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  • Serum metabolomics reveals metabolic profiling for women with hyperandrogenism and insulin resistance in polycystic ovary syndrome
    Metabolomics (IF 3.167) Pub Date : 2020-01-24
    Zhihao Zhang, Yanli Hong, Minmin Chen, Ninghua Tan, Shijia Liu, Xiaowei Nie, Wei Zhou

    Abstract Introduction Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder. Hyperandrogenism (HA) and insulin resistance (IR) are two important pathogenic factors. Objective We aimed to investigate the inherent disturbed metabolic profiles for women with HA or IR in PCOS as well as discover diagnostic biomarkers. Methods A total of 286 subjects were recruited for the study. They constituted the following groups: healthy women (C), those with HA (B1), those with IR but not obese (B2) and obese women with IR (B3) in PCOS. Nine cross-comparisons with PCOS were performed to characterize metabolic disturbances. Serum metabolomic profiles were determined by gas chromatography–mass spectrometry. Results and conclusion We found a total of 59 differential metabolites. 28 metabolites for B1 vs C, 32 for B2 vs C and 25 for B3 vs C were discovered. Among them, palmitic acid, cholesterol, myo-inositol, d-allose, 1,5-anhydro-d-sorbitol, 1-monopalmitin, 1-monostearin, glycerol 1-phosphate, malic acid and citric acid, were the common differential metabolites among B1 vs C, B2 vs C and B3 vs C, which related to biosynthesis of unsaturated fatty acids, citrate cycle etc. Besides, 9-biomarker panel can diagnose well between HA and IR in PCOS. They provided areas under the receiver operating characteristic curve of 0.8511 to 1.000 in the discovery phase, and predictive values of 90% to 92% in the validation set. The result indicated that the differential metabolites can reflect the underlying mechanism of PCOS and serve as biomarkers for complementary diagnosis of HA and IR in PCOS.

    更新日期:2020-01-24
  • Extracellular volatilomic alterations induced by hypoxia in breast cancer cells
    Metabolomics (IF 3.167) Pub Date : 2020-01-24
    Ravindra Taware, Khushman Taunk, Totakura V. S. Kumar, Jorge A. M. Pereira, José S. Câmara, H. A. Nagarajaram, Gopal C. Kundu, Srikanth Rapole

    Abstract Introduction The metabolic shift induced by hypoxia in cancer cells has not been explored at volatilomic level so far. The volatile organic metabolites (VOMs) constitute an important part of the metabolome and their investigation could provide us crucial aspects of hypoxia driven metabolic reconfiguration in cancer cells. Objective To identify the altered volatilomic response induced by hypoxia in metastatic/aggressive breast cancer (BC) cells. Methods BC cells were cultured under normoxic and hypoxic conditions and VOMs were extracted using HS-SPME approach and profiled by standard GC–MS system. Univariate and multivariate statistical approaches (p < 0.05, Log2 FC ≥ 0.58/≤ − 0.58, PC1 > 0.13/< − 0.13) were applied to select the VOMs differentially altered after hypoxic treatment. Metabolic pathway analysis was also carried out in order to identify altered metabolic pathways induced by the hypoxia in the selected BC cells. Results Overall, 20 VOMs were found to be significantly altered (p < 0.05, PC1 > 0.13/< − 0.13) upon hypoxic exposure to BC cells. Further, cell line specific volatilomic alterations were extracted by comparative metabolic analysis of aggressive (MDA-MB-231) vs. non-aggressive (MCF-7) cells incubated under hypoxia and normoxia. In this case, 15 and 12 VOMs each were found to be significantly altered in aggressive cells when exposed to hypoxic and normoxic condition respectively. Out of these, 9 VOMs were found to be uniquely associated with hypoxia, 6 were specific to normoxia and 6 were found common to both the conditions. Formic acid was identified as the most prominent molecule with higher abundance levels in aggressive as compared to non-aggressive cells in both conditions. Furthermore, metabolic pathway analyses revealed that fatty acid biosynthesis and nicotinate and nicotinamide metabolism were significantly altered in aggressive as compared to non-aggressive cells in normoxia and hypoxia respectively. Conclusions Higher formate overflow was observed in aggressive cells compared to non-aggressive cells incubated under both the conditions, reinforcing its correlation with aggressive and invasive cancer type. Moreover, under hypoxia, aggressive cells preferred to be bioenergetically more efficient whereas, under normoxia, fatty acid biosynthesis was favoured when compared to non-aggressive cells. Graphic Abstract

    更新日期:2020-01-24
  • Association between phospholipid metabolism in plasma and spontaneous preterm birth: a discovery lipidomic analysis in the cork pregnancy cohort
    Metabolomics (IF 3.167) Pub Date : 2020-01-24
    Aude-Claire Morillon, Shirish Yakkundi, Gregoire Thomas, Lee A. Gethings, James I. Langridge, Philip N. Baker, Louise C. Kenny, Jane A. English, Fergus P. McCarthy

    Abstract Introduction Preterm birth (PTB) is defined as birth occurring before 37 weeks’ gestation, affects 5–9% of all pregnancies in developed countries, and is the leading cause of perinatal mortality. Spontaneous preterm birth (sPTB) accounts for 31–50% of all PTB, but the underlying pathophysiology is poorly understood. Objective This study aimed to decipher the lipidomics pathways involved in pathophysiology of sPTB. Methods Blood samples were taken from SCreening fOr Pregnancy Endpoints (SCOPE), an international study that recruited 5628 nulliparous women, with a singleton low-risk pregnancy. Our analysis focused on plasma from SCOPE in Cork. Discovery profiling of the samples was undertaken using liquid chromatography-mass spectrometry Lipidomics, and features significantly altered between sPTB (n = 16) and Control (n = 32) groups were identified using empirical Bayes testing, adjusting for multiple comparisons. Results Twenty-six lipids showed lower levels in plasma of sPTB compared to controls (adjusted p < 0.05), including 20 glycerophospholipids (12 phosphatidylcholines, 7 phosphatidylethanolamines, 1 phosphatidylinositol) and 6 sphingolipids (2 ceramides and 4 sphingomyelines). In addition, a diaglyceride, DG (34:4), was detected in higher levels in sPTB compared to controls. Conclusions We report reduced levels of plasma phospholipids in sPTB. Phospholipid integrity is linked to biological membrane stability and inflammation, while storage and breakdown of lipids have previously been implicated in pregnancy complications. The contribution of phospholipids to sPTB as a cause or effect is still unclear; however, our results of differential plasma phospholipid expression represent another step in advancing our understanding of the aetiology of sPTB. Further work is needed to validate these findings in independent pregnancy cohorts.

