Publications
30 results found
Sands CJ, Gómez-Romero M, Correia G, et al., 2021, Representing the metabolome with high fidelity: range and response as quality control factors in LC-MS-based global profiling., Analytical Chemistry, Vol: 93, Pages: 1924-1933, ISSN: 0003-2700
Liquid chromatography-mass spectrometry (LC-MS) is a powerful and widely used technique for measuring the abundance of chemical species in living systems. Its sensitivity, analytical specificity, and direct applicability to biofluids and tissue extracts impart great promise for the discovery and mechanistic characterization of biomarker panels for disease detection, health monitoring, patient stratification, and treatment personalization. Global metabolic profiling applications yield complex data sets consisting of multiple feature measurements for each chemical species observed. While this multiplicity can be useful in deriving enhanced analytical specificity and chemical identities from LC-MS data, data set inflation and quantitative imprecision among related features is problematic for statistical analyses and interpretation. This Perspective provides a critical evaluation of global profiling data fidelity with respect to measurement linearity and the quantitative response variation observed among components of the spectra. These elements of data quality are widely overlooked in untargeted metabolomics yet essential for the generation of data that accurately reflect the metabolome. Advanced feature filtering informed by linear range estimation and analyte response factor assessment is advocated as an attainable means of controlling LC-MS data quality in global profiling studies and exemplified herein at both the feature and data set level.
Kurbatova N, Garg M, Whiley L, et al., 2020, Urinary metabolic phenotyping for Alzheimer's disease, Scientific Reports, Vol: 10, ISSN: 2045-2322
Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer’s Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer’s Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer’s Disease and age-matched controls, but also between individuals with Mild Cognitive Impairment who were later diagnosed with Alzheimer’s Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer’s pathology in previous studies.
Andreas NJ, Roy RB, Gomez-Romero M, et al., 2020, Performance of metabonomic serum analysis for diagnostics in paediatric tuberculosis, Scientific Reports, Vol: 10, Pages: 1-11, ISSN: 2045-2322
We applied a metabonomic strategy to identify host biomarkers in serum to diagnose paediatric tuberculosis (TB) disease. 112 symptomatic children with presumptive TB were recruited in The Gambia and classified as bacteriologically-confirmed TB, clinically diagnosed TB, or other diseases. Sera were analysed using 1H nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Multivariate data analysis was used to distinguish patients with TB from other diseases. Diagnostic accuracy was evaluated using Receiver Operating Characteristic (ROC) curves. Model performance was tested in a validation cohort of 36 children from the UK. Data acquired using 1H NMR demonstrated a sensitivity, specificity and Area Under the Curve (AUC) of 69% (95% confidence interval [CI], 56–73%), 83% (95% CI, 73–93%), and 0.78 respectively, and correctly classified 20% of the validation cohort from the UK. The most discriminatory MS data showed a sensitivity of 67% (95% CI, 60–71%), specificity of 86% (95% CI, 75–93%) and an AUC of 0.78, correctly classifying 83% of the validation cohort. Amongst children with presumptive TB, metabolic profiling of sera distinguished bacteriologically-confirmed and clinical TB from other diseases. This novel approach yielded a diagnostic performance for paediatric TB comparable to that of Xpert MTB/RIF and interferon gamma release assays.
