Integrated pharmacokinetic properties and tissue distribution of multiple active constituents in Qing-Yi Recipe: A comparison between granules and decoction.

BACKGROUND: Qing-Yi Recipe, a classic traditional Chinese medicine (TCM), is widely used for treating acute diseases of the abdomen, especially pancreatitis, the efficacy of which has been demonstrated in more than thirty clinical trials. However, the in-vivo pharmacodynamic material basis for this formula remains unclear. METHODS: A sensitive and accurate method for quantifying twenty-two potential bioactive constituents of Qing-Yi Recipe in biological samples was developed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), and this method was fully validated. Then, the integrated pharmacokinetic properties of Qing-Yi Recipe and its major metabolites in rats were investigated using the post-listed granules at both dosages. Subsequently, tissue distributions of those constituents in nine organs (especially the pancreas) were determined, and the overall parameters between the two formulations were compared. RESULTS: Though the chemical profiles of the formulas varied across formulations, the overall exposure level was very similar, and baicalin, wogonoside, geniposide, rhein, costunolide, and paeoniflorin were the top six bioactive compounds in the circulation. All twenty-two natural products reached their first peak within 2 h, and several of them exhibited bimodal or multimodal patterns under the complicated transformation of metabolic enzymes, and the parameters of these products markedly changed compared with those of monomers. Diverse metabolites of emodin and baicalin/baicalein were detected in circulation and tissues, augmenting the in vivo forms of these compounds. Finally, the enrichment of tetrahydropalmatine and corydaline in the pancreas were observed and most compounds remained in the gastrointestinal system, providing a foundation basis for their potential regulatory effects on the gut microbiota as well as the intestinal functions. CONCLUSION: Herein, the pharmacokinetic properties and tissue distribution of multiple potential active constituents in Qing-Yi Recipe were investigated at two dosages, providing a pharmacodynamic material basis of Qing-Yi Recipe for the first time. This investigation is expected to provide a new perspective and reference for future studies on the physiological disposition and potential pharmacodynamic basis of traditional Chinese medicine to treat acute abdomen diseases.

Integrative metagenomic and metabolomic analyses reveal the potential of gut microbiota to exacerbate acute pancreatitis.

Early dysbiosis in the gut microbiota may contribute to the severity of acute pancreatitis (AP), however, a comprehensive understanding of the gut microbiome, potential pathobionts, and host metabolome in individuals with AP remains elusive. Hence, we employed fecal whole-metagenome shotgun sequencing in 82 AP patients and 115 matched healthy controls, complemented by untargeted serum metabolome and lipidome profiling in a subset of participants. Analyses of the gut microbiome in AP patients revealed reduced diversity, disrupted microbial functions, and altered abundance of 77 species, influenced by both etiology and severity. AP-enriched species, mostly potential pathobionts, correlated positively with host liver function and serum lipid indicators. Conversely, many AP-depleted species were short-chain fatty acid producers. Gut microflora changes were accompanied by shifts in the serum metabolome and lipidome. Specifically, certain gut species, like enriched Bilophila wadsworthia and depleted Bifidobacterium spp., appeared to contribute to elevated triglyceride levels in biliary or hyperlipidemic AP patients. Through culturing and whole-genome sequencing of bacterial isolates, we identified virulence factors and clinically relevant antibiotic resistance in patient-derived strains, suggesting a predisposition to opportunistic infections. Finally, our study demonstrated that gavage of specific pathobionts could exacerbate pancreatitis in a caerulein-treated mouse model. In conclusion, our comprehensive analysis sheds light on the gut microbiome and serum metabolome in AP, elucidating the role of pathobionts in disease progression. These insights offer valuable perspectives for etiologic diagnosis, prevention, and intervention in AP and related conditions.

