Plasma lipidic fingerprint associated with type 2 diabetes in patients with coronary heart disease: CORDIOPREV study.

OBJECTIVE: We aimed to identify a lipidic profile associated with type 2 diabetes mellitus (T2DM) development in coronary heart disease (CHD) patients, to provide a new, highly sensitive model which could be used in clinical practice to identify patients at T2DM risk. METHODS: This study considered the 462 patients of the CORDIOPREV study (CHD patients) who were not diabetic at the beginning of the intervention. In total, 107 of them developed T2DM after a median follow-up of 60 months. They were diagnosed using the American Diabetes Association criteria. A novel lipidomic methodology employing liquid chromatography (LC) separation followed by HESI, and detection by mass spectrometry (MS) was used to annotate the lipids at the isomer level. The patients were then classified into a Training and a Validation Set (60-40). Next, a Random Survival Forest (RSF) was carried out to detect the lipidic isomers with the lowest prediction error, these lipids were then used to build a Lipidomic Risk (LR) score which was evaluated through a Cox. Finally, a production model combining the clinical variables of interest, and the lipidic species was carried out. RESULTS: LC-tandem MS annotated 440 lipid species. From those, the RSF identified 15 lipid species with the lowest prediction error. These lipids were combined in an LR score which showed association with the development of T2DM. The LR hazard ratio per unit standard deviation was 2.87 and 1.43, in the Training and Validation Set respectively. Likewise, patients with higher LR Score values had lower insulin sensitivity (P = 0.006) and higher liver insulin resistance (P = 0.005). The receiver operating characteristic (ROC) curve obtained by combining clinical variables and the selected lipidic isomers using a generalised lineal model had an area under the curve (AUC) of 81.3%. CONCLUSION: Our study showed the potential of comprehensive lipidomic analysis in identifying patients at risk of developing T2DM. In addition, the lipid species combined with clinical variables provided a new, highly sensitive model which can be used in clinical practice to identify patients at T2DM risk. Moreover, these results also indicate that we need to look closely at isomers to understand the role of this specific compound in T2DM development. Trials registration NCT00924937.

Changes in human sweat metabolome conditioned by severity of obstructive sleep apnea and intermittent hypoxemia.

Obstructive sleep apnea (OSA) is a sleep disorder that has been associated with the incidence of other pathologies. Diagnosis is mainly based on the apnea-hypopnea index (AHI) obviating other repercussions such as intermittent hypoxemia, which has been found to be associated to cardiovascular complications. Blood-based samples and urine have been the most utilised biofluids in metabolomics studies related to OSA, while sweat could be an alternative due to its non-invasive and accessible sampling, its reduced complexity, and comparability with other biofluids. Therefore, this research aimed to evaluate metabolic overnight changes in sweat collected from patients with OSA classified according to the AHI and oxygen desaturation index (ODI), looking for potential cardiovascular repercussions. Pre- and post-sleeping sweat samples from all individuals (n = 61) were analysed by gas chromatography coupled to high-resolution mass spectrometry after appropriate sample preparation to detect as many metabolites as possible. Permanent significant alterations in the sweat were reported for pyruvate, serine, lactose, and hydroxybutyrate. The most relevant overnight metabolic alterations in sweat were reported for lactose, succinate, urea, and oxoproline, which presented significantly different effects on factors such as the AHI and ODI for OSA severity classification. Overall metabolic alterations mainly affected energy production-related processes, nitrogen metabolism, and oxidative stress. In conclusion, this research demonstrated the applicability of sweat for evaluation of OSA diagnosis and severity supported by the detected metabolic changes during sleep.

Determination of vitamin D3 conjugated metabolites: a complementary view on hydroxylated metabolites.