Ovadia C, Perdones-Montero A, Spagou K, et al., 2019, Enhanced microbial bile acid deconjugation and impaired ileal uptake in pregnancy repress intestinal regulation of bile acid synthesis, Hepatology, Vol: 70, Pages: 276-293, ISSN: 0270-9139
Pregnancy is associated with progressive hypercholanemia, hypercholesterolemia and hypertriglyceridemia, which can result in metabolic disease in susceptible women. Gut signals modify hepatic homeostatic pathways, linking intestinal content to metabolic activity. We sought to identify whether enteric endocrine signals contribute to raised serum bile acids observed in human and murine pregnancies, by measuring fibroblast growth factor (FGF)19/15 protein and mRNA levels, and 7α-hydroxy-4-cholesten-3-one. Terminal ileal farnesoid X receptor(FXR)-mediated gene expression and apical sodium bile acid transporter (ASBT) protein concentration were measured by qPCR and western blotting. Shotgun whole genome sequencing and UPLC-MS were used to determine the cecal microbiome and metabonome. Targeted and untargeted pathway analyses were performed to predict the systemic effects of the altered metagenome and metabolite profiles. Dietary cholic acid supplementation was used to determine whether the observed alterations could be overcome by intestinal bile acids functioning as FXR agonists. Human and murine pregnancy were associated with reduced intestinal FXR signaling, with lower FGF19/15 and resultant increased hepatic bile acid synthesis. Terminal ileal ASBT protein was reduced in murine pregnancy. Cecal bile acid conjugation was reduced in pregnancy due to elevated bile salt hydrolase-producing Bacteroidetes. Cholic acid supplementation induced intestinal FXR signaling, which was not abrogated by pregnancy, with strikingly similar changes to the microbiota and metabonome as identified in pregnancy. CONCLUSION: the altered intestinal microbiota of pregnancy enhance bile acid deconjugation, reducing ileal bile acid uptake and lowering FXR induction in enterocytes. This exacerbates the effects mediated by reduced bile acid uptake transporters in pregnancy. Thus, in pregnant women and mice, there is reduced FGF19/15-mediated hepatic repression of hepatic bile acid synthesis
Gafson AR, Savva C, Thorne T, et al., 2019, Breaking the cycle: reversal of flux in the tricarboxylic acid cycle by dimethyl fumarate, Neurology, Neuroimmunology and Neuroinflammation, Vol: 6, ISSN: 2332-7812
ObjectiveTo infer possible molecular effectors of therapeutic effects and adverse events for the pro-drug dimethyl fumarate (DMF, Tecfidera) in the plasma of relapsing-remitting MS patients (RRMS) based on untargeted blood plasma metabolomics. MethodsBlood samples were collected from 27 RRMS patients at baseline and six weeks after initiation of treatment with DMF (BG-12; Tecfidera). Patients were separated into a discovery (n=15) and a validation cohort (n=12). Ten healthy controls were also recruited and blood samples were collected over the same time intervals. Untargeted metabolomic profiling using ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS) was performed on plasma samples from the discovery cohort and healthy controls at Metabolon Inc. (Durham, NC). UPLC-MS was then performed on samples from the validation cohort at the National Phenome Centre (Imperial College, UK). Plasma neurofilament concentration (NfL) was also assayed for all subjects using the Simoa platform (Quanterix, Lexington, MA). Time course and cross-sectional statistical analyses were performed to identify pharmacodynamic changes in the metabolome secondary to DMF and relate these to adverse events. Results In the discovery cohort, tricarboxylic acid (TCA) cycle intermediates fumarate and succinate and TCA cycle metabolites succinyl-carnitine and methyl succinyl-carnitine were increased 6-weeks after the start of treatment (q < 0.05). We confirmed that methyl succinyl carnitine was also increased in the validation cohort 6-weeks after the start of treatment (q < 0.05). Changes in concentrations of these metabolites were not seen over a similar time period in blood from the untreated healthy control population. Increased succinyl-carnitine and methyl succinyl-carnitine were associated with adverse events from DMF (flushing, abdominal symptoms. The mean plasma NfL concentration before treatment was higher in the RRMS patients than in the healthy contro
Izzi-Engbeaya CN, Comninos AN, Clarke S, et al., 2018, The effects of kisspeptin on β-cell function, serum metabolites and appetite in humans, Diabetes, Obesity and Metabolism, Vol: 20, Pages: 2800-2810, ISSN: 1462-8902
AimsTo investigate the effect of kisspeptin on glucose‐stimulated insulin secretion and appetite in humans.Materials and methodsIn 15 healthy men (age: 25.2 ± 1.1 years; BMI: 22.3 ± 0.5 kg m−2), we compared the effects of 1 nmol kg−1 h−1 kisspeptin versus vehicle administration on glucose‐stimulated insulin secretion, metabolites, gut hormones, appetite and food intake. In addition, we assessed the effect of kisspeptin on glucose‐stimulated insulin secretion in vitro in human pancreatic islets and a human β‐cell line (EndoC‐βH1 cells).ResultsKisspeptin administration to healthy men enhanced insulin secretion following an intravenous glucose load, and modulated serum metabolites. In keeping with this, kisspeptin increased glucose‐stimulated insulin secretion from human islets and a human pancreatic cell line in vitro. In addition, kisspeptin administration did not alter gut hormones, appetite or food intake in healthy men.ConclusionsCollectively, these data demonstrate for the first time a beneficial role for kisspeptin in insulin secretion in humans in vivo. This has important implications for our understanding of the links between reproduction and metabolism in humans, as well as for the ongoing translational development of kisspeptin‐based therapies for reproductive and potentially metabolic conditions.
