Transcription Factor Analysis to Investigate Immunosenescence in Rheumatoid Arthritis Patients.

Rheumatoid arthritis (RA) is linked to various signs of advanced aging, such as premature immunosenescence which occurs due to decline in regenerative ability of T cells. RA T cells develop a unique aggressive inflammatory senescent phenotype with an imbalance of Th17/T regulatory (Treg) cell homeostasis and presence of CD28- T cells. The phenotypic analysis and characterization of T cell subsets become necessary to ascertain if any functional deficiencies exist within with the help of transcription factor (TF) analysis. These subset-specific TFs dictate the functional characteristics of T-cell populations, leading to the production of distinct effector cytokines and functions. Examining the expression, activity, regulation, and genetic sequence of TFs not only aids researchers in determining their importance in disease processes but also aids in immunological monitoring of patients enrolled in clinical trials, particularly in evaluating various T-cell subsets [Th17 (CD3+CD4+IL17+RORγt+) cells and T regulatory (Treg) (CD3+CD4+CD25+CD127-FOXP3+) cells], markers of T-cell aging [aged Th17 cells (CD3+CD4+IL17+RORγt+CD28-), and aged Treg cells (CD3+CD4+CD25+CD127-FOXP3+CD28-)]. In this context, we propose and outline the protocols for assessing the expression of TFs in aged Th17 and Treg cells, highlighting the crucial aspects of this cytometric approach.

Role of per- and polyfluoroalkyl substances in the cardiorenal system: Unraveling crosstalk from the network of pollutants and phenotypes.

Although per- and polyfluoroalkyl substances (PFAS) have been frequently linked to cardiovascular and renal disease separately, evidence remains scarce regarding their systematic effect. Therefore, we recruited 546 newly diagnosed acute coronary syndrome (ACS) patients and detected seven myocardial enzymes and six kidney function biomarkers. Twelve PFAS were also assessed with ultra-high-performance liquid chromatography-tandem mass spectrometry. Generalized linear model and restricted cubic spline model were applied to single pollutant analysis. Quantile g-computation was used for mixture analysis. Network model was utilized to identify central and bridge nodes of pollutants and phenotypes. In the present study, perfluorohexane sulfonic acid was positively associated with uric acid (UA) (ß= 0.04, 95% confidence interval (CI): 0.01, 0.07), and perfluorobutanoic acid was negatively associated with estimated glomerular filtration rate (ß= -0.04, 95% CI: -0.07, -0.01) but positively associated with UA (ß= 0.03, 95% CI: 0.01, 0.06). In mixture analysis, each quantile increase in the PFAS mixture was significantly associated with UA (ß= 0.08, 95% CI: 0.04, 0.11). Network analysis revealed that perfluorooctanoate, UA, and myoglobin were denoted as bridge nodes, and the first principal component of lactate dehydrogenase and creatine kinase- myocardial band was identified as the node with the highest strength and expected influence. This study investigates the systematic impact of PFAS exposure through cardiorenal interaction network, which highlights that PFAS may serve as an upstream approach in UA-modulated cardiorenal network to affect cardiorenal system comprehensively.

Proteomic insights from extracellular vesicles into the molecular mechanisms of health effects induced by Per- and polyfluoroalkyl substances.

Per- and polyfluoroalkyl substances (PFASs) can induce a range of adverse health effects, with the precise molecular mechanisms remaining elusive. Extracellular vesicles (EVs) have demonstrated their potential to elucidate unknown molecular mechanisms. Building upon the close alignment of their biological functions with the observed health effects of PFASs, this study innovatively focuses on proteomic insights from EVs into the molecular mechanisms underlying the systemic health effects of PFASs. Through rat exposure experiments and proteomics technology, it not only demonstrated the occurrence of PFASs in EVs but also revealed the alterations in the serum EVs and the expression of their protein cargos following mixed exposure to PFASs, leading to changes in related pathways. These changes encompass various biological processes, including proteasome activity, immune response, cytoskeletal organization, oxidative stress, cell signaling, and nervous system function. Particularly noteworthy is the uncovering of the activation of the proteasome pathway, highlighting significant key contributing proteins. These novel findings provide a new perspective for exploring the molecular mechanism underlying the systemic health effects of PFASs and offer reliable screening for potential biomarkers. Additionally, comparisons with serum confirmed the potential of serum EVs as biological responders and measurable endpoints for evaluating PFASs-induced toxicity.