Experts typically define vitamin D deficiency levels by the determination of a circulating 25-hydroxyvitamin D3-calcifediol prohormone. A large part of the population is characterized by deficient vitamin D levels (calcifediol < 20 ng mL-1) despite individuals not being affected by any disorder. Cholecalciferol (vitamin D3) and/or calcifediol supplementation is a common practice for vitamin D-deficient individuals as recommended by international scientific societies and official agencies. In the last few years, several studies have reported the presence of conjugated vitamin D3 metabolites, mainly glucuronidation and sulfation derivatives, although simultaneous quantitative measurements involving phase I and II vitamin D metabolites have not been carried out. A quantitative method based on tandem mass spectrometry detection is proposed here for the combined determination of phase I and phase II vitamin D3 metabolites in human serum. As phase I and phase II metabolites are preferentially ionized in different modes, a switching polarity mode was adopted to determine both groups of compounds in serum at high sensitivity levels (pg mL-1). The validation of this proposal was successfully accomplished by following the Center for Drug Evaluation and Research (CDER) guidelines. Its applicability was tested in a cohort of volunteers with mostly deficient baseline levels. Considering the sulfated form of calcifediol, the sum of its concentrations showed sufficient baseline vitamin D levels in all individuals, suggesting that this could be a novel strategy for vitamin D deficiency definition. Therefore, phase II metabolites are proposed to be included when evaluating the vitamin D status since they provide more information about the overall status of the vitamin D endocrine system. Nevertheless, further studies are required to confirm the biological activity of these conjugated metabolites and the suitability of this strategy for the description of vitamin D deficiency.

The Longitudinal Changes in Subcutaneous Abdominal Tissue and Visceral Adipose Tissue Volumetries Are Associated with Iron Status.

Excess iron is known to trigger adipose tissue dysfunction and insulin resistance. Circulating markers of iron status have been associated with obesity and adipose tissue in cross-sectional studies. We aimed to evaluate whether iron status is linked to changes in abdominal adipose tissue longitudinally. Subcutaneous abdominal tissue (SAT) and visceral adipose tissue (VAT) and its quotient (pSAT) were assessed using magnetic resonance imaging (MRI), at baseline and after one year of follow-up, in 131 (79 in follow-up) apparently healthy subjects, with and without obesity. Insulin sensitivity (euglycemic- hyperinsulinemic clamp) and markers of iron status were also evaluated. Baseline serum hepcidin (p = 0.005 and p = 0.002) and ferritin (p = 0.02 and p = 0.01)) were associated with an increase in VAT and SAT over one year in all subjects, while serum transferrin (p = 0.01 and p = 0.03) and total iron-binding capacity (p = 0.02 and p = 0.04) were negatively associated. These associations were mainly observed in women and in subjects without obesity, and were independent of insulin sensitivity. After controlling for age and sex, serum hepcidin was significantly associated with changes in subcutaneous abdominal tissue index (iSAT) (ß = 0.406, p = 0.007) and visceral adipose tissue index (iVAT) (ß = 0.306, p = 0.04), while changes in insulin sensitivity (ß = 0.287, p = 0.03) and fasting triglycerides (ß = -0.285, p = 0.03) were associated with changes in pSAT. These data indicated that serum hepcidin are associated with longitudinal changes in SAT and VAT, independently of insulin sensitivity. This would be the first prospective study evaluating the redistribution of fat according to iron status and chronic inflammation.

Metabolomics analysis of type 2 diabetes remission identifies 12 metabolites with predictive capacity: a CORDIOPREV clinical trial study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is one of the most widely spread diseases, affecting around 90% of the patients with diabetes. Metabolomics has proven useful in diabetes research discovering new biomarkers to assist in therapeutical studies and elucidating pathways of interest. However, this technique has not yet been applied to a cohort of patients that have remitted from T2DM. METHODS: All patients with a newly diagnosed T2DM at baseline (n = 190) were included. An untargeted metabolomics approach was employed to identify metabolic differences between individuals who remitted (RE), and those who did not (non-RE) from T2DM, during a 5-year study of dietary intervention. The biostatistical pipeline consisted of an orthogonal projection on the latent structure discriminant analysis (O-PLS DA), a generalized linear model (GLM), a receiver operating characteristic (ROC), a DeLong test, a Cox regression, and pathway analyses. RESULTS: The model identified a significant increase in 12 metabolites in the non-RE group compared to the RE group. Cox proportional hazard models, calculated using these 12 metabolites, showed that patients in the high-score tercile had significantly (p-value < 0.001) higher remission probabilities (Hazard Ratio, HR, high versus low = 2.70) than those in the lowest tercile. The predictive power of these metabolites was further studied using GLMs and ROCs. The area under the curve (AUC) of the clinical variables alone is 0.61, but this increases up to 0.72 if the 12 metabolites are considered. A DeLong test shows that this difference is statistically significant (p-value = 0.01). CONCLUSIONS: Our study identified 12 endogenous metabolites with the potential to predict T2DM remission following a dietary intervention. These metabolites, combined with clinical variables, can be used to provide, in clinical practice, a more precise therapy. TRIAL REGISTRATION: ClinicalTrials.gov, NCT00924937.