    更新日期:2020-01-24
  • LC–MS untargeted approach showed that methyl jasmonate application on Vitis labrusca L. grapes increases phenolics at subtropical Brazilian regions
    Metabolomics (IF 3.167) Pub Date : 2020-01-23
    Laís Moro, Alessio Da Ros, Renata Vieira da Mota, Eduardo Purgatto, Fulvio Mattivi, Panagiotis Arapitsas

    Abstract Introduction Vitis labrusca L. grapes are largely cultivated in Brazil, but the tropical climate negatively affects the phenols content, especially anthocyanin. According to the projections of the incoming climatic changes, the climate of several viticulture zone might change to tropical. Therefore, researches are focusing on increasing grape phenols content; with methyl jasmonate application (MeJa) is considered a good alternative. Objectives The aim was to investigate with an untargeted approach the metabolic changes caused by the MeJa pre-harvest application on two Vitis labrusca L. cultivars grapes, both of them grown in two Brazilian regions. Methods Isabel Precoce and Concord grapes cultivated under subtropical climate, in the south and southeast of Brazil, received MeJa pre-harvest treatment. Grape metabolome was extracted and analyzed with a MS based metabolomics protocol by UPLC-HRMS-QTOF. Results Unsupervised data analysis revealed a clear separation between the two regions and the two cultivars, while supervised data analysis revealed biomarkers between the MeJa treatment group and the control group. Among the metabolites positively affected by MeJa were (a) flavonoids with a high degree of methylation at the B-ring (malvidin and peonidin derivatives and isorhamentin) for Isabel Precoce grapes; (b) glucosides of hydroxycinnamates, gallocatechin, epigallocatechin and cis-piceid for Concord grapes; and (c) hydroxycinnamates esters with tartaric acid, and procyanidins for the Southeast region grapes. Conclusion These results suggest that MeJa can be used as elicitor to secondary metabolism in grapes grown even under subtropical climate, affecting phenolic biosynthesis.

    更新日期:2020-01-23
  • Migrating from partial least squares discriminant analysis to artificial neural networks: a comparison of functionally equivalent visualisation and feature contribution tools using jupyter notebooks
    Metabolomics (IF 3.167) Pub Date : 2020-01-21
    Kevin M. Mendez, David I. Broadhurst, Stacey N. Reinke

    Abstract Introduction Metabolomics data is commonly modelled multivariately using partial least squares discriminant analysis (PLS-DA). Its success is primarily due to ease of interpretation, through projection to latent structures, and transparent assessment of feature importance using regression coefficients and Variable Importance in Projection scores. In recent years several non-linear machine learning (ML) methods have grown in popularity but with limited uptake essentially due to convoluted optimisation and interpretation. Artificial neural networks (ANNs) are a non-linear projection-based ML method that share a structural equivalence with PLS, and as such should be amenable to equivalent optimisation and interpretation methods. Objectives We hypothesise that standardised optimisation, visualisation, evaluation and statistical inference techniques commonly used by metabolomics researchers for PLS-DA can be migrated to a non-linear, single hidden layer, ANN. Methods We compared a standardised optimisation, visualisation, evaluation and statistical inference techniques workflow for PLS with the proposed ANN workflow. Both workflows were implemented in the Python programming language. All code and results have been made publicly available as Jupyter notebooks on GitHub. Results The migration of the PLS workflow to a non-linear, single hidden layer, ANN was successful. There was a similarity in significant metabolites determined using PLS model coefficients and ANN Connection Weight Approach. Conclusion We have shown that it is possible to migrate the standardised PLS-DA workflow to simple non-linear ANNs. This result opens the door for more widespread use and to the investigation of transparent interpretation of more complex ANN architectures.

    更新日期:2020-01-22
  • Canine metabolomics advances
    Metabolomics (IF 3.167) Pub Date : 2020-01-18
    Graciela Carlos, Francisco Paulo dos Santos, Pedro Eduardo Fröehlich

    Abstract Introduction Canis lupus familiaris is a domestic dog and many owners consider their pets as a family member. Medical bills with dogs are overcame only by the health care received by humans. Medical care is constantly progressing, and so is veterinary care. Metabolomics is the ‘‘omic” technique aimed to the study of metabolome, low-molecular weight molecules, through biofluids or tissue samples. And it also allows to evaluate disease diagnosis and prognosis, therapeutic evaluation and toxicological studies. Objectives The goal of this paper is to review the current and potential applications of metabolomics in domestic dogs. Method ScienceDirect, Scopus, Reaxys and PubMed were searched for papers that performed canine metabolomics in any research area. Results We analysed 38 papers, published until April 2019 in canine metabolomics approach. Metabolomic research in dogs so far can be divided into three areas: (a) Metabolomics studies in veterinary science, such as improving pet dogs health and welfare. (b) Diet, breeds and species discrimination. (c) Use of dogs as animal model in different diseases and drug development (evaluation toxicity and effect). Conclusions The results of this review showed that interest in metabolomics is growing in veterinary research. Several canine diseases have been evaluated with some promise for potential biomarker and/or disease mechanism discovery. Because canine metabolomics is a relatively new area, the researches spread across different research areas and with few studies in each area.

    更新日期:2020-01-21
  • Sex-related differences in urinary immune-related metabolic profiling of alopecia areata patients
    Metabolomics (IF 3.167) Pub Date : 2020-01-16
    Yu Ra Lee, Haksoon Kim, Bark Lynn Lew, Woo Young Sim, Jeongae Lee, Han Bin Oh, Jongki Hong, Bong Chul Chung

    Abstract Introduction Alopecia areata is a well-known autoimmune disease affecting humans. Polyamines are closely associated with proliferation and inflammation, and steroid hormones are involved in immune responses. Additionally, bile acids play roles in immune homeostasis by activating various signaling pathways; however, the roles of these substances and their metabolites in alopecia areata remain unclear. Objectives In this study, we aimed to identify differences in metabolite levels in urine samples from patients with alopecia areata and healthy controls. Methods To assess polyamine, androgen, and bile acid concentrations, we performed high-performance liquid chromatography–tandem mass spectrometry. Results Our results showed that spermine and dehydroepiandrosterone levels differed significantly between male patients and controls, whereas ursodeoxycholic acid levels were significantly higher in female patients with alopecia areata than in controls. Conclusion Our findings suggested different urinary polyamine, androgen, and bile acid concentrations between alopecia areata patients and normal controls. Additionally, levels of endogenous substances varied according to sex, and this should be considered when developing appropriate treatments and diagnostic techniques. Our findings improve our understanding of polyamine, androgen, and bile acid profiles in patients with alopecia areata and highlight the need to consider sex-related differences.

