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Life Sciences - Biochemistry & Biophysics | Metabolomics - incl. option to publish open access (Societies)

Metabolomics

Metabolomics

Editor-in-Chief: Royston Goodacre

ISSN: 1573-3882 (print version)
ISSN: 1573-3890 (electronic version)

Journal no. 11306

Welcome to the Metabolomics Journal Cover Gallery

October 2017, Volume 13: Number 10 

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As high-throughput metabolomics profiling from stored samples is getting easily available, added value of using multi-metabolic marker signatures for early prediction for diseases like diabetes emerges as a practical question for developing early diagnostic methods. Study investigates such marker signatures in blood and compares their prediction power to that of glucose in a prospective design. September 2017, 13:104

September 2017, Volume 13: Number 9 

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This study introduces Baitmet, an integrated computational tool written in R that performs high-throughput library-driven GC–MS profiling in complex samples. Additionally, it includes a novel strategy to automatically compute retention indexes without internal calibration (co-injection of standard materials). August 2017, 13:93

August 2017, Volume 13: Number 8 

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As computational resources nowadays are easily available, large-scale studies including several cohorts and sampling occasions are becoming more popular. A well-known challenge in this context is to suppress the effect this will have on the combined dataset, the so-called batch effect. We demonstrate how this suppression can be achieved by a multivariate modeling method using an in-house generated metabolomics in vitro pharmacology dataset. We also show how the very same method can be used to directly extract the biological variation of interest. The proposed method is generic and can easily be adapted to any type of life science dataset. July 2017, 13:79

July 2017, Volume 13: Number 7 

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In this study metabolomics is use to discover that LysoPC-acyl C16:0 associates with brown adipose tissue activity in men, Metabolomics, May 2017, 13:48

June 2017, Volume 13: Number 6 

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The front cover features the winner of the 2017 Best Review Award.
This award is for the best original article based on downloads during 2016. Congratulations to the authors Richard D. Beger, Warwick Dunn, Michael A. Schmidt, Steven S. Gross, Jennifer A. Kirwan, Marta Cascante, Lorraine Brennan, David S. Wishart, Matej Oresic, Thomas Hankemeier, David I. Broadhurst, Andrew N. Lane, Karsten Suhre, Gabi Kastenmüller, Susan J. Sumner, Ines Thiele, Oliver Fiehn, and Rima Kaddurah-Daouk , for “Precision Medicine and Pharmacometabolomics Task Group”- Metabolomics Society Initiative, for their article “Metabolomics enables precision medicine—“A white paper, community perspective””, Metabolomics 2016, 12:149.
Astronomers have used technology, pattern analysis, and knowledge development to describe the human within its world. In Metabolomics-enabled precision medicine, we use technology, pattern analysis, and knowledge development to describe the world within the human. Today, we stand before an expanding universe of grand ideas. As we gaze into the complexity of human biology in new ways, a previously unseen order begins to emerge. This advancing ability to detect patterns, to see with new eyes, has given birth to a new era of precision and invites the next generation of scientist-physicians to look beyond limits.
Link to the paper: http://link.springer.com/article/10.1007%2Fs11306-016-1094-6
Link to editorial on awards: http://link.springer.com/article/10.1007/s11306-017-1198-7

May 2017, Volume 13: Number 5 

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The front cover features the winner of the 2017 Best Review Award.
This award is for the best original article based on downloads during 2016. Congratulations to the authors Neil Swainston, Kieran Smallbone, Hooman Hefzi, Paul D. Dobson,Judy Brewer, Michael Hanscho, Daniel C. Zielinski, Kok Siong Ang, Natalie J. Gardiner, Jahir M. Gutierrez, Sarantos Kyriakopoulos, Meiyappan Lakshmanan, Shangzhong Li- Joanne K. Liu, Veronica S. Martínez, Camila A. Orellana, Lake-Ee Quek, Alex Thomas, Juergen Zanghellini, Nicole Borth, Dong-Yup Lee, Lars K. Nielsen, Douglas B. Kell, Nathan E. Lewis, and Pedro Mendes, for their article “Recon 2.2: from reconstruction to model of human metabolism”, Metabolomics 2016, 12: 109.

