PubMed

NMRPro: an integrated web component for interactive processing and visualization of NMR spectra. Bioinformatics. 2016 Feb 26; Authors: Mohamed A, Nguyen CH, Mamitsuka H Abstract The popularity of using NMR spectroscopy in metabolomics and natural products has driven the development of an array of NMR spectral analysis tools and databases. Particularly, web applications are well used recently because they are platform-independent and easy to extend through reusable web components. Currently available web applications provide the analysis of NMR spectra. However, they still lack the necessary processing and interactive visualization functionalities. To overcome these limitations, we present NMRPro, a web component that can be easily incorporated into current web applications, enabling easy-to-use online interactive processing and visualization. NMRPro integrates server-side processing with client-side interactive visualization through three parts: a python package to efficiently process large NMR datasets on the server-side, a Django App managing server-client interaction, and SpecdrawJS for client-side interactive visualization. AVAILABILITY AND IMPLEMENTATION: Demo and installation instructions are available at http://mamitsukalab.org/tools/nmrpro/ CONTACT: mohamed@kuicr.kyoto-u.ac.jpSupplementary information: Supplementary data are available at Bioinformatics online. PMID: 27153725 [PubMed - as supplied by publisher]

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. Bioinformatics. 2016 Feb 19; Authors: Cichonska A, Rousu J, Marttinen P, Kangas AJ, Soininen P, Lehtimäki T, Raitakari OT, Järvelin MR, Salomaa V, Ala-Korpela M, Ripatti S, Pirinen M Abstract MOTIVATION: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. RESULTS: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. AVAILABILITY AND IMPLEMENTATION: Code is available at https://github.com/aalto-ics-kepaco CONTACTS: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fiSupplementary information: Supplementary data are available at Bioinformatics online. PMID: 27153689 [PubMed - as supplied by publisher]

RIPPER: a framework for MS1 only metabolomics and proteomics label-free relative quantification. Bioinformatics. 2016 Feb 18; Authors: Van Riper SK, Higgins L, Carlis JV, Griffin TJ Abstract RIPPER is a framework for mass-spectrometry-based label-free relative quantification for proteomics and metabolomics studies. RIPPER combines a series of previously described algorithms for pre-processing, analyte quantification, retention time alignment, and analyte grouping across runs. It is also the first software framework to implement proximity-based intensity normalization. RIPPER produces lists of analyte signals with their unnormalized and normalized intensities that can serve as input to statistical and directed mass spectrometry (MS) methods for detecting quantitative differences between biological samples using MS. AVAILABILITY AND IMPLEMENTATION: http://www.z.umn.edu/ripper CONTACT: vanr0014@umn.eduSupplementary information: Supplementary data are available at Bioinformatics online. PMID: 27153682 [PubMed - as supplied by publisher]

Purine metabolism is dysregulated in patients with major depressive disorder. Psychoneuroendocrinology. 2016 Apr 30;70:25-32 Authors: Ali-Sisto T, Tolmunen T, Toffol E, Viinamäki H, Mäntyselkä P, Valkonen-Korhonen M, Honkalampi K, Ruusunen A, Velagapudi V, Lehto SM Abstract INTRODUCTION: The purine cycle and altered purinergic signaling have been suggested to play a role in major depressive disorder (MDD). Nevertheless, data on this topic are scarce. Based on previous studies, we hypothesized that compared with non-depressed controls, MDD patients have distinct purine metabolite profiles. METHODS: The samples comprised 99 MDD patients and 253 non-depressed controls, aged 20-71 years. Background data were collected with questionnaires. Fasting serum samples were analyzed using ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) to determine seven purine cycle metabolites belonging to the purine cycle. We investigated the levels of these metabolites in three settings: (1) MDD patients vs. non-depressed controls and (2) remitted vs. non-remitted MDD patients, and also (3) within-group changes in metabolite levels during the follow-up period. RESULTS: In logistic regression adjusted for age, gender, smoking, alcohol use, physical exercise, glycosylated hemoglobin, and high-density lipoprotein cholesterol, lower levels of inosine (OR 0.89, 95% CI 0.82-0.97) and guanosine (OR 0.32, 95% CI 0.17-0.59), and higher levels of xanthine (OR 2.21, 95% CI 1.30-3.75) were associated with MDD vs. the non-depressed group. Levels of several metabolites changed significantly during the follow-up period in the MDD group, but there were no differences between remitted and non-remitted groups. CONCLUSIONS: We observed altered purine metabolism in MDD patients compared with non-depressed controls. Furthermore, our observations suggest that circulating xanthine may accumulate in MDD patients. PMID: 27153521 [PubMed - as supplied by publisher]

