PubMed

Metabolomics study on primary dysmenorrhea patients during the luteal regression stage based on ultra performance liquid chromatography coupled with quadrupole‑time‑of‑flight mass spectrometry. Mol Med Rep. 2017 Jan 13;: Authors: Fang L, Gu C, Liu X, Xie J, Hou Z, Tian M, Yin J, Li A, Li Y Abstract Primary dysmenorrhea (PD) is a common gynecological disorder which, while not life‑threatening, severely affects the quality of life of women. Most patients with PD suffer ovarian hormone imbalances caused by uterine contraction, which results in dysmenorrhea. PD patients may also suffer from increases in estrogen levels caused by increased levels of prostaglandin synthesis and release during luteal regression and early menstruation. Although PD pathogenesis has been previously reported on, these studies only examined the menstrual period and neglected the importance of the luteal regression stage. Therefore, the present study used urine metabolomics to examine changes in endogenous substances and detect urine biomarkers for PD during luteal regression. Ultra performance liquid chromatography coupled with quadrupole‑time‑of‑flight mass spectrometry was used to create metabolomic profiles for 36 patients with PD and 27 healthy controls. Principal component analysis and partial least squares discriminate analysis were used to investigate the metabolic alterations associated with PD. Ten biomarkers for PD were identified, including ornithine, dihydrocortisol, histidine, citrulline, sphinganine, phytosphingosine, progesterone, 17‑hydroxyprogesterone, androstenedione, and 15‑keto‑prostaglandin F2α. The specificity and sensitivity of these biomarkers was assessed based on the area under the curve of receiver operator characteristic curves, which can be used to distinguish patients with PD from healthy controls. These results provide novel targets for the treatment of PD. PMID: 28098892 [PubMed - as supplied by publisher]

Distinguishing Benign from Malignant Pancreatic and Periampullary Lesions Using Combined Use of ¹H-NMR Spectroscopy and Gas Chromatography-Mass Spectrometry. Metabolites. 2017 Jan 13;7(1): Authors: McConnell YJ, Farshidfar F, Weljie AM, Kopciuk KA, Dixon E, Ball CG, Sutherland FR, Vogel HJ, Bathe OF Abstract Previous work demonstrated that serum metabolomics can distinguish pancreatic cancer from benign disease. However, in the clinic, non-pancreatic periampullary cancers are difficult to distinguish from pancreatic cancer. Therefore, to test the clinical utility of this technology, we determined whether any pancreatic and periampullary adenocarcinoma could be distinguished from benign masses and biliary strictures. Sera from 157 patients with malignant and benign pancreatic and periampullary lesions were analyzed using proton nuclear magnetic resonance (¹H-NMR) spectroscopy and gas chromatography-mass spectrometry (GC-MS). Multivariate projection modeling using SIMCA-P+ software in training datasets (n = 80) was used to generate the best models to differentiate disease states. Models were validated in test datasets (n = 77). The final ¹H-NMR spectroscopy and GC-MS metabolomic profiles consisted of 14 and 18 compounds, with AUROC values of 0.74 (SE 0.06) and 0.62 (SE 0.08), respectively. The combination of ¹H-NMR spectroscopy and GC-MS metabolites did not substantially improve this performance (AUROC 0.66, SE 0.08). In patients with adenocarcinoma, glutamate levels were consistently higher, while glutamine and alanine levels were consistently lower. Pancreatic and periampullary adenocarcinomas can be distinguished from benign lesions. To further enhance the discriminatory power of metabolomics in this setting, it will be important to identify the metabolomic changes that characterize each of the subclasses of this heterogeneous group of cancers. PMID: 28098776 [PubMed - in process]

Related Articles Biomedical Chromatography 2017. Biomed Chromatogr. 2017 Jan;31(1): Authors: Bartlett MG PMID: 27859468 [PubMed - indexed for MEDLINE]