    更新日期:2020-01-16
  • Anabolic androgenic steroids exert a selective remodeling of the plasma lipidome that mirrors the decrease of the de novo lipogenesis in the liver
    Metabolomics (IF 3.167) Pub Date : 2020-01-10
    David Balgoma, Sofia Zelleroth, Alfhild Grönbladh, Mathias Hallberg, Curt Pettersson, Mikael Hedeland

    The abuse of anabolic androgenic steroids (AASs) is a source of public concern because of their adverse effects. Supratherapeutic doses of AASs are known to be hepatotoxic and regulate the lipoproteins in plasma by modifying the metabolism of lipids in the liver, which is associated with metabolic diseases. However, the effect of AASs on the profile of lipids in plasma is unknown.

    更新日期:2020-01-10
  • Optimization of XCMS parameters for LC–MS metabolomics: an assessment of automated versus manual tuning and its effect on the final results
    Metabolomics (IF 3.167) Pub Date : 2020-01-10
    Oihane E. Albóniga, Oskar González, Rosa M. Alonso, Yun Xu, Royston Goodacre

    Several software packages containing diverse algorithms are available for processing Liquid Chromatography-Mass Spectrometry (LC–MS) chromatographic data and within these deconvolution packages different parameters settings can lead to different outcomes. XCMS is the most widely used peak picking and deconvolution software for metabolomics, but the parameter selection can be hard for inexpert users. To solve this issue, the automatic optimization tools such as Isotopologue Parameters Optimization (IPO) can be extremely helpful.

    更新日期:2020-01-10
  • The differential activation of metabolic pathways in leukemic cells depending on their genotype and micro-environmental stress
    Metabolomics (IF 3.167) Pub Date : 2020-01-10
    Caroline Lo Presti, Florence Fauvelle, Julie Mondet, Pascal Mossuz

    Abstract Introduction Acute myeloid leukemia (AML) is characterized by a set of malignant proliferations leading to an accumulation of blasts in the bone marrow and blood. The prognosis is pejorative due to the molecular complexity and pathways implicated in leukemogenesis. Objectives Our research was focused on comparing the metabolic profiles of leukemic cells in basal culture and deprivation conditions to investigate their behaviors under metabolic stress. Methods We performed untargeted metabolomics using 1H HRMAS-NMR. Five human leukemic cell lines—KG1, K562, HEL, HL60 and OCIAML3—were studied in the basal and nutrient deprivation states. A multivariate analysis of the metabolic profile was performed to find over- or under- expressed metabolites in the different cell lines, depending on the experimental conditions. Results In the basal state, each leukemic cell line exhibited a specific metabolic signature related to the diversity of AML subtypes represented and their phenotypes. When cultured in a serum-free medium, they showed quick metabolic adaptation and continued to proliferate and survive despite the lack of nutrients. Low apoptosis was observed. Increased phosphocholine and glutathione was a common feature of all the observed cell lines, with the maximum increase in these metabolites at 24 h of culture, suggesting the involvement of lipid metabolism and oxidative stress regulators in the survival mechanism developed by the leukemic cells. Conclusions Our study provides new insights into the metabolic mechanisms in leukemogenesis and suggests a hierarchy of metabolic pathways activated within leukemic cells, some dependent on their genotypes and others conserved among the subtypes but commonly induced under micro-environmental stress.

    更新日期:2020-01-10
  • DESI-MSI and METASPACE indicates lipid abnormalities and altered mitochondrial membrane components in diabetic renal proximal tubules
    Metabolomics (IF 3.167) Pub Date : 2020-01-10
    Guanshi Zhang, Jialing Zhang, Rachel J. DeHoog, Subramaniam Pennathur, Christopher R. Anderton, Manjeri A. Venkatachalam, Theodore Alexandrov, Livia S. Eberlin, Kumar Sharma

    Diabetic kidney disease (DKD) is the most prevalent complication in diabetic patients, which contributes to high morbidity and mortality. Urine and plasma metabolomics studies have been demonstrated to provide valuable insights for DKD. However, limited information on spatial distributions of metabolites in kidney tissues have been reported.

    更新日期:2020-01-10
  • Metabolomic profile overlap in prototypical autoimmune humoral disease: a comparison of myasthenia gravis and rheumatoid arthritis
    Metabolomics (IF 3.167) Pub Date : 2020-01-04
    Derrick Blackmore, Liang Li, Nan Wang, Walter Maksymowych, Elaine Yacyshyn, Zaeem A. Siddiqi

    Abstract Introduction Myasthenia gravis (MG) and rheumatoid arthritis (RA) are examples of antibody-mediated chronic, progressive autoimmune diseases. Phenotypically dissimilar, MG and RA share common immunological features. However, the immunometabolomic features common to humoral autoimmune diseases remain largely unexplored. Objectives The aim of this study was to reveal and illustrate the metabolomic profile overlap found between these two diseases and describe the immunometabolomic significance. Methods Metabolic analyses using acid- and dansyl-labelled was performed on serum from adult patients with seropositive MG (n = 46), RA (n = 23) and healthy controls (n = 49) presenting to the University of Alberta Hospital specialty clinics. Chemical isotope labelling liquid chromatography mass spectrometry (CIL LC–MS) methods were utilized to assess the serum metabolome in patients; 12C/13C-dansyl chloride (DnsCl) was used to label amine/phenol metabolites and 12C/13C-p-dimethylaminophenacyl bromide (DmPA) was used for carboxylic acids. Metabolites matching our criteria for significance were selected if they were present in both groups. Multivariate statistical analysis [including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA)] and biochemical pathway analysis was then conducted to gain understanding of the principal pathways involved in antibody-mediated pathogenesis. Results We found 20 metabolites dysregulated in both MG and RA when compared to healthy controls. Most prominently, observed changes were related to pathways associated with phenylalanine metabolism, tyrosine metabolism, ubiquinone and other terpenoid-quinone biosynthesis, and pyruvate metabolism. Conclusion From these results it is evident that many metabolites are common to humoral disease and exhibit significant immunometabolomic properties. This observation may lead to an enhanced understanding of the metabolic underpinnings common to antibody-mediated autoimmune disease. Further, contextualizing these findings within a larger clinical and systems biology context could provide new insights into the pathogenesis and management of these diseases.

    更新日期:2020-01-04
  • Metabolome response to anthropogenic contamination on microalgae: a review
    Metabolomics (IF 3.167) Pub Date : 2019-12-21
    Léa Gauthier, Juliette Tison-Rosebery, Soizic Morin, Nicolas Mazzella

    Microalgae play a key role in ecosystems and are widely used in ecological status assessment. Research focusing on such organisms is then well developed and essential. Anyway, approaches for a better comprehension of their metabolome’s response towards anthropogenic stressors are only emerging.