Lung Adenocarcinoma Distally Rewires Hepatic Circadian Homeostasis. Cell. 2016 May 5;165(4):896-909 Authors: Masri S, Papagiannakopoulos T, Kinouchi K, Liu Y, Cervantes M, Baldi P, Jacks T, Sassone-Corsi P Abstract The circadian clock controls metabolic and physiological processes through finely tuned molecular mechanisms. The clock is remarkably plastic and adapts to exogenous "zeitgebers," such as light and nutrition. How a pathological condition in a given tissue influences systemic circadian homeostasis in other tissues remains an unanswered question of conceptual and biomedical importance. Here, we show that lung adenocarcinoma operates as an endogenous reorganizer of circadian metabolism. High-throughput transcriptomics and metabolomics revealed unique signatures of transcripts and metabolites cycling exclusively in livers of tumor-bearing mice. Remarkably, lung cancer has no effect on the core clock but rather reprograms hepatic metabolism through altered pro-inflammatory response via the STAT3-Socs3 pathway. This results in disruption of AKT, AMPK, and SREBP signaling, leading to altered insulin, glucose, and lipid metabolism. Thus, lung adenocarcinoma functions as a potent endogenous circadian organizer (ECO), which rewires the pathophysiological dimension of a distal tissue such as the liver. PAPERCLIP. PMID: 27153497 [PubMed - as supplied by publisher]

Plasma sphingolipid changes with autopsy-confirmed Lewy Body or Alzheimer's pathology. Alzheimers Dement (Amst). 2016;3:43-50 Authors: Savica R, Murray ME, Persson XM, Kantarci K, Parisi JE, Dickson DW, Petersen RC, Ferman TJ, Boeve BF, Mielke MM Abstract INTRODUCTION: The clinical and pathological phenotypes of Dementia with Lewy Bodies (DLB) and Alzheimer's disease (AD) often overlap. We examined whether plasma lipids differed among individuals with autopsy-confirmed Lewy Body pathology or AD pathology. METHODS: We identified four groups with available plasma two years prior to death: high (n=12) and intermediate likelihood DLB (n=14) based on the third report of the DLB consortium; dementia with Alzheimer's pathology (AD; n=18); and cognitively normal with normal aging pathology (n=21). Lipids were measured using ESI/MS/MS. RESULTS: There were overall group differences in plasma ceramides C16:0, C18:1, C20:0 and C24:1 and monohexosylceramides C18:1 and C24:1. These lipids did not differ between the high likelihood DLB and AD groups, but both groups had higher levels than normals. Plasma fatty acid levels did not differ by group. DISCUSSION: Plasma ceramides and monohexosylceramides are elevated in people with dementia with either high likelihood DLB or AD pathology. PMID: 27152320 [PubMed - as supplied by publisher]