A Nucleotide Metabolism-Related Gene Signature for Risk Stratification and Prognosis Prediction in Hepatocellular Carcinoma Based on an Integrated Transcriptomics and Metabolomics Approach.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. The in-depth study of genes and metabolites related to nucleotide metabolism will provide new ideas for predicting the prognosis of HCC patients. This study integrated the transcriptome data of different cancer types to explore the characteristics and significance of nucleotide metabolism-related genes (NMGRs) in different cancer types. Then, we constructed a new HCC classifier and prognosis model based on HCC samples from TCGA and GEO, and detected the gene expression level in the model through molecular biology experiments. Finally, nucleotide metabolism-related products in serum of HCC patients were examined using untargeted metabolomics. A total of 97 NMRGs were obtained based on bioinformatics techniques. In addition, a clinical model that could accurately predict the prognostic outcome of HCC was constructed, which contained 11 NMRGs. The results of PCR experiments showed that the expression levels of these genes were basically consistent with the predicted trends. Meanwhile, the results of untargeted metabolomics also proved that there was a significant nucleotide metabolism disorder in the development of HCC. Our results provide a promising insight into nucleotide metabolism in HCC, as well as a tailored prognostic and chemotherapy sensitivity prediction tool for patients.

Qingyi granules ameliorate severe acute pancreatitis in rats by modulating the gut microbiota and serum metabolic aberrations.

CONTEXT: Qingyi granules can be used to effectively treat patients with severe acute pancreatitis (SAP). OBJECTIVE: To elucidate the role of gut microbiota-mediated metabolism in the therapeutic effects of Qingyi granules. MATERIALS AND METHODS: Sprague-Dawley rats were grouped into the sham operation, SAP model, Qingyi granule intervention (Q, 1.8 g/kg) and emodin intervention (E, 50 mg/kg) groups and observed for 24 h. H&E staining and ELISA were used for histopathological analysis and serum enzyme and cytokine assays. 16S rDNA sequencing and UHPLC-HRMS were used for gut microbiota analysis and untargeted metabolomics. RESULTS: In SAP rats, Qingyi granules decreased the pancreatic pathological score (Q, 7.4 ± 1.14; SAP, 11.6 ± 1.14, p < 0.01); serum amylase (Q, 121.2 ± 6.7; SAP, 144.3 ± 8.86, p < 0.05), lipase (Q, 566 ± 20.34; SAP, 656.7 ± 29.32, p < 0.01), and diamineoxidase (Q, 492.8 ± 26.08; SAP, 566.1 ± 26.83, p < 0.05) activities; and IL-1ß (Q, 29.48 ± 0.88; SAP, 36.17 ± 1.88, p < 0.01), IL-6 (Q, 112.2 ± 3.57; SAP, 128.9 ± 9.09, p < 0.05) and TNF-α (Q, 215.3 ± 8.67; SAP, 266.4 ± 28.03, p < 0.05) levels. SAP induced Helicobacter and Lactobacillus overgrowth and suppressed Romboutsia and Allobaculum growth and caused aberrations in bacterial metabolites, which were partly reversed by Qingyi granules. DISCUSSION AND CONCLUSIONS: Qingyi granules can modulate the gut microbiota and metabolic abnormalities to ameliorate SAP. Multi-omics approaches allow systematic study of the pharmacological mechanisms of compound prescriptions for critical illnesses.

Association between aberrant amino acid metabolism and nonchromosomal modifications fetal structural anomalies: A cohort study.

