A linear-polymer-based lactoferrin-selective recognition element for an ELISA mimic: A proof of concept.

The synthesis of polymers with tailored properties for the recognition of macromolecules such as proteins is challenging. In this work, the synthesis of a new polymer format, a linear polymer (LP), as the selective recognition element for the globular protein lactoferrin (LF) is proposed as a proof-of-concept study. For the synthesis, a solid-phase strategy using the reversible deactivation radical polymerisation (RDRP) mechanism is proposed. This approach, which is usually used in molecular imprinting, involves the immobilisation of LF on the surface of a solid support, but, unlike classical imprinting, a cross-linker in the polymerisation mixture is not required. Consequently, the copolymer is soluble and flexible, thus overcoming the drawbacks associated with traditional synthetic polymers for macromolecule imprinting. This new polymer format has great potential for replacing natural antibodies in bioassays such as enzyme-linked immunosorbent assays (ELISA), dot blot, western blot, or pull-down. In our case, the linear polymer was used as a recognition element to replace natural antibodies in a LF-selective ELISA. The responses of the linear polymer between LF concentrations of 0.1 nM and 0.25 µM were studied, and a significant difference was observed between the non-specific signals and the signals measured in the presence of the polymeric material. Further, the response versus log concentration curves were fitted to a logistic equation, allowing estimation of the EC50 value: 11.8 ± 1.4 nM. We also confirmed the selective detection of LF using the competitive inhibition of the selective LF-biotin conjugate (LF-Bi) binding to the plastic receptor (LP) for closely related proteins (e.g. those having similar molecular weights or isoelectric points) such as human lysozyme, trypsin, and albumin, which are present in human body fluids. The system presents a cross-reactivity value or selectivity of 1.95% for lysozyme, 0.028% for trypsin, and 0.016% for albumin. The applicability of this method for the determination of urine LF levels in inflammatory and infectious diseases of the human urinary tract is also demonstrated.

LC-QQQ-MS routine analysis method for new biomarker quantification in plasma aimed at early chronic kidney disease diagnosis.

Pediatric chronic kidney disease (CKD) is currently assessed using glomerular filtration rate (GFR), which is calculated from different equations based on serum creatinine concentration. However, serum creatinine is affected by several factors and is not reliable enough for the diagnosis of CKD, especially at early stages. Recent targeted and untargeted metabolomics studies found 7 new potential biomarkers that could be useful for early pediatric chronic kidney disease diagnosis. Thus, a new LC-QQQ-MS analytical method has been developed and validated aimed at routine analysis of these 7 potential biomarkers: NG,NG'-dimethyl-l-arginine di(p-hydroxyazobenzene-p'-sulfonate) (SDMA), S-adenosyl-l-methionine (SAM), n-butyryl-l-carnitine (nC4), iso-butyryl-l-carnitine (iC4), citrulline (CIT), creatinine (CNN) and d-erytro-sphingosine-1-phosphate (S1P), in addition to creatinine, the classical biomarker for CKD diagnosis. Then, this analytical method has been used for the quantification of plasma samples from a heterogeneous group of CKD pediatric patients and a control pediatric population. Data analysis of these results showed that it is possible to differentiate between CKD and control populations based on the metabolite concentration in plasma.

Untargeted metabolomics for plasma biomarker discovery for early chronic kidney disease diagnosis in pediatric patients using LC-QTOF-MS.