Type 2 Diabetes Dysregulates Glucose Metabolism in Cardiac Progenitor Cells. J Biol Chem. 2016 May 5; Authors: Salabei JK, Lorkiewicz PK, Mehra P, Gibb AA, Haberzettl P, Hong KU, Wei X, Zhang X, Li Q, Wysoczynski M, Bolli R, Bhatnagar A, Hill BG Abstract Type 2 diabetes is associated with increased mortality and progression to heart failure. Recent studies suggest that diabetes also impairs reparative responses after cell therapy. In this study, we examined potential mechanisms by which diabetes affects cardiac progenitor cells (CPCs). CPCs isolated from the diabetic heart showed diminished proliferation, a propensity for cell death, and a pro-adipogenic phenotype. The diabetic CPCs were insulin resistant, and they showed higher energetic reliance on glycolysis, which was associated with upregulation of the pro-glycolytic enzyme 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3). In WT CPCs, expression of a mutant form of PFKFB, which mimics PFKFB3 activity and increases glycolytic rate, was sufficient to phenocopy the mitochondrial and proliferative deficiencies found in diabetic cells. Consistent with activation of phosphofructokinase in diabetic cells, stable isotope carbon tracing in diabetic CPCs showed dysregulation of the pentose phosphate and glycero(phospho)lipid synthesis pathways. We describe diabetes-induced dysregulation of carbon partitioning using stable isotope metabolomics-based coupling quotients, which relate relative flux values between metabolic pathways. These findings suggest that diabetes causes an imbalance in glucose carbon allocation by uncoupling biosynthetic pathway activity, which could diminish the efficacy of CPCs for myocardial repair. PMID: 27151219 [PubMed - as supplied by publisher]

In vivo gene expression in a Staphylococcus aureus prosthetic joint infection characterized by RNA sequencing and metabolomics: a pilot study. BMC Microbiol. 2016;16(1):80 Authors: Xu Y, Maltesen RG, Larsen LH, Schønheyder HC, Le VQ, Nielsen JL, Nielsen PH, Thomsen TR, Nielsen KL Abstract BACKGROUND: Staphylococcus aureus gene expression has been sparsely studied in deep-sited infections in humans. Here, we characterized the staphylococcal transcriptome in vivo and the joint fluid metabolome in a prosthetic joint infection with an acute presentation using deep RNA sequencing and nuclear magnetic resonance spectroscopy, respectively. We compared our findings with the genome, transcriptome and metabolome of the S. aureus joint fluid isolate grown in vitro. RESULT: From the transcriptome analysis we found increased expression of siderophore synthesis genes and multiple known virulence genes. The regulatory pattern of catabolic pathway genes indicated that the bacterial infection was sustained on amino acids, glycans and nucleosides. Upregulation of fermentation genes and the presence of ethanol in joint fluid indicated severe oxygen limitation in vivo. CONCLUSION: This single case study highlights the capacity of combined transcriptome and metabolome analyses for elucidating the pathogenesis of prosthetic infections of major clinical importance. PMID: 27150914 [PubMed - in process]