April 2017, Volume 13: Number 4 

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This study used magnetic resonance spectroscopic metabolic profiles from intact breast tumor tissue to explore the metabolic changes occurring as an effect of preoperative chemotherapy, discriminate therapy responders from non-responders, and determine metabolic differences between patients receiving or not receiving the antiangiogenic drug bevacizumab. Changes as an effect of chemotherapy were detected and pathological responders were successfully discriminated from non-responders after treatment, showing potential for assessment of patient benefit to treatment and the understanding of underlying mechanisms affecting response. Although metabolic differences based on bevacizumab administration were not prominent, glutathione was identified to be possibly affected by the drug.

March 2017, Volume 13: Number 3 

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The recent development of intact lipid profiling of lipids from dried blood spot samples has allowed us to investigate the effect of diet on the lipid metabolism of infants and we have shown that there are many significant differences in the lipid metabolism between breast-fed infants and formula-fed infants. In this paper we show how we were able to obtain the minimal number of lipids necessary to robustly predict the infant’s diet and validated this in two different studies. We can therefore call these lipids biomarkers of infant nutrition.

February 2017, Volume 13: Number 2 

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Development of comprehensive metabolomics methods is hampered by the physiochemical diversity in metabolites, along with the array of tunable analytical parameters on the chosen detection method. Design of experiments is employed to concurrently optimize metabolite response across multiple HILIC liquid chromatography mass spectrometry (LC-MS) methods to enhance analyses of small polar compounds in a custom workfl ow we term Comprehensive Optimization of LC-MS Metabolomics methods using Design of experiments (COLMeD). This cover art shows an example of a response contour plot, indicating regions of the design space with improved chromatography, along with a depiction of the original 3D design space being constrained to 2D and focused round after round to settle on a fi nal LC-MS
parameter setting.

January 2017, Volume 13: Number 1 

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The isolation and extraction of metabolites directly from biological samples, as the first step of a typical metabolomics work flow, can affect the quality of the results. This research illustrates the power of in vivo solid-phase microextraction (SPME), coupled to both LCHRMS and GCxGC/MS platforms, to provide comprehensive metabolite coverage of Escherichia coli as a model organism with and without treatment with the antibacterial agent clove oil. The use of SPME coupled to different separation platforms identified new potential targets for clove oil as an antibacterial agent, disrupting E. coli metabolic pathways.

December 2016, Volume 12: Number 12 

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In the present work, we publish the first atlas of the common chicken (Gallus gallus) metabolome. Twelve biological matrices relevant to energy and growth metabolism were characterised by 1H NMR spectroscopy and compared with each other. 78 unique metabolic features were identified, of which only 8 core metabolites were detected in every biological matrice. This work will serve as a reference for future studies investigating chicken metabolism.

November 2016, Volume 12: Number 11 

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Precision medicine is guided by understanding the complex metabolic profile of an individual, which is further informed by how that individual compares to a chosen population. The scale of the metabolomics component is highlighted here, not to assert preeminence, but to illustrate the essential and prominent role that metabolomics can play in providing real time insights into molecular differences among individuals, and how such information can inform about treatment outcomes and contribute to success of precision medicine programs. [Image molecular insets: courtesy NIH \ Cover image: courtesy Sovaris Aerospace].
This article forms a part of a Themed Issue entitled “Recent advances in Pharmacometabolomics: enabling tools for precision medicine.”

October 2016, Volume 12: Number 10 

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The workflow to convert raw UHPLC-MS metabolomics data to a single data matrix for statistical analysis involves multiple computational steps. In this paper the normalisation, missing value imputation, transformation and scaling steps are assessed in relation to their impact on univariate and multivariate analysis. Appropriate workflows for univariate and multivariate analysis are reported.

September 2016, Volume 12: Number 9 

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This month is the 18 year anniversary of the first recorded use of the word metabolome in peer-reviewed literature. The front cover highlights this historic moment and is accompanied by a perspective by Profs Kell and Oliver who were instrumental in establishing this new exciting area of post-genomics science.