Related Articles Amino acid composition and amino acid-metabolic network in supragingival plaque. Biomed Res. 2016;37(4):251-7 Authors: Washio J, Ogawa T, Suzuki K, Tsukiboshi Y, Watanabe M, Takahashi N Abstract Dental plaque metabolizes both carbohydrates and amino acids. The former can be degraded to acids mainly, while the latter can be degraded to various metabolites, including ammonia, acids and amines, and associated with acid-neutralization, oral malodor and tissue inflammation. However, amino acid metabolism in dental plaque is still unclear. This study aimed to elucidate what kinds of amino acids are available as metabolic substrates and how the amino acids are metabolized in supragingival plaque, by a metabolome analysis. Amino acids and the related metabolites in supragingival plaque were extracted and quantified comprehensively by CE-TOFMS. Plaque samples were also incubated with amino acids, and the amounts of ammonia and amino acid-related metabolites were measured. The concentration of glutamate was the highest in supragingival plaque, while the ammonia-production was the highest from glutamine. The obtained metabolome profile revealed that amino acids are degraded through various metabolic pathways, including deamination, decarboxylation and transamination and that these metabolic systems may link each other, as well as with carbohydrate metabolic pathways in dental plaque ecosystem. Moreover, glutamine and glutamate might be the main source of ammonia production, as well as arginine, and contribute to pH-homeostasis and counteraction to acid-induced demineralization in supragingival plaque. PMID: 27545001 [PubMed - indexed for MEDLINE]

Related Articles An original method for producing acetaldehyde and diacetyl by yeast fermentation. Braz J Microbiol. 2016 Oct - Dec;47(4):949-954 Authors: Rosca I, Petrovici AR, Brebu M, Stoica I, Minea B, Marangoci N Abstract In this study a natural culture medium that mimics the synthetic yeast peptone glucose medium used for yeast fermentations was designed to screen and select yeasts capable of producing high levels of diacetyl and acetaldehyde. The presence of whey powder and sodium citrate in the medium along with manganese and magnesium sulfate enhanced both biomass and aroma development. A total of 52 yeasts strains were cultivated in two different culture media, namely, yeast peptone glucose medium and yeast acetaldehyde-diacetyl medium. The initial screening of the strains was based on the qualitative reaction of the acetaldehyde with Schiff's reagent (violet color) and diacetyl with Brady's reagent (yellow precipitate). The fermented culture media of 10 yeast strains were subsequently analyzed by gas chromatography to quantify the concentration of acetaldehyde and diacetyl synthesized. Total titratable acidity values indicated that a total titratable acidity of 5.5°SH, implying culture medium at basic pH, was more favorable for the acetaldehyde biosynthesis using strain D15 (Candida lipolytica; 96.05mgL(-1) acetaldehyde) while a total titratable acidity value of 7°SH facilitated diacetyl flavor synthesis by strain D38 (Candida globosa; 3.58mgL(-1) diacetyl). Importantly, the results presented here suggest that this can be potentially used in the baking industry. PMID: 27528084 [PubMed - indexed for MEDLINE]

Related Articles Antimicrobial profile of Arthrobacter kerguelensis VL-RK_09 isolated from Mango orchards. Braz J Microbiol. 2016 Oct - Dec;47(4):1030-1038 Authors: Munaganti RK, Muvva V, Konda S, Naragani K, Mangamuri UK, Dorigondla KR, Akkewar DM Abstract An actinobacterial strain VL-RK_09 having potential antimicrobial activities was isolated from a mango orchard in Krishna District, Andhra Pradesh (India) and was identified as Arthrobacter kerguelensis. The strain A. kerguelensis VL-RK_09 exhibited a broad spectrum of in vitro antimicrobial activity against bacteria and fungi. Production of bioactive metabolites by the strain was the highest in modified yeast extract malt extract dextrose broth, as compared to other media tested. Lactose (1%) and peptone (0.5%) were found to be the most suitable carbon and nitrogen sources, respectively, for the optimum production of the bioactive metabolites. The maximum production of the bioactive metabolites was detected in the culture medium with an initial pH of 7, in which the strain was incubated for five days at 30°C under shaking conditions. Screening of secondary metabolites obtained from the culture broth led to the isolation of a compound active against a wide variety of Gram-positive and negative bacteria and fungi. The structure of the first active fraction was elucidated using Fourier transform infrared spectroscopy, electrospray ionization mass spectrometry, (1)H and (13)C nuclear magnetic resonance spectroscopy. The compound was identified as S,S-dipropyl carbonodithioate. This study is the first report of the occurrence of this compound in the genus Arthrobacter. PMID: 27515463 [PubMed - indexed for MEDLINE]