Related Articles Stereotypical Metabolic Response to Endoscopic Retrograde Cholangiopancreatography Show Alterations in Pancreatic Function Regardless of Post-Procedure Pancreatitis. Clin Transl Gastroenterol. 2016;7:e169 Authors: Lusczek ER, Colling K, Muratore S, Conwell D, Freeman M, Beilman G Abstract OBJECTIVES: Metabolomics-based diagnosis or prediction of risk may improve patient outcomes and improve understanding of the pathogenesis of acute pancreatitis (AP). Endoscopic retrograde cholangiopancreatography (ERCP) is a risk factor for developing AP. This pilot study examined metabolomes of patients before and after ERCP, hypothesizing that metabolomics could differentiate between patients who did and did not develop post-ERCP pancreatitis, and that biomarkers associated with development of AP could be identified. METHODS: Patients at high risk for developing post-ERCP pancreatitis were prospectively enrolled at the University of Minnesota from October 2012 to February 2014. Urine and serum samples were collected before ERCP, 2 h after ERCP, and daily thereafter if patients were admitted to the hospital with AP. Pancreatitis severity was calculated with Bedside Index for Severity in Acute Pancreatitis (BISAP) and Modified Glasgow scores. Patients who developed AP (n=9) were matched to patients who did not develop AP (n=18) by age and gender. Urine and serum metabolites were profiled with nuclear magnetic resonance spectroscopy. Partial least squares discriminant analysis (PLS-DA) was performed to detect changes in metabolic profiles associated with development of pancreatitis. Metabolic networks were constructed to probe functional relationships among metabolites. RESULTS: Of the 113 enrolled patients, 9 developed mild AP according to BISAP and modified Glasglow scores. PLS-DA showed common differences between pre- and post-ERCP metabolic profiles in urine and serum regardless of AP status, characterized by increases in serum and urine ketones and serum glucose. Pre-ERCP lipase levels were somewhat elevated in those who went on to develop AP, though this did not reach statistical significance. Metabolic networks differed between patients with AP and those without after ERCP; however, metabolomics did not identify specific prognostic or diagnostic markers of ERCP-induced AP. Aspartate and asparagine were identified as well-connected hubs in post-ERCP serum networks of cases and were correlated with aspartate transaminase (AST) and white blood cell count levels. These features were not evident in controls. Serum aspartate was elevated in AP patients relative to those without AP after ERCP (P=0.03). CONCLUSIONS: In this pilot study, ERCP was found to induce global changes in urine and serum metabolomes indicative of alterations in pancreatic function and insulin resistance. This should be taken into consideration in future research on this topic. Post-ERCP serum metabolic networks indicate functional differences surrounding aspartate metabolism between patients with AP and those without. Further study must be done in larger patient populations to test elevated lipase as a prognostic biomarker associated with risk of developing AP and to examine active metabolic mechanisms at work. PMID: 27148850 [PubMed]

Related Articles Reliability of Serum Metabolites over a Two-Year Period: A Targeted Metabolomic Approach in Fasting and Non-Fasting Samples from EPIC. PLoS One. 2015;10(8):e0135437 Authors: Carayol M, Licaj I, Achaintre D, Sacerdote C, Vineis P, Key TJ, Onland Moret NC, Scalbert A, Rinaldi S, Ferrari P Abstract OBJECTIVE: Although metabolic profiles have been associated with chronic disease risk, lack of temporal stability of metabolite levels could limit their use in epidemiological investigations. The present study aims to evaluate the reliability over a two-year period of 158 metabolites and compare reliability over time in fasting and non-fasting serum samples. METHODS: Metabolites were measured with the AbsolueIDQp180 kit (Biocrates, Innsbruck, Austria) by mass spectrometry and included acylcarnitines, amino acids, biogenic amines, hexoses, phosphatidylcholines and sphingomyelins. Measurements were performed on repeat serum samples collected two years apart in 27 fasting men from Turin, Italy, and 39 non-fasting women from Utrecht, The Netherlands, all participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Reproducibility was assessed by estimating intraclass correlation coefficients (ICCs) in multivariable mixed models. RESULTS: In fasting samples, a median ICC of 0.70 was observed. ICC values were <0.50 for 48% of amino acids, 27% of acylcarnitines, 18% of lysophosphatidylcholines and 4% of phosphatidylcholines. In non-fasting samples, the median ICC was 0.54. ICC values were <0.50 for 71% of acylcarnitines, 48% of amino acids, 44% of biogenic amines, 36% of sphingomyelins, 34% of phosphatidylcholines and 33% of lysophosphatidylcholines. Overall, reproducibility was lower in non-fasting as compared to fasting samples, with a statistically significant difference for 19-36% of acylcarnitines, phosphatidylcholines and sphingomyelins. CONCLUSION: A single measurement per individual may be sufficient for the study of 73% and 52% of the metabolites showing ICCs >0.50 in fasting and non-fasting samples, respectively. ICCs were higher in fasting samples that are preferable to non-fasting. PMID: 26274920 [PubMed - indexed for MEDLINE]