August 2016, Volume 12: Number 8  

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The front cover features the winner of the 2016 Best Review Award. This award is for the best review article based on downloads during 2015; this and the other award winners and runners up are detailed in Goodacre, R. (2016) NEWS: the 2016 Metabolomics publication awards. Metabolomics 12: 119. DOI: 10.1007/s11306-016-1060-3. Congratulations to the authors of: Emwas, A-H., Luchinat, C., Turano, P., Tenori, L., Roy, R., Salek, R., Ryan, D., Merzaban, J.S., Kaddurah-Daouk, R., Zeri, A.C., Gowda, G.A.N., Raftery, D., Wang, Y., Brennan, L. & Wishart, D.S. (2015) Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review. Metabolomics 11, 872–894.

July 2016, Volume 12: Number 7 

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The front cover features the winner of the 2016 Best Paper Award. This award is for the best original article based on downloads during 2015; this and the other award winners and runners up are detailed in article 119 in this issue. Congratulations to the authors of: Bro, R., Kamstrup-Nielsen, M.H., Engelsen, S.B., Savorani, F., Rasmussen, M.A., Hansen, L., Olsen, A., Tjønneland, A. & Dragsted, L.O. (2015) Forecasting individual breast cancer risk using plasma metabolomics and biocontours Metabolomics 11, 1376-1380.

June 2016, Volume 12: Number 6 

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The cover figure illustrates a time-series NMR spectra of fermentation of lactic acid bacteria (colored by the time), measured by the protocol that we developed for real-time in vitroNMR measurements of bacterial fermentation. The protocol makes suggestions for in vitro investigation of bacterial metabolomics from sample preparation, over data acquisition and preprocessing, to the extraction of the kinetic metabolic profiles. PCA results of an ASCA effect matrix for two strains of LAB and two different pH values are also illustrated. These fermentation trajectories show how nutrients are consumed and new metabolites are produced by the different samples. The protocol allows a elatively easy investigation of different fermentation factors such as new strains, new substrates, cohabitations, temperature, and pH and has a great potential in biopreservation studies to discover new efficient bioprotective cultures.

May 2016, Volume 12: Number 5 

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Reducing acidity is particularly desirable for wines produced in cooler-climate regions, such as Chablis in France. Therefore local winemakers usually perform a biological deacidification, called malolactic fermentation, carried out by lactic acid bacteria Oenococcus oeni. Unlike many other biological processes, the detailed mechanism of the malolactic reaction remains still unclear. The main factor, the winemakers have mostly control over, is the selection of the yeast strain for primary fermentation. Provided this knowledge Liu et al. suggested a complete workflow based on non-targeted metabolomics showing molecular evidences of yeast-bacteria interactions. Moreover specific compounds were validated which allow a refined control of the biological process.

April 2016, Volume 12: Number 4 

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In the present work ion mobility mass spectrometry was used to enhance the detection of low abundance lipid species being significantly increased in the substantia nigra of a brain at the very early stages of a Parkinson's disease murine model. The overlapped comparison of ion mobility maps (drift time Vs m/z plots, mobilograms) revealed the sharp upregulation of a family of N-acyl-phosphatidylethanolamines (NAPEs), naturally present in the brain at ppb to low ppm levels. This artwork depicts a LC-MS full scan mobilogram of a total lipid extract, with the upregulated lipids encompassed by a white rectangle and magnified in a 3D inset. As representative of this lipid class, the molecular structure of a NAPE (16:0/22:6/N18:0) is reported.

March 2016, Volume 12: Number 3 

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Molecular Landscape beneath the Artificial Gravity Phenotype: The image represents the impact of natural or artificial gravity conditions on molecular networks that shape the physiological, morphological, and behavioral phenotypes typically being measured. More sophisticated characterization of this underlying molecular landscape may add greater sensitivity and precision to development of the proper artificial gravity parameters, as a means to improve human safety and performance during prolonged space flight. Such characterization can also lead to astronaut personalization strategies that are optimized to a given space (gravity) environment.