Influence of the fatty acid profile on the volatile components of virgin olive oil subjected to thermal stress.

BACKGROUND: Virgin olive oil (VOO) is greatly appreciated for its organoleptic features, which can be ascribed mainly to the presence of very chemically diverse volatile components. It is well known that the VOO volatile fraction depends strongly on different aspects, which encompass genetic, agronomic, processing, and post-processing factors. In this research, we developed a method for the qualitative and semiquantitative determination of volatile components in VOOs subjected to thermal stress by headspace extraction online coupled to gas chromatography-mass spectrometry (HS-GC-MS). RESULTS: The method was applied to 100 extra-virgin olive oil (EVOO) samples, which led to the tentative identification of 52 volatile components, including 12 alcohols, 17 aldehydes, three ketones, one ether, two furans, two carboxylic acids, and 15 hydrocarbons. The method was used to study the cultivar effect and the main biochemical pathways involved in the synthesis of volatile compounds, with special emphasis on those formed by degradation of unsaturated fatty acids (FAs). Principal component analysis (PCA), explaining 76.7% of the total variability, showed that the volatile profile of EVOOs subjected to thermal stress allowed discriminating samples from different cultivars. CONCLUSION: Volatiles detected in EVOOs subjected to thermal stress with the highest contribution to discrimination between the selected cultivars were correlated with the concentration of the three main FAs in VOO, namely oleic, linoleic, and linolenic acids. The FA profile seems to be especially relevant to explain the concentration of certain volatile compounds with direct incidence on the organoleptic properties. © 2021 Society of Chemical Industry.

Serum Phospholipid Fatty Acids and Mammographic Density in Premenopausal Women.

BACKGROUND: The role of fatty acids (FAs) on mammographic density (MD) is unclear, and available studies are based on self-reported dietary intake. OBJECTIVES: This study assessed the association between specific serum phospholipid fatty acids (PLFAs) and MD in premenopausal women. METHODS: The cross-sectional study DDM-Madrid recruited 1392 Spanish premenopausal women, aged 39-50 y, who attended a screening in a breast radiodiagnosis unit of Madrid City Council. Women completed lifestyle questionnaires and FFQs. Percentage MD was estimated using a validated computer tool (DM-Scan), and serum PLFA percentages were measured by GC-MS. Multivariable linear regression models were used to quantify the association of FA tertiles with MD. Models were adjusted for age, education, BMI, waist circumference, parity, oral contraceptive use, previous breast biopsies, and energy intake, and they were corrected for multiple testing. RESULTS: Women in the third tertile of SFAs showed significantly higher MD compared with those in the first tertile (ßT3vsT1 = 7.53; 95% CI: 5.44, 9.61). Elevated relative concentrations of palmitoleic (ßT3vsT1 = 3.12; 95% CI: 0.99, 5.25) and gondoic (ßT3vsT1 = 2.67; 95% CI: 0.57, 4.77) MUFAs, as well as high relative concentrations of palmitelaidic (ßT3vsT1 = 5.22; 95% CI: 3.15, 7.29) and elaidic (ßT3vsT1 = 2.69; 95% CI: 0.59, 4.79) trans FAs, were also associated with higher MD. On the contrary, women with elevated relative concentrations of n-6 (ω-6) linoleic (ßT3vsT1 = -5.49; 95% CI; -7.62, -3.35) and arachidonic (ßT3vsT1 = -4.68; 95% CI: -6.79, -2.58) PUFAs showed lower MD. Regarding desaturation indices, an elevated palmitoleic to palmitic ratio and a low ratio of oleic to steric and arachidonic to dihomo-γ-linolenic acids were associated with higher MD. CONCLUSIONS: Spanish premenopausal women with high relative concentrations of most SFAs and some MUFAs and trans FAs showed an increased MD, whereas those with high relative concentrations of some n-6 PUFAs presented lower density. These results, which should be confirmed in further studies, underscore the importance of analyzing serum FAs individually.