    更新日期:2019-12-21
  • Citrate NMR peak irreproducibility in blood samples after reacquisition of spectra
    Metabolomics (IF 3.167) Pub Date : 2019-12-19
    Munsoor A. Hanifa, Raluca G. Maltesen, Bodil S. Rasmussen, Katrine B. Buggeskov, Hanne B. Ravn, Martin Skott, Søren Nielsen, Jørgen Frøkiær, Troels Ring, Reinhard Wimmer

    Abstract Background In our metabolomics studies we have noticed that repeated NMR acquisition on the same sample can result in altered metabolite signal intensities. Aims To investigate the reproducibility of repeated NMR acquisition on selected metabolites in serum and plasma from two large human metabolomics studies. Methods Two peak regions for each metabolite were integrated and changes occurring after reacquisition were correlated. Results Integral changes were generally small, but serum citrate signals decreased significantly in some samples. Conclusions Several metabolite integrals were not reproducible in some of the repeated spectra. Following established protocols, randomising analysis order and biomarker validation are important.

    更新日期:2019-12-19
  • Cerebrospinal fluid lipidomics: effects of an intravenous triglyceride infusion and apoE status
    Metabolomics (IF 3.167) Pub Date : 2019-12-12
    Angela J. Hanson, William A. Banks, Lisa F. Bettcher, Robert Pepin, Daniel Raftery, Suzanne Craft

    High-fat diets increase risk for Alzheimer’s disease, but individuals with the risk gene APOE ε4 (E4) paradoxically have improved memory soon after high fat feeding. Little is known about how dietary lipids affect CNS lipids, especially in older adults.

    更新日期:2019-12-13
  • Statistical reporting of metabolomics data: experience from a high-throughput NMR platform and epidemiological applications
    Metabolomics (IF 3.167) Pub Date : 2019-12-10
    Stefan Mutter, Carrie Worden, Kara Paxton, Ville-Petteri Mäkinen

    Meta-analysis is the cornerstone of robust biomedical evidence.

    更新日期:2019-12-11
  • Machine learning distilled metabolite biomarkers for early stage renal injury
    Metabolomics (IF 3.167) Pub Date : 2019-12-05
    Yan Guo, Hui Yu, Danqian Chen, Ying-Yong Zhao

    With chronic kidney disease (CKD), kidney becomes damaged overtime and fails to clean blood. Around 15% of US adults have CKD and nine in ten adults with CKD do not know they have it.

    更新日期:2019-12-05
  • Common and distinct variation in data fusion of designed experimental data
    Metabolomics (IF 3.167) Pub Date : 2019-12-03
    Masoumeh Alinaghi, Hanne Christine Bertram, Anders Brunse, Age K. Smilde, Johan A. Westerhuis

    Integrative analysis of multiple data sets can provide complementary information about the studied biological system. However, data fusion of multiple biological data sets can be complicated as data sets might contain different sources of variation due to underlying experimental factors. Therefore, taking the experimental design of data sets into account could be of importance in data fusion concept.

    更新日期:2019-12-04
  • Serum lipidome analysis of healthy beagle dogs receiving different diets
    Metabolomics (IF 3.167) Pub Date : 2019-12-03
    Felicitas S. Boretti, Bo Burla, Jeremy Deuel, Liang Gao, Markus R. Wenk, Annette Liesegang, Nadja S. Sieber-Ruckstuhl

    Food and dietary ingredients have significant effects on metabolism and health.

    更新日期:2019-12-04
  • Correction to: Metabolomics profiles of patients with Wilson disease reveal a distinct metabolic signature
    Metabolomics (IF 3.167) Pub Date : 2019-12-03
    Gaurav V. Sarode, Kyoungmi Kim, Dorothy A. Kieffer, Noreene M. Shibata, Tomas Litwin, Anna Czlonkowska, Valentina Medici

    In the originally published version of this article, there was an error. The metabolomics platform used for the analysis is GC-TOF-MS, Gas Chromatography Time-of-Flight Mass Spectrometry and not Hydrophilic Interaction Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry as indicated in the original version.

    更新日期:2019-12-03
  • A laboratory approach for characterizing chronic fatigue: what does metabolomics tell us?
    Metabolomics (IF 3.167) Pub Date : 2019-11-27
    Elardus Erasmus, Shayne Mason, Mari van Reenen, Francois E. Steffens, B. Chris Vorster, Carolus J. Reinecke

    Manifestations of fatigue range from chronic fatigue up to a severe syndrome and myalgic encephalomyelitis. Fatigue grossly affects the functional status and quality of life of affected individuals, prompting the World Health Organization to recognize it as a chronic non-communicable condition.

    更新日期:2019-11-28
  • Untargeted analysis of plasma samples from pre-eclamptic women reveals polar and apolar changes in the metabolome
    Metabolomics (IF 3.167) Pub Date : 2019-11-27
    Katrin N. Sander, Dong-Hyun Kim, Catharine A. Ortori, Averil Y. Warren, Uchenna C. Anyanwagu, Daniel P. Hay, Fiona Broughton Pipkin, Raheela N. Khan, David A. Barrett

    Pre-eclampsia is a hypertensive gestational disorder that affects approximately 5% of all pregnancies.

    更新日期:2019-11-27
  • A model for determining cardiac mitochondrial substrate utilisation using stable 13 C-labelled metabolites
    Metabolomics (IF 3.167) Pub Date : 2019-11-26
    Ross T. Lindsay, Demetris Demetriou, Dominic Manetta-Jones, James A. West, Andrew J. Murray, Julian L. Griffin

    Relative oxidation of different metabolic substrates in the heart varies both physiologically and pathologically, in order to meet metabolic demands under different circumstances. 13C labelled substrates have become a key tool for studying substrate use—yet an accurate model is required to analyse the complex data produced as these substrates become incorporated into the Krebs cycle.

    更新日期:2019-11-27
  • Clinical and metabolomics analysis of hepatocellular carcinoma patients with diabetes mellitus
    Metabolomics (IF 3.167) Pub Date : 2019-11-26
    Hongping Xia, Jianxiang Chen, Karthik Sekar, Ming Shi, Tian Xie, Kam M. Hui

    Diabetes and cancer are among the most frequent causes of death worldwide. Recent epidemiological findings have indicated a link between diabetes and cancer in several organs, particularly the liver. A number of epidemiological studies have demonstrated that diabetes is an established independent risk factor for hepatocellular carcinoma (HCC). However, the metabolites connecting diabetes and HCC remains less well understood.

