A miniaturized stir bar sorptive dispersive microextraction method for the determination of bisphenols in follicular fluid using a magnetic covalent organic framework.

BACKGROUND: Bisphenols, particularly bisphenol A (BPA), are the primary monomers used as additives in the manufacturing of many consumer products. The exposure to these compounds is related to endocrine-disrupting and reproductive effects, among others. For this reason, the development of analytical methods for their determination in biological matrixes is needed to monitor the population exposure to these compounds. Their quantification at ovarian level (i.e., follicular fluid) is interesting for the assessment of the bisphenol content to draw conclusions about infertility problems. However, the background does not meet all requirements by focusing mainly on BPA. RESULTS: In this work, a miniaturized stir bar sorptive dispersive microextraction (mSBSDME) approach has been developed for the determination of BPA and eight analogues in follicular fluid. In the proposed method, the sample is previously cleaned-up using a zirconia-based solid-phase extraction cartridge, removing proteins and phospholipids, and then subjected to the mSBSDME for the preconcentration of the analytes. For this purpose, a magnetic covalent organic framework was used as sorbent. A Plackett-Burman design was applied to select the significant variables affecting the mSBSDME. Afterwards, the only significant variable (i.e., sorbent amount) was optimized. Under the optimized conditions, the proposed method was properly validated, and satisfactory analytical parameters in terms of linearity (up to 50 ng mL-1), enrichment factors (8.5-14.3), limits of detection in the low ng mL-1 range, and precision (relative standard deviations below 11.5 %) were obtained. Finally, the method was successfully applied to five samples, detecting BPA and other two analogues. SIGNIFICANCE: This method expands the potential applicability of the mSBSDME to other low-availability complex matrixes, which would otherwise be difficult to analyze. Moreover, it offers a valuable tool for monitoring the female population's exposure to bisphenols with the final aim of evaluating if infertility problems of women might be associated to the exposure to these highly endocrine disrupting compounds.

Microbiome-mediated fructose depletion restricts murine gut colonization by vancomycin-resistant Enterococcus.

Multidrug-resistant organisms (MDRO) are a major threat to public health. MDRO infections, including those caused by vancomycin-resistant Enterococcus (VRE), frequently begin by colonization of the intestinal tract, a crucial step that is impaired by the intestinal microbiota. However, the specific members of the microbiota that suppress MDRO colonization and the mechanisms of such protection are largely unknown. Here, using metagenomics and mouse models that mimic the patients' exposure to antibiotics, we identified commensal bacteria associated with protection against VRE colonization. We further found a consortium of five strains that was sufficient to restrict VRE gut colonization in antibiotic treated mice. Transcriptomics in combination with targeted metabolomics and in vivo assays indicated that the bacterial consortium inhibits VRE growth through nutrient depletion, specifically by reducing the levels of fructose, a carbohydrate that boosts VRE growth in vivo. Finally, in vivo RNA-seq analysis of each strain of the consortium in combination with ex vivo and in vivo assays demonstrated that a single bacterium (Olsenella sp.) could recapitulate the effect of the consortium. Our results indicate that nutrient depletion by specific commensals can reduce VRE intestinal colonization, which represents a novel non-antibiotic based strategy to prevent infections caused by this multidrug-resistant organism.

Calorie restriction improves metabolic state independently of gut microbiome composition: a randomized dietary intervention trial.

