Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics.

BACKGROUND: Quality assurance (QA) and quality control (QC) practices are key tenets that facilitate study and data quality across all applications of untargeted metabolomics. These important practices will strengthen this field and accelerate its success. The Best Practices Working Group (WG) within the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) focuses on community use of QA/QC practices and protocols and aims to identify, catalogue, harmonize, and disseminate current best practices in untargeted metabolomics through community-driven activities. AIM OF REVIEW: A present goal of the Best Practices WG is to develop a working strategy, or roadmap, that guides the actions of practitioners and progress in the field. The framework in which mQACC operates promotes the harmonization and dissemination of current best QA/QC practice guidance and encourages widespread adoption of these essential QA/QC activities for liquid chromatography-mass spectrometry. KEY SCIENTIFIC CONCEPTS OF REVIEW: Community engagement and QA/QC information gathering activities have been occurring through conference workshops, virtual and in-person interactive forum discussions, and community surveys. Seven principal QC stages prioritized by internal discussions of the Best Practices WG have received participant input, feedback and discussion. We outline these stages, each involving a multitude of activities, as the framework for identifying QA/QC best practices. The ultimate planned product of these endeavors is a "living guidance" document of current QA/QC best practices for untargeted metabolomics that will grow and change with the evolution of the field.

Detection of 26 Drugs of Abuse and Metabolites in Quantitative Dried Blood Spots by Liquid Chromatography-Mass Spectrometry.

A method was developed for the determination of 26 drugs of abuse from different classes, including illicit drugs in quantitative dried blood spots (qDBSs), with the aim to provide a convenient method for drug testing by using only 10 µL of capillary blood. A satisfactory limit of quantification (LOQ) of 2.5 ng/mL for 9 of the compounds and 5 ng/mL for 17 of the compounds and a limit of detection (LOD) of 0.75 ng/mL for 9 of the compounds and 1.5 ng/mL for 17 of the compounds were achieved for all analytes. Reversed-phase liquid chromatography was applied on a C18 column coupled to MS, providing selective detections with both +ESI and -ESI modes. Extraction from the qDBS was performed using AcN-MeOH, 1:1 (v/v), with recovery ranging from 84.6% to 106%, while no significant effect of the hematocrit was observed. The studied drugs of abuse were found to be stable over five days under three different storage conditions (at ambient temperature 21 °C, at -20 °C, and at 35 °C), thus offering a highly attractive approach for drug screening by minimally invasive sampling for individuals that could find application in forensic toxicology analysis.

Ensuring Fact-Based Metabolite Identification in Liquid Chromatography-Mass Spectrometry-Based Metabolomics.

Metabolite identification represents a major bottleneck in contemporary metabolomics research and a step where critical errors may occur and pass unnoticed. This is especially the case for studies employing liquid chromatography-mass spectrometry technology, where there is increased concern on the validity of the proposed identities. In the present perspective article, we describe the issue and categorize the errors into two types: identities that show poor biological plausibility and identities that do not comply with chromatographic data and thus to physicochemical properties (usually hydrophobicity/hydrophilicity) of the proposed molecule. We discuss the problem, present characteristic examples, and propose measures to improve the situation.

Current Practices in LC-MS Untargeted Metabolomics: A Scoping Review on the Use of Pooled Quality Control Samples.

Untargeted metabolomics is an analytical approach with numerous applications serving as an effective metabolic phenotyping platform to characterize small molecules within a biological system. Data quality can be challenging to evaluate and demonstrate in metabolomics experiments. This has driven the use of pooled quality control (QC) samples for monitoring and, if necessary, correcting for analytical variance introduced during sample preparation and data acquisition stages. Described herein is a scoping literature review detailing the use of pooled QC samples in published untargeted liquid chromatography-mass spectrometry (LC-MS) based metabolomics studies. A literature query was performed, the list of papers was filtered, and suitable articles were randomly sampled. In total, 109 papers were each reviewed by at least five reviewers, answering predefined questions surrounding the use of pooled quality control samples. The results of the review indicate that use of pooled QC samples has been relatively widely adopted by the metabolomics community and that it is used at a similar frequency across biological taxa and sample types in both small- and large-scale studies. However, while many studies generated and analyzed pooled QC samples, relatively few reported the use of pooled QC samples to improve data quality. This demonstrates a clear opportunity for the field to more frequently utilize pooled QC samples for quality reporting, feature filtering, analytical drift correction, and metabolite annotation. Additionally, our survey approach enabled us to assess the ambiguity in the reporting of the methods used to describe the generation and use of pooled QC samples. This analysis indicates that many details of the QC framework are missing or unclear, limiting the reader's ability to determine which QC steps have been taken. Collectively, these results capture the current state of pooled QC sample usage and highlight existing strengths and deficiencies as they are applied in untargeted LC-MS metabolomics.