Chekmeneva E, Dos Santos Correia G, Gomez Romero M, et al., 2018, Ultra performance liquid chromatography-high resolution mass spectrometry and direct infusion-high resolution mass spectrometry for combined exploratory and targeted metabolic profiling of human urine, Journal of Proteome Research, Vol: 17, Pages: 3492-3502, ISSN: 1535-3893
The application of metabolic phenotyping to epidemiological studies involving thousands of biofluid samples presents a challenge for the selection of analytical platforms that meet the requirements of high-throughput precision analysis and cost-effectiveness. Here, direct infusion nanoelectrospray (DI-nESI)- was compared to an ultra-performance (UPLC)-high resolution mass spectrometry (HRMS) method for metabolic profiling of an exemplary set of 132 human urine samples from a large epidemiological cohort. Both methods were developed and optimised to allow simultaneous collection of high resolution urinary metabolic profiles and quantitative data for a selected panel of 35 metabolites. The total run time for measuring the sample set in both polarities by UPLC-HRMS was of 5 days compared to 9 hours by DI-nESI-HRMS. To compare the classification ability of the two MS methods we performed exploratory analysis of the full-scan HRMS profiles to detect sex-related differences in biochemical composition. Although metabolite identification is less specific in DI-nESI-HRMS, the significant features responsible for discrimination between sexes were mostly the same in both MS-based platforms. Using the quantitative data we showed that 10 metabolites have strong correlation (Pearson’s r > 0.9 and Passing-Bablok regression slope 0.8-1.3) and good agreement assessed by Bland-Altman plots between UPLC-HRMS and DI-nESI-HRMS and thus, can be measured using a cheaper and less sample- and time-consuming method. Only five metabolites showed weak correlation (Pearson’s r< 0.4) and poor agreement due to the overestimation of the results by DI-nESI-HRMS, and the rest of metabolites showed acceptable correlation between the two methods.
Puthucheary ZA, Astin R, Mcphail MJW, et al., 2018, Metabolic phenotype of skeletal muscle in early critical illness, THORAX, Vol: 73, Pages: 926-935, ISSN: 0040-6376
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- Citations: 84
Domingo-Almenara X, Montenegro-Burke JR, Ivanisevic J, et al., 2018, CMS-MRM and METLIN-MRM: a cloud library and public resource for targeted analysis of small molecules, Nature Methods, Vol: 15, Pages: 681-684, ISSN: 1548-7091
We report XCMS-MRM and METLIN-MRM (http://xcmsonline-mrm.scripps.edu/ and http://metlin.scripps.edu/), a cloud-based data-analysis platform and a public multiple-reaction monitoring (MRM) transition repository for small-molecule quantitative tandem mass spectrometry. This platform provides MRM transitions for more than 15,500 molecules and facilitates data sharing across different instruments and laboratories.