BACKGROUND: The gut microbiota has been suggested to play a significant role in the development of overweight and obesity. However, the effects of calorie restriction on gut microbiota of overweight and obese adults, especially over longer durations, are largely unexplored. METHODS: Here, we longitudinally analyzed the effects of intermittent calorie restriction (ICR) operationalized as the 5:2 diet versus continuous calorie restriction (CCR) on fecal microbiota of 147 overweight or obese adults in a 50-week parallel-arm randomized controlled trial, the HELENA Trial. The primary outcome of the trial was the differential effects of ICR versus CCR on gene expression in subcutaneous adipose tissue. Changes in the gut microbiome, which are the focus of this publication, were defined as exploratory endpoint of the trial. The trial comprised a 12-week intervention period, a 12-week maintenance period, and a final follow-up period of 26 weeks. RESULTS: Both diets resulted in ~5% weight loss. However, except for Lactobacillales being enriched after ICR, post-intervention microbiome composition did not significantly differ between groups. Overall weight loss was associated with significant metabolic improvements, but not with changes in the gut microbiome. Nonetheless, the abundance of the Dorea genus at baseline was moderately predictive of subsequent weight loss (AUROC of 0.74 for distinguishing the highest versus lowest weight loss quartiles). Despite the lack of consistent intervention effects on microbiome composition, significant study group-independent co-variation between gut bacterial families and metabolic biomarkers, anthropometric measures, and dietary composition was detectable. Our analysis in particular revealed associations between insulin sensitivity (HOMA-IR) and Akkermansiaceae, Christensenellaceae, and Tanerellaceae. It also suggests the possibility of a beneficial modulation of the latter two intestinal taxa by a diet high in vegetables and fiber, and low in processed meat. CONCLUSIONS: Overall, our results suggest that the gut microbiome remains stable and highly individual-specific under dietary calorie restriction. TRIAL REGISTRATION: The trial, including the present microbiome component, was prospectively registered at ClinicalTrials.gov NCT02449148 on May 20, 2015.

Prediagnostic alterations in circulating bile acid profiles in the development of hepatocellular carcinoma.

Bile acids (BAs) play different roles in cancer development. Some are carcinogenic and BA signaling is also involved in various metabolic, inflammatory and immune-related processes. The liver is the primary site of BA synthesis. Liver dysfunction and microbiome compositional changes, such as during hepatocellular carcinoma (HCC) development, may modulate BA metabolism increasing concentration of carcinogenic BAs. Observations from prospective cohorts are sparse. We conducted a study (233 HCC case-control pairs) nested within a large observational prospective cohort with blood samples taken at recruitment when healthy with follow-up over time for later cancer development. A targeted metabolomics method was used to quantify 17 BAs (primary/secondary/tertiary; conjugated/unconjugated) in prediagnostic plasma. Odd ratios (OR) for HCC risk associations were calculated by multivariable conditional logistic regression models. Positive HCC risk associations were observed for the molar sum of all BAs (ORdoubling  = 2.30, 95% confidence intervals [CI]: 1.76-3.00), and choline- and taurine-conjugated BAs. Relative concentrations of BAs showed positive HCC risk associations for glycoholic acid and most taurine-conjugated BAs. We observe an association between increased HCC risk and higher levels of major circulating BAs, from several years prior to tumor diagnosis and after multivariable adjustment for confounders and liver functionality. Increase in BA concentration is accompanied by a shift in BA profile toward higher proportions of taurine-conjugated BAs, indicating early alterations of BA metabolism with HCC development. Future studies are needed to assess BA profiles for improved stratification of patients at high HCC risk and to determine whether supplementation with certain BAs may ameliorate liver dysfunction.

A UPLC-MS/MS method for the determination of oxidative stress biomarkers in amniotic fluid.

Oxidative stress in the fetal period is associated with preterm birth as well as short and long-term adverse clinical outcomes. Here, an Ultra-Performance Liquid Chromatography-tandem Mass Spectrometry (UPLC-MS/MS) method for the simultaneous quantification of biomarkers of oxidative stress-derived damage to proteins and DNA in amniotic fluid (AF) samples is presented. Appropriate accuracy and precision levels, as well as sensitivity with limits of detection in the low nanomolar (<2 nM) range were achieved. The analytical method was applied to a set of AF samples and reference ranges of the biomarker panel are presented. Median concentrations of biomarkers of protein oxidation (ortho-, 3-chloro-, and 3-nitrotyrosine) and their precursors (para-tyrosine and phenylalanine) ranged between 0.6 and 3 nM and 23 and 30 µM, respectively, while levels of a biomarker of DNA-oxidation (8-hydroxydeoxyguanosine, 8OHdG) and its precursor (2'-deoxyguanosine) were found to be 0.18 and 3 nM, respectively. Detection frequencies of all metabolites were 100% with exception of 3-chlorotyrosine (3Cl-Tyr) and 8OHdG, that were only detected in 8% of samples. The developed method may be applied in research studies focusing on oxidative stress-related complications during pregnancy.

Lipid Peroxidation Assessment in Preclinical Alzheimer Disease Diagnosis.

