[Experimental study on improvement of cognitive impairment in Alzheimer's disease by different degrees of steaming and sunning of Polygoni Multiflori Radix based on fecal metabolomics].

The fecal metabolomics method was employed to investigate the cognitive improvement mechanism of Polygoni Multiflori Radix in Alzheimer's disease(AD) and examine the effects of different degrees of steaming and sunning on cognitive function in AD model mice. Additionally, the processing principle of Polygoni Multiflori Radix was discussed. Forty-eight 5-month-old APP/PS1 mice were randomly assigned to the following groups: model group, positive group, raw product group, three-steaming and three-sunning product group, six-steaming and six-sunning product group, and nine-steaming and nine-sunning product group. Seven negative control mice from the same litter were included as the blank group. After 150 days of intragastric administration, the learning and memory abilities of mice in each group were assessed by using the Barnes maze and dark avoidance tests. Fecal samples were collected for extensive targeted metabolomics testing. Principal component analysis(PCA), orthogonal partial least squares discriminant analysis(OPLS-DA), and other multivariate statistical methods were utilized to analyze metabolites in mouse feces. Comparison of behavioral results between the model group and different product groups demonstrated that the six-steaming and six-sunning product group exhibited significantly reduced latency in the Barnes maze positioning and navigation test(P<0.05), as well as a notable decrease in the number of errors in the space exploration experiment(P<0.05). Moreover, the latency of mice entering the dark box for the first time in the dark avoidance experiment was significantly prolonged(P<0.05), indicating the best overall improvement in the learning and memory ability of AD model mice. Metabolomics results revealed that compared with the model group, the differential metabolites in other groups in descending order were as follows: six-steaming and six-sunning product group > nine-steaming and nine-sunning product group > raw product group > three-steaming and three-sunning product group, encompassing 146, 120, 95, and 81 potential biomarkers, respectively. Among them, 16 differential metabolites were related to AD disease. Further comparisons based on the degree of processing indicated that the six-steaming and six-sunning product group exhibited the most significant adjustments in total metabolic pathways, particularly regulating the interconversion of pentose and glucuronic acid, as well as amino acid anabolism and other pathways. In summary, the mechanism of Polygoni Multiflori Radix after processing in enhancing the learning and memory ability of APP/PS1 mice may be associated with improved amino acid metabolism and increased energy metabolism in the body. The six-steaming and six-sunning yielded the best outcomes.

AST to ALT ratio as a prospective risk predictor for liver cirrhosis in patients with chronic HBV infection.

BACKGROUND: Serum aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio (AAR) is one of the most frequent indicators to discriminate fibrosis and cirrhosis. However, the results remained controversial. The aim of this study was to evaluate the predictive effect of AAR on hepatitis B virus (HBV)-related cirrhosis development. METHOD: A retrospective cohort study was conducted based on 1754 chronic HBV-infected patients. Clinical variables at their initial visit and follow-up data were collected. Cox proportional hazards model was constructed to evaluate the predictive value of AAR on cirrhosis risk, and its discrimination accuracy was determined by receiver operating characteristic (ROC). The time-dependent effect was assessed by a Fine and Gray competing risk model. RESULTS: Compared to patients with lower AAR, those with elevated AAR level had higher risk of cirrhosis development by adjusting for host characteristics (dichotomized analyses: hazard ratio = 2.77, P = 8.25 × 10 -4 ; tertile analyses: hazard ratio = 2.95, P = 1.61 × 10 -3 ), with an increasing risk trend ( Ptrend = 4.56 × 10 -4 ). The effect remained prominent when ALT or AST was abnormal, while no significant risk was observed when AST and ALT were simultaneously normal. Time-dependent effect analysis demonstrated a persistently higher risk, with the average hazard ratio equivalent to 1.92. AAR level could improve the discrimination efficacy of host variables with area under the curve increased from 0.684 to 0.711 ( P  =  0.039 ). CONCLUSION: Higher AAR was significantly associated with increased risk of HBV-related cirrhosis, and might be a potential predictor of cirrhosis development.