Metabolic Fingerprinting of Muscat of Alexandria Grape Musts during Industrial Alcoholic Fermentation Using HS-SPME and Liquid Injection with TMS Derivatization GC-MS Methods.

Muscat of Alexandria is one of the most aromatic grape cultivars, with a characteristic floral and fruity aroma, producing popular appellation of origin wines. The winemaking process is a critical factor contributing to the quality of the final product, so the aim of this work was to study metabolomic changes during the fermentation of grape musts at the industrial level from 11 tanks, 2 vintages, and 3 wineries of Limnos Island. A Headspace Solid-Phase Microextraction (HS-SPME) and a liquid injection with Trimethylsilyl (TMS) derivatization Gas Chromatography-Mass Spectrometry (GC-MS) methods were applied for the profiling of the main volatile and non-volatile polar metabolites originating from grapes or produced during winemaking, resulting in the identification of 109 and 69 metabolites, respectively. Multivariate statistical analysis models revealed the differentiation between the four examined time points during fermentation, and the most statistically significant metabolites were investigated by biomarker assessment, while their trends were presented with boxplots. Whilst the majority of compounds (ethyl esters, alcohols, acids, aldehydes, sugar alcohols) showed an upward trend, fermentable sugars, amino acids, and C6-compounds were decreased. Terpenes presented stable behavior, with the exception of terpenols, which were increased at the beginning and were then decreased after the 5th day of fermentation.

Hepatic Metabolic Profiling of Lifelong Exercise Training Rats.

Regular physical exercise has been investigated as a primary preventive measure of several chronic diseases and premature death. Moreover, it has been shown to synchronize responses across multiple organs. In particular, hepatic tissue has proven to be a descriptive matrix to monitor the effect of physical activity. In this study, we performed an untargeted metabolomics-based analysis of hepatic tissue extracts from rats that have undergone either lifelong or chronic exercise training. For this purpose, 56 hepatic samples were collected and were analyzed by UHPLC-TOF-MS in negative ionization mode. This approach involved untargeted metabolite detection on hepatic tissue extracts accompanied by an in-house retention time/accurate mass library enabling confident metabolite identification. Unsupervised (PCA) and supervised (OPLS-DA) multivariate analysis showed significant metabolic perturbation on a panel of 28 metabolites, including amino acids, vitamins, nucleotides, and sugars. The training regime employed in this study resulted in a probable acceleration of the bioenergetic processes (glycolysis, glycogen metabolism), promoted catabolism of purines, and supplied biosynthetic precursors via the pentose phosphate pathway and pentose and glucuronate interconversions. Overall, the applied methodology was able to discriminate the different training schedules based on the rat liver metabolome.

Is Current Practice Adhering to Guidelines Proposed for Metabolite Identification in LC-MS Untargeted Metabolomics? A Meta-Analysis of the Literature.

Metabolite identification remains a bottleneck and a still unregulated area in untargeted LC-MS metabolomics. The metabolomics research community and, in particular, the metabolomics standards initiative (MSI) proposed minimum reporting standards for metabolomics including those for reporting metabolite identification as long ago as 2007. Initially, four levels were proposed ranging from level 1 (unambiguously identified analyte) to level 4 (unidentified analyte). This scheme was expanded in 2014, by independent research groups, to give five levels of confidence. Both schemes provided guidance to the researcher and described the logical steps that had to be made to reach a confident reporting level. These guidelines have been presented and discussed extensively, becoming well-known to authors, editors, and reviewers for academic publications. Despite continuous promotion within the metabolomics community, the application of such guidelines is questionable. The scope of this meta-analysis was to systematically review the current LC-MS-based literature and effectively determine the proportion of papers following the proposed guidelines. Also, within the scope of this meta-analysis was the measurement of the actual identification levels reported in the literature, that is to find how many of the published papers really reached full metabolite identification (level 1) and how many papers did not reach this level.