GC-MS study of changes in polar/mid-polar and volatile compounds in Persian lime (Citrus latifolia) during fruit growth.

BACKGROUND: Citrus fruits possess a high content of bioactive compounds whose changes during fruit maturation have not been studied in depth. Fruits were sampled from week 1, after fruit onset (7 days after flowering), to week 14. Volatile compounds isolated by headspace-solid-phase microextraction and polar extracts from all samples were analyzed by gas chromatography-mass spectrometry. RESULTS: The relative abundance of 107 identified metabolites allowed differences among samples at different stages of fruit growth to be established. Principal component analysis showed a clear discrimination among samples, and analysis of variance revealed significant differences in 94 out of the 107 metabolites. Among total volatiles, monoterpenes increased their relative abundance from 86% to 94% during fruit growth, d-limonene, γ-terpinene and ß-pinene being the most abundant; conversely, sesquiterpenes decreased from 11.5% to 2.8%, ß-bisabolene and α-bergamotene being the most concentrated. Sugars, in general, exhibited a gradual increase in abundance, reaching a maximum between weeks 9 and 12. Citric and malic acids, representing approximately 90% of the total identified carboxylic acids, reached a maximum concentration at commercial maturity (week 14). CONCLUSION: Of the 107 tentatively identified metabolites during Persian lime growth, sugars, carboxylic acids, and volatiles were those that experienced more significant changes and more clearly created differences among fruit growth stages. © 2018 Society of Chemical Industry.

Untargeted analysis to monitor metabolic changes of garlic along heat treatment by LC-QTOF MS/MS.

Black garlic is increasing its popularity in cuisine around the world; however, scant information exists on the composition of this processed product. In this study, polar compounds in fresh garlic and in samples taken at different times during the heat treatment process to obtain black garlic have been characterized by liquid chromatography coupled to tandem mass spectrometry in high resolution mode. Ninety-five compounds (mainly amino acids and metabolites, organosulfur compounds, and saccharides and derivatives) were tentatively identified in all the analysed samples and classified as a function of the family they belong to. Statistical analysis of the results allowed establishing that the major changes in garlic occur during the first days of treatment, and they mainly affect to the three representative families. The main pathways involved in the synthesis of the compounds affected by heat treatment, and their evolution during the process were studied.

HS-GC/MS volatile profile of different varieties of garlic and their behavior under heating.

Garlic is one of the most used seasonings in the world whose beneficial health effects, mainly ascribed to organosulfur compounds, are shared with the rest of the Allium family. The fact that many of these compounds are volatile makes the evaluation of the volatile profile of garlic interesting. For this purpose, three garlic varieties-White, Purple, and Chinese-cultivated in the South of Spain were analyzed by a method based on a headspace (HS) device coupled to a gas chromatograph and mass detector (HS-GC/MS). The main temperatures in the HS were optimized to achieve the highest concentration of volatiles. A total number of 45 volatiles were tentatively identified (among them 17 were identified for the first time in garlic); then, all were classified, also for the first time, and their relative concentration in three garlic varieties was used to evaluate differences among them and to study their profiles according to the heating time. Chinese garlic was found to be the richest variety in sulfur volatiles, while the three varieties presented a similar trend under preset heating times allowing differentiation between varieties and heating time using principal component analysis. Graphical Abstract HS-GC/MS analysis of the volatile profile of garlic.

Enhancing detection coverage in untargeted metabolomics analysis by solid-phase extraction on-line coupled to LC-MS/MS.

One of the main limitations of untargeted metabolomics analysis is the low detection coverage of analytical techniques such as NMR, LC-MS, or GC-MS. In this research, the detection coverage of an automated approach configured by the on-line coupling of SPE to LC-MS/MS was evaluated by combination of sorbents based on different retention mechanisms. The approach was applied to the analysis of human serum using three types of sorbents: alkyl bonded silica, polymeric resins, and mixed-mode ionic resins. The combination of four sorbents (C18, a modified polystyrene-divinylbenzene resin and two mixed-mode ionic resins) led to the best extraction results and, therefore, the best detection coverage, which is explained by their complementary retention mechanisms. However, some of the sorbents provide a high detection coverage by themselves, as is the case with C18, which can afford to retain almost 83% of all detected entities. Taking into account the complementarity between pairs of these sorbents (C18 and the polystyrene-divinylbenzene resin with the mixed-mode ionic resins), dual cartridge SPE-LC-MS/MS configurations were designed for serum analysis. These configurations allowed increasing the detection coverage up to 91% of the total number of molecular features detected with all sorbents tested. An additional benefit of the SPE-LC-MS/MS strategy was the improvement of sensitivity as compared to protein precipitation and fractionation with methanol and chloroform. Thus, an average preconcentration factor of 10-75 was obtained in the SPE-based approach versus the two-phase protocol for metabolites extraction.