Related Articles Ligninolytic fungus Polyporus sp. S133 mediated metabolic degradation of fluorene. Braz J Microbiol. 2016 Jul-Sep;47(3):610-6 Authors: Lazim ZM, Hadibarata T Abstract This study aimed to investigate the impact of nonionic surfactants on the efficacy of fluorine degradation by Polyporus sp. S133 in a liquid culture. Fluorene was observed to be degraded in its entirety by Polyporus sp. S133 subsequent to a 23-day incubation period. The fastest cell growth rate was observed in the initial 7 days in the culture that was supplemented with Tween 80. The degradation process was primarily modulated by the activity of two ligninolytic enzymes, laccase and MnP. The highest laccase activity was stimulated by the addition of Tween 80 (2443U/L) followed by mixed surfactant (1766U/L) and Brij 35 (1655U/L). UV-vis spectroscopy, TLC analysis and mass spectrum analysis of samples subsequent to the degradation process in the culture medium confirmed the biotransformation of fluorene. Two metabolites, 9-fluorenol (λmax 270, tR 8.0min and m/z 254) and protocatechuic acid (λmax 260, tR 11.3min and m/z 370), were identified in the treated medium. PMID: 27287336 [PubMed - indexed for MEDLINE]

Related Articles Dual Roles of 17-β Estradiol in Estrogen Receptor-dependent Growth Inhibition in Renal Cell Carcinoma. Cancer Genomics Proteomics. 2016 May-Jun;13(3):219-30 Authors: Chen KC, Lin CM, Huang CJ, Chen SK, Wu ST, Chiang HS, Ku WC Abstract BACKGROUND: It has been proposed that 17-β-estradiol (E2) activates estrogen receptor and inhibits renal cell carcinoma (RCC) growth. In the present study we explored the role of E2 and ER in the regulation of RCC growth. MATERIALS AND METHODS: The RCC cell line ACHN was treated by E2 combining with E2 antagonist Fulvestrant or ER knockdown, and cell growth was monitored. Quantitative phosphoproteomics was applied to study the E2 regulated non-genomic phosphorylation changes. Western blotting, immunofluorescence microscopy, and apoptosis assays were used for validation. RESULTS: E2 induced ER-dependent growth inhibition in RCC cell lines. Quantitative phosphoproteomics revealed that E2 induced both apoptosis and autophagy. Cellular apoptosis was confirmed by altered mitochondrial membrane potential, and ER-dependent autophagosome formation was also found. CONCLUSION: Our data revealed the potential dual roles of E2 in regulating RCC growth via autophagy and apoptosis pathways. PMID: 27107064 [PubMed - indexed for MEDLINE]

Related Articles Metabonomic characteristics and biomarker research of human lung cancer tissues by HR1H NMR spectroscopy. Cancer Biomark. 2016 Mar 18;16(4):653-64 Authors: Chen W, Lu S, Ou J, Wang G, Zu Y, Chen F, Bai C Abstract BACKGROUND: The combination of NMR spectroscopy and multivariate data analysis (MVDA), such as orthogonal partial least squares-discriminant analysis (OPLS-DA), has been collectively acknowledged as an excellent tool to investigate tissue metabolism and provide metabolite information for the diagnosis of disease, and become an important metabonomic platform for studies in biological tissues so far. METHODS: Both ex vivo high resolution magic-angle spinning1H NMR and in vitro1H NMR spectroscopy technique were synchronously employed to analyze the metabonomic characteristics of 102 lung tissues from 34 patients with lung cancer in hope to identify potential diagnostic biomarkers for malignancy detection in lung tissues. RESULTS: Significant elevations in the levels of lipids and lactate and significant reductions in the levels of myo-inositol and valine in the cancer tissues had been identified when compared with the adjacent non-involved tissues. Furthermore, the OPLSDA models calculated by two1H NMR spectra provided for relatively high sensitivity, specificity and good prediction accuracy in the identification of class membership regardless of the number of metabolites involved. CONCLUSIONS: MVDA in combination with1H NMR spectra highlighted the potential of metabonomics in clinical settings so that the techniques might be further exploited for future lung cancer biomarker research or identification. PMID: 27002768 [PubMed - indexed for MEDLINE]

17 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 2017/01/18PubMed comprises more than millions of 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.

17 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 2017/01/17PubMed comprises more than millions of 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.