Associations of polycyclic aromatic hydrocarbons exposure with serum uric acid and hyperuricemia in US adults: The role of systemic inflammation.

The associations of polycyclic aromatic hydrocarbon (PAH) exposure with serum uric acid (SUA) or hyperuricemia have been rarely assessed. We aimed to investigate the relationships between urinary PAH metabolites and SUA or hyperuricemia among US adults and to explore the mediating role of systemic inflammation in the associations. A total of 10,307 US adults were conducted to assess the associations of seven urinary hydroxy­PAH with SUA and hyperuricemia and evaluate the role of C-reactive protein (CRP), a biomarker of systemic inflammation, in such associations. Results showed that each 1-unit increase in ln-transformed 2-hydroxynaphthalene (2-OHNa), 1-hydroxyphenanthrene (1-OHPh), 2&3-hydroxyphenanthrene (2&3-OHPh) and total hydroxyphenanthrene (ΣOHPh) was associated with a 1.68 (95% confidence interval (CI): 0.19 to 3.17), 2.46 (0.78 to 4.13), 3.34 (1.59 to 5.09), and 2.99 (1.23 to 4.75) µmol/L increase in SUA, and a 8% (odds ratio (OR): 1.08, 1.02 to 1.15), 9% (OR: 1.09, 1.02 to 1.18), 13% (OR: 1.13, 1.05 to 1.22), and 12% (OR: 1.12, 95% CI: 1.03, 1.21) increase in hyperuricemia, respectively. Co-exposure of seven PAHs was positively associated with SUA and hyperuricemia, with 2&3-OHPh showing the highest weight (components weights: 0.83 and 0.78, respectively). The CRP mediated 11.47% and 10.44% of the associations of ΣOHPh and 2&3-OHPh with SUA and mediated 8.60% and 8.62% in associations of ΣOHPh and 2&3-OHPh with hyperuricemia, respectively. In conclusion, internal levels of PAH metabolites were associated with elevated SUA levels and the increased risk of hyperuricemia among US adults, and CRP played a mediating role in the associations.

Isolation, Culture, and Quality Assessment of Clinical-Grade Corneal Stromal Stem Cells.

The challenge of treating corneal scarring through keratoplasties lies in the limited availability of donor tissue. Various studies have shown the therapeutic use of cultivated corneal stromal stem cells (CSSCs) to mitigate tissue inflammation and suppress fibrosis and scar tissue formation in preclinical corneal wound models. To develop CSSC therapy for clinical trials on patients with corneal scarring, it is necessary to generate clinical-grade CSSCs in compliant to Good Manufacturing Practice (GMP) regulations. This chapter elucidates human CSSC isolation, culture, and cryopreservation under GMP-compliant conditions. It underscores quality assessment encompassing morphological traits, expression of stemness markers, anti-inflammatory activity, and keratocyte differentiation potency.

Identifying Putative Biomarkers of Foodborne Pathogens Using a Metabolomic Approach.

Metabolomics is the study of low molecular weight biochemical molecules (typically <1500 Da) in a defined biological organism or system. In case of food systems, the term "food metabolomics" is often used. Food metabolomics has been widely explored and applied in various fields including food analysis, food intake, food traceability, and food safety. Food safety applications focusing on the identification of pathogen-specific biomarkers have been promising. This chapter describes a nontargeted metabolite profiling workflow using gas chromatography coupled with mass spectrometry (GC-MS) for characterizing three globally important foodborne pathogens, Escherichia coli O157:H7, Listeria monocytogenes, and Salmonella enterica, from selective enrichment liquid culture media. The workflow involves a detailed description of food spiking experiments followed by procedures for the extraction of polar metabolites from media, the analysis of the extracts using GC-MS, and finally chemometric data analysis using univariate and multivariate statistical tools to identify potential pathogen-specific biomarkers.

Persistent acute kidney injury biomarkers: A systematic review and meta-analysis.