Human sweat metabolomics for lung cancer screening.

Sweat is one of the less employed biofluids for discovery of markers in spite of its increased application in medicine for detection of drugs or for diagnostic of cystic fibrosis. In this research, human sweat was used as clinical sample to develop a screening tool for lung cancer, which is the carcinogenic disease with the highest mortality rate owing to the advanced stage at which it is usually detected. In this context, a method based on the metabolite analysis of sweat to discriminate between patients with lung cancer versus smokers as control individuals is proposed. The capability of the metabolites identified in sweat to discriminate between both groups of individuals was studied and, among them, a trisaccharide phosphate presented the best independent performance in terms of the specificity/sensitivity pair (80 and 72.7%, respectively). Additionally, two panels of metabolites were configured using the PanelomiX tool as an attempt to reduce false negatives (at least 80% specificity) and false positives (at least 80% sensitivity). The first panel (80% specificity and 69% sensitivity) was composed by suberic acid, a tetrahexose, and a trihexose, while the second panel (69% specificity and 80% sensitivity) included nonanedioic acid, a trihexose, and the monoglyceride MG(22:2). Thus, the combination of the five metabolites led to a single panel providing 80% specificity and 79% sensitivity, reducing the false positive and negative rates to almost 20%. The method was validated by estimation of within-day and between-days variability of the quantitative analysis of the five metabolites.

Composition of fatty acids in virgin olive oils from cross breeding segregating populations by gas chromatography separation with flame ionization detection.

BACKGROUND: Recent technological advances to improve the quality of virgin olive oil (VOO) have been focused on olive breeding programs by selecting outstanding cultivars and target progenies. Fatty acid (FA) composition, with special emphasis on oleic acid (C18:1) and palmitic acid (C16:0), is one of the most critical quality factors to be evaluated in VOO. For this reason, the profile of FAs is frequently used as a decision tool in olive breeding programs. RESULTS: A method based on gas chromatography with flame ionization detection (GC-FID) was used to study the influence of genotype on the concentration of ten of the most important FAs in VOOs from target crosses Arbequina × Arbosana, Picual × Koroneiki and Sikitita × Arbosana and their corresponding genitors Arbequina, Arbosana, Koroneiki, Picual and Sikitita. For this purpose, a targeted approach was selected for determination of esterified FAs (EFAs) and non-esterified FAs (NEFAs) in a dual analysis by the same chromatographic method. A Pearson analysis revealed correlations between pairs of FAs, which allowed detecting metabolic connections through desaturation and elongation enzymes. An ANOVA test (with P < 0.01) led to identification of C16:0 EFA, C16:1 EFA and C18:1 EFA and also C16:1 NEFA and C18:0 NEFA as the FAs more influenced by cross breeding. Statistical analysis was carried out by unsupervised analysis using principal component analysis (PCA) and cluster analysis (CA) to look for variability sources. CONCLUSION: Crosses with a common genitor (Arbequina × Arbosana and Sikitita × Arbosana) were partially overlapped in the PCAs using the profile of FAs. The CA results revealed clear differences between Sikitita × Arbosana and Picual × Koroneiki crosses in the composition of the most significant FAs, while Arbequina × Arbosana was not properly discriminated from the other crosses.

Quantitative analysis of glycated proteins.

The proposed protocol presents a comprehensive approach for large-scale qualitative and quantitative analysis of glycated proteins (GP) in complex biological samples including biological fluids and cell lysates such as plasma and red blood cells. The method, named glycation isotopic labeling (GIL), is based on the differential labeling of proteins with isotopic [(13)C6]-glucose, which supports quantitation of the resulting glycated peptides after enzymatic digestion with endoproteinase Glu-C. The key principle of the GIL approach is the detection of doublet signals for each glycated peptide in MS precursor scanning (glycated peptide with in vivo [(12)C6]- and in vitro [(13)C6]-glucose). The mass shift of the doublet signals is +6, +3 or +2 Da depending on the peptide charge state and the number of glycation sites. The intensity ratio between doublet signals generates quantitative information of glycated proteins that can be related to the glycemic state of the studied samples. Tandem mass spectrometry with high-energy collisional dissociation (HCD-MS2) and data-dependent methods with collision-induced dissociation (CID-MS3 neutral loss scan) are used for qualitative analysis.

