Outcomes of COVID-19 in multiple myeloma patients treated with daratumumab.

Despite concerns about an increased risk of adverse outcomes following coronavirus disease (COVID-19) in multiple myeloma patients treated with anti-CD38 Abs, the impact of COVID-19 on this group of patients is unclear. We tried to evaluate the clinical outcomes of these patients. We collected data from 1036 patients with multiple myeloma and enrolled 509 cases with COVID-19. We divided enrolled patients into daratumumab or nondaratumumab cohorts based on whether they had received daratumumab-based treatment within 6 months of COVID-19 infection. We applied a propensity score matching method to reduce the bias of baseline characteristics, and then compared the incidence of adverse outcomes between these two cohorts. A total of 117 patients were enrolled in the daratumumab cohort, and 392 patients in the nondaratumumab cohort. After propensity score matching, 204 patients were matched. The proportions of patients who developed COVID-19 pneumonia (59.8% vs. 34.3%, p < 0.001), were hospitalized (33.3% vs. 11.8%, p < 0.001) and developed severe disease (23.5% vs. 6.9%, p = 0.001) were higher in the matched daratumumab cohort. By multivariate analysis, daratumumab exposure was an independent risk factor for severe disease. An ECOG performance status >2 and history of chronic kidney disease were independent risk factors for COVID-19-related mortality among patients who received daratumumab-based therapy. This study suggested that multiple myeloma patients exposed to daratumumab were at a higher risk of adverse outcomes from COVID-19.

Steroid profiling for the diagnosis of congenital adrenal hyperplasia by microbore ultra-performance liquid chromatography-tandem mass spectrometry.

BACKGROUND: A rapid and accurate measurement approach for 17α-hydroxyprogesterone (17-OHP) and related steroids in amount/volume-limited clinic samples is of importance for precise newborn diagnosis of congenital adrenal hyperplasia (CAH) and its subtypes in clinic. METHODS: Sixteen steroids (17-OHP, androstenedione, cortisol, tetrahydro-11-deoxycortisol, pregnenolone, progesterone, 11-deoxycorticosterone, corticosterone, 21-deoxycortisol, 11-deoxycortisol, dehydroepiandrosterone, testosterone, aldosterone, 17α-hydroxypregnenolone, dihydrotestosterone and 18-hydroxycorticosterone) were included in the panel of high-throughput microbore ultra-performance liquid chromatography-tandem mass spectrometry. Samples were collected from 126 normal subjects and 65 patients including different subtypes of CAH. RESULTS: The method was validated with satisfactory analytical performance in linearity, repeatability, recovery and limit of detection. Reference intervals for 16 steroids were established by quantifying the level of steroids detected in normal infants. The applicability of the method was tested by differentiating steroid metabolic characteristics between normal infants and infants with CAH, as well as between infants with different CAH subtypes. The relevance of 17-OHP, 21-deoxycortisol, and 17-OHP/11-deoxycortisol for 21-hydroxylase deficiency screening was demonstrated. The level of 11-deoxycorticosterone, 11-deoxycortisol, progesterone and androstenedione can be used for the diagnosis of different rare subtypes of CAH. CONCLUSION: This study provides a strategy for highly efficient steroid analysis of amount/volume-limited clinic samples and holds great potential for clinical diagnosis of CAH.

A review of the botany, ethnopharmacology, phytochemistry, pharmacology, toxicology and quality of Anemarrhena asphodeloides Bunge.