Background: More than half of the cases of fetal structural anomalies have no known cause with standard investigations like karyotype testing and chromosomal microarray. The differential metabolic profiles of amniotic fluid (AF) and maternal blood may reveal valuable information about the physiological processes of fetal development, which may provide valuable biomarkers for fetal health diagnostics. Methods: This cohort study of singleton-pregnant women had indications for amniocentesis, including structural anomalies and a positive result from maternal serum screening or non-invasive prenatal testing, but did not have any positive abnormal karyotype or chromosomal microarray analysis results. A total of 1580 participants were enrolled between June 2021 and March 2022. Of the 1580 pregnant women who underwent amniocentesis, 294 were included in the analysis. There were 137 pregnant women in the discovery cohort and 157 in the validation cohort. Results: High-coverage untargeted metabolomic analysis of AF revealed distinct metabolic signatures with 321 of the 602 metabolites measured (53%) (false discovery rate, q < 0.005), among which amino acids predominantly changed in structural anomalies. Targeted metabolomics identified glutamate and glutamine as novel predictive markers for structural anomalies, their vital role was also confirmed in the validation cohort with great predictive ability, and the area under the receiver operating characteristic curves (AUCs) were 0.862 and 0.894 respectively. And AUCs for glutamine/glutamate were 0.913 and 0.903 among the two cohorts. Conclusions: Our results suggested that the aberrant glutamine/glutamate metabolism in AF is associated with nonchromosomal modificantions fetal structural anomalies. Based on our findings, a novel screening method could be established for the nonchromosomal modificantions fetal structural anomalies. And the results also indicate that monitoring fetal metabolic conditions (especially glutamine and glutamine metabolism) may be helpful for antenatal diagnosis and therapy.

Research progress on molecular biomarkers of acute myeloid leukemia.

Acute myeloid leukemia (AML) is the most common type of adult acute leukemia. The pathophysiology of the disease has been studied intensively at the cellular and molecular levels. At present, cytogenetic markers are an important basis for the early diagnosis, prognostic stratification and treatment of AML. However, with the emergence of new technologies, the detection of other molecular markers, such as gene mutations and epigenetic changes, began to play important roles in evaluating the occurrence and development of diseases. Recent evidence shows that identifying new AML biomarkers contributes to a better understanding of the molecular mechanism of the disease and is essential for AML screening, diagnosis, prognosis monitoring, and individualized treatment response. In this review, we summarized the promising AML biomarkers from four aspects, which contributing to a better understanding of the disease. Of course, it must be soberly aware that we have not listed all biomarkers of AML. Anyway, the biomarkers we mentioned are representative. For example, mutations in TP53, FLT3, and ASXL1 suggest poor prognosis, low remission rate, short survival period, and often require allogeneic hematopoietic stem cell transplantation. The CEBPA double mutation, NPM1 and CBF mutation suggest that the prognosis is good, the remission rate is high, the survival period is long, and the effect of chemotherapy or autotherapy is good. As for other mutations mentioned in the article, they usually predict a moderate prognosis. All in all, we hope it could provide a reference for the precise diagnosis and treatment of AML.

Metabolic changes in bile acids with pregnancy progression and their correlation with perinatal complications in intrahepatic cholestasis of pregnant patients.

Intrahepatic cholestasis of pregnancy (ICP) is a rare liver disease occurring during pregnancy that is characterized by disordered bile acid (BA) metabolism. It is related to adverse clinical outcomes in both the mother and fetus. Our aim was to evaluate the BA metabolism profiles in different types of ICP and investigate the association between specific BAs and perinatal complications in ICP patients. We consecutively evaluated 95 patients with ICP, in which 53 patients were diagnosed with early-onset ICP (EICP) and 42 patients were diagnosed with late-onset ICP (LICP). Concentrations of 15 BA components were detected using high-performance liquid chromatography tandem mass spectrometry. Clinical information was abstracted from the medical records. The percentage of conjugated bile acids increased in ICP patients. Specifically, taurocholic acid (TCA) accumulated in LICP patients, and glycocholic acid (GCA) predominated in EICP patients. A higher preterm birth incidence was observed among ICP patients. Albumin, total bile acids, total bilirubin and GCA percentage values at ICP diagnosis predicts 83.5% of preterm birth in EICP, and the percentage of TCA in total bile acids at ICP diagnosis predicts 93.2% of preterm birth in LICP. This analysis showed that the BA metabolism profiles of EICP and LICP were distinct. Increased hepatic load was positively correlated with preterm birth in EICP. An elevated TCA percentage in total bile acids provides a biomarker to predict preterm birth in LICP.

Metabolomics study identified bile acids as potential biomarkers for gastric cancer: A case control study.

