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Automatic Characterization of Lipids Using Charge Remote Fragmentation Ions and Peaks Characteristic of Fatty Acid Fragmentation From MALDI MS/MS Data
Ningombam Sanjib Meitei*(1); Arun Apte(2); Dietmar Waidelich(3); Fadi Abdi(4); Matthias Glueckmann(3)

Automated identification of lipids using CRF ions and high energy MS/MS fragment ions and novel software.

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Characterization of Metabolites From Medicago truncatula Using Gas Chromatography Mass Spectrometry—Addressing the Knowns and Unknowns Using High Resolution Time-of-Flight
Joe Binkley, David Alonso, Jeff Patrick, David V. Huhman, Feng Qiu, Dennis Fine, and Lloyd W. Sumner

Analyses of the M. truncatula extracts were performed, and data processing focused on qualitative analyses. This provided the opportunity for known analyte verification and unknown identification in a meaningful matrix and the demonstration of the key attributes and benefits of GC-HRT.

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Utilization of Hydrogen Carrier Gas on a High Resolution GC-TOFMS System: An Application Compendium
Joe Binkley, David Alonso

GC-HRT methods utilizing hydrogen carrier gas were developed for analysis of representative specialty chemical, forensic, and metabolomic markets.

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Integrated platform including automated bligh and dyer extraction and dual-column
Emmanuel Varesio, Guenter Boehm, Sandra Jahn, Renzo Picenoni, Gérard Hopfgartner

• Automated Bligh and Dyer extraction for metabolomic studies.
• Dual-column UHPLC setup for the analysis of the polar and lipidic fractions.
• Alternating acidic and basic mobile phase for the separation of the polar fraction.
• Identification of unknown compounds by SWATH HR MS2 spectra acquisition.

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Deciphering Regulatory Mechanisms in M. xanthus Using Isotopic Ratio Outlier Analysis (IROA) for Metabolome-wide Quantitation
Daniel Krug 1,2, Carsten Volz 1, Aiko Barsch 3, Chris Beecher 4, Felice de Jong 4, Rolf Müller 1,2

Comprehensive study of regulation in myxobacteria with an untargeted metabolomics setup using Isotopic Ratio Outlier Analysis (IROA) and UHR-Q-TOF

Reliable relative quantitation of known and unknown metabolites from a myxobacterial mutant strain in response to induction of the transcriptional antirepressor taA

Compound identification facilitated by the use of ultra-high resolution MS and the knowledge of the number of carbons in each molecule due to IROA

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Identification and classification of antifouling compounds secreted by anti MIC microorganisms. A metabolomic analysis.
Albillos SM; Balaña-Fouce R; Montero O; Barreiro-Mendez C; Blas-Galindo E; Barros-García R; Guedella-Bustamante E; Ullán RV

BIOCORIN project, aims to develop a green alternative to the coatings and solutions used up to date for MIC corrosion control. Some of the results of this project are presented here, with the identification of several relevant antifouling compounds secreted by environmentally isolated anti-MIC strains of microorganisms via a metabolomic approach.

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Rapid Identification of Microorganisms by Touch Spray and Paper Spray Ambient Ionization
Ahmed M. Hamid, Alan K. Jarmusch, Valentina Pirro and R. Graham Cooks

The rapid and accurate identification of microorganisms is necessary in order to improve public health. Molecular-based identification allows for rapid patient treatment and provides more accurate diagnoses, two crucial aspects for successful treatment, yet a great challenge. In this work PS-MS, an existing ambient method, and TS-MS, a newly developed technique, are being utilized in the rapid discrimination of microorganisms (<2 min).

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Molecular Dynamics Simulation Study of Pulmonary Surfactant Interacting With Nanoparticles
Syed Kashif Zafar, Syed Tarique Moin and Zaheer-ul-Haq

MD simulation studies using NAMD of lipid bilayers supported on alpha-quartz (nanoparticles) and kaolinite with explicit water molecules will be presented to understand the physiochemical effects of nanoparticles on pulmonary surfactant.

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Transforming Analytical Data into Knowledge with Software for Metabolite Studies
Tara Sinclair, Graham A. McGibbon and Susan Ling

ACD/Labs has been developing specialized software for chemical and pharmaceutical research for over 16 years. Their expertise includes multi-technique, multi-instrument data handling, knowledge management of analytical and separations data, chemical drawing, and prediction software for a range of chemical properties as well as spectra and chromatograms.

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Scientific News
Fat Cells That Amplify Nerve Signals in Response to Cold Also Affect Blood Sugar Metabolism
Researchers at UTSW have found that the protein connexin 43 forms cell-to-cell communication channels on the surface of emerging beige fat cells that amplify the signals from those few nerve fibers.
Adipose Tissue Secretes Factors That Activate Metabolism
Study finds brown adipose tissue secretes signalling factors that activates metabolism of fat and carbohydrates.
Gene Deletion Reveals Cell Secrets
Researchers have deleted 174 genes in yeast to analyse the effect of individual gene deletion.
Targeting Fat to Treat Cancer
Researchers develop novel cancer treatment that halts fat synthesis in cells, stunting tumors.
NIH Study Finds Link Between Depression, Gestational Diabetes
Researchers at NIH have discovered that the depression in early pregnancy doubles risk for gestational diabetes, and gestational diabetes increases risk for postpartum depression.
Gut Pathogens Thrive on Body's Tissue-Repair Mechanism
Researcher have discovered that harm caused by pathogens in the intestinal tract benefit from immune system response to damaged intestinal lining.
Cancer's Taste for Fat
Researchers discovered signalling pathway for fat burning is disrupted in certain cancers.
‘Tracking Bugs’ Reveal Secret of Cancer Cell Metabolism
Unexpected finding shows instead of throwing away valuable nutrients, the cells squeeze out every last drop of energy.
Ginger Nano-Lipid Particles May Improve Cancer Treatment
Edible ginger-derived nano-lipids show promise for effectively targeting and delivering chemotherapeutic drugs used to treat colon cancer.
Genetic Diversity of Enzymes Alters Metabolic Individuality
ToMMo scientists have shown that genetic polymorphisms, structural location of mutation and effect for phenotype correlate with each other.
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