BACKGROUND: Various biomarkers reportedly predict persistent acute kidney injury (AKI) despite their varying predictive performance across clinical trials. This study aims to compare the accuracy of various biomarkers in predicting persistent AKI in different populations and regions. METHODS: In this meta-analysis, we searched for urinary C-C motif chemokine ligand 14 (CCL14), Tissue inhibitor of metalloproteinase-2&insulin-like growth factor-binding protein-7 (TIMP-2&IGFBP7), Neutrophil Gelatinase-Associated Lipocalin (NGAL), plasma Cystatin C (pCysC), Soluble urokinase plasminogen activator receptor (suPAR), Proenkephalin (PenK) and urinary dickkopf-3:urinary creatinine (uDKK3:uCr) from various databases including Medline, PubMed, Embase, and Cochrane. This was geared towards predicting persistent AKI in adults (>18 years). Hierarchically summarized subject work characteristic curves (HSROC) and diagnostic odds ratio (DOR) values were used to summarize the diagnostic accuracy of the biomarkers. Further, meta-regression and subgroup analyses were carried out to identify sources of heterogeneity as well as evaluate the best predictive biomarkers in different populations and regions. RESULTS: We screened 31 studies from 2,356 studies and assessed the diagnostic value of 7 biomarkers for persistent AKI. Overall, CCL14 had the best diagnostic efficacy with an AUC of 0.79 (95 % CI 0.75-0.82), whereas TIMP-2 & IGFBP7, NGAL, and pCysC had diagnostic efficacy of 0.75 (95 % CI 0.71-0.79),0.71 (95 % CI 0.67-0.75), and 0.7007, respectively. Due to a limited number of studies, PenK, uDKK3:uCr, and suPAR were not subjected to meta-analysis; however, relevant literature reported diagnostic efficacy above 0.70. Subgroup analyses based on population, region, biomarker detection time, AKI onset time, and AKI duration revealed that in the intensive care unit (ICU) population, the AUC of CCL14 was 0.8070, the AUC of TIMP-2 & IGFBP7 was 0.726, the AUC of pCysC was 0.72, and the AUC of NGAL was 0.7344; in the sepsis population, the AUC of CCL14 was 0.85, the AUC of TIMP-2&IGFBP7 was 0.7438, and the AUC of NGAL was 0.544; in the post-operative population, the AUC of CCL14 was 0.83-0.93, the AUC of TIMP-2&IGFBP7 was 0.71, and the AUC of pCysC was 0.683. Regional differences were observed in biomarker prediction of persistent kidney injury, with AUCs of 0.8558 for CCL14, 0.7563 for TIMP-2 & IGFBP7, and 0.7116 for NGAL in the Eurasian American population. In the sub-African population, TIMP-2 & IGFBP7 had AUCs of 0.7945, 0.7418 for CCL14, 0.7097 for NGAL, and 0.7007 for pCysC. for TIMP-2 & IGFBP7 was 0.7945, AUC for CCL14 was 0.7418, AUC for NGAL was 0.7097, and AUC for pCysC was 0.7007 in the sub-African population. Duration of biomarker detection, AKI onset, and AKI did not influence the optimal predictive performance of CCL14. Subgroup analysis and meta-regression of CCL14-related studies revealed that CCL14 is the most appropriate biomarker for predicting persistent stage 2-3 AKI, with heterogeneity stemming from sample size and AKI staging. CONCLUSION: This meta-analysis discovered CCL14 as the best biomarker to predict persistent AKI, specifically persistent stage 2-3 AKI.

Copeptin associates with major adverse cardiovascular events in patients on maintenance hemodialysis.

BACKGROUND: End-stage renal disease (ESRD) necessitating hemodialysis pose substantial cardiovascular risks, with cardiovascular disease (CVD) as a leading cause of mortality. Biomarkers like copeptin have emerged as potential indicators of cardiovascular stress and prognosis in CKD populations. OBJECTIVE: This study aimed to assess the prognostic value of copeptin in predicting major adverse cardiovascular events (MACEs) among hemodialysis patients, alongside traditional cardiac biomarkers. METHODS: ESRD patients undergoing maintenance hemodialysis were enrolled. Copeptin levels were measured, and patients were followed for MACEs, defined as cardiovascular deaths, myocardial infarction, stroke, or heart failure-related hospitalizations. Cox proportional-hazards models were used to evaluate the association between copeptin and outcomes, adjusting for relevant covariates. RESULTS: Among 351 patients followed for a median of 22.7 months, elevated copeptin levels were significantly associated with an increased risk of MACEs (HR 1.519, 95 % CI 1.140 to 2.023; p = 0.00425). Copeptin demonstrated predictive capability across multiple statistical tests (Log-rank p = 0.024; Gehan p < 0.001; Tarone-Ware p < 0.001; Peto-Peto p = 0.027), although significance was attenuated in pairwise comparisons post-adjustment for multiple testing. Combining copeptin with NT-proBNP or hs-cTnT further enhanced risk stratification for MACEs. CONCLUSION: Elevated copeptin levels independently predict adverse cardiovascular outcomes in hemodialysis patients. Integrating copeptin with traditional cardiac biomarkers may refine risk stratification and guide personalized therapeutic strategies in this high-risk population.