Gastric cancer (GC) is a common lethal malignancy worldwide. Gastroscopy is an effective screening technique for decreasing mortality. However, there are still limited useful non-invasive markers for early detection of GC. Bile acids are important molecules for the modulation of energy metabolism. With an in-depth targeted method for accurate quantitation of 80 bile acids (BAs), we aimed to find potential biomarkers for the early screening of GC. A cohort with 280 participants was enrolled, including 113 GC, 22 benign gastric lesions (BGL) and 145 healthy controls. Potential markers were identified using a random forest machine algorithm in the discovery cohort (n=180), then validated in an internal validation cohort (n=78) and a group with 22 BGL. The results represented significant alterations in the circulating BA pool between GC and the controls. BAs also exhibited significant correlations with various clinical traits. Then, we developed a diagnostic panel that comprised six BAs or ratios for GC detection. The panel showed high accuracy for the diagnosis of GC with AUC of 1 (95%CI: 1.00-1.00) and 0.98 (95%CI: 0.93-1.00) in the discovery and validation cohort, respectively. This 6-BAs panel was also able to identify early GC with AUC of 1 (95%CI: 0.999-1.00) and 0.94 (95%CI: 0.83-1.00) in the discovery and validation cohort, respectively. Meanwhile, this panel achieved a good differential diagnosis between GC and BGL and the AUC was 0.873 (95%CI: 0.812-0.934). The alternations of serum bile acids are characteristic metabolic features of GC. Bile acids could be promising biomarkers for the early diagnosis of GC.

Metabolic reprogramming enables the auxiliary diagnosis of breast cancer by automated breast volume scanner.

Breast cancer is the leading cause of female cancer-related deaths worldwide. New technologies with enhanced sensitivity and specificity for early diagnosis and monitoring of postoperative recurrence are in critical demand. Automatic breast full volume scanning system (ABVS) is an emerging technology used as an alternative imaging method for breast cancer screening. Despite its improved detection rate of malignant tumors, ABVS cannot accurately stage breast cancer preoperatively in 30-40% of cases. As a major hallmark of breast cancer, the characteristic metabolic reprogramming may provide potential biomarkers as an auxiliary method for ABVS. Objective: The objective of this study was to identify differential metabolomic signatures between benign and malignant breast tumors and among different subtypes of breast cancer patients based on untargeted metabolomics and improve breast cancer detection rate by combining key metabolites and ABVS. Methods: Untargeted metabolomics approach was used to profile serum samples from 70 patients with different subtypes of breast cancer and benign breast tumor to determine specific metabolomic profiles through univariate and multivariate statistical data analysis. Results: Metabolic profiles correctly distinguished benign and malignant breast tumors patients, and a total of 791 metabolites were identified. There were 54 different metabolites between benign and malignant breast tumors and 17 different metabolites between invasive and non-invasive breast cancer. Notably, the missed diagnosis rate of ABVS could be reduced by differential metabolite analysis. Moreover, the diagnostic performance analyses of combined metabolites (pelargonic acid, N-acetylasparagine, and cysteine-S-sulfate) with ABVS performance gave a ROC area under the curve of 0.967 (95% CI: 0.926, 0.993). Conclusions: Our study identified metabolic features both in benign and malignant breast tumors and in invasive and non-invasive breast cancer. Combined ultrasound ABVS and a panel of differential serum metabolites could further improve the accuracy of preoperative diagnosis of breast cancer and guide surgical therapy.

Tissue metabolomics identified new biomarkers for the diagnosis and prognosis prediction of pancreatic cancer.

