Quasi-MSn identification of flavanone 7-glycoside isomers in Da Chengqi Tang by high performance liquid chromatography-tandem mass spectrometry

<p>Abstract</p> <p>Background</p> <p><it>Da Chengqi Tang </it>(DCT) is a common purgative formula in Chinese medicine. Flavanones are its major active compounds derived from <it>Fructus Aurantii Immaturus</it>. The present study developed an LC-MS/MS method to characterize two pairs of flavanone 7-glycoside isomers, i.e., hesperidin versus neohesperidin and naringin versus isonaringin.</p> <p>Methods</p> <p>After solid phase purification, components in sample were separated on a Agilent zorbax SB-C18 (5 μm, 250 mm × 4.6 mm) analytical column. ESI-MS and quasi-MSⁿwere performed in negative ion mode to obtain structural data of these two pairs of flavanone 7-glycoside isomers. Moreover, UV absorption was measured.</p> <p>Results</p> <p>There was no intra-pairs difference in the UV-Vis and MS/MS spectra of the two pairs of 7-glycoside isomers, whereas the mass spectrometry fragmentation pathways between pairs were different.</p> <p>Conclusion</p> <p>The present study developed a LC-MS/MS method to explore the inter- and intra-pair difference of two pairs of flavanone 7-glycoside isomers.</p

Biomarker Discovery for Cytochrome P450 1A2 Activity Assessment in Rats, Based on Metabolomics

Cytochrome P450 1A2 (CYP1A2) is one of the major CYP450 enzymes (CYPs) in the liver, and participates in the biotransformation of various xenobiotics and endogenous signaling molecules. The expression and activity of CYP1A2 show large individual differences, due to genetic and environmental factors. In order to discover non-invasive serum biomarkers associated with hepatic CYP1A2, mass spectrometry-based, untargeted metabolomics were first conducted, in order to dissect the metabolic differences in the serum and liver between control rats and &beta;-naphthoflavone (an inducer of CYP1A2)-treated rats. Real-time reverse transcription polymerase chain reaction and pharmacokinetic analysis of phenacetin and paracetamol were performed, in order to determine the changes of mRNA levels and activity of CYP1A2 in these two groups, respectively. Branched-chain amino acids phenylalanine and tyrosine were ultimately focalized, as they were detected in both the serum and liver with the same trends. These findings were further confirmed by absolute quantification via a liquid chromatography&ndash;tandem mass spectrometry (LC-MS/MS)-based targeted metabolomics approach. Furthermore, the ratio of phenylalanine to tyrosine concentration was also found to be highly correlated with CYP1A2 activity and gene expression. This study demonstrates that metabolomics can be a potentially useful tool for biomarker discovery associated with CYPs. Our findings contribute to explaining interindividual variations in CYP1A2-mediated drug metabolism

Untargeted Metabolomics Study of the In Vitro Anti-Hepatoma Effect of Saikosaponin d in Combination with NRP-1 Knockdown

Saikosaponin d (SSd) is one of the main active ingredients in Radix Bupleuri. In our study, network pharmacology databases and metabolomics were used in combination to explore the new targets and reveal the in-depth mechanism of SSd. A total of 35 potential targets were chosen through database searching (HIT and TCMID), literature mining, or chemical similarity predicting (Pubchem). Out of these obtained targets, Neuropilin-1 (NRP-1) was selected for further research based on the degree of molecular docking scores and novelty. Cell viability and wound healing assays demonstrated that SSd combined with NRP-1 knockdown could significantly enhance the damage of HepG2. Metabolomics analysis was then performed to explore the underlying mechanism. The overall difference between groups was quantitatively evaluated by the metabolite deregulation score (MDS). Results showed that NRP-1 knockdown exhibited the lowest MDS, which demonstrated that the metabolic profile experienced the slightest interference. However, SSd alone, or NRP-1 knockdown in combination with SSd, were both significantly influenced. Differential metabolites mainly involved short- or long-chain carnitines and phospholipids. Further metabolic pathway analysis revealed that disturbed lipid transportation and phospholipid metabolism probably contributed to the enhanced anti-hepatoma effect by NRP-1 knockdown in combination with SSd. Taken together, in this study, we provided possible interaction mechanisms between SSd and its predicted target NRP-1