Ouchemoukh S, Amessis-Ouchemoukh N, Gomez-Romero M, et al., 2017, Characterisation of phenolic compounds in Algerian honeys by RP-HPLC coupled to electrospray time-of-flight mass spectrometry, LWT-FOOD SCIENCE AND TECHNOLOGY, Vol: 85, Pages: 460-469, ISSN: 0023-6438
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- Citations: 30
Bajoub A, Medina-Rodriguez S, Gomez-Romero M, et al., 2017, Assessing the varietal origin of extra-virgin olive oil using liquid chromatography fingerprints of phenolic compound, data fusion and chemometrics, FOOD CHEMISTRY, Vol: 215, Pages: 245-255, ISSN: 0308-8146
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- Citations: 79
Kim JU, Shariff MI, Crossey MM, et al., 2016, Hepatocellular carcinoma: Review of disease and tumor biomarkers., World Journal of Hepatology, Vol: 8, Pages: 471-484, ISSN: 1948-5182
Hepatocellular carcinoma (HCC) is a common malignancy and now the second commonest global cause of cancer death. HCC tumorigenesis is relatively silent and patients experience late symptomatic presentation. As the option for curative treatments is limited to early stage cancers, diagnosis in non-symptomatic individuals is crucial. International guidelines advise regular surveillance of high-risk populations but the current tools lack sufficient sensitivity for early stage tumors on the background of a cirrhotic nodular liver. A number of novel biomarkers have now been suggested in the literature, which may reinforce the current surveillance methods. In addition, recent metabonomic and proteomic discoveries have established specific metabolite expressions in HCC, according to Warburg's phenomenon of altered energy metabolism. With clinical validation, a simple and non-invasive test from the serum or urine may be performed to diagnose HCC, particularly benefiting low resource regions where the burden of HCC is highest.
McPhail MJW, Shawcross D, Lewis MR, et al., 2016, Mutlivariate metabotyping of plasma accurately predicts survival in decompensated cirrhosis, Journal of Hepatology, Vol: 64, Pages: 1058-1067, ISSN: 1600-0641
Background & AimsPredicting survival in decompensated cirrhosis (DC) is important in decision making for liver transplantation and resource allocation. We investigated whether high-resolution metabolic profiling can determine a metabolic phenotype associated with 90-day survival.MethodsTwo hundred and forty-eight subjects underwent plasma metabotyping by 1H nuclear magnetic resonance (NMR) spectroscopy and reversed-phase ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC-TOF-MS; DC: 80-derivation set, 101-validation; stable cirrhosis (CLD) 20 and 47 healthy controls (HC)).Results1H NMR metabotyping accurately discriminated between surviving and non-surviving patients with DC. The NMR plasma profiles of non-survivors were attributed to reduced phosphatidylcholines and lipid resonances, with increased lactate, tyrosine, methionine and phenylalanine signal intensities. This was confirmed on external validation (area under the receiver operating curve [AUROC] = 0.96 (95% CI 0.90–1.00, sensitivity 98%, specificity 89%). UPLC-TOF-MS confirmed that lysophosphatidylcholines and phosphatidylcholines [LPC/PC] were downregulated in non-survivors (UPLC-TOF-MS profiles AUROC of 0.94 (95% CI 0.89–0.98, sensitivity 100%, specificity 85% [positive ion detection])). LPC concentrations negatively correlated with circulating markers of cell death (M30 and M65) levels in DC. Histological examination of liver tissue from DC patients confirmed increased hepatocyte cell death compared to controls. Cross liver sampling at time of liver transplantation demonstrated that hepatic endothelial beds are a source of increased circulating total cytokeratin-18 in DC.ConclusionPlasma metabotyping accurately predicts mortality in DC. LPC and amino acid dysregulation is associated with increased mortality and severity of disease reflecting hepatocyte cell death.