Pancreatic cancer (PC) is burdened with a low 5-year survival rate and high mortality due to a severe lack of early diagnosis methods and slow progress in treatment options. To improve clinical diagnosis and enhance the treatment effects, we applied metabolomics using ultra-high-performance liquid chromatography with a high-resolution mass spectrometer (UHPLC-HRMS) to identify and validate metabolite biomarkers from paired tissue samples of PC patients. Results showed that the metabolic reprogramming of PC mainly featured enhanced amino acid metabolism and inhibited sphingolipid metabolism, which satisfied the energy and biomass requirements for tumorigenesis and progression. The altered metabolism results were confirmed by the significantly changed gene expressions in PC tissues from an online database. A metabolites biomarker panel (six metabolites) was identified for the differential diagnosis between PC tumors and normal pancreatic tissues. The panel biomarker distinguished tumors from normal pancreatic tissues in the discovery group with an area under the curve (AUC) of 1.0 (95%CI, 1.000-1.000). The biomarker panel cutoff was 0.776. In the validation group, an AUC of 0.9000 (95%CI = 0.782-1.000) using the same cutoff, successfully validated the biomarker signature. Moreover, this metabolites panel biomarker had a great capability to predict the overall survival (OS) of PC. Taken together, this metabolomics method identifies and validates metabolite biomarkers that can diagnose the onsite progression and prognosis of PC precisely and sensitively in a clinical setting. It may also help clinicians choose proper therapeutic interventions for different PC patients and improve the survival of PC patients.

Integration of transcriptomics, proteomics, and metabolomics data to reveal HER2-associated metabolic heterogeneity in gastric cancer with response to immunotherapy and neoadjuvant chemotherapy.

Background: Currently available prognostic tools and focused therapeutic methods result in unsatisfactory treatment of gastric cancer (GC). A deeper understanding of human epidermal growth factor receptor 2 (HER2)-coexpressed metabolic pathways may offer novel insights into tumour-intrinsic precision medicine. Methods: The integrated multi-omics strategies (including transcriptomics, proteomics and metabolomics) were applied to develop a novel metabolic classifier for gastric cancer. We integrated TCGA-STAD cohort (375 GC samples and 56753 genes) and TCPA-STAD cohort (392 GC samples and 218 proteins), and rated them as transcriptomics and proteomics data, resepectively. 224 matched blood samples of GC patients and healthy individuals were collected to carry out untargeted metabolomics analysis. Results: In this study, pan-cancer analysis highlighted the crucial role of ERBB2 in the immune microenvironment and metabolic remodelling. In addition, the metabolic landscape of GC indicated that alanine, aspartate and glutamate (AAG) metabolism was significantly associated with the prevalence and progression of GC. Weighted metabolite correlation network analysis revealed that glycolysis/gluconeogenesis (GG) and AAG metabolism served as HER2-coexpressed metabolic pathways. Consensus clustering was used to stratify patients with GC into four subtypes with different metabolic characteristics (i.e. quiescent, GG, AAG and mixed subtypes). The GG subtype was characterised by a lower level of ERBB2 expression, a higher proportion of the inflammatory phenotype and the worst prognosis. However, contradictory features were found in the mixed subtype with the best prognosis. The GG and mixed subtypes were found to be highly sensitive to chemotherapy, whereas the quiescent and AAG subtypes were more likely to benefit from immunotherapy. Conclusions: Transcriptomic and proteomic analyses highlighted the close association of HER-2 level with the immune status and metabolic features of patients with GC. Metabolomics analysis highlighted the co-expressed relationship between alanine, aspartate and glutamate and glycolysis/gluconeogenesis metabolisms and HER2 level in GC. The novel integrated multi-omics strategy used in this study may facilitate the development of a more tailored approach to GC therapy.

Gut Microbiota-Derived Diaminopimelic Acid Promotes the NOD1/RIP2 Signaling Pathway and Plays a Key Role in the Progression of Severe Acute Pancreatitis.