ETHNOPHARMACOLOGICAL RELEVANCE: The rhizomes of Anemarrhena asphodeloides Bunge., belonging to the family Liliaceae, are named 'Zhi-mu' according to traditional Chinese medicine theory. It is a medicinal plant that has long been used as a tonic agent in various ethnomedicinal systems in East Asia, especially in China, and also for treating arthralgia, hematochezia, tidal fever, night sweats, cough, dry mouth and tongue, hemoptysis, etc. THE ARM OF THE REVIEW: The review aims to provide a systematic overview of botany, ethnopharmacology, phytochemistry, pharmacology, toxicology and quality control of Anemarrhena asphodeloides and to explore the future therapeutic potential and scientific potential of this plant. MATERIALS AND METHODS: A comprehensive literature search was performed on Anemarrhena asphodeloides using scientific databases including Web of Science, PubMed, Google Scholar, CNKI, Elsevier, SpringerLink, ACS publications, ancient books, Doctoral and master's Theses. Collected data from different sources was comprehensively summarised for botany, ethnopharmacology, phytochemistry, pharmacology, toxicology and quality control of Anemarrhena asphodeloides. RESULTS: A comprehensive analysis of the literature as mentioned above confirmed that the ethnomedical uses of Anemarrhena asphodeloides had a history of thousands of years in eastern Asian countries. Two hundred sixty-nine compounds have been identified from Anemarrhena asphodeloides, including steroidal saponins, flavonoids, phenylpropanoids, alkaloids, steroids, organic acids, polysaccharides, benzophenones and other ingredients. Studies have shown that the extracts and compounds from Anemarrhena asphodeloides have extensive pharmacological activities, such as nervous system activity, antitumour, anti-inflammatory, antidiabetic, antiosteoporotic, antiallergic, antiplatelet aggregation, antimicrobial, antiviral, anti-ageing, hair growth promoting, preventing cell damage, etc. Evaluating the quality and toxicity of Anemarrhena asphodeloides is essential to confirm its safe use in humans. CONCLUSION: Anemarrhena asphodeloides is widely used in traditional medicine and have diverse chemical constituents with obvious biological activities. Nevertheless, more studies should be carried out in animals and humans to evaluate the cellular and molecular mechanisms involved in its biological activity and confirm its safe use.

A review on the advances in the extraction methods and structure elucidation of Poria cocos polysaccharide and its pharmacological activities and drug carrier applications.

Poria cocos polysaccharide (PCP) is one of the main active components of Poria cocos that is extensively used in the world. PCP can be divided into intro-polysaccharides and exopolysaccharides. PCP is mainly composed of glucose, galactose and mannose. There are many methods to exact PCP, and methods can affect its yield. PCP and its derivatives exhibit diverse biological functions such as antitumour, antioxidant, anti-inflammatory, immune-regulatory, hepatoprotective, etc. There is the potential application of PCP as drug carriers. The review provides a comprehensive summary of the latest extraction and purification methods of PCP, its chemistry, synthesis of PCP derivates, their pharmacological activities and their applications as drug carriers. This review provides comprehensive information on PCP, which can be used as the basis for further research on PCP and its derivates.

Bortezomib-Based Regimens for Newly Diagnosed Multiple Myeloma in China: A Report of 12-Year Real-World Data.

Background: Improve the treatment quality might affect patients' efficacy and survival. Methods: Five hundred thirty multiple myeloma patients treated in four hematological centers in China from February 2006 to August 2018 were enrolled. General characteristics, treatment regimens and cycles, efficacy, survival and adverse events of the patients treated before and after August 2013 (later refer to as the before-2013 and after-2013 group) were analyzed and compared. Results: The results suggested that patients who received optimized treatment regimen and route of administration completed more cycles of treatment in the after-2013 group. Although the overall response rate was similar between the two groups (88.6 vs. 90.5%), patients in the after-2013 group had higher complete remission rate (39.1 vs. 28.6%) and better progression-free survival. Subgroup analysis suggested that patients aged 65 years and older, with non-high-risk D-S, ISS, and R-ISS stages, had a significant benefit in progression-free survival. Conclusion: Therefore, in clinical practice in China, by reducing the economic burden brought by the treatment on patients and optimizing the treatment regimen, more patients can be treated with better regimens in a prolonged duration to achieve better efficacy and survival, especially in elderly and non-high-risk patients.

Long non-coding RNA zinc finger antisense 1 functions as an oncogene in acute promyelocytic leukemia cells.