Quality assurance and quality control reporting in untargeted metabolic phenotyping: mQACC recommendations for analytical quality management.

BACKGROUND: Demonstrating that the data produced in metabolic phenotyping investigations (metabolomics/metabonomics) is of good quality is increasingly seen as a key factor in gaining acceptance for the results of such studies. The use of established quality control (QC) protocols, including appropriate QC samples, is an important and evolving aspect of this process. However, inadequate or incorrect reporting of the QA/QC procedures followed in the study may lead to misinterpretation or overemphasis of the findings and prevent future metanalysis of the body of work. OBJECTIVE: The aim of this guidance is to provide researchers with a framework that encourages them to describe quality assessment and quality control procedures and outcomes in mass spectrometry and nuclear magnetic resonance spectroscopy-based methods in untargeted metabolomics, with a focus on reporting on QC samples in sufficient detail for them to be understood, trusted and replicated. There is no intent to be proscriptive with regard to analytical best practices; rather, guidance for reporting QA/QC procedures is suggested. A template that can be completed as studies progress to ensure that relevant data is collected, and further documents, are provided as on-line resources. KEY REPORTING PRACTICES: Multiple topics should be considered when reporting QA/QC protocols and outcomes for metabolic phenotyping data. Coverage should include the role(s), sources, types, preparation and uses of the QC materials and samples generally employed in the generation of metabolomic data. Details such as sample matrices and sample preparation, the use of test mixtures and system suitability tests, blanks and technique-specific factors are considered and methods for reporting are discussed, including the importance of reporting the acceptance criteria for the QCs. To this end, the reporting of the QC samples and results are considered at two levels of detail: "minimal" and "best reporting practice" levels.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC).

INTRODUCTION: The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research. OBJECTIVES: This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data. RESULTS: The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities. CONCLUSIONS: The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

A HILIC-MS/MS method development and validation for the quantitation of 13 acylcarnitines in human serum.

Acylcarnitines are essential diagnostic markers for complex diseases and fatty acid metabolism disorders, and play an important role in cardiovascular diseases. Herein, a HILIC-MS/MS method was developed and validated for the rapid quantitation of the acylcarnitines C2, C3, C4, C5, C6, C8, C10, C12, C14, C16, C18, C18:1 and C18:2 in human serum. RPLC and HILIC modes were tested, and HILIC was selected since it provided optimum analyte separation. Intra- and interday accuracy ranged from 90.4% to 114% and from 96% to 112%, respectively, while intra- and interday precision ranged from 0.37% to 13.7% and from 1.3% to 9.5%, respectively. A limit of quantitation (LOQ) of 78.1 ng/mL was found for C2, 2.4 ng/mL for C3, C18:1 and C18:2, and 1.2 ng/mL for C4, C5, C6, C8, C10, C12, C14, C16, and C18. Method validation was performed in accordance with bioanalytical method guidelines. Subsequently the method was applied in the analysis of approximately 1040 samples from patients with coronary artery disease.

Liquid chromatography-mass spectrometry method for the determination of polyethylene terephthalate and polybutylene terephthalate cyclic oligomers in blood samples.

Food contact materials (FCM) polyethylene terephthalate (PET) and polybutylene terephthalate (PBT) used extensively in food packaging may contain cyclic oligomers which may migrate into food and thus cause toxic effects on human health. A simple, fast, and sensitive ultra-high-performance liquid chromatography method quadrupole time-of-flight mass spectrometer was developed for the analysis of 7 cyclic oligomers in post-mortem blood samples. The targeted analytes were separated on a Waters BEH C18 (150 × 2.1 mm, 1.7 µm) analytical column by gradient elution. Calibration curves were constructed based on standard solutions and blood samples and Student's t-test was applied to evaluate the matrix effect. The LODs ranged from 1.7 to 16.7 µg mL-1, while the method accuracy was assessed by recovery experiments and resulting within the range 84.2-114.6%. Such an analytical method for the determination of PET and PBT cyclic oligomers in biological samples is reported for the first time. The developed methodology allows the determination of these oligomers in blood providing a useful analytical tool to assess the exposure and thus the potential hazard and health risks associated with these non-intentionally added substances (NIAS) from PET and PBT FCM through food consumption. The method was validated and successfully applied to the analysis of 34 post-mortem whole blood samples. Polyethylene terephthalate trimer was detected in four of them, for the first time in literature.