Interval-specific likelihood ratios and probability-based models for interpreting combined CSF biomarkers for Alzheimer's disease.

BACKGROUND: In Alzheimer's disease (AD) diagnosis, a cerebrospinal fluid (CSF) biomarker panel is commonly interpreted with binary cutoff values. However, these values are not generic and do not reflect the disease continuum. We explored the use of interval-specific likelihood ratios (LRs) and probability-based models for AD using a CSF biomarker panel. METHODS: CSF biomarker (Aß1-42, tTau and pTau181) data for both a clinical discovery cohort of 241 patients (measured with INNOTEST) and a clinical validation cohort of 129 patients (measured with EUROIMMUN), both including AD and non-AD dementia/cognitive complaints were retrospectively retrieved in a single-center study. Interval-specific LRs for AD were calculated and validated for univariate and combined (Aß1-42/tTau and pTau181) biomarkers, and a continuous bivariate probability-based model for AD, plotting Aß1-42/tTau versus pTau181 was constructed and validated. RESULTS: LR for AD increased as individual CSF biomarker values deviated from normal. Interval-specific LRs of a combined biomarker model showed that once one biomarker became abnormal, LRs increased even further when another biomarker largely deviated from normal, as replicated in the validation cohort. A bivariate probability-based model predicted AD with a validated accuracy of 88% on a continuous scale. CONCLUSIONS: Interval-specific LRs in a combined biomarker model and prediction of AD using a continuous bivariate biomarker probability-based model, offer a more meaningful interpretation of CSF AD biomarkers on a (semi-)continuous scale with respect to the post-test probability of AD across different assays and cohorts.

Biological variation of methylmalonic acid in urine in spanish population.

BACKGROUND-AIM: Methylmalonic acid (MMA) is currently the best biomarker of functional vitamin B12 deficiency. However, for a correct interpretation of the patient's results it is necessary to know its biological variation (BV). No BV data are available for urine MMA values, as measured by mass spectrometry. Hence, the aim of this study was to estimate the within- and between-person coefficients of variation (CVw, CVg) for MMA in a healthy population, and the associated index of individuality (II), as well as to define quality specifications based on BV and the reference change value (RCV). METHODS: Random urine samples from 34 healthy volunteers were collected over four consecutive weeks. Samples were stored at -80 °C until analysis in a single analytical run. MMA excretion was quantified by tandem liquid chromatography coupled to mass spectrometry (HPLC-MS/MS). Results were normalized to urine creatinine. The coefficients of variation were estimated by CV-ANOVA. Confidence intervals (95 %) were calculated. Quality specifications were defined according to international recommendations. RESULTS: A total of 128 samples were included. The coefficients of variation were CVw = 35.7 % (26.1-45.3) and CVg = 67.7 % (58.3-77.0). The associated II was 0.5 and the RCV was 88.1 %. CONCLUSION: Considering the II obtained, MMA in urine has high individuality, therefore, RCV is better to evaluate serial clinical results. Our results will contribute to a better clinical interpretation of this biomarker and will represent a great aid when defining analytical performance specifications for this magnitude.

Dual excitation channel ratiometric fluorescent probes for visual and fluorescent detection of anthrax spore biomarker and tetracycline hydrochloride.

Long-term and excessive use of tetracycline hydrochloride (TC) can lead to its accumulation in the environment, which can cause water contamination, bacterial resistance, and food safety problems. 2,6-Pyridine dicarboxylic acid (DPA) is a major biomarker of Bacillus anthracis spores, and its rapid and sensitive detection is of great significance for disease prevention and counter-terrorism. A bifunctional ratiometric fluorescent nanoprobe has been fabricated to detect DPA and TC. 3,5-dicarboxyphenylboronic acid (BOP) was intercalated into layered europium hydroxide (LEuH) by the ion-exchange method and exfoliated into nanosheets as a fluorescent nanoprobe (PNP). DPA and TC could significantly enhance the red fluorescence of Eu3+ through the antenna effect under different excitation wavelengths, while the fluorescence of BOP can be used as a reference based on the constant emission intensity, realizing ratiometric detection. A low limit of detection (LOD) for the target (DPA: 9.7 nM, TC: 21.9 nM) can be achieved. In addition, visual detection of DPA and TC was realized using color recognition software based on the obvious color changes. This is the first ratiometric fluorescent nanoprobe based on layered rare-earth hydroxide (LRH) for the detection of DPA and TC simultaneously, which opens new ideas in the design of multifunctional probes.