Despite progress in the diagnosis and treatment of acute promyelocytic leukemia (APL), its prognosis remains poor. Multiple studies have shown that long non-coding RNAs (lncRNAs) are involved in carcinogenesis and metastasis. The present study assessed the function of the lncRNA zinc finger antisense 1 (ZFAS1) in APL. In a cohort of 33 patients, ZFAS1 was significantly overexpressed compared with the level in healthy controls. To investigate the specific mechanisms of this upregulation, in vitro studies showed that silencing of ZFAS1 by small interfering RNA significantly inhibited cell proliferation in APL cells. Moreover, downregulation of ZFAS1 increased cellular apoptosis, decreased expression of B-cell lymphoma-2 and of induced myeloid leukemia cell differentiation protein Mcl-1, increased the expression of apoptosis regulator BAX and promoted the release of cytochrome c and Diablo homolog mitochondrial into the cytoplasm. In conclusion, these data indicate that ZFAS1 may serve as an oncogene in APL and may thus be a useful target for future clinical management.

Expression of interleukin-32 in bone marrow of patients with myeloma and its prognostic significance.

BACKGROUND: The guiding effect of prognostic stratification in multiple myeloma (MM) for treatment has been increasingly emphasized in recent years. The stratification of risk factors based on the International Staging System (ISS), Durie-Salmon (DS) staging and related indicators is affected by the renal function of patients, resulting in poor performance. This study assesses the relationship between interleukin-32 (IL-32) and related risk factors in 67 patients with MM and their clinical outcomes. AIM: To investigate the feasibility of IL-32 in evaluating prognosis in patients with MM and the factors influencing prognosis. METHODS: This was a pragmatic, prospective observational study of patients with MM at a single center. According to IL-32 level, patients were divided into two groups. The variables under consideration included age, blood ß2-microglobulin, albumin, C-reactive protein, serum calcium, serum creatinine, lactate dehydrogenase, M protein type, ISS stage, DS stage, and IL-32 levels and minimal residual disease (MRD) after induction treatment. The main outcomes were progression-free survival (PFS) and overall survival (OS). RESULTS: IL-32 was an important factor affecting PFS and OS in patients with MM. Compared with patients with IL-32 levels ≥ 856.4 pg/mL, patients with IL-32 levels < 856.4 pg/mL had longer PFS (P = 0.0387) and OS (P = 0.0379); Univariate analysis showed that IL-32 level and MRD were significantly associated with OS and PFS (P < 0.05). Multivariate analysis showed that IL-32 levels ≥ 856.4 pg/mL and MRD positive were still independent risk factors for OS and PFS (P < 0.05). CONCLUSION: IL-32 is valuable for assessing the prognosis of MM patients. IL-32 level combined with MRD may be a useful routine evaluation index for MM patients after treatment.

Serum Metabolomics Study of Gliclazide-Modified-Release-Treated Type 2 Diabetes Mellitus Patients Using a Gas Chromatography-Mass Spectrometry Method.

Sulfonylureas are one of the commonly used drugs in type 2 diabetes mellitus (T2DM) but with considerable incidence of monotherapy failure. However, the mechanism of patients' drug response is unclear, and suitability evaluation biomarkers are in urgent need for precision medicine. In this study, a pseudotargeted gas chromatography-mass spectrometry method was employed to investigate the serum metabolic profiling of 66 significant responders and 24 nonsignificant responders at baseline and 16 weeks after gliclazide modified-release (MR) monotherapy. Clinical improvements in blood glucose level and insulin sensitivity were closely associated with the alterations of TCA cycle, ketone body metabolism, lipid oxidation, branched-chain amino acid catabolism, and gut flora metabolism. The different baseline metabolic profiling observed in the two groups implied that patients with lower dyslipidemia level may be more suitable for sulfonylurea therapy. The biomarker panel consisting of HbA1c, 5,8,11,14,17-eicosapentaenoic acid, methyl 8,11,14-eicosatrienoate, and methyl hexadecanoate shows a very good prediction ability for the suitability of gliclazide treatment, and it may be meaningful in personalized medicine of T2DM patients by sulfonylurea therapy.

Multiple reaction monitoring-ion pair finder: a systematic approach to transform nontargeted mode to pseudotargeted mode for metabolomics study based on liquid chromatography-mass spectrometry.