Impaired intestinal barrier function and gut microbiota dysbiosis are believed to be related to exacerbation of acute pancreatitis (AP). As a bacterial cell wall peptidoglycan component, diaminopimelic acid (DAP) is a specific ligand of NOD1 that regulates the NOD1/RIP2/NF-kB signaling pathway. Here, we investigated the role of DAP in the crosstalk between the gut microbiota and pancreas during the occurrence of AP. Upregulation of NOD1/RIP2/NF-kB and elevated serum DAP levels were found in severe AP (SAP) model rats. The accumulation of DAP in SAP patients corroborated its ability to serve as an indicator of disease severity. Subsequently, SAP rats were treated with oral administration of the traditional Chinese medicine Qingyi Keli (QYKL) as well as neomycin, which can widely eliminate DAP-containing bacteria. Both QYKL and neomycin intervention ameliorated intestinal and pancreatic damage and systemic inflammation in SAP rats. Through 16S rDNA sequencing, we found that QYKL could rehabilitate the gut microbiota structure and selectively inhibit the overgrowth of enteric bacteria, such as Helicobacter and Lactobacillus, in SAP rats without affecting some protective strains, including Romboutsia and Allobaculum. Interestingly, we demonstrated that the decrease in serum DAP was accompanied by suppression of the NOD1/RIP2/NF-kB signaling pathway in both the intestine and pancreas of the two intervention groups. Taken together, these results suggested that the gut microbiota-DAP-NOD1/RIP2 signaling pathway might play a critical role in the progression of AP and that SAP could be alleviated via intervention in the signaling pathway. Our work provides new potential early warning indicators of SAP and targets for intervention.

Gut Microbiome and the Role of Metabolites in the Study of Graves' Disease.

Graves' disease (GD) is an autoimmune thyroid disease (AITD), which is one of the most common organ-specific autoimmune disorders with an increasing prevalence worldwide. But the etiology of GD is still unclear. A growing number of studies show correlations between gut microbiota and GD. The dysbiosis of gut microbiota may be the reason for the development of GD by modulating the immune system. Metabolites act as mediators or modulators between gut microbiota and thyroid. The purpose of this review is to summarize the correlations between gut microbiota, microbial metabolites and GD. Challenges in the future study are also discussed. The combination of microbiome and metabolome may provide new insight for the study and put forward the diagnosis, treatment, prevention of GD in the future.

HR-MS Based Untargeted Lipidomics Reveals Characteristic Lipid Signatures of Wilson's Disease.

Background and Aims: The diagnosis of Wilson's disease (WD) is challenging by clinical or genetic criteria. A typical early pathological change of WD is the increased liver lipid deposition and lowered serum triglyceride (TG). Therefore, the contents of serum lipids may provide evidence for screening of biomarkers for WD. Methods: 34 WD patients, 31 WD relatives, and 65 normal controls were enrolled in this study. Serum lipidomics data was acquired by an ultra-high-performance liquid chromatography high-resolution mass spectrometry system, and the data were analyzed by multivariate statistical methods. Results: Of all 510 identified lipids, there are 297 differential lipids between the WD and controls, 378 differential lipids between the relatives and controls, and 119 differential lipids between the patients and relatives. In WD, the abundances of most saturated TG were increased, whereas other unsaturated lipids decreased, including phosphatidylcholine (PC), sphingomyelin (SM), lysophosphatidylcholine (LPC), ceramide (Cer), and phosphatidylserine (PS). We also found many serum lipid species may be used as biomarkers for WD. The areas under the receiver operating characteristic curve (AUC) of PS (35:0), PS (38:5), and PS (34:0) were 0.919, 0.843, and 0.907. The AUCs of TG (38:0) and CerG1 (d42:2) were 0.948 and 0.915 and the AUCs of LPC (17:0) and LPC (15:0) were 0.980 and 0.960, respectively. The lipid biomarker panel exhibits good diagnostic performance for WD. The correlation networks were built among the different groups and the potential mechanisms of differential lipids were discussed. Interestingly, similar lipid profile of WD is also found in their relatives, which indicated the changes may also related to the mutation of the ATP7B gene. Conclusions: Lipid deregulation is another important hallmark of WD besides the deposition of copper. Our lipidomic results provide new insights into the diagnostic and therapeutic targets of WD.

An Integrated Metabolomic Study of Osteoporosis: Discovery and Quantification of Hyocholic Acids as Candidate Markers.