Lamour SD, Gomez-Romero M, Vorkas PA, et al., 2015, Discovery of Infection Associated Metabolic Markers in Human African Trypanosomiasis., PLOS Neglected Tropical Diseases, Vol: 9, ISSN: 1935-2735
Human African trypanosomiasis (HAT) remains a major neglected tropical disease in Sub-Saharan Africa. As clinical symptoms are usually non-specific, new diagnostic and prognostic markers are urgently needed to enhance the number of identified cases and optimise treatment. This is particularly important for disease caused by Trypanosoma brucei rhodesiense, where indirect immunodiagnostic approaches have to date been unsuccessful. We have conducted global metabolic profiling of plasma from T.b.rhodesiense HAT patients and endemic controls, using 1H nuclear magnetic resonance (NMR) spectroscopy and ultra-performance liquid chromatography, coupled with mass spectrometry (UPLC-MS) and identified differences in the lipid, amino acid and metabolite profiles. Altogether 16 significantly disease discriminatory metabolite markers were found using NMR, and a further 37 lipid markers via UPLC-MS. These included significantly higher levels of phenylalanine, formate, creatinine, N-acetylated glycoprotein and triglycerides in patients relative to controls. HAT patients also displayed lower concentrations of histidine, sphingomyelins, lysophosphatidylcholines, and several polyunsaturated phosphatidylcholines. While the disease metabolite profile was partially consistent with previous data published in experimental rodent infection, we also found unique lipid and amino acid profile markers highlighting subtle but important differences between the host response to trypanosome infections between animal models and natural human infections. Our results demonstrate the potential of metabolic profiling in the identification of novel diagnostic biomarkers and the elucidation of pathogenetic mechanisms in this disease.
Abbassi-Ghadi N, Jones EA, Gomez-Romero M, et al., 2015, A Comparison of DESI-MS and LC-MS for the Lipidomic Profiling of Human Cancer Tissue, Journal of the American Society for Mass Spectrometry, Vol: 27, Pages: 255-264, ISSN: 1044-0305
In this study, we make a direct comparison between desorptionelectrospray ionization-mass spectrometry (DESI-MS) and ultraperformance liquidchromatography-electrospray ionization-mass spectrometry (UPLC-ESI-MS) platformsfor the profiling of glycerophospholipid (GPL) species in esophageal cancertissue. In particular, we studied the similarities and differences in the range of GPLsdetected and the congruency of their relative abundances as detected by eachanalytical platform. The main differences between mass spectra of the two modalitieswere found to be associated with the variance in adduct formation of common GPLs,rather than the presence of different GPL species. Phosphatidylcholines as formateadducts in UPLC-ESI-MS accounted for the majority of differences in negative ionmode and alkali metal adducts of phosphatidylcholines in DESI-MS for positive ion mode. Comparison of therelative abundance of GPLs, normalized to a common peak, revealed a correlation coefficient of 0.70 (P < 0.001).The GPL profile detected by DESI-MS is congruent to UPLC-ESI-MS, which reaffirms the role of DESI-MS forlipidomic profiling and a potential premise for quantification.
Chekmeneva E, Correia G, Denes J, et al., 2015, Development of nanoelectrospray high resolution isotope dilution mass spectrometry for targeted quantitative analysis of urinary metabolites: application to population profiling and clinical studies, Analytical Methods, Vol: 7, Pages: 5122-5133, ISSN: 1759-9679
An automated chip-based electrospray platform was used to develop a high-throughput nanoelectrospray high resolution mass spectrometry (nESI-HRMS) method for multiplexed parallel untargeted and targeted quantitative metabolic analysis of urine samples. The method was demonstrated to be suitable for metabolic analysis of large sample numbers and can be applied to large-scale epidemiological and stratified medicine studies. The method requires a small amount of sample (5 μL of injectable volume containing 250 nL of original sample), and the analysis time for each sample is three minutes per sample to acquire data in both negative and positive ion modes. Identification of metabolites was based on the high resolution accurate mass and tandem mass spectrometry using authentic standards. The method was validated for 8 targeted metabolites and was shown to be precise and accurate. The mean accuracy of individual measurements being 106% and the intra- and inter-day precision (expressed as relative standard deviations) were 9% and 14%, respectively. Selected metabolites were quantified by standard addition calibration using the stable isotope labelled internal standards in a pooled urine sample, to account for any