    更新日期:2019-11-27
  • An untargeted metabolomic approach reveals significant postharvest alterations in vitamin metabolism in response to LED irradiation in pak-choi ( Brassica campestris L. ssp. chinensis (L.) Makino var. communis Tsen et Lee)
    Metabolomics (IF 3.167) Pub Date : 2019-11-26
    Fuhui Zhou, Jinhua Zuo, Lipu Gao, Yuan Sui, Qing Wang, Aili Jiang, Junyan Shi

    The main objective of this study was to investigate the effect of low-level light emitting diode (LED) irradiation on the metabolite profile of pak-choi. A total of 633 different molecular features (MFs) were identified among sample groups (initial, dark-treated, light-treated) using an untargeted metabolomic approach. The identified metabolites were associated with 24 different metabolic pathways. Four of the pathways including carbon pool by folate, folate biosynthesis, thiamine metabolism, and glutathione metabolism, all of which are associated with vitamin biosynthesis, changed significantly. Metabolites in four of the pathways exhibited significant differences from the control in response to LED irradiation. Additionally, porphyrin and chlorophyll metabolism, as well as glucosinolate biosynthesis, riboflavin metabolism, and carotenoid biosynthesis were positively induced by LED irradiation. These results indicate that postharvest LED illumination represents a potential tool for modifying the metabolic profile of pak-choi to maintain quality and nutritional levels.

    更新日期:2019-11-27
  • The anti-inflammatory effects of formononetin and ononin on lipopolysaccharide-induced zebrafish models based on lipidomics and targeted transcriptomics
    Metabolomics (IF 3.167) Pub Date : 2019-11-25
    Liyu Luo, Junyi Zhou, Haiyu Zhao, Miaoxuan Fan, Wenyuan Gao

    Formononetin (MBHS) and its glycosylated derivative ononin (MBHG), as the major isoflavones, have exhibited the anti-inflammatory impacts on the lipopolysaccharide (LPS)-induced inflammation. Although various researches have focused on interpreting the pharmaceutical activities of MBHG and MBHS, the molecular mechanisms in zebrafish models are still unclear.

    更新日期:2019-11-26
  • Metabolomics facilitates the discovery of metabolic biomarkers and pathways for ischemic stroke: a systematic review
    Metabolomics (IF 3.167) Pub Date : 2019-11-21
    Chaofu Ke, Chen-Wei Pan, Yuxia Zhang, Xiaohong Zhu, Yonghong Zhang

    Ischemic stroke (IS) is a major contributor to the global disease burden, and effective biomarkers for IS management in clinical practice are urgently needed. Metabolomics can detect metabolites that are small enough to cross the blood–brain barrier in a high-throughput manner, and thus represents a powerful tool for discovering biomarkers of IS.

    更新日期:2019-11-22
  • Global metabolite profiles of rice brown planthopper-resistant traits reveal potential secondary metabolites for both constitutive and inducible defenses
    Metabolomics (IF 3.167) Pub Date : 2019-11-19
    Umaporn Uawisetwathana, Olivier P. Chevallier, Yun Xu, Wintai Kamolsukyeunyong, Intawat Nookaew, Thapakorn Somboon, Theerayut Toojinda, Apichart Vanavichit, Royston Goodacre, Christopher T. Elliott, Nitsara Karoonuthaisiri

    Brown planthopper (BPH) is a phloem feeding insect that causes annual disease outbreaks, called hopper burn in many countries throughout Asia, resulting in severe damage to rice production. Currently, mechanistic understanding of BPH resistance in rice plant is limited, which has caused slow progression on developing effective rice varieties as well as effective farming practices against BPH infestation.

    更新日期:2019-11-19
  • A comparative evaluation of the generalised predictive ability of eight machine learning algorithms across ten clinical metabolomics data sets for binary classification
    Metabolomics (IF 3.167) Pub Date : 2019-11-15
    Kevin M. Mendez, Stacey N. Reinke, David I. Broadhurst

    Metabolomics is increasingly being used in the clinical setting for disease diagnosis, prognosis and risk prediction. Machine learning algorithms are particularly important in the construction of multivariate metabolite prediction. Historically, partial least squares (PLS) regression has been the gold standard for binary classification. Nonlinear machine learning methods such as random forests (RF), kernel support vector machines (SVM) and artificial neural networks (ANN) may be more suited to modelling possible nonlinear metabolite covariance, and thus provide better predictive models.

    更新日期:2019-11-15
  • Novel associations between blood metabolites and kidney function among Bogalusa Heart Study and Multi-Ethnic Study of Atherosclerosis participants
    Metabolomics (IF 3.167) Pub Date : 2019-11-13
    Jovia L. Nierenberg, Jiang He, Changwei Li, Xiaoying Gu, Mengyao Shi, Alexander C. Razavi, Xuenan Mi, Shengxu Li, Lydia A. Bazzano, Amanda H. Anderson, Hua He, Wei Chen, Jason M. Kinchen, Casey M. Rebholz, Josef Coresh, Andrew S. Levey, Lesley A. Inker, Michael Shlipak, Tanika N. Kelly

    Chronic kidney disease (CKD) is a major public health challenge given its high global prevalence and associated risks of cardiovascular disease and progression to end stage renal disease. Although it is known that numerous metabolic changes occur in CKD patients, identifying novel metabolite associations with kidney function may enhance our understanding of the physiologic pathways relating to CKD.

    更新日期:2019-11-13
  • Clinical applications of breast cancer metabolomics using high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS): systematic scoping review
    Metabolomics (IF 3.167) Pub Date : 2019-11-06
    Almir G. V. Bitencourt, Johanna Goldberg, Katja Pinker, Sunitha B. Thakur

    Breast cancer is a heterogeneous disease with different prognoses and responses to systemic treatment depending on its molecular characteristics, which makes it imperative to develop new biomarkers for an individualized diagnosis and personalized oncological treatment. Ex vivo high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS) is the most common technique for metabolic quantification in human surgical and biopsy tissue specimens.

    更新日期:2019-11-06
  • A metabolic profile of routine needle biopsies identified tumor type specific metabolic signatures for breast cancer stratification: a pilot study
    Metabolomics (IF 3.167) Pub Date : 2019-11-04
    Narumi Harada-Shoji, Tomoyoshi Soga, Hiroshi Tada, Minoru Miyashita, Mutsuo Harada, Gou Watanabe, Yohei Hamanaka, Akiko Sato, Takashi Suzuki, Akihiko Suzuki, Takanori Ishida

    Metabolomics has recently emerged as a tool for understanding comprehensive tumor-associated metabolic dysregulation. However, only limited application of this technology has been introduced into the clinical setting of breast cancer.