February 2016, Volume 12: Number 2 

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There are many different types of rice which have contrasting taste and which have very strong local geographical and cultural preferences. The two major classes are referred to as basmati and jasmine rices. These not only look different (longer and thinner versus shorter and fatter) but also smell and taste different when cooked. The basis of these differences are related not only to their genetics but also to their moment of consumption (long-term stored versus fresh). In a broad, multi-platform analysis of over 30 different genotypes Mumm et al., have started to define the metabolic basis of these quality-related phenotypic differences between some of Asia’s most important rice varieties.

January 2016, Volume 12: Number 1 

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Scientists and data managers are faced with handling,mining and preserving huge amounts of metabolomics data.This paper describes standards embedded experiments,where data annotation is part of the standard operational procedures.Data standards can boost metabolomics research, and where there is a will, there is a way!

December 2015, Volume 11: Number 6 

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Picture of a root tip from the Arabidopsis thaliana GFP-expressing enhancer trap line J0521, showing strong GFP-expression in cortical and endodermal cell files (green). The picture was taken using a Zeiss Axio Imager fluorescence microscope at 20x magnification equipped with the ZEN Blue software. Deconvolution was done in Huygens (SVI) and image processing in FIJI (open source software). In the middle is a PCA score plot showing separation of root tissue (red) and sorted protoplasts (blue and green) coming from root tips from the J0521 line.

June 2012, Volume 11: Number 5 

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The front cover features the winner of the 2015 Best Paper Award, which is detailed in the Metabolomics Society News Section. Congratulations to the authors of: Szyman´ ska, E., Saccenti, E., Smilde, A.K. & Westerhuis, J.A. (2012) Double-check: validation of diagnostic statistics for PLS-DA models in metabolomics studies. Metabolomics 8, S3–S16

August 2015, Volume 11: Number 4 

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The continuous flow of substrates through the various compartments provides energy and metabolites for cellular functions. The Warburg effect represents a flow pattern typical of proliferating cells. The artwork was prepared by JK Yee and WNP Lee.

June 2015, Volume 11: Number 3 

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The front cover is from a paper that describes the inference of intracellular meabolic states from extracellular (metabolomic) measurements based on the human metabolic model and for two lymphoblastic leukemia cell lines. Similar approaches can be applied to the investigation of perturbations of the intracellular network, hallmark of all major human diseases.

April 2015, Volume 11: Number 2 

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The front cover features the jewel wasp Nasonia vitripennis injects venom into the pupa of its fleshfly host. Mrinalini and colleagues use the relative abundance of 249 diverse metabolites in the host to reveal that N. vitripennis venom targets specific metabolic processes while keeping the host alive.Venom downregulates glycolysis and oxidative metabolism, upregulates polyol and amino acid biosynthesis, and arrests chitin biosynthesis in the host.

February 2015, Volume 11: Number 1 

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The front cover features Integrated metabolomics using GC-MS and LC-MS was applied to a population of 1200 normal human individuals. From this epidemiology study variations in metabolites could be related to differences in gender, age, BMI, blood pressure, and smoking.

December 2014, Volume 10, Number 6 

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The front cover features Novel workflow to classify compounds detected in freshwater roach exposed to complex effluents as either endogenous metabolites or xenobiotics.

October 2014, Volume 10, Number 5 

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The front cover features the winner of the 2014 Best paper Award,
which is detailed in the Metabolomics Society News Section. Congratulations to the authors of: Koek, M.M., van der Kloet, F.M., Kleemann, R., Kooistra, T., Verheij, E.R. & Hankemeier, T. (2011) Semi-automated non-target processing in GC × GC-MS metabolomics analysis: applicability for biomedical studies. Metabolomics 7, 1–14.

August 2014, Volume 10, Number 4 

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Thirty-six specialized metabolites, including five new flavonoids and eight rare flavonolignan isomers, were isolated and identified from rice leaves by using MS/MS and NMR analyses. The MS/MS spectral data of the isolated compounds have been uploaded to the plant-specific MS/MS-based database, ReSpect (http://spectra.psc.riken.jp).