matrix effect. The multiple point standard addition calibration curves yielded correlation coefficients greater than 0.99, and the linear dynamic range was more than three orders of magnitude. As a proof-of-concept the developed method was applied for targeted quantitative analysis of a set of 101 urine samples obtained from female participants with different pregnancy outcomes. In addition to the specifically targeted metabolites, several other metabolites were quantified relative to the internal standards. Based on the calculated concentrations, some metabolites showed significant differences according to different pregnancy outcomes. The acquired high resolution full-scan data were used for further untargeted fingerprinting and improved the differentiation of
Andreas NJ, Hyde MJ, Gomez-Romero M, et al., 2015, Multiplatform characterization of dynamic changes in breast milk during lactation., Electrophoresis, Vol: 36, Pages: 2269-2285, ISSN: 1522-2683
The multicomponent analysis of human breast milk (BM) by metabolic profiling is a new area of study applied to determining milk composition, and is capable of associating BM composition with maternal characteristics, and subsequent infant health outcomes. A multi-platform approach combining high-performance as well as ultra-performance liquid-chromatography (HPLC-MS and UPLC-MS), gas chromatography (GC-MS), capillary electrophoresis (CE-MS) coupled to mass spectrometry and (1) H NMR spectroscopy was used to comprehensively characterize metabolic profiles from seventy BM samples. A total of 710 metabolites spanning multiple molecular classes were defined. The utility of the individual and combined analytical platforms was explored in relation to numbers of metabolites identified, as well as the reproducibility of the methods. The greatest number of metabolites were identified by the single phase HPLC-MS method, whilst CE-MS uniquely profiled amino acids in detail and NMR was the most reproducible, whereas GC-MS targeted volatile compounds and short chain fatty acids. Dynamic changes in BM composition were characterized over the first 3 months of lactation. Metabolites identified as altering in abundance over lactation included fucose, di- and triacylglycerols and short chain fatty acids, known to be important for infant immunological, neurological and gastrointestinal development, as well as being an important source of energy. This extensive metabolic coverage of the dynamic BM metabolome provides a baseline for investigating the impact of maternal characteristics, as well as establishing the impact of environmental and dietary factors on the composition of BM, with a focus on the downstream health consequences this may have for infants. This article is protected by copyright. All rights reserved.
Sheridan DA, Romero MG, Bridge S, et al., 2015, LIPIDOMICS ANALYSIS OF FASTING SERUM IDENTIFIES NOVEL LIPID BIOMARKERS SPECIFIC FOR HCV GENOTYPE 3 AND GENOTYPE 1 CHRONIC HEPATITIS C VIRUS INFECTION, 50th International Liver Congress of the European-Association-for-the-Study-of-the-Liver, Publisher: ELSEVIER SCIENCE BV, Pages: S596-S596, ISSN: 0168-8278
Ladep NG, Lewis M, Gomez-Romero M, et al., 2014, BIOMARKER DISCOVERY USING ULTRA-PERFORMANCE LIQUID CHROMATOGRAPHY QUADRUPOLE TIME-OF-FLIGHT MASS SPECTROMETRY IDENTIFIES DIAGNOSTIC URINARY METABOLIC PANELS FOR HCC IN AFRICANS, 49th Annual International Liver Congress of the European-Association-for-the-Study-of-the-Liver, Publisher: ELSEVIER SCIENCE BV, Pages: S256-S256, ISSN: 0168-8278
Hurtado-Fernández E, Gómez-Romero M, Pacchiarotta T, et al., 2014, Determination of avocado fruit metabolites by UHPLC–MS complementarity with other analytical platforms, Ultra Performance Liquid Chromatography Mass Spectrometry: Evaluation and Applications in Food Analysis, Pages: 175-212, ISBN: 9781466591547
Botanically, avocado (Persea americana) is a berry that consists of a large central seed and pericarp, which is the sum of the skin, the edible portion, and the inner layer surrounding the seed [1]. It is a fruit of an evergreen tree that belongs to the Lauraceae family, which is typically from tropical or subtropical climates. Although the origin of this crop is Central America and Mexico, it is widely cultivated throughout the world [2,3]. In 2011, the world production of avocado was 4,434,425 tons, increasing by 10% over the previous year. The main producers are Mexico (28.5%), Chile (8.3%), Dominican Republic (6.7%), and Indonesia (6.2%), and the principal importers of this tropical fruit are the United States (8.6%), The Netherlands (2.6%), France (2.3%), and Japan (1.1%) [4]. The increased production of avocado over the last few years has been driven by a higher demand, as this fruit has distinctive and pleasant sensory attributes and is perceived by buyers as beneficial to health [5,6].