Osteoporosis is becoming a highly prevalent disease in a large proportion of the global aged population. Serum metabolite markers may be important for the treatment and early prevention of osteoporosis. Serum samples from 32 osteoporosis and 32 controls were analyzed by untargeted metabolomics and lipidomic approaches performed on an ultra-high performance liquid chromatography and high-resolution mass spectrometry (UHPLC-HRMS) system. To find systemic disturbance of osteoporosis, weighted gene correlation network analysis (WGCNA) and statistical methods were employed for data-mining. Then, an in-depth targeted method was utilized to determine potential markers from the family of key metabolites. As a result, 1,241 metabolites were identified from untargeted methods and WGCNA indicated that lipids metabolism is deregulated and glycerol phospholipids, sphingolipids, fatty acids, and bile acids (BA) are majorly affected. As key metabolites of lipids metabolism, 66 bile acids were scanned and 49 compounds were quantified by a targeted method. Interestingly, hyocholic acids (HCA) were found to play essential roles during the occurrence of osteoporosis and may be potential markers. These metabolites may be new therapeutic or diagnosis targets for the screening or treatment of osteoporosis. Quantified measurement of potential markers also enables the establishment of diagnostic models for the following translational research in the clinic.

N-Ethyl-2-Pyrrolidinone-Substituted Flavan-3-Ols with Anti-inflammatory Activity in Lipopolysaccharide-Stimulated Macrophages Are Storage-Related Marker Compounds for Green Tea.

Fresh green tea (GT) is commonly considered to have better sensory flavor and higher commercial value than long-term-stored GT; however, the chemical variations during storage are unclear. In this study, the chemical profiles of stored GT were surveyed among time-series samples from 0 to 19 months using a nontargeted metabolomics method. Seven N-ethyl-2-pyrrolidinone-substituted flavan-3-ols (EPSFs) increased from 0.022 ± 0.019 to 3.212 ± 0.057 mg/g within 19 months (correlation coefficients with storage duration ranging from 0.936 to 0.965), and they were the most significantly increased compounds among the 127 identified compounds. Two representative EPSFs (R-EGCG-cThea and S-EGCG-cThea) possess potential anti-inflammatory properties by suppressing the expression, phosphorylation, and nuclear translocation of nuclear factor kappa-B (NF-κB) p65 in lipopolysaccharide-stimulated macrophages based on western blotting and immunofluorescence results. In conclusion, EPSFs were found to be marker compounds for stored GT and showed potential anti-inflammatory activity by regulating the NF-κB signaling pathway.

Switching from Fatty Acid Oxidation to Glycolysis Improves the Outcome of Acute-On-Chronic Liver Failure.

Acute-on-chronic liver failure (ACLF) has a high mortality rate. Metabolic reprogramming is an important mechanism for cell survival. Herein, the metabolic patterns of ACLF patients are analyzed. An in vitro model of ACLF is established using Chang liver cells under hyperammonemia and hypoxia. A randomized clinical trial (ChiCTR-OPC-15006839) is performed with patients receiving L-ornithine and L-aspartate (LOLA) daily intravenously (LOLA group) and trimetazidine (TMZ) tid orally (TMZ group) based on conventional treatment (control group). The primary end point is 90-day overall survival, and overall survival is the secondary end point. By analyzing metabolic profiles in liver tissue samples from hepatitis B virus (HBV)-related ACLF patients and the controls, the metabolic characteristics of HBV-related ACLF patients are identified: inhibited glycolysis, tricarboxylic acid cycle and urea cycle, and enhanced fatty acid oxidation (FAO) and glutamine anaplerosis. These effects are mainly attributed to hyperammonemia and hypoxia. Further in vitro study reveals that switching from FAO to glycolysis could improve hepatocyte survival in the hyperammonemic and hypoxic microenvironment. Importantly, this randomized clinical trial confirms that inhibiting FAO using TMZ improves the prognosis of patients with HBV-related ACLF. In conclusion, this study provides a practical strategy for targeting metabolic reprogramming using TMZ to improve the survival of patients with HBV-related ACLF.

Which is the urine sample material of choice for metabolomics-driven biomarker studies?