UHPLC-MS/MS method for the simultaneous determination of nicotine and tobacco-specific nitrosamines NNN and NNK for use in preclinical studies.

A new method was developed and validated for the simultaneous determination of nicotine and tobacco-specific nitrosamines (TSNAs) 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N-nitrosonornicotine (NNN) in two different tests matrices: porcine buccal epithelium tissue and phosphate buffered saline (PBS) extracts of smokeless tobacco products. The novelty of this work is in the development of a liquid chromatography tandem mass spectrometry method that can provide simultaneous quantification of trace levels of TSNAs and high concentrations of nicotine in biological media. Precision, accuracy, and stability were evaluated during method validation to ensure the method was fit for purpose. Several sample preparation and extraction methods were evaluated to minimize matrix effects and maximize analyte recoveries. The method was accurate in the range of 81.1% - 117%; repeatability was estimated in the range of 1.5% - 13.6% across multiple concentrations. The linear regression correlation coefficient (R2) was greater than 0.9959 for all analytes, and the limit of detection (LOD) was determined for nicotine, NNK, and NNN at 1 ng/mL 0.005 ng/mL, and 0.006 ng/ mL, respectively. Our method was found to be appropriate for the analysis of nicotine, NNN, and NNK in the porcine buccal epithelium and PBS extracts of smokeless tobacco products.

Blood Metabolomics May Discriminate a Sub-Group of Patients with First Demyelinating Episode in the Context of RRMS with Increased Disability and MRI Characteristics Indicative of Poor Prognosis.

Biomarker research across the health-to-disease continuum is being increasingly applied. We applied blood-based metabolomics in order to identify patient clusters with a first demyelinating episode, and explored the prognostic potential of the method by thoroughly characterizing each cluster in terms of clinical, laboratory and MRI markers of established prognostic potential for Multiple Sclerosis (MS). Recruitment consisted of 11 patients with Clinically Isolated Syndrome (CIS), 37 patients with a first demyelinating episode in the context of Relapsing-Remitting MS (RRMS) and 11 control participants. Blood-based metabolomics and hierarchical clustering analysis (HCL) were applied. Constructed OPLS-DA models illustrated a discrimination between patients with CIS and the controls (p = 0.0014), as well as between patients with RRMS and the controls (p = 1 × 10−5). Hierarchical clustering analysis (HCL) for patients with RRMS identified three clusters. RRMS-patients-cluster-3 exhibited higher mean cell numbers in the Cerebro-spinal Fluid (CSF) compared to patients with CIS (18.17 ± 6.3 vs. 1.09 ± 0.41, p = 0.004). Mean glucose CSF/serum ratio and infratentorial lesion burden significantly differed across CIS- and HCL-derived RRMS-patient clusters (F = 14.95, p < 0.001 and F = 6.087, p = 0.002, respectively), mainly due to increased mean values for patients with RRMS-cluster-3. HCL discriminated a cluster of patients with a first demyelinating episode in the context of RRMS with increased disability, laboratory findings linked with increased pathology burden and MRI markers of poor prognosis.

Correlation of the severity of coronary artery disease with patients' metabolic profile- rationale, design and baseline patient characteristics of the CorLipid trial.