    更新日期:2019-11-04
  • Metabolomic biomarkers in cervicovaginal fluid for detecting endometrial cancer through nuclear magnetic resonance spectroscopy
    Metabolomics (IF 3.167) Pub Date : 2019-10-29
    Shih-Chun Cheng, Kueian Chen, Chih-Yung Chiu, Kuan-Ying Lu, Hsin-Ying Lu, Meng-Han Chiang, Cheng-Kun Tsai, Chi-Jen Lo, Mei-Ling Cheng, Ting-Chang Chang, Gigin Lin

    Endometrial cancer (EC) is one of the most common gynecologic neoplasms in developed countries but lacks screening biomarkers.

    更新日期:2019-10-29
  • Urinary metabolomics reveals kynurenine pathway perturbation in newborns with transposition of great arteries after surgical repair
    Metabolomics (IF 3.167) Pub Date : 2019-10-28
    Manuela Simonato, Igor Fochi, Luca Vedovelli, Sonia Giambelluca, Cristiana Carollo, Massimo Padalino, Virgilio P. Carnielli, Paola Cogo

    Transposition of the great arteries (TGA) is a cyanotic congenital heart defect that requires surgical correction, with the use of cardiopulmonary-bypass (CPB), usually within 3 weeks of life. The use of CPB in open heart surgery results in brain hypoperfusion and in a powerful systemic inflammatory response and oxidative stress.

    更新日期:2019-10-28
  • Phenotyping reproductive stage chilling and frost tolerance in wheat using targeted metabolome and lipidome profiling
    Metabolomics (IF 3.167) Pub Date : 2019-10-20
    Bo Eng Cheong, William Wing Ho Ho, Ben Biddulph, Xiaomei Wallace, Tina Rathjen, Thusitha W. T. Rupasinghe, Ute Roessner, Rudy Dolferus

    Frost events lead to A$360 million of yield losses annually to the Australian wheat industry, making improvement of chilling and frost tolerance an important trait for breeding.

    更新日期:2019-10-21
  • Metabolomic identification of novel diagnostic biomarkers in ectopic pregnancy
    Metabolomics (IF 3.167) Pub Date : 2019-10-19
    Onur Turkoglu, Ayse Citil, Ceren Katar, Ismail Mert, Praveen Kumar, Ali Yilmaz, Dilek S. Uygur, Salim Erkaya, Stewart F. Graham, Ray O. Bahado-Singh

    Ectopic pregnancy (EP) is a potentially life-threatening condition and early diagnosis still remains a challenge, causing a delay in management leading to tubal rupture.

    更新日期:2019-10-19
  • The application of artificial neural networks in metabolomics: a historical perspective
    Metabolomics (IF 3.167) Pub Date : 2019-10-18
    Kevin M. Mendez, David I. Broadhurst, Stacey N. Reinke

    Metabolomics data, with its complex covariance structure, is typically modelled by projection-based machine learning (ML) methods such as partial least squares (PLS) regression, which project data into a latent structure. Biological data are often non-linear, so it is reasonable to hypothesize that metabolomics data may also have a non-linear latent structure, which in turn would be best modelled using non-linear equations. A non-linear ML method with a similar projection equation structure to PLS is artificial neural networks (ANNs). While ANNs were first applied to metabolic profiling data in the 1990s, the lack of community acceptance combined with limitations in computational capacity and the lack of volume of data for robust non-linear model optimisation inhibited their widespread use. Due to recent advances in computational power, modelling improvements, community acceptance, and the more demanding needs for data science, ANNs have made a recent resurgence in interest across research communities, including a small yet growing usage in metabolomics. As metabolomics experiments become more complex and start to be integrated with other omics data, there is potential for ANNs to become a viable alternative to linear projection methods.

    更新日期:2019-10-19
  • Post-periodontal surgery propounds early repair salivary biomarkers by 1 H NMR based metabolomics
    Metabolomics (IF 3.167) Pub Date : 2019-10-14
    Manvendra Pratap Singh, Mona Saxena, Charanjit S. Saimbi, Mohammed Haris Siddiqui, Raja Roy

    Oral microflora is a well-orchestrated and acts as a sequential defense mechanism for any infection related to oral disease. Chronic periodontitis is a disease of a microbial challenge to symbiosis and homeostasis. Periodontal surgery is the most promising cure with repair process during periodontal regeneration. It has an encouraging outcome in terms of early recovery biomarkers.

    更新日期:2019-10-14
  • Elevated serum ceramides are linked with obesity-associated gut dysbiosis and impaired glucose metabolism
    Metabolomics (IF 3.167) Pub Date : 2019-10-11
    Brandon D. Kayser, Edi Prifti, Marie Lhomme, Eugeni Belda, Maria-Carlota Dao, Judith Aron-Wisnewsky, MICRO-Obes Consortium, Anatol Kontush, Jean-Daniel Zucker, Salwa W. Rizkalla, Isabelle Dugail, Karine Clément

    Low gut microbiome richness is associated with dyslipidemia and insulin resistance, and ceramides and other sphingolipids are implicated in the development of diabetes.

    更新日期:2019-10-12
  • An LCMS-based untargeted metabolomics protocol for cochlear perilymph: highlighting metabolic effects of hydrogen gas on the inner ear of noise exposed Guinea pigs
    Metabolomics (IF 3.167) Pub Date : 2019-10-05
    Kristian Pirttilä, Pernilla Videhult Pierre, Jakob Haglöf, Mikael Engskog, Mikael Hedeland, Göran Laurell, Torbjörn Arvidsson, Curt Pettersson

    Noise-induced hearing loss (NIHL) is an increasing problem in society and accounts for a third of all cases of acquired hearing loss. NIHL is caused by formation of reactive oxygen species (ROS) in the cochlea causing oxidative stress. Hydrogen gas (H2) can alleviate the damage caused by oxidative stress and can be easily administered through inhalation.

    更新日期:2019-10-07
  • Diverse therapeutic efficacies and more diverse mechanisms of nicotinamide
    Metabolomics (IF 3.167) Pub Date : 2019-10-05
    Seon Beom Song, Jin Sung Park, Gu June Chung, In Hye Lee, Eun Seong Hwang

    Nicotinamide (NAM) is a form of vitamin B3 that, when administered at near-gram doses, has been shown or suggested to be therapeutically effective against many diseases and conditions. The target conditions are incredibly diverse ranging from skin disorders such as bullous pemphigoid to schizophrenia and depression and even AIDS. Similar diversity is expected for the underlying mechanisms. In a large portion of the conditions, NAM conversion to nicotinamide adenine dinucleotide (NAD+) may be a major factor in its efficacy. The augmentation of cellular NAD+ level not only modulates mitochondrial production of ATP and superoxide, but also activates many enzymes. Activated sirtuin proteins, a family of NAD+-dependent deacetylases, play important roles in many of NAM’s effects such as an increase in mitochondrial quality and cell viability countering neuronal damages and metabolic diseases. Meanwhile, certain observed effects are mediated by NAM itself. However, our understanding on the mechanisms of NAM’s effects is limited to those involving certain key proteins and may even be inaccurate in some proposed cases.