Related Articles Deep metabolome annotation in natural products research: towards a virtuous cycle in metabolite identification. Curr Opin Chem Biol. 2017 Jan 12;36:40-49 Authors: Allard PM, Genta-Jouve G, Wolfender JL Abstract Natural products (NPs) research is changing and rapidly adopting cutting-edge tools, which radically transform the way to characterize extracts and small molecules. With the innovations in metabolomics, early integration of deep metabolome annotation information allows to efficiently guide the isolation of valuable NPs only and, in parallel, to generate massive metadata sets for the study of given extracts under various perspectives. This is the case for chemotaxonomy studies where common biosynthetic traits among species can be evidenced, but also for drug discovery purpose where such traits, in combination with bioactivity studies on extracts, may evidence bioactive molecules even before their isolation. One of the major bottlenecks of such studies remains the level of accuracy at which NPs can be identified. We discuss here the advancements in LC-MS and associated mining methods by addressing what would be ideal and what is achieved today. We propose future developments for reinforcing generic NPs databases both in the spectral and structural dimensions by heading towards a virtuous metabolite identification cycle allowing annotation of both known and unreported metabolites in an iterative manner. Such approaches could significantly accelerate and improve our knowledge of the huge chemodiversity found in nature. PMID: 28088695 [PubMed - as supplied by publisher]

Related Articles Metabolic profiles of exudates from chronic leg ulcerations. J Pharm Biomed Anal. 2017 Jan 10;137:13-22 Authors: Junka A, Wojtowicz W, Ząbek A, Krasowski G, Smutnicka D, Bakalorz B, Boruta A, Dziadas M, Młynarz P, Sedghizadeh PP, Bartoszewicz M Abstract Chronic leg ulceration is a disease usually associated with other comorbidities, and significantly reduces patient quality of life. Infected leg ulcers can lead to limb-threatening sequelae or mortality. Leg ulcerations are colonized by a number of microbes that are able to cause life-threating infections in susceptible patients. Wound exudate is a body fluid that collects metabolites from patient eukaryotic cells and from prokaryotic bacterial communities inhabiting the wound. This study aimed at identification of metabolites in exudates collected from chronic leg ulcers, and correlation of this metabolome with patient comorbidities and microbiological status of the wound. By means of NMR spectroscopy we detected 42 metabolites of microbial or patient origin. The metabolites that were in abundance in exudates analyzed were lactate, lysine, and leucine. Metabolites were associated with the presence of neutrophils in wounds and destruction of high quantities of microbes, but also with hypoxia typical for venous insufficiency. The combination of nuclear magnetic resonance spectroscopy technique and partial least squares discriminant analysis allowed us to further discriminate groups of metabolites with regards to potential clinical meaning. For example, to discriminate between S.aureus versus all other isolated microbial species, or between patients suffering from type I or II diabetes versus patients without diabetes. Therefore, wound exudate seems to be highly applicable material for discriminant analysis performed with the use of NMR technique to provide for rapid metabolomics of chronic wound status. PMID: 28088662 [PubMed - as supplied by publisher]

Related Articles Metabolomic analysis of urine samples by UHPLC-QTOF-MS: Impact of normalization strategies. Anal Chim Acta. 2017 Feb 22;955:27-35 Authors: Gagnebin Y, Tonoli D, Lescuyer P, Ponte B, de Seigneux S, Martin PY, Schappler J, Boccard J, Rudaz S Abstract Among the various biological matrices used in metabolomics, urine is a biofluid of major interest because of its non-invasive collection and its availability in large quantities. However, significant sources of variability in urine metabolomics based on UHPLC-MS are related to the analytical drift and variation of the sample concentration, thus requiring normalization. A sequential normalization strategy was developed to remove these detrimental effects, including: (i) pre-acquisition sample normalization by individual dilution factors to narrow the concentration range and to standardize the analytical conditions, (ii) post-acquisition data normalization by quality control-based robust LOESS signal correction (QC-RLSC) to correct for potential analytical drift, and (iii) post-acquisition data normalization by MS total useful signal (MSTUS) or probabilistic quotient normalization (PQN) to prevent the impact of concentration variability. This generic strategy was performed with urine samples from healthy individuals and was further implemented in the context of a clinical study to detect alterations in urine metabolomic profiles due to kidney failure. In the case of kidney failure, the relation between creatinine/osmolality and the sample concentration is modified, and relying only on these measurements for normalization could be highly detrimental. The sequential normalization strategy was demonstrated to significantly improve patient stratification by decreasing the unwanted variability and thus enhancing data quality. PMID: 28088278 [PubMed - in process]