BACKGROUND: Coronary artery disease (CAD) remains one of the leading causes of mortality and morbidity worldwide. As oxygen and nutrient supply to the myocardium significantly decrease during ischemic periods, important changes occur regarding myocardial intermediary energy metabolism. Metabolomics is an emerging field in systems biology, which quantifies metabolic changes in response to disease progression. This study aims to evaluate the diagnostic utility of plasma metabolomics-based biomarkers for determining the complexity and severity of CAD, as it is assessed via the SYNTAX score. METHODS: Corlipid is a prospective, non-interventional cohort trial empowered to enroll 1065 patients with no previous coronary intervention history, who undergo coronary angiography in University Hospital AHEPA, Thessaloniki. Venous blood samples are collected before coronary angiography. State-of the-art analytical methods are performed to calculate the serum levels of novel biomarkers: ceramides, acyl-carnitines, fatty acids, and proteins such as galectin-3, adiponectin, and the ratio of apolipoprotein B/apolipoprotein A1. Furthermore, all patients will be categorized based on the indication for coronary angiography (acute coronary syndrome, chronic coronary syndrome, preoperative coronary angiography) and on the severity of CAD using the SYNTAX score. Follow-up of 12 months after enrollment will be performed to record the occurrence of major adverse cardiovascular events. A risk prediction algorithm will be developed by combining clinical characteristics with established and novel biomarkers to identify patients at high risk for complex CAD based on their metabolite signatures. The first patient was enrolled in July 2019 and completion of enrollment is expected until May 2021. DISCUSSION: CorLipid is an ongoing trial aiming to investigate the correlation between metabolic profile and complexity of coronary artery disease in a cohort of patients undergoing coronary angiography with the potential to suggest a decision-making tool with high discriminative power for patients with CAD. To our knowledge, Corlipid is the first study aspiring to create an integrative metabolomic biomarkers-based algorithm by combining metabolites from multiple classes, involved in a wide range of pathways with well-established biochemical markers. Trial registration CorLipid trial registration: ClinicalTrials.gov number: NCT04580173. Registered 8 October 2020-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04580173 .

Evaluation of Cocaine Effect on Endogenous Metabolites of HepG2 Cells Using Targeted Metabolomics.

Cocaine toxicity has been a subject of study because cocaine is one of the most common and potent drugs of abuse. In the current study the effect of cocaine on human liver cancer cell line (HepG2) was assessed. Cocaine toxicity (IC50) on HepG2 cells was experimentally calculated using an XTT assay at 2.428 mM. The metabolic profile of HepG2 cells was further evaluated to investigate the cytotoxic activity of cocaine at 2 mM at three different time points. Cell medium and intracellular material samples were analyzed with a validated HILIC-MS/MS method for targeted metabolomics on an ACQUITY Amide column in gradient mode with detection on a triple quadrupole mass spectrometer in multiple reaction monitoring. About 106 hydrophilic metabolites from different metabolic pathways were monitored. Multivariate analysis clearly separated the studied groups (cocaine-treated and control samples) and revealed potential biomarkers in the extracellular and intracellular samples. A predominant effect of cocaine administration on alanine, aspartate, and glutamate metabolic pathway was observed. Moreover, taurine and hypotaurine metabolism were found to be affected in cocaine-treated cells. Targeted metabolomics managed to reveal metabolic changes upon cocaine administration, however deciphering the exact cocaine cytotoxic mechanism is still challenging.

Serum-Targeted HILIC-MS Metabolomics-Based Analysis in Infants with Ureteropelvic Junction Obstruction.

Ureteropelvic junction obstruction (UPJO) constitutes the predominant cause of obstructive nephropathy in both neonates and infants. Fundamental questions regarding UPJO's mechanism, assessment, and treatment still remain unanswered. The aim of the present study was to elucidate potential differences through serum metabolic profiling of surgical cases of infants with UPJO compared to both nonsurgical cases and healthy age-matched controls. Early diagnosis of renal dysfunction in this cohort based on highlighted biomarkers was the ultimate goal. Thus, serum samples were collected from 20 patients preoperatively, 19 patients with mild stenosis treated conservatively, and 17 healthy controls. All samples were subjected to targeted metabolomics analysis by hydrophilic interaction liquid chromatography coupled to mass spectrometry (HILIC LC-MS/MS). Both univariate and multivariate statistical analyses were performed. Principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) score plots showed that the studied groups differed significantly, with a panel of metabolites, including creatinine, tryptophan, choline, and aspartate, distinguishing patients who required surgery from those followed by systematical monitoring as well as from healthy controls, showing high performance as indicators of UPJO disease.

Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners.

INTRODUCTION: The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics. OBJECTIVES: In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics. METHODS: All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach. RESULTS: For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%). CONCLUSIONS: Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.

Effect of exercise on key pharmacokinetic parameters related to metformin absorption in healthy humans: A pilot study.