June 2014, Volume 10, Number 3 

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Untargeted metabolomics permits unbiased characterization of genetically modified cells for validation of disease models. Colorized representation of a bioluminescent, luciferase-expressing lymphoma cell. Original electron micrograph courtesy of NIAID.

April 2014, Volume 10, Number 2 

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A mechanism has been proposed for how methane production by bovine ruminal fluid is significantly reduced through the step-wise degradation of (+)-catechin, a common phenolic constituent in plant materials. By acting as a strong hydrogen sink, catechin degradation competes with methane synthesis and hence a catechin rich feedstuff might be used to reduce greenhouse gas emission by cattle.

February 2014, Volume 10, Number 1 

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The first issue of 2014 front cover celebrates the 10th volume of Metabolomics. A new year prompts the Society to continue successful frameworks as well as pursue new initiatives. Image very kindly generated by Dr Stephen O’Hagan (School of Chemistry and Manchester Institute of Biotechnology, University of Manchester, UK)

December 2013, Volume 9: Number 6 

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The behavior of molecular networks in humans encountering the space flight environment can be elucidated by applying integrated omics techniques (genomics, transcriptomics, proteomics, metabolomics, phenomics) to space flight research. Knowledge derived from these methods can lead to new analytical technologies, form the basis for development of individualized countermeasures, and establish personalized medicine as the standard of care for humans in space. Image credit: Sovaris Aerospace, LLC © 2013

October 2013, Volume 9: Number 5 

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The front cover features the winner of the 2013 Best Paper Award, which is detailed in the Metabolomics Society News Section. Saliva is a readily accessible and informative biofluid, making it ideal for the early detection of a wide range of diseases. This metabolomics study revealed hydrophilic metabolite profiles in saliva have potential for discriminating oral, breast, and pancreatic cancers from healthy controls.

August 2013, Volume 9: Number 4 

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The recent publication of the consensus genome-scale metabolic reconstruction, Recon 2, was a result of an international collaborative effort over a number of years. Through integration of biochemical knowledge, experimental data, and domain expertise, the most comprehensive computational and mathematical representation of human metabolism is now freely available to the community. The discipline of metabolomics will be instrumental in exploiting this new resource, and in its ongoing development.

June 2013, Volume 9: Number 3 

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The cover illustration depicts the crossing point of primary and secondary metabolism was investigated by applying oxidative stress to Arabidopsis thaliana and performing GC-MS and LC-MS analysis from the same sample. Using the metabolomics toolbox COVAIN the data were interpreted with Granger causality and metabolic modelling revealing biochemical pathways and perturbation points at the interface of primary and secondary metabolism.

April 2013, Volume 9: Number 2 

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The cover illustration abstractly depicts the rapidly expanding field of translational biomarker discovery in clinical metabolomics. Metabolomics is increasingly being applied towards the identification of biomarkers for disease diagnosis, prognosis and risk prediction. Here, the primary focus is to identify a small number of key, reproducibly quantifiable, metabolites for a given disease and rigorously assess the performance of the resulting multivariate mathematical classifiers using clinically applicable methods such as receiver operating characteristic (ROC) curve analysis.

March 2013, Volume 9, Special Issue 1  

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The cover figure represents “Data fusion in metabolomic cancer diagnostics” it is shown how modern metabolomics tools such as NMR and fluorescence spectroscopy can give huge gains in specificity and sensitivity of cancer classification models compared to using traditional state-of-the-art biomarkers.

February 2013, Volume 9, Number 1 

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The cover figure represents the workflow from a diverse range of sample types through mass spectrometric analysis to biological knowledge

December 2012, Volume 8: Number 6 

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The cover figure represents “Comprehensive, targeted metabolomic profiling of serum oxylipins in IgA nephropathy patients revealed kidney functional alterations in response to omega-3 fatty acid supplementation. These results suggest that serum oxylipin profiles may become useful tools for the discovery of biomarkers of responsiveness to inflammation-modifying supplements, foods, and medications.”