Pseudotargeted metabolic profiling is a novel strategy combining the advantages of both targeted and untargeted methods. The strategy obtains metabolites and their product ions from quadrupole time-of-flight (Q-TOF) MS by information-dependent acquisition (IDA) and then picks targeted ion pairs and measures them on a triple-quadrupole MS by multiple reaction monitoring (MRM). The picking of ion pairs from thousands of candidates is the most time-consuming step of the pseudotargeted strategy. Herein, a systematic and automated approach and software (MRM-Ion Pair Finder) were developed to acquire characteristic MRM ion pairs by precursor ions alignment, MS(2) spectrum extraction and reduction, characteristic product ion selection, and ion fusion. To test the reliability of the approach, a mixture of 15 metabolite standards was first analyzed; the representative ion pairs were correctly picked out. Then, pooled serum samples were further studied, and the results were confirmed by the manual selection. Finally, a comparison with a commercial peak alignment software was performed, and a good characteristic ion coverage of metabolites was obtained. As a proof of concept, the proposed approach was applied to a metabolomics study of liver cancer; 854 metabolite ion pairs were defined in the positive ion mode from serum. Our approach provides a high throughput method which is reliable to acquire MRM ion pairs for pseudotargeted metabolomics with improved metabolite coverage and facilitate more reliable biomarkers discoveries.

Study of urinary steroid hormone disorders: difference between hepatocellular carcinoma in early stage and cirrhosis.

Hepatocellular carcinoma (HCC) is the fifth most common cancer in the world. Discovery of novel biomarkers for early HCC from other liver diseases such as cirrhosis is of great clinical benefit. In this study, a novel steroid hormone metabolomic method based on liquid chromatography-mass spectrometry combined with logistic regression analysis was applied to study the steroid hormone disorders and to screen potential urinary steroid hormone biomarkers of early HCC. Thirty-six urinary steroid hormones were detected and quantified in healthy controls, cirrhotic patients, and early HCC patients. Heat map analysis and multivariate statistical analysis suggested severe disorders of steroid hormone network and holistically decreased urinary steroid hormone pattern in cirrhotic and early HCC patients. Logistic regression analysis reveals that a panel of two urinary steroid hormones (epitestosterone and allotetrahydrocortisol) displayed excellent diagnostic capability for distinguishing early HCC from cirrhosis with area under the curve (AUC) = 0.938 of receiver operating characteristic (ROC) analysis. These results help to overcome the disadvantage of lower sensitivity and specificity of alpha-fetoprotein for distinguishing early HCC from cirrhosis. Our work shows that steroid hormone metabolomics is a promising biomarker tool for biomarker study of early HCC.

Study of induction chemotherapy efficacy in oral squamous cell carcinoma using pseudotargeted metabolomics.

The effect of induction chemotherapy on oral cancer is controversial owing to inconsistent results. However, the efficacy of induction chemotherapy is closely related to locoregional recurrence, distant metastasis, and overall survival after the treatment. A pseudotargeted metabolomics revealed that metabolites involved in glycolysis and amino acid metabolism were inversely regulated in patients with different chemotherapy responses, and most fatty acids, steroids, and antioxidant substances were up-regulated in all patients after the treatment. Among the metabolites, lactic acid, glucose, glutamic acid, aspartic acid, leucine, and glycerol were remarkably associated with induction chemotherapy efficacy. Subsequently, lactic acid, glutamic acid, and aspartic acid were defined as potential biomarkers of the suitability and efficacy of induction chemotherapy. Our results show that 100.0 and 84.37% of patients with different chemotherapy efficacy were correctly identified in the training and test sets, respectively. Moreover, patient suitability for treatment was correctly predicted for 100.0, 81.25, and 100.0% of patients in the training, test, and external validation sets, respectively. In conclusion, metabolites related to glycolysis, redox homeostasis, and anabolic progress were indicative of induction chemotherapy efficacy both pre- and post-chemotherapy and beneficial for outcome evaluation and prediction. These results illustrate the potentials of metabolomics in personalized induction chemotherapy.