    更新日期:2019-10-07
  • Metabolomics: a search for biomarkers of visceral fat and liver fat content
    Metabolomics (IF 3.167) Pub Date : 2019-10-05
    Sebastiaan Boone, Dennis Mook-Kanamori, Frits Rosendaal, Martin den Heijer, Hildo Lamb, Albert de Roos, Saskia le Cessie, Ko Willems van Dijk, Renée de Mutsert

    Excess visceral and liver fat are known risk factors for cardiometabolic disorders. Metabolomics might allow for easier quantification of these ectopic fat depots, instead of using invasive and costly tools such as MRI or approximations such as waist circumference.

    更新日期:2019-10-07
  • Botanical metabolite ions extraction from full electrospray ionization mass spectrometry using high-dimensional penalized regression
    Metabolomics (IF 3.167) Pub Date : 2019-10-04
    Bety Rostandy, Xiaoli Gao

    Mass spectrometric data analysis of complex biological mixtures can be a challenge due to its vast datasets. There is lack of data treatment pipelines to analyze chemical signals versus noise. These tasks, so far, have been up to the discretion of the analysts.

    更新日期:2019-10-05
  • Impact of matrix effects and ionization efficiency in non-quantitative untargeted metabolomics
    Metabolomics (IF 3.167) Pub Date : 2019-10-04
    Casey A. Chamberlain, Vanessa Y. Rubio, Timothy J. Garrett

    LC–MS-based untargeted metabolomics has become increasingly popular due to the vast amount of information gained in a single analysis. Many studies utilize metabolomics to profile metabolic changes in various representative biofluids, tissues, or other sample types. Most analyses are performed measuring changes in the metabolic pool of a single biological matrix due to an altered phenotype, such as disease versus normal. Measurements in such experiments are typically highly reproducible with little variation due to analytical and technological advancements in mass spectrometry. With the expanded application of metabolomics into various non-analytical scientific disciplines, the emergence of studies comparing the signal intensities of specific analytes across different biological matrices (e.g. plasma vs. urine) is becoming more common, but the matrix effect between sample types is often neglected. Additionally, the practice of comparing the signal intensities of different analytes and correlating to relative abundance is also increasingly prevalent, but the response ratio between analytes due to differences in ionization efficiency is not always accounted for in data analysis. This report serves to communicate and raise awareness of these two well-recognized issues to prevent improper data interpretation in the field of metabolomics.

    更新日期:2019-10-04
  • Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data
    Metabolomics (IF 3.167) Pub Date : 2019-10-03
    Marion Brandolini-Bunlon, Mélanie Pétéra, Pierrette Gaudreau, Blandine Comte, Stéphanie Bougeard, Estelle Pujos-Guillot

    Metabolomics is a powerful phenotyping tool in nutrition and health research, generating complex data that need dedicated treatments to enrich knowledge of biological systems. In particular, to investigate relations between environmental factors, phenotypes and metabolism, discriminant statistical analyses are generally performed separately on metabolomic datasets, complemented by associations with metadata. Another relevant strategy is to simultaneously analyse thematic data blocks by a multi-block partial least squares discriminant analysis (MBPLSDA) allowing determining the importance of variables and blocks in discriminating groups of subjects, taking into account data structure.

    更新日期:2019-10-04
  • Predicting response to lisinopril in treating hypertension: a pilot study
    Metabolomics (IF 3.167) Pub Date : 2019-10-03
    Brandon J. Sonn, Jessica L. Saben, Glenn McWilliams, Shelby K. Shelton, Hania K. Flaten, Angelo D’Alessandro, Andrew A. Monte

    Only ~ 50% of hypertensive patients will respond to treatment.

    更新日期:2019-10-03
  • In vitro profiling of endothelial volatile organic compounds under resting and pro-inflammatory conditions
    Metabolomics (IF 3.167) Pub Date : 2019-10-03
    V. Longo, A. Forleo, S. Capone, E. Scoditti, M. A. Carluccio, P. Siciliano, M. Massaro

    The evaluation of volatile organic compounds(VOCs) emitted by human body offers a unique tool to set up new non-invasive devices for early diagnosis and long-lasting monitoring of most human diseases. However, their cellular origin and metabolic fate have not been completely elucidated yet, thus limiting their clinical application. Endothelium acts as an interface between blood and surrounding tissues. As such, it adapts its physiology in response to different environmental modifications thus playing a role in the pathogenesis of many metabolic and inflammatory diseases.

    更新日期:2019-10-03
  • Metabolomic analysis of Shiga toxin 2a-induced injury in conditionally immortalized glomerular endothelial cells
    Metabolomics (IF 3.167) Pub Date : 2019-10-01
    Christian Patry, Kathrin Plotnicki, Christian Betzen, Alba Perez Ortiz, Kirk L. Pappan, Simon C. Satchell, Peter W. Mathieson, Martina Bielaszewska, Helge Karch, Burkhard Tönshoff, Neysan Rafat

    Shiga toxin 2a (Stx2a) induces hemolytic uremic syndrome (STEC HUS) by targeting glomerular endothelial cells (GEC).

    更新日期:2019-10-02
  • Leaf metabolic signatures induced by real and simulated herbivory in black mustard ( Brassica nigra )
    Metabolomics (IF 3.167) Pub Date : 2019-09-28
    Stefano Papazian, Tristan Girdwood, Bernard A. Wessels, Erik H. Poelman, Marcel Dicke, Thomas Moritz, Benedicte R. Albrectsen

    The oxylipin methyl jasmonate (MeJA) is a plant hormone active in response signalling and defence against herbivores. Although MeJA is applied experimentally to mimic herbivory and induce plant defences, its downstream effects on the plant metabolome are largely uncharacterized, especially in the context of primary growth and tissue-specificity of the response.

    更新日期:2019-09-29
  • Compound danshen dripping pills normalize a reprogrammed metabolism of myocardial ischemia rats to interpret its time-dependent efficacy in clinic trials: a metabolomic study
    Metabolomics (IF 3.167) Pub Date : 2019-09-20
    Nan Aa, Jia-Hua Guo, Bei Cao, Run-Bin Sun, Xiao-Hui Ma, Yang Chu, Shui-Ping Zhou, Ji-Ye Aa, Zhi-Jian Yang, He Sun, Guang-Ji Wang

    Clinical trials of Compound danshen dripping pills (CDDP) indicated distinct improvement in patients with chronic stable angina. Daily fluctuation of therapeutic effect agreed with a peak-valley PK profile during a 4-week CDDP regimen, but stabilized after 8-week treatment.