BACKGROUND: Alzheimer disease (AD) is an increasingly common neurodegenerative disease, especially in countries with aging populations. Its diagnosis is complex and is usually carried out in advanced stages of the disease. In addition, lipids and oxidative stress have been related to AD since the earliest stages. A diagnosis in the initial or preclinical stages of the disease could help in a more effective action of the treatments. METHODS: Isoprostanoid biomarkers were determined in plasma samples from preclinical AD participants (n = 12) and healthy controls (n = 31) by chromatography and mass spectrometry (UPLC-MS/MS). Participants were accurately classified according to cerebrospinal fluid (CSF) biomarkers and neuropsychological examination. RESULTS: Isoprostanoid levels did not show differences between groups. However, some of them correlated with CSF biomarkers (t-tau, p-tau) and with cognitive decline. In addition, a panel including 10 biomarkers showed an area under curve (AUC) of 0.96 (0.903-1) and a validation AUC of 0.90 in preclinical AD prediction. CONCLUSIONS: Plasma isoprostanoids could be useful biomarkers in preclinical diagnosis for AD. However, these results would require a further validation with an external cohort.

Isoprostanoids Levels in Cerebrospinal Fluid Do Not Reflect Alzheimer's Disease.

Previous studies showed a relationship between lipid oxidation biomarkers from plasma samples and Alzheimer's Disease (AD), constituting a promising diagnostic tool. In this work we analyzed whether these plasma biomarkers could reflect specific brain oxidation in AD. In this work lipid peroxidation compounds were determined in plasma and cerebrospinal fluid (CSF) samples from AD and non-AD (including other neurological pathologies) participants, by means of an analytical method based on liquid chromatography coupled with mass spectrometry. Statistical analysis evaluated correlations between biological matrices. The results did not show satisfactory correlations between plasma and CSF samples for any of the studied lipid peroxidation biomarkers (isoprostanes, neuroprostanes, prostaglandines, dihomo-isoprostanes). However, some of the analytes showed correlations with specific CSF biomarkers for AD and with neuropsychological tests (Mini-Mental State Examination (MMSE), Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)). In conclusion, lipid peroxidation biomarkers in CSF samples do not reflect their levels in plasma samples, and no significant differences were observed between participant groups. However, some of the analytes could be useful as cognitive decline biomarkers.

Plasma alterations in cholinergic and serotonergic systems in early Alzheimer Disease: Diagnosis utility.

BACKGROUND: Alzheimer Disease (AD) is the most common cause of dementia and it involves a high social and economic cost worldwide, and the health system still does not count with an effective treatment. This may be explained by the lack of a reliable early diagnosis and the complex physiological mechanisms involved in the disease development. In this sense, the cholinergic and serotonergic systems may be altered in the disease course. METHODS: In this study, metabolites from these pathways were determined in order to develop a non-invasive and early diagnosis model, as well as to advance in the knowledge of the physiopathological mechanisms of the disease. For this, plasma samples from mild cognitive impairment due to AD patients (MCI-AD, n = 25) and healthy controls (n = 25) were analysed. RESULTS: choline and tryptophan pathways were deregulated in MCI-AD. Therefore, a model based on betaine, cytidine, uridine, choline, acetylcholine, serotonin and tryptophan was developed, showing an AUC-ROC of 0.862, and sensitivity and specificity of 96% and 72%, respectively. CONCLUSION: Alterations in metabolites from these pathways are related to cognitive impairment and neurodegeneration, and they could be useful in AD diagnosis. Nevertheless, further research is required in order to validate this diagnosis model.

Prediagnostic Plasma Bile Acid Levels and Colon Cancer Risk: A Prospective Study.