Pseudotargeted metabolomics method and its application in serum biomarker discovery for hepatocellular carcinoma based on ultra high-performance liquid chromatography/triple quadrupole mass spectrometry.

Untargeted analysis performed using full-scan mass spectrometry (MS) coupled with liquid chromatography (LC) is commonly used in metabolomics. Although they are commonly employed, full-scan MS methods such as quadrupole-time-of-flight (Q-TOF) MS have been restricted by various factors including their limited linear range and complicated data processing. LC coupled with triple quadrupole (QQQ) MS operated in the multiple reaction monitoring (MRM) mode is the gold standard for metabolite quantification; however, only known metabolites are generally quantified, limiting its applications in metabolomic analysis. In this study, a pseudotargeted approach was proposed to perform serum metabolomic analysis using an ultra high-performance liquid chromatography (UHPLC)/QQQ MS system operated in the MRM mode, for which the MRM ion pairs were acquired from the serum samples through untargeted tandem MS using UHPLC/Q-TOF MS. The UHPLC/QQQ MRM MS-based pseudotargeted method displayed better repeatability and wider linear range than the traditional UHPLC/Q-TOF MS-based untargeted metabolomics method, and no complicated peak alignment was required. The developed method was applied to discover serum biomarkers for patients with hepatocellular carcinoma (HCC). Patients with HCC had decreased lysophosphatidylcholine, increased long-chain and decreased medium-chain acylcarnitines, and increased aromatic and decreased branched-chain amino acid levels compared to healthy controls. The novelty of this work is that it provides an approach to acquire MRM ion pairs from real samples, is not limited to metabolite standards, and it provides a foundation to achieve pseudotargeted metabolomic analysis on the widely used LC/QQQ MS platform.

A comparative study of volatile components in green, oolong and black teas by using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry and multivariate data analysis.

The difference of volatile components in green, oolong and black teas was studied by using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS). Simultaneous distillation extraction was proved to be a suitable technique to extract the analytes with interest. A total of 450 compounds were tentatively identified with comparison to the standard mass spectra in available databases, retention index on the first dimension and structured chromatogram. 33 tea samples, including 12, 12 and 9 samples of green, oolong and black tea were analyzed by using GC×GC-TOFMS. After peak alignment, around 3600 peaks were detected. Partial least squares - discriminant analysis and hierarchical cluster analysis were used to classify these samples, then non-parametric hypothesis test (Mann-Whitney U test) and the variable importance in the projection (VIP) were applied to discover the key components to distinguish the three types of tea with significant difference amongst them. 74 differential compounds are defined to interpret the chemical differences of 3 types of tea. This study shows the power of GC×GC-TOFMS method combined with multivariate data analysis to investigate natural products with high complexity for information extraction.

Analysis of urinary metabolic signatures of early hepatocellular carcinoma recurrence after surgical removal using gas chromatography-mass spectrometry.

The objective of present study was to offer insights into the metabolic responses of hepatocellular carcinoma (HCC) to surgical resection and the metabolic signatures latent in early HCC recurrence (one year after operation). Urinary metabolic profiling employing gas chromatography time-of-flight mass spectrometry (GC-TOF MS) was utilized to investigate the complex physiopathologic regulations in HCC after operational intervention. It was revealed that an intricate series of metabolic regulations including energy metabolism, amino acid metabolism, nucleoside metabolism, tricarboxylic acid (TCA) cycle, gut floral metabolism, etc., principally leading to the direction of biomass synthesis, could be observed after tumor surgical removal. Moreover, metabolic differences between recurrent and nonrecurrent patients had emerged 7 days after initial operation. The metabolic signatures of HCC recurrence principally comprised notable up-regulations of lactate excretion, succinate production, purine and pyrimidine nucleosides turnover, glycine, serine and threonine metabolism, aromatic amino acid turnover, cysteine and methionine metabolism, and glyoxylate metabolism, similar to metabolic behaviors of HCC burden. Sixteen metabolites were found to be significantly increased in the recurrent patients compared with those in nonrecurrent patients and healthy controls. Five metabolites (ethanolamine, lactic acid, acotinic acid, phenylalanine and ribose) were further defined; they were favorable to the prediction of early recurrence.

