphocyte to monocyte ratio[LMR,5.67(4.41,7.14)vs 3.43(2.07,3.74)](all P<0.05).Besides,the ACD patients displayed significant elevations in plasma BMP4[581.26(389.85,735.64)pg/mL vs 653.97(510.95,890.43)pg/mL],TNF-α[254.16(182.96,340.70)pg/mL vs 293.29(238.90,383.44)pg/mL],and VE-cadherin[1.54(1.08,2.13)ng/mL vs 1.85(1.30,2.54)ng/mL],and decrease in IL-10[175.89(118.39,219.25)pg/mL vs 135.92(95.80,178.04)pg/mL](all P<0.05).While the levels of IL-1β remained statistically comparable between the 2 groups(P=0.09).Furthermore,the plasma BMP4 levels were further revealed to be positively correlated with the levels of IL-1β(r=0.35),TNF-α(r=0.31)and VE-cadherin(r=0.47),while they were negatively correlated with the levels of IL-10(r=-0.37;all P<0.01). Conclusion:After ACD occurrence,the patients'plasma concentrations of BMP4 would be upregulated,which may serve as a candidate to indicate the levels of inflammation and vascular injury.

Objective:The results of the three lipid detection systems were compared to analyze their influence on risk stratification and clinical treatment in lipid management, especially the target goal cut-off point determination, and to find ways to reduce the impact on target goal determination of various lipid measurement system.Methods:A total of 196 serum samples with triglyceride TG <4.5 mmol/L were collected from people undergoing physical examinations and in-patients in the Second Xiangya Hospital of Central South University from August to October 2022. Triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were directly detected with Hitachi-Woke (HW), Roche and Mindray detection systems, respectively. The non high-density lipoprotein cholesterol (non HDL-C) was calculated by formula (TC-HDL-C) and LDL-C (F-LDL-C) was calculated by Friedewald formula, and results from various methodology were compared. The coefficient of variation ( CV) of these six indicators derived from the three detection systems were calculated to evaluate the consistency of the obtained results from different venders. In addition, the Pearson correlation coefficient was analyzed to evaluate the correlation of each indicator among different systems. According to the Chinese Guidelines for Blood Lipid Management, samples were divided into groups with LDL-C levels of <1.4, 1.4-<1.8, 1.8-<2.6, 2.6-<3.4 and ≥3.4 mmol/L according to the recommended LDL-C levels for different risk stratification levels. The sample size and percentage of LDL-C test results from different systems in the same group were counted to evaluate the impact of LDL-C differences between systems on clinical decision-making of blood lipid management. The correction factor was calculated through two methods: (1) The average deviation of LDL-C between systems was estimated by EP9-A3 method; (2) Multiple linear stepwise regression was used to establish the regression model of LDL-C difference and related indexes between systems. The two correction factors were used to correct the deviation of LDL-C value obtained from various systems, and Chi-square test was used to compare the difference of LDL-C grouping consistency rate before and after correction. Result:The average CV values of TG, TC, LDL-C, F-LDL-C, HDL-C, and non HDL-C among the three detection systems were 4.84%, 1.92%, 11.96%, 3.81%, 5.82% and 2.61%, respectively. Correlation analysis showed that when comparing the three systems in pairs, except for LDL-C derived from HW and Roche′s, and Mindray and Roche′s LDL-C ( R 2=0.938 and 0.947), the R 2 of other indicators were all greater than 0.97. The consistency rates of the three systems on LDL-C and F-LDL-C were 51.0% (100/196) and 90.8% (178/196), respectively, according to the risk stratification standard values and the difference was statistically significant ( P<0.05). When comparing in pairs, the consistency rates of Roche and HW, Mindray and HW, Mindray and Roche system LDL-C grouping were 60.7% (119/196), 82.7% (162/196), and 54.1% (106/196), respectively. After adjusting for mean deviation, the group consistency rate of Roche and HW increased to 73.7%-79.4% ( P<0.05), and the group consistency rate of Roche and Mindray increased to 72.3%-79.0% ( P<0.05). After adjusting for difference regression model, the group consistency rate of Roche and HW increased to 82.5%-84.0%, and the group consistency rate of Roche and Mindray increased to 81.0%-89.2%. However, there was no significant change in the group consistency rate of Mindray and HW after adjusting for both correction methods ( P>0.05) .Conclusions:There are significant differences in LDL-C derived from different detection systems, and the consistency rate of grouping according to the lipid-lowering standard value is relatively low, which may affect clinical decision-making in lipid management. Adjusted by the correction factor, the consistency rate of grouping between Roche and HW, Roche and Mindray systems with large differences in LDL-C can be improved. Using the difference multiple linear regression model as a correction factor is superior to the average deviation.