Exercise is widely accepted as having therapeutic effects; thus, it is important to know whether it interacts with medications. The aim of the present pilot study was to examine the effect of high-intensity interval exercise (known to have antidiabetic action) on key pharmacokinetic parameters related to absorption of metformin (the first-line medication against type 2 diabetes). Ten healthy men participated in two sessions, spaced one to two weeks apart in random, counterbalanced order. In both sessions, participants received 1000 mg of metformin orally, 1-1.5 hours after breakfast. Then, they either ran for 60 minutes at alternating intensity, starting at 40 minutes after metformin administration, and rested without food consumption over the next 3 hours or they rested without food consumption during the entire testing period. Venous blood samples were collected before and at 0.5, 2, 2.5, 3, 3.5, 4, and 4.5 hours after metformin administration for metformin determination by liquid chromatography-mass spectrometry. Capillary blood samples were also collected for lactate and glucose measurements. Data from the two sessions were compared through Wilcoxon or Student's t test, as appropriate. Maximum plasma concentration of metformin (Cmax ) was higher at exercise compared to rest (P = .059). Time to reach Cmax (Tmax ) decreased with exercise (P = .009), and the area under the metformin concentration vs time curve was higher at exercise (P = .047). The addition of exercise to metformin administration did not cause hypoglycemia or lactic acidosis. In conclusion, our results provide the first evidence that pharmacokinetic values related to metformin absorption are affected by exercise.

Wine and grape marc spirits metabolomics.

INTRODUCTION: Mass spectrometry (MS)-based and nuclear magnetic resonance (NMR) spectroscopic analyses play a key role in the field of metabolomics due to their important advantages. The use of metabolomics in wine and grape marc spirits allows a more holistic perspective in monitoring and gaining information on the making processes and thus it can assist on the improvement of their quality. OBJECTIVES: This review surveys the latest metabolomics approaches for wine and grape marc spirits with a focus on the description of MS-based and NMR spectroscopic analytical techniques. METHODS: We reviewed the literature to identify metabolomic studies of wine and grape marc spirits that were published until the end of 2017, with the key term combinations of 'metabolomics', 'wine' and 'grape marc spirits'. Through the reference lists from these studies, additional articles were identified. RESULTS: The results of this review showed that the application of different metabolomics approaches has significantly increased the knowledge of wine metabolome and grape marc spirits; however there is not yet a single analytical platform that can completely separate, detect and identify all metabolites in one analysis. CONCLUSIONS: The authentication and quality control of wines and grape marc spirits has to be taken with caution, since the product's chemical composition could be affected by many factors. Despite intrinsic limitations, NMR spectroscopy and MS based strategies remain the key analytical methods in metabolomics studies. Authenticity, traceability and health issues related to their consumption are the major research initiatives in wine and grape marc spirits metabolomics analysis.

Targeted LC-MS/MS for the evaluation of proteomics biomarkers in the blood of neonates with necrotizing enterocolitis and late-onset sepsis.

Late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) are severe life-threatening conditions for neonates. Accurate, early diagnosis and timely initiation of treatment are crucial. Non-specific overlapping clinical signs along with the non-sensitive/specific diagnostic tools set obstacles to speedy, trustful diagnosis including differential diagnosis. The objective of this study was to evaluate the potential of targeted LC-MS/MS proteomics in identifying diagnostic biomarkers of NEC or LOS. We conducted a prospective case-control study evaluating serum proteomics profiles of 25 NEC, 18 LOS, and an equal number of matched control neonates, over three sampling points. Eighty-three concatemers and synthetic peptides belonging to 47 protein markers of the two diseases were selected after thorough literature search. A novel selected reaction monitoring (SRM), LC-MS/MS method was developed for their analysis and evaluation as potential biomarkers. Multivariate and univariate statistical analyses highlighted significant proteins in differentiating LOS and NEC neonates and diseased from controls. Moreover, panels of proteins were tested for their ability to distinguish LOS from NEC and controls. We suggest two panels of three proteins each, exhibiting very high diagnostic value for LOS and excellent diagnostic performance at the critical LOS-NEC differentiation, reaching an AUC ROC value close to 1 (0.999). These panels constitute a valuable starting point for further validation with broader cohorts of neonates, aiming to improve the clinical practice. Graphical abstract ᅟ.