A support vector machine-recursive feature elimination feature selection method based on artificial contrast variables and mutual information.

Filtering the discriminative metabolites from high dimension metabolome data is very important in metabolomics study. Support vector machine-recursive feature elimination (SVM-RFE) is an efficient feature selection technique and has shown promising applications in the analysis of the metabolome data. SVM-RFE measures the weights of the features according to the support vectors, noise and non-informative variables in the high dimension data may affect the hyper-plane of the SVM learning model. Hence we proposed a mutual information (MI)-SVM-RFE method which filters out noise and non-informative variables by means of artificial variables and MI, then conducts SVM-RFE to select the most discriminative features. A serum metabolomics data set from patients with chronic hepatitis B, cirrhosis and hepatocellular carcinoma analyzed by liquid chromatography-mass spectrometry (LC-MS) was used to demonstrate the validation of our method. An accuracy of 74.33±2.98% to distinguish among three liver diseases was obtained, better than 72.00±4.15% from the original SVM-RFE. Thirty-four ion features were defined to distinguish among the control and 3 liver diseases, 17 of them were identified.

[Exploring the mechanism of rhizoma coptidis in treating type II diabetes mellitus based on metabolomics by gas chromatography-mass spectrometry].

Metabolomics was used to explore the mechanism of Rhizoma coptidis in treating type II diabetes mellitus. The rat model of type II diabetes mellitus was constructed by an injection of streptozocin (40 mg/kg), along with diets of fat emulsion. The rats were divided into four groups, the control group, the model group, the Rhizoma coptidis group (10 g/kg) and the metformin group (0.08 g/kg). After the treatment for 30 d, blood samples were collected to test biomedical indexes, and 24 h urine samples were collected for the metabolomics experiment. In the Rhizoma coptidis group, fasting blood glucose (FBG), total cholesterol (TC) and total plasma triglycerides (TG) were significantly decreased by 59.26%, 58.66% and 42.18%, respectively, compared with those in the model group. Based on gas chromatography-mass spectrometry, a urinary metabolomics method was used to study the mechanism of Rhizoma coptidis in treating diabetes mellitus. Based on the principal component analysis, it was found that the model group and control group were separated into two different clusters. The Rhizoma coptidis group was located between the model group and the control group, closer to the control group. Twelve significantly changed metabolites of diabetes mellitus were detected and identified, including 4-methyl phenol, benzoic acid, aminomalonic acid, and so on. After diabetic rats were administered with Rhizoma coptidis, 7 metabolites were significantly changed, and L-ascorbic acid and aminomalonic acid which related with the oxidative stress were significantly regulated to normal. The pharmacological results showed that Rhizoma coptidis could display anti-hyperglycemic and anti-hyperlipidemic effects. The Rhizoma coptidis had antioxidation function in preventing the occurrence of complications with diabetes mellitus to some extent. The work illustrates that the metabolomics method is a useful tool to study the treatment mechanism of traditional Chinese medicine.

Plasma metabonomics study of rheumatoid arthritis and its Chinese medicine subtypes by using liquid chromatography and gas chromatography coupled with mass spectrometry.

Rheumatoid arthritis (RA) is the most severe type of chronic inflammatory disease and has always been a research hotspot in different fields. In this study, a non-targeted metabonomics approach was carried out to profile metabolic characteristics of RA and its Chinese medicine subtypes by using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Plasma samples of 57 RA patients and 23 healthy controls were collected. On the basis of the traditional Chinese medicine (TCM), RA patients were classified into two main patterns, the cold pattern and the heat pattern. By using univariate and multivariate data analysis, we found that the RA patients presented diverse dysfunctions in inositol phosphate metabolism, lipid metabolism, amino acid metabolism, glucose metabolism, ascorbate metabolism, glyoxylate and dicarboxylate metabolism. The metabolic phenotypes were different between the RA cold pattern and the RA heat pattern. Compared with the RA cold pattern, the RA heat pattern showed elevated plasma concentrations of glycochenodeoxycholate, proline, saturated and mono-unsaturated phosphatidylcholine (PC) but decreased levels of urea, free fatty acid (FFA) and polyunsaturated PC. Our data show that metabonomics is a valuable tool in disease and TCM subtype research.