Objective: In this study, black tea and Citrus maxima (BT-CM), yellow tea and C. maxima (YT-CM), green tea and C. maxima (GT-CM) as subjects, the active ingredient content and antioxidant activity of three tea and C. maxima (T-CM) were analyzed. The effects of three T-CMs on apoptosis of liver cells in vitro and its mechanism were further explored. Methods: National standard method and HPLC were used for active ingredient analysis. MTT, cell flow cytometry and Western blot were used to analyze the effects of three T-CMs on cell proliferation, apoptosis, and its underlying molecular mechanism. Results: The content of tea polyphenols, free amino acids, ratio of polyphenols and amino acids, ester catechins, non-ester catechins and caffeine in YT-CM and GT-CM was significantly higher than that of BT-CM. The in vitro antioxidant capacity of YT-CM and GT-CM was also significantly stronger than that of BT-CM. Three T-CMs had the effects of inhibiting proliferation, arresting cell cycle and inducing apoptosis in HepG2 and Bel7402 cells, especially YT-CM and GT-CM. Western blot analysis showed three T-CMs activated PI3K/AKT/mTOR signaling pathway and regulated the expression levels of apoptosis-related proteins Bax, Bcl-2 and Caspase-3/9. YT-CM and GT-CM had better ability to change the signal pathway than BT-CM. Conclusion: In short, T-CMs, which combined different degrees of fermentation tea with C. maxima, were rich in nutrients and biologically active substances. T-CMs, especially YT-CM and GT-CM, are healthy drinks that help to prevent and treat liver cancer.

Objectives To analyze the changes of serum complement C1q level in patients with metabolic syndrome (MS) and investigate whether it is associated with lipid metabolism and glycometabolism. Methods In a cross-sectional study, the subjects were selected as the patients and healthy people who went to the second xiangya hospital of central south university from July 2017 to June 2018. A total of 152 MS patients were enrolled and another 90 healthy subjects were enrolled as control group. Anthropometry parameters such as body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP) were measured. Serum concentrations of C1q and other biochemical indexes including blood glucose (GLU), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) were measured in all groups. The correlations between C1q and these parameters were analyzed by spearman's rho test and the clinical value of C1q in predicting MS was further evaluated by stepwise multiple linear regression analysis. Results MS group had higher serum C1q levels (244.34±62.66) mg/L compared with the control group (202.37±35.92) mg/L (t=-6.250, P=0.000). C1q levels (244.34±62.66) mg/L were positively associated with TG levels [2.34(1.89, 3.62)] mmol/L (r=0.245, P=0.001), TC levels (4.91±1.26) mmol/L (r=0.398, P=0.000), LDL-C levels (3.23±1.03) mmol/L (r=0.325, P=0.000) in MS group, While C1q levels (258.92±69.59)mg/L were positively associated with SBP (144.76 ± 22.94) mmHg (r=0.388, P=0.018), TG levels [2.65(1.87, 3.82)] mmol / L (r=0.482, P=0.003), TC levels (5.18±1.31) mmol/L (r=0.529,P=0.001) in MS patients with obesity. The stepwise multiple regression analysis showed that TG levels were independently correlated with serum C1q levels both in MS patients (β=0.302, P=0.000) and in MS patients with obesity (β=0.653, P=0.000) after adjusting for age, gender and other biochemical markers. Conclusions MS patients had higher C1q levels than healthy subjects and serum C1q levels were closely positive related to harmful lipid profiles. Serum TG level was an independent influencing factor of serum C1q in MS patients.