October 2012, Volume 8: Number 5 

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The cover figure shows how the use of PTR-ToF-MS on different cultivars of whole apple fruits may tackle the challenge of clone characterization. Examining fruit metabolomics, the study aimed to increase the effectiveness of volatile compound detection and quantification.

August 2012, Volume 8: Number 4 

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The cover figure presents a workflow for a holistic chromatography-mass spectrometry study of placental tissue to deduce biochemical mechanisms related to blood perfusion, energy and oxygen supply and the pregnancy complication pre-eclampsia.

June 2012, Volume 8: Number 3 

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The cover figure illustrates Diabetic kidney disease (diagnosed by urinary albumin) is a critical symptom of chronic vascular injury and predicts mortality in diabetes. Sphingolipids have been implicated in kidney injury in animal studies; here an untargeted NMR metabolomics study revealed a strong correlation between serum sphingomyelin and albuminuria in a set of human patients with type 1 diabetes.

June 2012, Volume 8: Number 1 Special Issue 

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The cover figure illustrates how data analysis is essential in metabolomics to unify the knowledge about the studied biological system with the advanced analytical chemical data that the platforms generate. We would like to show our gratitude to Miss. Ellis Balder for making the illustration.

April 2012, Volume 8: Number 2 

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The cover figure illustrates key aspects of a GC–MS metabolomics investigation of urine samples from a pediatric clinic, aimed to provide clinicians with an improved screening approach for inherited disorders of Complex I to IV of the mitochondrial respiratory chain.

February 2012, Volume 8: Number 1 

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The cover figure shows a flow chart describing the biomarker qualification process at the US FDA over a sample ROC plot. A qualified biomarker will reliably support a specified manner of interpretation and purpose of use, particularly in regulatory decision-making.

December 2011, Volume 7: Number 4 

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In the MEDE Study we developed well characterized, practical and reproducible protocols for volunteer handling and urine sampling in human nutrition studies which use metabolomics approaches. We also developed protocols for data analysis which demonstrated that metabolite fingerprinting can be used efficiently to identify metabolites associated with specific dietary components which are potential biomarkers of food consumption.

September 2011, Volume 7: Number 3 

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The front cover image shows a fibroblast transiently transfected with the Src oncogene. Cells were stained with fluorescent antibodies to actin (green) and Src (red). Metabolomics, as a global approach, combined with multivariate statistical and/or mathematical tools can be useful in identifying biomarkers or overall metabolic changes associated with cancer development and progression. The image was taken by Andrew Burke.

June 2011, Volume 7: Number 2 

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The front cover highlights the relative amino acid concentrations in the embryo culture media were analyzed by HPLC-MS, HPLC-MS/MS as well as 1H NMR spectroscopy. Chemometric models were performed with SIMCA which was able to differentiate between non-pregnancy and pregnancy cycles.

December 2012, Volume 7: Number 1 

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The front cover highlights Unbiased non-target quantification of GC × GC–MS data poses a major challenge in Metabolomics analysis. In this study the quality of (semi)automated GC × GC–MS data processing was compared to targeted GC–MS processing.

December 2010, Volume 6: Number 4 

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The front cover highlights work on using Metabolomics to investigate whether feed restriction during late gestation, with or without postnatal carbohydrate and fat hypernutrition, leads to changes in metabolic pathways.

September 2010, Volume 6: Number 3 

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The cover figure presents a schematic overview of an UPLC-qTOF-mass spectrometry-driven non-targeted metabolomics approach investigating metabolite fingerprints of human fasting plasma and spot urine to reveal pre-diabetic metabolic traits.

June 2010, Volume 6: Number 2 

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Depicted is the contribution of pyruvate carboxylation (PC) to glutamate/glutamine cycling between neuron and astrocyte for sustaining neurotransmission. PC is previously unknown to occur in neuron and was stimulated by bipolar drug LiCl in both neurons and astrocytes.

March 2010, Volume 6: Number 1 

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The cover figure highlights the idea of exploring supervised learning approaches in mass spectrometry data to extract functional class label information for unidentified metabolites. This idea is demonstrated using well-known supervised methods in the context of lipidomics data, generated from UPLC/MS experiments.

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    Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:

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