Pediatric reference values of NT-proBNP and Galectin-3 based on a French cohort.

BACKGROUND: In pediatric cardiology, the fact that some new biomarkers have assay-specific normal values has to be considered for correct clinical decisions. The current study aimed to provide age-adjusted normative values for NT-proBNP and Galectin-3 using the Abbott immunoassay system from a prospective French pediatric cohort sera collection and to validate our data for NT-proBNP on a second retrospective cohort. METHODS: We analyzed 283 consecutive samples for NT-proBNP and 140 samples for Galectin-3 collected from apparently healthy children (0-18 years) with outpatient treatment at our institution (Hôpital Necker-Enfants malades, Paris, France) during 24 months. RESULTS: For NT-proBNP and Galectin-3, we establish four age partitions, respectively two (<2 years / >2 years) and establish upper reference values and their 90 % CI for each biomarker (Galectin-3 (ng/mL): 56 [44-70] / 26 [23-29]). We evaluated the diagnostic performance of our upper reference values of NT-proBNP on a retrospective cohort (n = 428) with positive predictive value of 0.92. CONCLUSIONS: Using Abbott immunoassay system, we report age-specific reference values for NT-proBNP and for the first time for Galectin-3 in a healthy French pediatric cohort. These data call for larger cohort studies to define more robustly percentiles and diagnostic performance for NT-proBNP.

Accuracy study of Angiotensin 1-7 composite index test to predict pulmonary fibrosis and guide treatment.

BACKGROUND: Pulmonary fibrosis can develop after acute respiratory distress syndrome (ARDS). The hypothesis is we are able to measure phenotypes that lie at the origin of ARDS severity and fibrosis development. The aim is an accuracy study of prognostic circulating biomarkers. METHODS: A longitudinal study followed COVID-related ARDS patients with medical imaging, pulmonary function tests and biomarker analysis, generating 444 laboratory data. Comparison to controls used non-parametrical statistics; p < 0·05 was considered significant. Cut-offs were obtained through receiver operating curve. Contingency tables revealed predictive values. Odds ratio was calculated through logistic regression. RESULTS: Angiotensin 1-7 beneath 138 pg/mL defined Angiotensin imbalance phenotype. Hyper-inflammatory phenotype showed a composite index test above 34, based on high Angiotensin 1-7, C-Reactive Protein, Ferritin and Transforming Growth Factor-ß. Analytical study showed conformity to predefined goals. Clinical performance gave a positive predictive value of 95 % (95 % confidence interval, 82 %-99 %), and a negative predictive value of 100 % (95 % confidence interval, 65 %-100 %). Those severe ARDS phenotypes represented 34 (Odds 95 % confidence interval, 3-355) times higher risk for pulmonary fibrosis development (p < 0·001). CONCLUSIONS: Angiotensin 1-7 composite index is an early and objective predictor of ARDS evolving to pulmonary fibrosis. It may guide therapeutic decisions in targeted phenotypes.

(Pre)Clinical Metabolomics Analysis.

Metabolomics is the scientific field with the eager goal to comprehensively analyze the entirety of all small molecules of a biological system, i.e., the metabolome. Over the last few years, metabolomics has matured to become an analytical cornerstone of life science research across diverse fields, from fundamental biochemical applications to preclinical studies, including biomarker discovery and drug development. In this chapter, we provide an introduction to (pre)clinical metabolomics. We define key metabolomics aspects and provide the basis to thoroughly understand the relevance of this field in a biological and clinical context. We present and explain state-of-the-art analytical technologies devoted to metabolomic analysis as well as emerging technologies, discussing both strengths and weaknesses. Given the ever-increasing demand for handling complex datasets, the role of bioinformatics approaches in the context of metabolomic analysis is also illustrated.

Global Metabolomics Using LC-MS for Clinical Applications.

Metabolomics can be used for a multitude of purposes, including monitoring of treatment effects and for increasing the knowledge of the pathophysiology of a wide range of diseases. Global (commonly referred to as "untargeted") metabolomics is hypothesis-generating and provides the opportunity to discover new biomarkers. Being versatile and having a high degree of selectivity and sensitivity, liquid chromatography-mass spectrometry (LC-MS) is the most common technique applied for metabolomics. We here present our global metabolomics LC-electrospray ionization-MS/MS method. The sample preparation procedures for plasma, serum, dried blood spots, urine, and cerebrospinal fluid are simple and nonspecific to reduce the risk of analyte loss. The method is based on reversed-phase chromatography using a diphenyl column. The high-resolution Q Exactive Orbitrap MS with data-dependent acquisition provides MS/MS spectra of a wide range of analytes. Our method covers a large part of the metabolome regarding hydrophobicity and compound class.