Urine-based metabolomics-driven strategies for the discovery of biomarkers are increasingly developed and applied in analytical chemistry. But valid, data-based recommendations for a urine sample material of choice are lacking. We investigated first and second morning urine (MU), which are the most commonly used urine specimens. Potential major factors biasing metabolomics biomarker results in these sample materials were studied. First, 35 1st and 2nd MU samples were collected from healthy, young men after an overnight fast. Subsequently, two subgroups were built, one having fast food at lunch and dinner (n = 17), the other vegetarian meals (n = 18). Again 1st and 2nd MU were collected. Non-targeted liquid chromatography-mass spectrometry was applied for analyses. More than half of the >5400 urinary ion features showed a significant difference between 1st and 2nd MU. Just two fast food meals on previous day significantly affected around 30% of all metabolites in 1st and 2nd MU. In contrast, the effects of two vegetarian meals in 2nd MU were only minor. Additionally, we describe 47 metabolites in urine, possible hits in biomarker studies, which are susceptible to the diet the day before sample collection. They should be handled with caution until validation in diet-controlled studies. Based on our results we think the second MU, ideally collected after standardized vegetarian meals and drinking only water on the previous day, is most suitable for valid analysis of biomarkers in urine.

Characteristics of Blood Metabolic Profile in Coronary Heart Disease, Dilated Cardiomyopathy and Valvular Heart Disease Induced Heart Failure.

Purpose: Metabolic impairment is one key contributor to heart failure (HF) pathogenesis and progression. The major causes of HF, coronary heart disease (CHD), dilated cardiomyopathy (DCM), and valvular heart disease (VHD) remains poorly characterized in patients with HF from the view of metabolic profile. We sought to determine metabolic differences in CHD-, VHD-, and DCM-induced HF patients and identify significantly altered metabolites and their correlations. Procedure: In this study, a total of 96 HF cases and 97 controls were enrolled. The contents of 23 amino acids and 26 carnitines in fasting plasma were measured by a targeted liquid chromatography and mass spectrometry (LC-MS) approach. Results: Nine metabolites (Histidine, Arginine, Citrulline, Glutamine, Valine, hydroxyhexadecenyl-carnitine, acylcarnitine C22, hydroxytetradecanoyl-carnitine, and carnitine) were found to be related with the occurrence of HF. Arginine, Glutamine and hydroxytetradecanoyl-carnitine could effectively distinguish CHD and DCM patients, and hydroxytetradecanoyl-carnitine and aspartic acid were able to classify CHD and VHD cohorts. Conclusion: This study indicated that circulating amino acids and long-chain acylcarnitine levels were closely associated with progression of heart failure. Monitoring these metabolic alterations by LC-MS may help the differentiation of CHD, VHD, and DCM in the early stage, and provide new diagnostics targets or therapeutic interventions.

Parallel derivatization strategy coupled with liquid chromatography-mass spectrometry for broad coverage of steroid hormones.

Steroid hormones are a type of crucial substances that mediate numerous vital physiological functions. The comprehensive detection of steroid hormones can help understand the physiopathologic mechanism of steroid hormone-related diseases. It is very difficult to determine steroid hormones in biological samples due to their low endogenous concentrations and poor ionization efficiency. In this study, an efficient and sensitive approach was developed for profiling steroid hormones by combining liquid-liquid extraction and parallel derivatization with liquid chromatography-tandem mass spectrometry. Methoxyamine and dansyl chloride were used to derivatize steroid hormones containing carbonyl and phenolic hydroxyl groups, respectively. Our established method achieved simultaneous analysis of carbonyl and phenolic hydroxyl-containing steroid hormones and could cover estrogens, androgens, corticoids and progestogens. Twenty-nine steroid hormones were detected at pg/mL levels with the sensitivity enhanced by three orders of magnitude after derivatization. The linearity (with linear range of 2-4 orders of magnitude), precision (less than 15%) and recovery (71.1-128.7%) were satisfactory for quantitative analysis of steroid hormones. Finally, the established method was successfully employed to the determination of steroid hormones in serum samples of healthy males and females as well as ovarian cancer patients. The results showed that this approach was suitable and reliable for routine test of steroid hormones containing carbonyl and phenolic hydroxyl groups.