Contreras-Gutierrez PK, Hurtado-Fernandez E, Gomez-Romero M, et al., 2013, Determination of changes in the metabolic profile of avocado fruits (Persea americana) by two CE-MS approaches (targeted and non-targeted), ELECTROPHORESIS, Vol: 34, Pages: 2928-2942, ISSN: 0173-0835
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- Citations: 25
Hurtado-Fernandez E, Pacchiarotta T, Gomez-Romero M, et al., 2011, Ultra high performance liquid chromatography-time of flight mass spectrometry for analysis of avocado fruit metabolites: Method evaluation and applicability to the analysis of ripening degrees, JOURNAL OF CHROMATOGRAPHY A, Vol: 1218, Pages: 7723-7738, ISSN: 0021-9673
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- Citations: 37
Valero-Navarro A, Gomez-Romero M, Fernandez-Sanchez JF, et al., 2011, Synthesis of caffeic acid molecularly imprinted polymer microspheres and high-performance liquid chromatography evaluation of their sorption properties, JOURNAL OF CHROMATOGRAPHY A, Vol: 1218, Pages: 7289-7296, ISSN: 0021-9673
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- Citations: 45
Gomez-Romero M, Zurek G, Schneider B, et al., 2011, Automated identification of phenolics in plant-derived foods by using library search approach, FOOD CHEMISTRY, Vol: 124, Pages: 379-386, ISSN: 0308-8146
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- Citations: 36
Hurtado-Fernandez E, Gomez-Romero M, Carrasco-Pancorbo A, et al., 2010, Application and potential of capillary electroseparation methods to determine antioxidant phenolic compounds from plant food material, JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, Vol: 53, Pages: 1130-1160, ISSN: 0731-7085
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- Citations: 84
Gomez-Romero M, Segura-Carretero A, Fernandez-Gutierrez A, 2010, Metabolite profiling and quantification of phenolic compounds in methanol extracts of tomato fruit, PHYTOCHEMISTRY, Vol: 71, Pages: 1848-1864, ISSN: 0031-9422
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- Citations: 185
Gomez-Romero M, Arraez-Roman D, Segura-Carretero A, et al., 2007, Analytical determination of antioxidants in tomato: Typical components of the Mediterranean diet, JOURNAL OF SEPARATION SCIENCE, Vol: 30, Pages: 452-461, ISSN: 1615-9306
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- Citations: 51
Gomez-Romero M, Arraez-Roman D, Moreno-Torres R, et al., 2007, Antioxidant compounds of propolis determined by capillary electrophoresis-mass spectrometry, JOURNAL OF SEPARATION SCIENCE, Vol: 30, Pages: 595-603, ISSN: 1615-9306
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- Citations: 25
Arraez-Roman D, Gomez-Caravaca AM, Gomez-Romero M, et al., 2006, Identification of phenolic compounds in rosemary honey using solid-phase extraction by capillary electrophoresis-electrospray ionization-mass spectrometry, JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, Vol: 41, Pages: 1648-1656, ISSN: 0731-7085
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- Citations: 58
Gomez-Caravaca AM, Gomez-Romero M, Arraez-Roman D, et al., 2006, Advances in the analysis of phenolic compounds in products derived from bees, JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS, Vol: 41, Pages: 1220-1234, ISSN: 0731-7085
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- Citations: 270
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