Screening and Validation Potential Therapeutic Marker of Early to Middle Stage ACLF Patients Treated by ALSSs.

BACKGROUND: Artificial liver support systems (ALSSs) are important approaches for treating acute-on-chronic liver failure (ACLF) patients. Few studies have investigated potential serum therapeutic markers of ACLF patients treated by ALSSs. METHODS: Serum samples were obtained from 57 early to middle stage ACLF patients before and after ALSSs treatment and analyzed by metabonomics. The diagnostic values were evaluated by the area under receiver-operating characteristic curve (AUROC). A retrospective cohort analysis was further employed. RESULTS: Metabonomic study showed that serum ratios of lactate: creatinine in ACLF patients is significantly altered and then restored to normal levels after ALSSs treatment. A retrospective cohort analysis (n = 47) validated that the lactate: creatinine ratio of ACLF patients in the one-month death group remained unchanged after ALSSs treatment, but fell markedly in the survival group with AUROC of 0.682 for diagnosis of survival group from death group, which is a more sensitive measure than measures of prothrombin time activity (PTA) to evaluate the therapeutic effect of ALSSs treatment. CONCLUSIONS: Our results demonstrated the greater the decline in the serum lactate: creatinine ratio with better effective treatments of ALSSs in the ACLF patients with early to middle stage, which presents a potential therapeutic biomarker of ALSSs treatment.

Active learning model for extracting elastic modulus of cell on substrate.

The cell elastic modulus (Ec) is widely used as the mechanics-based marker to analyze the biological effects of substrates on cells. However, the employment of the Hertz model to extract the apparent Ec can cause errors due to the disobedience of the small deformation assumption and the infinite half-space assumption, as well as an inability to deduct the deformation of the substrate. So far, no model can effectively solve the errors caused by the above-mentioned aspects simultaneously. In response to this, herein, we propose an active learning model to extract Ec. The numerical calculation with finite element suggests the good prediction accuracy of the model. The indentation experiments on both hydrogel and cell indicate that the established model can efficiently reduce the error caused by the method of extracting Ec. The application of this model may facilitate our understanding about the role of Ec in correlating the stiffness of substrate and the biological behavior of cell.

Machine learning method for extracting elastic modulus of cells.

The Hertz contact mechanics model is commonly used to extract the elastic modulus of the cell, but the basic assumptions of the model are often not met in cell indentation experiments, which can lead to errors in the obtained elastic modulus of cell. The establishment of theoretical formulas or modification of the Hertz formulas has been proposed to reduce the errors introduced by indentation depth and cell thickness, but errors from cell radius and probe radius are largely neglected. Herein, we build a neural network model in machine learning to extract the elastic modulus of cell, which takes into account of four variables: indentation depth, cell thickness, cell radius, and probe radius. The validity of the model is demonstrated by the indentation experiment. The introduction of machine learning methods provides an alternative solution for extracting the elastic modulus of the cell and has potential for application.

Urine miR-93-5p is a promising biomarker for early detection of HBV-related hepatocellular carcinoma.

INTRODUCTION: The mortality rate of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC)continues to increase because sensitive, early and readily available diagnostic tools are lacking. To address this problem, we aimed to identify diagnosticbio markers to be used for early detection of HCC. MATERIALS AND METHODS: miR-93-5p was selected as a candidate biomarker based on the analyses of relevant Gene Expression Omnibus (GEO) datasets; it was validated using qPCR to quantify its expression levels in tissue, plasma and saliva sample sets. RESULTS: miR-93-5p was significantly upregulated in HBV-related HCC tissue. Notably, miR-93-5p in plasma and urine was also significantly increased in patients with early HBV-related HCC. The expression of miR-93-5p was significantly and positively correlated in pairwise comparisons of samples (tissue vs. plasma, tissue vs. urine, plasma vs. urine). Moreover, after curative hepatectomy,miR-93-5p in plasma and urine decreased significantly over one month after the curative hepatectomy and returned to normal levels. Furthermore, receiver operating characteristic (ROC) analysis indicated that both plasma and urine miR-39-5p could detect be used to early, advanced and overall HBV-related HCC cases with more than 85% sensitivities and 93% of specificities. Finally, urine miR-93-5p could be used to predict progress-free survival for early HCC patients who received curative hepatectomy and overall survival for advanced HCC patients without curative treatments. CONCLUSIONS: Plasma and urine miR-93-5p show great promise as potential novel biomarkers for early detection of HBV-related HCC. Moreover, urine miR-93-5p could be used to predict the prognosis of patients with HBV-related HCC.