BACKGROUND: Bile acids have been proposed to promote colon carcinogenesis. However, there are limited prospective data on circulating bile acid levels and colon cancer risk in humans. METHODS: Associations between prediagnostic plasma levels of 17 primary, secondary, and tertiary bile acid metabolites (conjugated and unconjugated) and colon cancer risk were evaluated in a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Bile acid levels were quantified by tandem mass spectrometry in samples from 569 incident colon cancer cases and 569 matched controls. Multivariable logistic regression analyses were used to estimate odds ratios (ORs) for colon cancer risk across quartiles of bile acid concentrations. RESULTS: Positive associations were observed between colon cancer risk and plasma levels of seven conjugated bile acid metabolites: the primary bile acids glycocholic acid (ORquartile 4 vs quartile 1= 2.22, 95% confidence interval [CI] = 1.52 to 3.26), taurocholic acid (OR = 1.78, 95% CI = 1.23 to 2.58), glycochenodeoxycholic acid (OR = 1.68, 95% CI = 1.13 to 2.48), taurochenodeoxycholic acid (OR = 1.62, 95% CI = 1.11 to 2.36), and glycohyocholic acid (OR = 1.65, 95% CI = 1.13 to 2.40), and the secondary bile acids glycodeoxycholic acid (OR = 1.68, 95% CI = 1.12 to 2.54) and taurodeoxycholic acid (OR = 1.54, 95% CI = 1.02 to 2.31). By contrast, unconjugated bile acids and tertiary bile acids were not associated with risk. CONCLUSIONS: This prospective study showed that prediagnostic levels of certain conjugated primary and secondary bile acids were positively associated with risk of colon cancer. Our findings support experimental data to suggest that a high bile acid load is colon cancer promotive.

Oxidative Damage of DNA as Early Marker of Alzheimer's Disease.

Alzheimer's Disease (AD) is the most common cause of dementia, and its characteristic histopathological hallmarks are neurofibrillary tangles and senile plaques. Among involved mechanisms, oxidative stress plays an important role in damaging cell components (e.g., proteins, nucleic acids). In this study, different oxidized products of proteins and DNA were determined in the urine samples from mild cognitive impairment due to AD patients (n = 53) and healthy controls (n = 27) by means of ultra-performance liquid chromatography-tandem mass spectrometry analysis. A multivariate model developed by partial least squares generated a diagnostic model for AD with an AUC-ROC (area under the curve-receiver operating characteristic) of 0.843. From the studied analytes, 8-OHdG (8-hydroxy-2'-deoxyguanosine) and the ratio 8-OHdG/2dG (2'-deoxyguanosine) were able to distinguish between AD and healthy participants, showing statistically significant differences between groups, postulating DNA oxidation as a molecular pathway involved in early AD.

New screening approach for Alzheimer's disease risk assessment from urine lipid peroxidation compounds.

Alzheimer Disease (AD) standard biological diagnosis is based on expensive or invasive procedures. Recent research has focused on some molecular mechanisms involved since early AD stages, such as lipid peroxidation. Therefore, a non-invasive screening approach based on new lipid peroxidation compounds determination would be very useful. Well-defined early AD patients and healthy participants were recruited. Lipid peroxidation compounds were determined in urine using a validated analytical method based on liquid chromatography coupled to tandem mass spectrometry. Statistical studies consisted of the evaluation of two different linear (Elastic Net) and non-linear (Random Forest) regression models to discriminate between groups of participants. The regression models fitted to the data from some lipid peroxidation biomarkers (isoprostanes, neuroprostanes, prostaglandines, dihomo-isoprostanes) in urine as potential predictors of early AD. These prediction models achieved fair validated area under the receiver operating characteristics (AUC-ROCs > 0.68) and their results corroborated each other since they are based on different analytical principles. A satisfactory early screening approach, using two complementary regression models, has been obtained from urine levels of some lipid peroxidation compounds, indicating the individual probability of suffering from early AD.

Validated analytical method to determine new salivary lipid peroxidation compounds as potential neurodegenerative biomarkers.

Lipid peroxidation is closely related to neurodegenerative diseases since brain shows high lipid composition and oxygen consumption. The determination of lipid peroxidation compounds in non-invasive biological samples would help to monitor the patients' oxidative stress status. A new analytical method based on ultrasound-assisted liquid-liquid semi-microextraction (UA-LLsME) followed by Ultra Performance Liquid Chromatography coupled to tandem Mass Spectrometry was developed to determine 18 lipid peroxidation biomarkers in saliva samples. The variables affecting the UA-LLsME efficiency were systematically studied. Under the optimum conditions, the methodology was validated and showed high-throughput, high sensitivity (limits of detection 0.02-2 nmol L-1), and satisfactory precision (coefficients of variation 2-11% (intra-day) and 5-12% (inter-day)). The reliability of the described method was assessed analysing spiked saliva samples, and the recoveries were between 80% and 120% for most of the analytes. Then, the method suitability was demonstrated by analysing saliva samples (n = 30) from elderly people with neurodegenerative diseases. To conclude, the new developed analytical method is a useful tool to determine salivary lipid peroxidation compounds as potential biomarkers in further clinical studies in which oxidative stress plays an important role.