Advances in Chiral Metabolomic Profiling and Biomarker Discovery.

Chiral metabolomics entails the enantioselective measurement of the metabolome present in a biological system. Over recent years, it has garnered significant interest for its potential in discovering disease biomarkers and aiding clinical diagnostics. D-Amino acids and D-hydroxy acids, traditionally overlooked as unnatural, are now emerging as novel signaling molecules and potential biomarkers for a range of metabolic disorders, brain diseases, kidney disease, diabetes, and cancer. Despite their significance, simultaneous measurements of multiple classes of chiral metabolites in a biological system remain challenging. Hence, limited information is available regarding the metabolic pathways responsible for synthesizing D-amino/hydroxy acid and their associated pathophysiological mechanisms in various diseases. Capitalizing on recent advancements in sensitive analytical techniques, researchers have developed various targeted chiral metabolomic methods for the analysis of chiral biomarkers. Here, we highlight the pivotal role of chiral metabolic profiling studies in disease diagnosis, prognosis, and therapeutic interventions. Furthermore, we describe cutting-edge chromatographic and mass spectrometry methods that enable enantioselective analysis of chiral metabolites. These advanced techniques are instrumental in unraveling the complexities of disease biomarkers, contributing to the ongoing efforts in disease biomarker discovery.

A Method for Analysis of Oxidized Phospholipids from Biological Samples Using Mass Spectrometry.

Oxidized phospholipids (oxPLs) are generated during innate immunity and inflammation, where they play a variety of biological roles, including regulation of autoimmunity and coagulation. Some are generated by enzymatic reactions, leading to stereo- and regiospecificity, while many others can be formed through nonenzymatic oxidation and truncation and can be used as biomarkers of oxidative stress. Mass spectrometry methods have been developed over many years for oxPL analysis, which can provide robust estimations of molecular species and amounts, where standards are available. Here we present a method used for the analysis of enzymatically-generated oxPL (eoxPL), which allows quantification of mono-hydroxy oxylipin-containing species. We also show profiling of many other partially characterized structures in tissue samples and provide typical chromatograms obtained.

Prostaglandin Metabolites Analysis in Urine by LC-MS/MS.

The analysis of prostaglandin urinary metabolites is valuable for assessing physiological processes and identifying disease biomarkers. These metabolites, derived from the breakdown of prostaglandins, offer a noninvasive means to gauge prostaglandin production and its potential impact on various biological functions. We report an efficient LC-MS method of four commonly analyzed prostaglandin urinary metabolites including tetranor-PGEM (derived from PGE2), tetranor-PGDM, 11ß-PGF2α, and 2,3-dinor-11ß-PGF2α (derived from PGD2). Each metabolite possesses distinct characteristics and clinical applications, collectively contributing to our understanding of prostaglandin-mediated pathways.

Nonenzymatic Oxidized Polyunsaturated Fatty Acid Products in Human Plasma and Urine Samples by LC-QTOF-MS/MS.

Oxidative stress induces autooxidation of polyunsaturated fatty acids, producing numerous isoprostanoids and isofuranoids. These oxidized products are measurable in human plasma and urine and serve as oxidative stress biomarkers for chronic diseases. This chapter details the preparation and measurement of α-linolenic acid-derived phytoprostanes and phytofurans in human samples using liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (LC-QToF-MS/MS).

Rapid Lipid Mediator Profiling by Convergence Chromatography-MS/MS.

Bioactive lipid mediators derived from arachidonic acid constitute an attractive pool of metabolites that reflect cellular function and signaling, as well as potential biomarkers that may respond quantitatively to disease progression or pharmacological treatment. Their quantitative measurement in biological samples is complicated by the number of isomers that share common structural features, which are not easily distinguished by immunoassays or reverse phase chromatography-tandem mass spectrometry. Here, we present a method that enables the rapid analysis of a panel of over 25 biologically important eicosanoids in a 96-well format for cell culture supernatants, plasma, and organ tissues using convergence chromatography-tandem mass spectrometry to resolve these analytes of interest.