Circulating Cell-Free mtDNA Content as a Non-invasive Prognostic Biomarker in HCC Patients Receiving TACE and Traditional Chinese Medicine.

Hepatocellular carcinoma (HCC) accounts for 70-85% of liver cancer, and about 85% of HCC are hepatitis B virus-related (HBV-HCC) in China. Transarterial chemoembolization (TACE) combined with traditional Chinese medicine (TCM) has been reported as an effective treatment. Potential biomarkers to stratify patients who may benefit from this treatment are needed. In this study, we aimed to evaluate whether circulating cell-free mitochondrial DNA (ccf-mtDNA) content was associated with the outcome of HCC patients, especially of those who received the combination treatment of TACE and TCM. Univariate and multivariate Cox analyses were conducted to evaluate the association between ccf-mtDNA content and the overall survival of HBV-HCC patients. Kaplan-Meier analysis was used to compare the survival differences between patients with low and high ccf-mtDNA content. In a hospital-based cohort with 141 HBV-HCC patients, there was no statistically significant association between the ccf-mtDNA content and the overall survival of HBV-HCC patients in the univariate analysis, but a borderline significant association was found in the multivariate analyses. In a subcohort of 50 HBV-HCC patients who received TACE and TCM treatment, high ccfDNA content conferred an increased death risk with a hazard ratio of 4.01 (95% confidence interval: 1.25-12.84, p = 0.019) in the multivariate analysis. Kaplan-Meier survival analysis also showed that patients with high ccf-mtDNA content had unfavorable survival (log rank p = 0.097). Our findings suggest that ccf-mtDNA content is a potential non-invasive prognostic biomarker in HCC patients receiving TACE and TCM treatment.

Metabonomics of d-glucaro-1,4-lactone in preventing diethylnitrosamine-induced liver cancer in rats.

CONTEXT: d-Glucaro-1,4-lactone (1,4-GL) exists in many vegetables and fruits. Metabonomics has not been used to investigate the role of 1,4-GL in preventing liver cancer. OBJECTIVE: The pharmacological effects and metabolite alterations of 1,4-GL on the prevention of diethylnitrosamine (DEN)-induced liver cancer were investigated. MATERIALS AND METHODS: Ten healthy Sprague-Dawley rats served as control and 46 were used to establish rat liver cancer model. 1HNMR-based metabonomics was used to compare the effects of oral 1,4-GL (50 mg/kg) in liver cancer rats (n = 26) after 10 consecutive weeks of intervention. The amino acids in rat serum were quantified by HPLC-UV, and the changes in Fischer's ratio were calculated. RESULTS: The 20-week survival rate of DEN-induced liver cancer rats administered with oral 1,4-GL was increased from 45.0 to 70.0% with reduced carcinogenesis of the liver and significantly lowered serum α-fetoprotein level (14.28 ± 2.89 ng/mL vs. 18.56 ± 4.65 ng/mL, p = 0.012). The serum levels of leucine, valine, 3-hydroxybutyrate, lactate, acetate and glutamine in the DEN + 1,4-GL group returned to normal levels compared with those of the DEN group on week 20. Fischer's ratio in the rat serum of DEN group was 1.62 ± 0.21, which was significantly lower than that in healthy rats (2.3 ± 0.12). However, Fischer's ratio increased to 1.89 ± 0.22 in the DEN + 1,4-GL group. DISCUSSION AND CONCLUSIONS: 1,4-GL exerted positive effects on liver carcinogenesis in rats by pathological examination and metabonomic analysis. Its mechanism may be related to the restoration of amino acid and energy metabolism.