CHALLENGES IN DETECTING SUBSTANCES FOR EQUINE ANTI-DOPING. Drug Test Anal. 2017 Jan 14;: Authors: Fragkaki AG, Kioukia-Fougia N, Kiousi P, Kioussi M, Tsivou M Abstract The artificial increase of the physical capability of horses using drugs is well-known in racing and in other equine sports. Both illicit and therapeutic substances are regarded as prohibited substances in competition in most countries. Some countries do make distinctions for a few, specific drugs which are, however, allowed for use in other countries. The primary objective in the case of doping control is the detection of any trace of drug exposure, either parent drug or any of its metabolites, using the most powerful analytical methods which generally are based on chromatographic/mass spectrometric techniques. Major concern in horseracing is the absence of a single organization regulating the anti-doping framework; instead of this, individual racing authorities provide rules and regulations often resulting in variations in the applied doping control programs of different countries. The aim of this paper is the review of the recent literature (approximately from 2012 to mid-2016) in order to highlight the numerous and diverse challenges faced in the doping control of the racing and equestrian sports, including the detection of designer drugs (anabolic steroids or stimulants) and of other emerging prohibited substances, such as peptides and noble gases in horses urine and plasma. Moreover, the application of "omics" techniques (especially of metabolomics) deserves attention for establishing possible fingerprints of drug abuse as well as the evolution of instrumental analysis resulting a powerful ally in the fight against doping in equine sports. PMID: 28087984 [PubMed - as supplied by publisher]

Related Articles Defining genetic and chemical diversity in wheat grain by 1H-NMR spectroscopy of polar metabolites. Mol Nutr Food Res. 2017 Jan 13;: Authors: Shewry PR, Corol DI, Jones HD, Beale MH, Ward JL Abstract SCOPE: The application of high throughput 1H-NMR of unpurified extracts to determine to determine genetic diversity and the contents of polar components in grain of wheat. METHODS AND RESULTS: milled whole wheat grain was extracted with 80:20 D2O:CD3OD containing 0.05% d4- trimethylsilylpropionate (TSP). 1H-NMR spectra were acquired under automation at 300 °K using an Avance Spectrometer operating at 600.0528 MHz. Regions for individual metabolites were identified by comparison to a library of known standards run under identical conditions. The individual 1H-NMR peaks or levels of known metabolites were then compared by Principal Component Analysis using SIMCA-P software. CONCLUSIONS: high throughput 1H-NMR is an excellent tool to compare the extent of genetic diversity within and between wheat species, and to quantify specific components (including glycine betaine, choline and asparagine) in individual genotypes. It can also be used to monitor changes in composition related environmental factors and to support comparisons of the substantial equivalence of transgenic lines. This article is protected by copyright. All rights reserved. PMID: 28087883 [PubMed - as supplied by publisher]

Related Articles Production of N-acyl homoserine lactones by the sponge-associated marine actinobacteria Salinispora arenicola and Salinispora pacifica. FEMS Microbiol Lett. 2017 Jan 12;: Authors: Bose U, Ortori CA, Sarmad S, Barrett DA, Hewavitharana AK, Hodson MP, Fuerst JA, Shaw PN Abstract The structures of acyl homoserine lactone (AHL) compounds and their quantification was accomplished using an integrated liquid chromatography-mass spectrometry approach. The precursor and product ions, along with retention times of peaks, were searched against an in-house database of AHLs and structures confirmed by accurate mass and by comparison with authentic AHL standards. The two compounds, N-(3-oxodecanoyl)-L-homoserine lactone and N-(3-oxododecanoyl)-L-homoserine lactone were characterised and quantified in Salinispora sp. cultures. PMID: 28087611 [PubMed - as supplied by publisher]