Enhanced detection and identification in metabolomics by use of LC-MS/MS untargeted analysis in combination with gas-phase fractionation.

Liquid chromatography coupled to tandem mass spectrometry is one of the most widely used analytical platforms for profiling analysis in metabolomics. One weakness of untargeted metabolomic analysis, however, is the difficulty of identifying metabolites. In fact, the process typically involves mass-based searching of LC-MS and LC-MS/MS data and requires using MS/MS data for unequivocal identification. Current strategies use LC-MS analysis in the scan mode prior to acquiring MS/MS information about targeted metabolites or the "auto MS/MS" mode to fragment automatically the most intense precursor ions. Therefore, in both cases additional injections are required to obtain MS/MS data after data treatment to identify significant compounds whose signals are not so intense. Because an additional procedure is needed to enhance the fraction of metabolites with MS/MS data, in this work, the effectiveness of utilizing different MS/MS parameters across an analytical batch or repetitions of the same sample by using exclusion or inclusion criteria to select precursor ions is assessed. The procedure, known as "gas-phase fractionation (GPF)", was used here for untargeted analysis of serum. The joint use of four methods with a different mass range for selection of precursor ions each provided useful MS/MS information for at least 80% of all molecular entities detected in the MS scan replicates. By contrast, the conventional "auto MS/MS" mode of data acquisition provided MS/MS data for only 48-57% of entities and was therefore less effective toward identifying metabolites. The additional use of GPF improved the detection and annotation of metabolite families such as phospholipids, amino acids, bile acids, carnitines, and fatty acids and their derivatives.

Ultrasound-assisted extraction with LC-TOF/MS identification and LC-UV determination of imazamox and its metabolites in leaves of wheat plants.

INTRODUCTION: imazamox is a herbicide used in many legominous and cereal crops. There are few methods in the literature for determination of imazamox and its metabolites in plants because of the lack of commercial standards or owing to expensive and/or complex synthesis. OBJECTIVE: To develop a method based on liquid chromatography and ultraviolet absorption detection for simultaneous determination of imazamox and its metabolites in plants. METHODS: Sample preparation was based on ultrasound-assisted extraction (70 W power and duty cycle of 0.7 s/s for 10 min) with subsequent filtration of the extracts and clean-up and concentration prior to chromatographic separation and detection at 240 nm. The chromatographic analysis was completed in 30 min using a Luna® HILIC column. Identification and confirmatory analysis of the presence of imazamox and its metabolites in extracts from treated plants was performed by LC-TOF/MS in high resolution mode for precursor ions. The metabolites were quantified using a surrogate approach based on an imazamox standard. The method was validated by analysing wheat samples treated with 200 g per hectare of active ingredient imazamox. RESULTS: The linear dynamic range of the calibration curve was within 0.27-600 µg/mL, with a correlation coefficient of 0.998 and precision--studied at 0.1 and 2 µg/mL--of 2.9% and 5.0% for repeatability, and 4.7% and 6.9% for reproducibility, respectively. CONCLUSION: The analytical characteristics of the method make it recommendable for evaluating the metabolism of imazamox in plants.

Comparative profiling analysis of woody flavouring from vine-shoots and oak chips.

BACKGROUND: Woody liquid flavourings extracted from different varieties of vine shoots and oak chips have been characterized by gas chromatography-mass spectrometry to compare the profile of compounds as potential contributors to the organoleptical properties of wine and spirits aged in oak barrels. Oak chips are frequently added to barrels to accelerate the ageing process, while vine shoots are produced in high amounts in wine-producing countries. RESULTS: The extracts were isolated by superheated liquid extraction (SHLE) after optimization of extraction variables. The SHLE protocol was performed using ethanol-water mixtures (pH 3) at 220 °C for 60 min. Compounds were identified using NIST databases, and the resulting profile was used as a dataset for qualitative and semi-quantitative comparison between extracts obtained from different varieties of vine shoots and oak chips. CONCLUSION: Statistical analysis enabled demonstration of the similarity among extracts from vine shoots and oak wood, providing the first study on this subject. The special role of phenols and furanic derivatives has been described. This study is the first stage for characterization of vine shoots as a by-product with potential for use in the oenological field.