Related Articles Malignancy-associated metabolic profiling of human glioma cell lines using 1H NMR spectroscopy. Mol Cancer. 2014;13:197 Authors: Shao W, Gu J, Huang C, Liu D, Huang H, Huang Z, Lin Z, Yang W, Liu K, Lin D, Ji T Abstract BACKGROUND: Ambiguity in malignant transformation of glioma has made prognostic diagnosis very challenging. Tumor malignant transformation is closely correlated with specific alterations of the metabolic profile. Exploration of the underlying metabolic alterations in glioma cells of different malignant degree is therefore vital to develop metabolic biomarkers for prognosis monitoring. METHODS: We conducted (1)H nuclear magnetic resonance (NMR)-based metabolic analysis on cell lines (CHG5, SHG44, U87, U118, U251) developed from gliomas of different malignant grades (WHO II and WHO IV). Several methods were applied to analyze the (1)H-NMR spectral data of polar extracts of cell lines and to identify characteristic metabolites, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), fuzzy c-means clustering (FCM) analysis and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). The expression analyses of glial fibrillary acidic protein (GFAP) and matrix metal proteinases (MMP-9) were used to assess malignant behaviors of cell lines. GeneGo pathway analysis was used to associate characteristic metabolites with malignant behavior protein markers GFAP and MMP-9. RESULTS: Stable and distinct metabolic profiles of the five cell lines were obtained. The metabolic profiles of the low malignancy grade group (CHG5, SHG44) were clearly distinguished from those of the high malignancy grade group (U87, U118, U251). Seventeen characteristic metabolites were identified that could distinguish the metabolic profiles of the two groups, nine of which were mapped to processes related to GFAP and MMP-9. Furthermore, the results from both quantitative comparison and metabolic correlation analysis indicated that the significantly altered metabolites were primarily involved in perturbation of metabolic pathways of tricarboxylic acid (TCA) cycle anaplerotic flux, amino acid metabolism, anti-oxidant mechanism and choline metabolism, which could be correlated with the changes in the glioma cells' malignant behaviors. CONCLUSIONS: Our results reveal the metabolic heterogeneity of glioma cell lines with different degrees of malignancy. The obtained metabolic profiles and characteristic metabolites are closely associated with the malignant features of glioma cells, which may lay the basis for both determining the molecular mechanisms underlying glioma malignant transformation and exploiting non-invasive biomarkers for prognosis monitoring. PMID: 25163530 [PubMed - indexed for MEDLINE]

Related Articles Integrated proteomic and metabolomic analysis to assess the effects of pure and benzo[a]pyrene-loaded carbon black particles on energy metabolism and motility in the human endothelial cell line EA.hy926. Arch Toxicol. 2014 Apr;88(4):913-34 Authors: Pink M, Verma N, Rettenmeier AW, Schmitz-Spanke S Abstract Epidemiological studies suggest that environmental exposure to airborne particulate matter may promote cardiovascular diseases; however, it is not clear whether this observation actually reflects exposure to nanosized particles in the environment. In the present study, the human endothelial cell line EA.hy926 was exposed to pure carbon black and, to mimic exposure to diesel exhaust, carbon black loaded with benzo[a]pyrene to ascertain effects of these particles on the cell proteome and metabolom. Particular emphasis was laid on an extended exposure period (14 days) and a low particle concentration (100 ng/mL). While ROS production essentially remained unaffected, exposure of the cells to the particles resulted in a significantly enhanced cell proliferation. Evaluation of the obtained proteomic and phosphoproteomic data revealed modulations of proteins involved in catalytic processes and cytoskeleton maintenance. The bioinformatic evaluation of the data revealed the possible involvement of the transcription factor peroxisome proliferator-activated receptor gamma. The further analysis of the cytoskeleton indicated changes of the cell motility, which is in agreement with an observed increase in the cellular migration and invasion, and macroscopic changes of the cytoskeleton of the exposed cells. PMID: 24464499 [PubMed - indexed for MEDLINE]