[Analysis of volatile oils of Ligusticum chuanxiong Hort. from different geographical origins by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry].

The volatile oils of 23 Ligusticum chuanxiong Hort. samples from 4 different regions were analyzed by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GC x GC/TOF MS). The group-type separation of 4 terpenoids and phthalides was well accomplished based on a DB-Petro x DB-17 column system. With the MS library search, 215 compounds were tentatively identified based on the NIST database and the 43 compounds of them were confirmed by using the retention index or comparing with the standard compounds in a typical sample from Xindu City. Twenty three samples were apparently classified into 4 groups by partial least square-discriminant analysis. A brief list of 20 differential compounds is presented, including cnidilide, 3-n-butylphthalide and butylidene phthalide. DPPH (1,1-diphenyl-2-picrylhydrazyl), stable free radical scavenging assay was adopted to differentiate the antioxidative potency of these samples, which was expressed as EC50. Based on the orthogonal partial least square model the biochemical discrimination of samples was achieved with ligustilide, senkyunolide A and neocnidilide as important differential compounds according to geographical origins. All the results indicated that phthalides exert a great influence on the chemical and biochemical classifications of Rhizoma Chuanxiong, and the samples from Pengzhou City have the highest contents of phthalides.

Metabonomics study of atherosclerosis rats by ultra fast liquid chromatography coupled with ion trap-time of flight mass spectrometry.

An ultra fast liquid chromatography coupled with IT-TOF mass spectrometry (UFLC/MS-IT-TOF) metabonomic approach was employed to study the plasma and urine metabolic profiling of atherosclerosis rats. Acquired data were subjected to principal component analysis (PCA) for differentiating the atherosclerosis and the control groups. Potential biomarkers were screened by using S-plot and were identified by the accurate mass and MS(n) fragments information obtained from UFLC/MS-IT-TOF analysis. 12 metabolites in rat plasma and 8 metabolites in urine were identified as potential biomarkers. Concentrations of leucine, phenylalanine, tryptophan, acetylcarnitine, butyrylcarnitine, propionylcarnitine and spermine in plasma and 3-O-methyl-dopa, ethyl N2-acetyl-L-argininate, leucylproline, glucuronate, t6A N(6)-(N-threonylcarbonyl)-adenosine and methyl-hippuric acid in urine decreased in atherosclerosis rats. Ursodeoxycholic acid, chenodeoxycholic acid, LPC (C16:0), LPC (C18:0) and LPC (C18:1) in plasma and hippuric acid in urine were in higher levels in atherosclerosis rats. The alterated metabolites demonstrated abnormal metabolism of phenylalanine, tryptophan, bile acids and amino acids. This research proved that metabonomics is a promising tool for disease research.

Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry for metabonomics: Biomarker discovery for diabetes mellitus.

Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry (GCxGC-TOFMS) coupled with pattern recognition methods was applied to analyze plasma from diabetic patients and healthy controls. After sample preparation and GCxGC-TOFMS analysis, collected data were transformed, the peak alignment between different chromatograms was performed to generate the metabolites' peak table, then orthogonal signal correction filtered partial least-squares discriminant analysis (OSC-PLSDA) was carried out to model the data and discover metabolites with a significant concentration change in diabetic patients. With the method above, diabetic patients and healthy controls could be correctly distinguished based on the metabolic abnormity in plasma. Five potential biomarkers including glucose, 2-hydroxyisobutyric acid, linoleic acid, palmitic acid and phosphate were identified. It was found that elevated free fatty acids were essential pathophysiological factors in diabetes mellitus which reflected either the hyperglycemia or the deregulation of fatty acids metabolism. These potential biomarkers in plasma, e.g. palmitic acid, linoleic acid and 2-hydroxybutyric acid might be helpful in the diagnosis or further study of diabetes mellitus. This study shows the practicability and advantage of GCxGC-TOFMS coupled with data analysis and mining for metabonomics in biomarker discovery.