The Effect of Shear Rate on Dynamic Gelation of Phenol Formaldehyde Resin Gel in Porous Media

Polymer gel is the most widely used plugging agent in profile control, whose formula and injected speed are very important process parameters. It is very significant to study the effect of shear rates on the dynamic gelation of polymer gel in porous media for selecting suitable formula and injection speed. Taking the phenol formaldehyde resin gel with static gelation time of 21 h in ampoule bottle as research objective, it was studied the dynamic gelation process and subsequent water flooding in porous media under different injected speeds by a circulated equipment. The results shown that final dynamic gelation time is 2.4 times longer than the static gelation time in porous media. The gel particles are formed and mainly accumulated in the near wellbore zone after dynamic gelation. Injection speed has little effect on the dynamic gelation time in porous media, but has a great effect on the gel strength. The effect of injection speed on dynamic gel strength is evaluated by established the quantitative relationship between shear rate and dynamic gel strength. According to subsequent water flooding results, gel particles have certain plugging capacity in the near wellbore zone. The plugging ability declines obviously with an increasing injection speed. The experimental results provide theoretical support for the successful application of polymer gel used in profile control

Discovery of Potential Biomarkers with Dose- and Time-Dependence in Cisplatin-Induced Nephrotoxicity Using Metabolomics Integrated with a Principal Component-Based Area Calculation Strategy

Cisplatin is a potent chemotherapeutic agent. However, its clinical usage is restricted by serious adverse effects, especially nephrotoxicity. For revealing the dose- and time-dependence of cisplatin-induced nephrotoxicity, mass spectrometry-based metabolomics integrated with a principal component-based area calculation (PCAC) strategy was proposed in the present study. Area plots based on the first two principal components of the principal component analysis model were constructed first. Then, the sums of cumulative areas under PC-T curves (AUC_PC‑T) were calculated. Finally, the fold change of AUC_PC‑T between experimental and control groups at different time points was calculated and used as an indicative parameter. With the PCAC approach, dose- and time-dependence of cisplatin-induced metabolic change was quantitatively confirmed for the first time. Furthermore, 27 potential biomarkers with dose- and time-dependence related to nephrotoxicity induced by cisplatin were screened out and tentatively identified. Metabolic pathways interrupted by cisplatin mainly included energy, amino acid, and lipid metabolism

Discovery of Metabolite Biomarkers for Acute Ischemic Stroke Progression

Stroke remains a major public health problem worldwide; it causes severe disability and is associated with high mortality rates. However, early diagnosis of stroke is difficult, and no reliable biomarkers are currently established. In this study, mass-spectrometry-based metabolomics was utilized to characterize the metabolic features of the serum of patients with acute ischemic stroke (AIS) to identify novel sensitive biomarkers for diagnosis and progression. First, global metabolic profiling was performed on a training set of 80 human serum samples (40 cases and 40 controls). The metabolic profiling identified significant alterations in a series of 26 metabolites with related metabolic pathways involving amino acid, fatty acid, phospholipid, and choline metabolism. Subsequently, multiple algorithms were run on a test set consisting of 49 serum samples (26 cases and 23 controls) to develop different classifiers for verifying and evaluating potential biomarkers. Finally, a panel of five differential metabolites, including serine, isoleucine, betaine, PC­(5:0/5:0), and LysoPE(18:2), exhibited potential to differentiate AIS samples from healthy control samples, with area under the receiver operating characteristic curve values of 0.988 and 0.971 in the training and test sets, respectively. These findings provided insights for the development of new diagnostic tests and therapeutic approaches for AIS