18 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2016/05/06PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Biochanin A improves hepatic steatosis and insulin resistance by regulating the hepatic lipid and glucose metabolic pathways in diet-induced obese mice. Mol Nutr Food Res. 2016 May 4; Authors: Park HS, Hur HJ, Kim SH, Park SJ, Hong MJ, Sung MJ, Kwon DY, Kim MS Abstract SCOPE: Natural compounds that regulate peroxisome proliferator-activated receptor alpha (PPARα) have been reported to have beneficial effects in obesity-mediated metabolic disorders. In this study, we demonstrated that biochanin A (BA), an agonist of PPARα, improved hepatic steatosis and insulin resistance by regulating hepatic lipid and glucose metabolism. METHODS AND RESULTS: C57BL/6 mice were fed a normal chow diet, a high-fat diet (HFD), and a HFD supplemented with 0.05% BA for 12 weeks. Histological and biochemical examinations indicated that BA prevented obesity-induced hepatic steatosis and insulin resistance in HFD-fed mice. BA stimulated the transcriptional activation of PPARα in vitro and increased the expression of PPARα and its regulatory proteins in the liver. CE-TOF/MS analyses indicated that BA administration promoted the recovery of metabolites involved in phosphatidylcholine synthesis, lipogenesis, and beta-oxidation in the livers of obese mice. BA also suppressed the levels of gluconeogenesis-related metabolites and the expression of the associated enzymes, glucose 6-phosphatase and pyruvate kinase. CONCLUSION: Taken together, these results showed that BA ameliorated metabolic disorders such as hepatic steatosis and insulin resistance by modulating lipid and glucose metabolism in diet-induced obesity. Thus, BA may be a potential therapeutic agent for the prevention of obesity-mediated hepatic steatosis and insulin resistance. This article is protected by copyright. All rights reserved. PMID: 27145114 [PubMed - as supplied by publisher]

Metabolomics of silver nanoparticles toxicity in HaCaT cells: structure-activity relationships and role of ionic silver and oxidative stress. Nanotoxicology. 2016 May 4;:1-13 Authors: Carrola J, Bastos V, Jarak I, Oliveira-Silva R, Malheiro E, Daniel-da-Silva AL, Oliveira H, Santos C, Gil AM, Duarte IF Abstract The widespread use of silver nanoparticles (AgNPs) is accompanied by a growing concern regarding their potential risks to human health, thus calling for an increased understanding of their biological effects. The aim of this work was to systematically study the extent to which changes in cellular metabolism were dependent on the properties of AgNPs, using NMR metabolomics. Human skin keratinocytes (HaCaT cells) were exposed to citrate-coated AgNPs of 10, 30 or 60 nm diameter and to 30 nm AgNPs coated either with citrate (CIT), polyethylene glycol (PEG) or bovine serum albumin (BSA), to assess the influence of NP size and surface chemistry. Overall, CIT-coated 60 nm and PEG-coated 30 nm AgNPs had the least impact on cell viability and metabolism. The role of ionic silver and reactive oxygen species (ROS)-mediated effects was also studied, in comparison to CIT-coated 30 nm particles. At concentrations causing an equivalent decrease in cell viability, Ag(+ )ions produced a change in the metabolic profile that was remarkably similar to that seen for AgNPs, the main difference being the lesser impact on the Krebs cycle and energy metabolism. Finally, this study newly reported that while down-regulated glycolysis and disruption of energy production were common to AgNPs and H2O2, the impact on some metabolic pathways (GSH synthesis, glutaminolysis and the Krebs cycle) was independent of ROS-mediated mechanisms. In conclusion, this study shows the ability of NMR metabolomics to define subtle biochemical changes induced by AgNPs and demonstrates the potential of this approach for rapid, untargeted screening of pre-clinical toxicity of nanomaterials in general. PMID: 27144425 [PubMed - as supplied by publisher]