High-resolution mass spectrometry to evaluate the influence of cross-breeding segregating populations on the phenolic profile of virgin olive oils.

BACKGROUND: The growing demand for high-quality virgin olive oils (VOOs) has increased the interest in olive breeding programs. Cross-breeding is considered, within these programs, the best strategy to generate new cultivars as an attempt to improve the present cultivars. In this research, the phenolic profile of VOOs from target crosses (Arbequina × Arbosana, Picual × Koroneiki and Sikitita × Arbosana) and their corresponding genitors (Arbequina, Arbosana, Koroneiki, Picual and Sikitita) has been evaluated using a targeted metabolomics approach. RESULTS: The phenolic profiles were obtained by liquid chromatographic-hybrid quadrupole time-of-flight mass spectrometric targeted analysis of 37 phenols or compounds involved in the main pathways for their biosynthesis. Statistical multivariate analysis by principal component analysis was applied to study the influence of genotype on phenol composition. Phenolic compounds with the highest contribution to explain the observed variability associated to genotype were identified through fold change algorithms (cut-off > 2.0) and t-test analysis. CONCLUSION: A total of nine phenols (viz. quercetin, ligstroside aglycon (p-HPEA-EA), demethyl oleuropein aglycon, oleuropein aglycon (3,4-DHPEA-EA), hydroxypinoresinol, hydroxytyrosol and phenolic acids such as p-coumaric acid, ferulic acid and protocatechuic acid) contributed to explain the observed variability with 99% confidence (P<0.01).

Targeted analysis of omega-6-derived eicosanoids in human serum by SPE-LC-MS/MS for evaluation of coronary artery disease.

A targeted approach has been applied to quantitative analysis of eicosanoids derived from omega-6 fatty acids in serum from individuals diagnosed with coronary artery disease (CAD). The target metabolites were series-2 prostaglandins, thromboxane B2, hydroxyeicosatetraenoic acids, and hydroxyoctadecadienoic acids. The method was based on SPELC-MS/MS in selected reaction monitoring mode for highly selective and sensitive determination of the target eicosanoids. The combination of SPE and LC-MS/MS involved the benefits from both direct analysis of serum without a step for protein precipitation and fully automation of the analysis. The method allowed comparison of omega-6-derived eicosanoids in serum from patients diagnosed with CAD and from control individuals. The effect of treatment with aspirin on the profile of the target compounds was evaluated through its incidence on the different pathways. Finally, the serum levels of the target metabolites in patients diagnosed with CAD were also statistically examined according to the severity of the coronary lesion stratified as stable angina, non-ST-elevation acute coronary syndrome, and acute myocardial infarction.

An approach for quantitative analysis of vitamins D and B9 and their metabolites in human biofluids by on-line orthogonal sample preparation and sequential mass spectrometry detection.

An approach for quantitative analysis of two vitamins with different polarities (vitamins D and B9) and their metabolites is presented here. The approach is based on an experimental setup based on hyphenation of an automated workstation for preparation of liquid samples and an LC-MS/MS system with a triple quadrupole mass spectrometer. This configuration enabled development of an orthogonal protocol for sequential SPE retention of analytes with different polarities for subsequent elution and chromatographic separation prior to detection. The resulting method was validated by application to three human biofluids. Estimation of recovery factors in the SPE step led to values from 85.2 to 100% for vitamin D and metabolites and from 93.1 to 100% for vitamin B9 and metabolites (folic acid and folates). The influence of sample matrix variability by analysis of human serum, urine and breast milk was minimized with a complete optimization of the SPE step. The utility of the proposed configuration is shown by the sensitivity and precision of the method, expressed as limits of detection (between 0.2 and 0.30 ng mL(-1) or 4 and 60 pg on-column) and within-laboratory reproducibility (lower than 6.7%, as relative standard deviation). The present application represents an example of determination methods involving targeted analysis of compounds with different polarities using a single aliquot of the sample.