    更新日期:2019-09-21
  • The omics approach to bee nutritional landscape
    Metabolomics (IF 3.167) Pub Date : 2019-09-20
    Priyadarshini Chakrabarti, Jeffery T. Morré, Hannah M. Lucas, Claudia S. Maier, Ramesh R. Sagili

    Significant annual honey bee colony losses have been reported in the USA and across the world over the past years. Malnutrition is one among several causative factors for such declines. Optimal nutrition serves as the first line of defense against multiple stressors such as parasites/pathogens and pesticides. Given the importance of nutrition, it is imperative to understand bee nutrition holistically, identifying dietary sources that may fulfill bee nutritional needs. Pollen is the primary source of protein for bees and is critical for brood rearing and colony growth. Currently, there is significant gap in knowledge regarding the chemical and nutritional composition of pollen.

    更新日期:2019-09-20
  • GC/MS based metabolite profiling of Indonesian specialty coffee from different species and geographical origin
    Metabolomics (IF 3.167) Pub Date : 2019-09-18
    Sastia Prama Putri, Tomoya Irifune, Yusianto, Eiichiro Fukusaki

    The consumption of high quality coffee such as specialty Arabica and fine Robusta coffee is increasing steadily in recent years. Development of single origin coffee is an important strategy to maintain coffee quality, grade and high cupping score. Indonesia is a top exporting country for Arabica coffee with high variety of specialty coffees from different origins. Despite its long standing reputation in global coffee market, very few is known about the variability among Indonesian specialty coffees.

    更新日期:2019-09-19
  • Toward collaborative open data science in metabolomics using Jupyter Notebooks and cloud computing
    Metabolomics (IF 3.167) Pub Date : 2019-09-14
    Kevin M. Mendez, Leighton Pritchard, Stacey N. Reinke, David I. Broadhurst

    A lack of transparency and reporting standards in the scientific community has led to increasing and widespread concerns relating to reproduction and integrity of results. As an omics science, which generates vast amounts of data and relies heavily on data science for deriving biological meaning, metabolomics is highly vulnerable to irreproducibility. The metabolomics community has made substantial efforts to align with FAIR data standards by promoting open data formats, data repositories, online spectral libraries, and metabolite databases. Open data analysis platforms also exist; however, they tend to be inflexible and rely on the user to adequately report their methods and results. To enable FAIR data science in metabolomics, methods and results need to be transparently disseminated in a manner that is rapid, reusable, and fully integrated with the published work. To ensure broad use within the community such a framework also needs to be inclusive and intuitive for both computational novices and experts alike.

    更新日期:2019-09-16
  • Metabolomics to reveal biomarkers and pathways of preterm birth: a systematic review and epidemiologic perspective
    Metabolomics (IF 3.167) Pub Date : 2019-09-10
    R. A. Carter, K. Pan, E. W. Harville, S. McRitchie, S. Sumner

    Most known risk factors for preterm birth, a leading cause of infant morbidity and mortality, are not modifiable. Advanced molecular techniques are increasingly being applied to identify biomarkers and pathways important in disease development and progression.

    更新日期:2019-09-10
  • Genome-wide association studies of 74 plasma metabolites of German shepherd dogs reveal two metabolites associated with genes encoding their enzymes
    Metabolomics (IF 3.167) Pub Date : 2019-09-06
    Pamela Xing Yi Soh, Juliana Maria Marin Cely, Sally-Anne Mortlock, Christopher James Jara, Rachel Booth, Siria Natera, Ute Roessner, Ben Crossett, Stuart Cordwell, Mehar Singh Khatkar, Peter Williamson

    German shepherd dogs (GSDs) are a popular breed affected by numerous disorders. Few studies have explored genetic variations that influence canine blood metabolite levels.

    更新日期:2019-09-06
  • Xenobiotics metabolization in Salix alba leaves uncovered by mass spectrometry imaging
    Metabolomics (IF 3.167) Pub Date : 2019-08-30
    Claire Villette, Loïc Maurer, Adrien Wanko, Dimitri Heintz

    Micropollutants are increasingly monitored as their presence in the environment is rising due to human activities, and they are potential threats to living organisms.

    更新日期:2019-08-30
  • Metabolic switches from quiescence to growth in synchronized Saccharomyces cerevisiae
    Metabolomics (IF 3.167) Pub Date : 2019-08-29
    Jinrui Zhang, Karla Martinez-Gomez, Elmar Heinzle, Sebastian Aljoscha Wahl

    The switch from quiescence (G0) into G1 and cell cycle progression critically depends on specific nutrients and metabolic capabilities. Conversely, metabolic networks are regulated by enzyme–metabolite interaction and transcriptional regulation that lead to flux modifications to support cell growth. How cells process and integrate environmental information into coordinated responses is challenging to analyse and not yet described quantitatively.

    更新日期:2019-08-29
  • Metabolomics by UHPLC–MS: benefits provided by complementary use of Q-TOF and QQQ for pathway profiling
    Metabolomics (IF 3.167) Pub Date : 2019-08-28
    Katrin Freiburghaus, Carlo Rodolfo Largiadèr, Christoph Stettler, Georg Martin Fiedler, Lia Bally, Cédric Bovet

    Non-targeted metabolic profiling using high-resolution mass spectrometry (HRMS) is a standard approach for pathway identification despite technical limitations.

    更新日期:2019-08-29
  • Metabolites profiling of date palm ( Phoenix dactylifera L.) commercial by-products (pits and pollen) in relation to its antioxidant effect: a multiplex approach of MS and NMR metabolomics
    Metabolomics (IF 3.167) Pub Date : 2019-08-27
    Asmaa M. Otify, Aly M. El-Sayed, Camilia G. Michel, Mohamed A. Farag

    Phoenix dactylifera L. (date palm) is one of the most valued crops worldwide for its economical and nutraceutical applications of its date fruit (pericarp). Currently date pits, considered as a waste product, is employed as coffee substitute post roasting. Whereas, pollen represents another valuable by-product used as a dietary supplement.

    更新日期:2019-08-27
  • Metabolome-based discrimination of chrysanthemum cultivars for the efficient generation of flower color variations in mutation breeding
    Metabolomics (IF 3.167) Pub Date : 2019-08-26
    Yuji Sawada, Muneo Sato, Mami Okamoto, Junichi Masuda, Satoshi Yamaki, Mitsuo Tamari, Yuki Tanokashira, Sanae Kishimoto, Akemi Ohmiya, Tomoko Abe, Masami Yokota Hirai

    The color variations of ornamental flowers are often generated by ion-beam and gamma irradiation mutagenesis. However, mutation rates differ significantly even among cultivars of the same species, resulting in high cost and intensive labor for flower color breeding.

    更新日期:2019-08-27
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