Related Articles The application of high-resolution mass spectrometry-based data-mining tools in tandem to metabolite profiling of a triple drug combination in humans. Anal Chim Acta. 2015 Oct 15;897:34-44 Authors: Xing J, Zang M, Zhang H, Zhu M Abstract Patients are usually exposed to multiple drugs, and metabolite profiling of each drug in complex biological matrices is a big challenge. This study presented a new application of an improved high resolution mass spectrometry (HRMS)-based data-mining tools in tandem to fast and comprehensive metabolite identification of combination drugs in human. The model drug combination was metronidazole-pantoprazole-clarithromycin (MET-PAN-CLAR), which is widely used in clinic to treat ulcers caused by Helicobacter pylori. First, mass defect filter (MDF), as a targeted data processing tool, was able to recover all relevant metabolites of MET-PAN-CLAR in human plasma and urine from the full-scan MS dataset when appropriate MDF templates for each drug were defined. Second, the accurate mass-based background subtraction (BS), as an untargeted data-mining tool, worked effectively except for several trace metabolites, which were buried in the remaining background signals. Third, an integrated strategy, i.e., untargeted BS followed by improved MDF, was effective for metabolite identification of MET-PAN-CLAR. Most metabolites except for trace ones were found in the first step of BS-processed datasets, and the results led to the setup of appropriate metabolite MDF template for the subsequent MDF data processing. Trace metabolites were further recovered by MDF, which used both common MDF templates and the novel metabolite-based MDF templates. As a result, a total of 44 metabolites or related components were found for MET-PAN-CLAR in human plasma and urine using the integrated strategy. New metabolic pathways such as N-glucuronidation of PAN and dehydrogenation of CLAR were found. This study demonstrated that the combination of accurate mass-based multiple data-mining techniques in tandem, i.e., untargeted background subtraction followed by targeted mass defect filtering, can be a valuable tool for rapid metabolite profiling of combination drugs in vivo. PMID: 26515003 [PubMed - indexed for MEDLINE]

Related Articles Monitoring of drug intake during pregnancy by questionnaires and LC-MS/MS drug urine screening: evaluation of both monitoring methods. Drug Test Anal. 2015 Aug;7(8):695-702 Authors: Hoeke H, Roeder S, Bertsche T, Lehmann I, Borte M, von Bergen M, Wissenbach DK Abstract Various studies pointed towards a relationship between chronic diseases such as asthma and allergy and environmental risk factors, which are one aspect of the so-called Exposome. These environmental risk factors include also the intake of drugs. One critical step in human development is the prenatal period, in which exposures might have critical impact on the child's health outcome. Thereby, the health effects of drugs taken during gestation are discussed controversially with regard to newborns' disease risk. Due to this, the drug intake of pregnant women in the third trimester was monitored by questionnaire, in addition to biomonitoring using a local birth cohort study, allowing correlations of drug exposure with disease risk. Therefore, 622 urine samples were analyzed by an untargeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) urine screening and the results were compared to self-administered questionnaires. In total, 48% (n = 296) reported an intake of pharmaceuticals, with analgesics as the most frequent reported drug class in addition to dietary supplements. 182 times compounds were detected by urine screening, with analgesics (42%; n = 66) as the predominantly drug class. A comparison of reported and detected drug intake was performed for three different time spans between completion of the questionnaires and urine sampling. Even if the level of accordance was low in general, similar percentages (~25%, ~19%, and ~ 20%) were found for all groups. This study illustrates that a comprehensive evaluation of drug intake is neither achieved by questionnaires nor by biomonitoring alone. Instead, a combination of both monitoring methods, providing complementary information, should be considered. PMID: 25545167 [PubMed - indexed for MEDLINE]