Plasma lipid peroxidation biomarkers for early and non-invasive Alzheimer Disease detection.

INTRODUCTION: Alzheimer Disease (AD) standard diagnosis is based on evaluations and biomarkers that are non-specific, expensive, or requires invasive sampling. Therefore, an early, and non-invasive diagnosis is required. As regards molecular mechanisms, recent research has shown that lipid peroxidation plays an important role. METHODS: Well-defined participants groups were recruited. Lipid peroxidation compounds were determined in plasma using a validated analytical method. Statistical studies consisted of an elastic-net-penalized logistic regression adjustment. RESULTS: The regression model fitted to the data included six variables (lipid peroxidation biomarkers) as potential predictors of early AD. This model achieved an apparent area under the receiver operating characteristics (AUC-ROCs) of 0.883 and a bootstrap-validated AUC-ROC of 0.817. Calibration of the model showed very low deviations from real probabilities. CONCLUSION: A satisfactory early diagnostic model has been obtained from plasma levels of 6 lipid peroxidation compounds, indicating the individual probability of suffering from early AD.

Determination of atranol and chloroatranol in perfumes using simultaneous derivatization and dispersive liquid-liquid microextraction followed by gas chromatography-mass spectrometry.

A new analytical method based on simultaneous derivatization and dispersive liquid-liquid microextraction (DLLME) followed by gas chromatography-mass spectrometry (GC-MS), for the determination of the allergenic compounds atranol and chloroatranol in perfumes, is presented. Derivatization of the target analytes by means of acetylation with anhydride acetic in carbonate buffer was carried out. Thereby volatility and detectability were increased for improved GC-MS sensitivity. In addition, extractability by DLLME was also enhanced due to a less polar character of the solutes. A liquid-liquid extraction was performed before DLLME to clean up the sample and to obtain an aqueous sample solution, free of the low polar matrix from the essential oils, as donor phase. Different parameters, such as the nature and volume of both the extraction and disperser solvents, the ionic strength of the aqueous donor phase or the effect of the derivatization reagent volume, were optimized. Under the selected conditions (injection of a mixture of 750µL of acetone as disperser solvent, 100µL of chloroform as extraction solvent and 100µL of anhydride acetic as derivatization reagent) the figures of merit of the proposed method were evaluated. Limits of detection in the low ngmL(-1) range were obtained. Matrix effect was observed in real perfume samples and thus, standard addition calibration is recommended.

Development of a selective solid phase extraction method for nitro musk compounds in environmental waters using a molecularly imprinted sorbent.

A powerful analytical method for the determination of the family of the nitro musk compounds at trace level in environmental waters-river, sea, and water from a treatment plant-is presented. The method is based on the use of molecularly imprinted silica (MIS) as sorbent for solid phase extraction (SPE) used for the clean-up and the concentration step of the target analytes previous to their determination by gas chromatography-mass spectrometry. The optimized extraction procedure allowed extraction recoveries between 61% and 87% using the MIS. The comparison with a non-imprinted silica (NIS) sorbent, for which extraction recoveries between 8% and 26% were obtained, showed the high selectivity of the MIS for the nitro musks. Moreover, high enrichment factors, ranging between 580 and 827, were achieved. The imprinted sorbent was compared to a conventional polymeric SPE sorbent for the extraction of the target compounds from environmental waters, showing high selectivity of the MIS and its clean-up potential. For the first time, the five nitro musk compounds were selectively extracted with an imprinted material.

A chromatochemometric approach for evaluating and selecting the perfume maceration time.

A chemometric treatment of the data obtained by gas chromatography (GC) with flame ionization detector (FID) has been proposed to study the maceration time involved in perfumes manufacture with the final purpose of reducing this time but preserving the organoleptic characteristics of the perfume that is being elaborated. In this sense, GC-FID chromatograms were used as a fingerprint of perfume samples subjected to different maceration times, and data were treated by linear discriminant analysis (LDA), by comparing to a set of samples known to be macerated or not, which were used as calibration objects. The GC-FID methodology combined with the treatment of data by LDA has been applied successfully to seven different perfumes. The constructed LDA models exhibited excellent Wilks' lambdas (0.013-0.118, depending on the perfume), and up to a reduction of 57% has been achieved with respect to the maceration time initially established.