Related Articles Nicotiana attenuata Data Hub (NaDH): an integrative platform for exploring genomic, transcriptomic and metabolomic data in wild tobacco. BMC Genomics. 2017 Jan 13;18(1):79 Authors: Brockmöller T, Ling Z, Li D, Gaquerel E, Baldwin IT, Xu S Abstract BACKGROUND: Nicotiana attenuata (coyote tobacco) is an ecological model for studying plant-environment interactions and plant gene function under real-world conditions. During the last decade, large amounts of genomic, transcriptomic and metabolomic data have been generated with this plant which has provided new insights into how native plants interact with herbivores, pollinators and microbes. However, an integrative and open access platform that allows for the efficient mining of these -omics data remained unavailable until now. DESCRIPTION: We present the Nicotiana attenuata Data Hub (NaDH) as a centralized platform for integrating and visualizing genomic, phylogenomic, transcriptomic and metabolomic data in N. attenuata. The NaDH currently hosts collections of predicted protein coding sequences of 11 plant species, including two recently sequenced Nicotiana species, and their functional annotations, 222 microarray datasets from 10 different experiments, a transcriptomic atlas based on 20 RNA-seq expression profiles and a metabolomic atlas based on 895 metabolite spectra analyzed by mass spectrometry. We implemented several visualization tools, including a modified version of the Electronic Fluorescent Pictograph (eFP) browser, co-expression networks and the Interactive Tree Of Life (iTOL) for studying gene expression divergence among duplicated homologous. In addition, the NaDH allows researchers to query phylogenetic trees of 16,305 gene families and provides tools for analyzing their evolutionary history. Furthermore, we also implemented tools to identify co-expressed genes and metabolites, which can be used for predicting the functions of genes. Using the transcription factor NaMYB8 as an example, we illustrate that the tools and data in NaDH can facilitate identification of candidate genes involved in the biosynthesis of specialized metabolites. CONCLUSION: The NaDH provides interactive visualization and data analysis tools that integrate the expression and evolutionary history of genes in Nicotiana, which can facilitate rapid gene discovery and comparative genomic analysis. Because N. attenuata shares many genome-wide features with other Nicotiana species including cultivated tobacco, and hence NaDH can be a resource for exploring the function and evolution of genes in Nicotiana species in general. The NaDH can be accessed at: http://nadh.ice.mpg.de/ . PMID: 28086860 [PubMed - in process]

Related Articles Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke. BMC Neurosci. 2017 Jan 13;18(1):13 Authors: Jiménez-Xarrié E, Davila M, Candiota AP, Delgado-Mederos R, Ortega-Martorell S, Julià-Sapé M, Arús C, Martí-Fàbregas J Abstract BACKGROUND: Magnetic resonance spectroscopy (MRS) provides non-invasive information about the metabolic pattern of the brain parenchyma in vivo. The SpectraClassifier software performs MRS pattern-recognition by determining the spectral features (metabolites) which can be used objectively to classify spectra. Our aim was to develop an Infarct Evolution Classifier and a Brain Regions Classifier in a rat model of focal ischemic stroke using SpectraClassifier. RESULTS: A total of 164 single-voxel proton spectra obtained with a 7 Tesla magnet at an echo time of 12 ms from non-infarcted parenchyma, subventricular zones and infarcted parenchyma were analyzed with SpectraClassifier ( http://gabrmn.uab.es/?q=sc ). The spectra corresponded to Sprague-Dawley rats (healthy rats, n = 7) and stroke rats at day 1 post-stroke (acute phase, n = 6 rats) and at days 7 ± 1 post-stroke (subacute phase, n = 14). In the Infarct Evolution Classifier, spectral features contributed by lactate + mobile lipids (1.33 ppm), total creatine (3.05 ppm) and mobile lipids (0.85 ppm) distinguished among non-infarcted parenchyma (100% sensitivity and 100% specificity), acute phase of infarct (100% sensitivity and 95% specificity) and subacute phase of infarct (78% sensitivity and 100% specificity). In the Brain Regions Classifier, spectral features contributed by myoinositol (3.62 ppm) and total creatine (3.04/3.05 ppm) distinguished among infarcted parenchyma (100% sensitivity and 98% specificity), non-infarcted parenchyma (84% sensitivity and 84% specificity) and subventricular zones (76% sensitivity and 93% specificity). CONCLUSION: SpectraClassifier identified candidate biomarkers for infarct evolution (mobile lipids accumulation) and different brain regions (myoinositol content). PMID: 28086802 [PubMed - in process]

17 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 2017/01/14PubMed comprises more than millions of 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.