(1)H NMR- based metabolomics approaches as non- invasive tools for diagnosis of endometriosis. Int J Reprod Biomed (Yazd). 2016 Jan;14(1):1-8 Authors: Ghazi N, Arjmand M, Akbari Z, Mellati AO, Saheb-Kashaf H, Zamani Z Abstract BACKGROUND: So far, non-invasive diagnostic approaches such as ultrasound, magnetic resonance imaging, or blood tests do not have sufficient diagnostic power for endometriosis disease. Lack of a non-invasive diagnostic test contributes to the long delay between onset of symptoms and diagnosis of endometriosis. OBJECTIVE: The present study focuses on the identification of predictive biomarkers in serum by pattern recognition techniques and uses partial least square discriminant analysis, multi-layer feed forward artificial neural networks (ANNs) and quadratic discriminant analysis (QDA) modeling tools for the early diagnosis of endometriosis in a minimally invasive manner by (1)H- NMR based metabolomics. MATERIALS AND METHODS: This prospective cohort study was done in Pasteur Institute, Iran in June 2013. Serum samples of 31 infertile women with endometriosis (stage II and III) who confirmed by diagnostic laparoscopy and 15 normal women were collected and analyzed by nuclear magnetic resonance spectroscopy. The model was built by using partial least square discriminant analysis, QDA, and ANNs to determine classifier metabolites for early prediction risk of disease. RESULTS: The levels of 2- methoxyestron, 2-methoxy estradiol, dehydroepiandrostion androstendione, aldosterone, and deoxy corticosterone were enhanced significantly in infertile group. While cholesterol and primary bile acids levels were decreased. QDA model showed significant difference between two study groups. Positive and negative predict value levels obtained about 71% and 78%, respectively. ANNs provided also criteria for detection of endometriosis. CONCLUSION: The QDA and ANNs modeling can be used as computational tools in noninvasive diagnose of endometriosis. However, the model designed by QDA methods is more efficient compared to ANNs in diagnosis of endometriosis patients. PMID: 27141542 [PubMed - as supplied by publisher]

Trial Watch: Immunostimulation with Toll-like receptor agonists in cancer therapy. Oncoimmunology. 2016 Mar;5(3):e1088631 Authors: Iribarren K, Bloy N, Buqué A, Cremer I, Eggermont A, Fridman WH, Fucikova J, Galon J, Špíšek R, Zitvogel L, Kroemer G, Galluzzi L Abstract Accumulating preclinical evidence indicates that Toll-like receptor (TLR) agonists efficiently boost tumor-targeting immune responses (re)initiated by most, if not all, paradigms of anticancer immunotherapy. Moreover, TLR agonists have been successfully employed to ameliorate the efficacy of various chemotherapeutics and targeted anticancer agents, at least in rodent tumor models. So far, only three TLR agonists have been approved by regulatory agencies for use in cancer patients. Moreover, over the past decade, the interest of scientists and clinicians in these immunostimulatory agents has been fluctuating. Here, we summarize recent advances in the preclinical and clinical development of TLR agonists for cancer therapy. PMID: 27141345 [PubMed - as supplied by publisher]

Prime time for immune-checkpoint targeted therapy at ASCO 2015. Oncoimmunology. 2016 Mar;5(3):e1068494 Authors: Marabelle A, Routy B, Michels J, Kroemer G, Zitvogel L Abstract Cancer immunotherapy has been one of the dominant topics in oral presentations and abstracts during the 2015 annual meeting of the American Society of Clinical Oncology (ASCO). The renewed interest in immunotherapy is explained by the wide spectrum of activity, the durability of tumor responses and the rapid clinical development of immune-checkpoint targeted monoclonal antibodies. These new drugs are currently revolutionizing the field of oncology. Here we highlight what were to us the most important results announced during the annual meeting of ASCO held in Chicago, IL from May, 29th to June, 2nd 2015. In addition, we searched all the posters/published abstracts pertinent to the field of immunooncology from this year conference. Among more than 400 published abstracts on this topic, we have grouped and briefly summarized the most relevant ones. PMID: 27141332 [PubMed - as supplied by publisher]