Pediatric chronic kidney disease (CKD) is a clinical syndrome characterized by renal hypofunction occurring due to gradual and irreversible kidney damage that can further progress over time. New biomarkers may help early diagnosis of pediatric patients suffering from CKD and improve the outcome. Untargeted metabolomics based on LC-QTOF-MS has been used to find new biomarkers for the early diagnosis of CKD in plasma from pediatric patients. In order to avoid any bias in the determination of statistically significant entities as a consequence of the data analysis method followed, two different chemometric approaches have been used, Mass Profiler Professional (MPP) software and Matlab R2015a software. Metabolic fingerprints of control and CKD pediatric patients were compared and five metabolites which showed a significant change common to both data analysis procedures were identified. Sphingosine-1-phosphate, n-butyrylcarnitine, cis-4-decenoylcarnitine and an unidentified feature with 126.0930 m/z were found to be increased in plasma from pediatric patients with CKD, whereas bilirubin was significantly decreased. A partial least squares discriminant analysis model built with these 5 entities classified correctly 96% of the samples. In addition, when considering only early CKD patients against controls, a performance of 97% was obtained. Thus, these promising metabolites could be suitable biomarkers for the early diagnosis of pediatric CKD in a clinical setting.

Plasma biomarker discovery for early chronic kidney disease diagnosis based on chemometric approaches using LC-QTOF targeted metabolomics data.

Chronic kidney disease (CKD) is a progressive pathological condition in which renal function deteriorates in time. The first diagnosis of CKD is often carried out in general care attention by general practitioners by means of serum creatinine (CNN) levels. However, it lacks sensitivity and thus, there is a need for new robust biomarkers to allow the detection of kidney damage particularly in early stages. Multivariate data analysis of plasma concentrations obtained from LC-QTOF targeted metabolomics method may reveal metabolites suspicious of being either up-regulated or down-regulated from urea cycle, arginine methylation and arginine-creatine metabolic pathways in CKD pediatrics and controls. The results show that citrulline (CIT), symmetric dimethylarginine (SDMA) and S-adenosylmethionine (SAM) are interesting biomarkers to support diagnosis by CNN: early CKD samples and controls were classified with an increase in classification accuracy of 18% when using these 4 metabolites compared to CNN alone. These metabolites together allow classification of the samples into a definite stage of the disease with an accuracy of 74%, being the 90% of the misclassifications one level above or below the CKD stage set by the nephrologists. Finally, sex-related, age-related and treatment-related effects were studied, to evaluate whether changes in metabolite concentration could be attributable to these factors, and to correct them in case a new equation is developed with these potential biomarkers for the diagnosis and monitoring of pediatric CKD.

Untargeted metabolomic analysis using liquid chromatography quadrupole time-of-flight mass spectrometry for non-volatile profiling of wines.

The current study presents a method for comprehensive untargeted metabolomic fingerprinting of the non-volatile profile of the Graciano Vitis vinifera wine variety, using liquid chromatography/electrospray ionization time of flight mass spectrometry (LC-ESI-QTOF). Pre-treatment of samples, chromatographic columns, mobile phases, elution gradients and ionization sources, were evaluated for the extraction of the maximum number of metabolites in red wine. Putative compounds were extracted from the raw data using the extraction algorithm, molecular feature extractor (MFE). For the metabolite identification the WinMet database was designed based on electronic databases and literature research and includes only the putative metabolites reported to be present in oenological matrices. The results from WinMet were compared with those in the METLIN database to evaluate how much the databases overlap for performing identifications. The reproducibility of the analysis was assessed using manual processing following replicate injections of Vitis vinifera cv. Graciano wine spiked with external standards. In the present work, 411 different metabolites in Graciano Vitis vinifera red wine were identified, including primary wine metabolites such as sugars (4%), amino acids (23%), biogenic amines (4%), fatty acids (2%), and organic acids (32%) and secondary metabolites such as phenols (27%) and esters (8%). Significant differences between varieties Tempranillo and Graciano were related to the presence of fifteen specific compounds.

Plant tolerance to diesel minimizes its impact on soil microbial characteristics during rhizoremediation of diesel-contaminated soils.

Soil contamination due to petroleum-derived products is an important environmental problem. We assessed the impacts of diesel oil on plants (Trifolium repens and Lolium perenne) and soil microbial community characteristics within the context of the rhizoremediation of contaminated soils. For this purpose, a diesel fuel spill on a grassland soil was simulated under pot conditions at a dose of 12,000 mg diesel kg(-1) DW soil. Thirty days after diesel addition, T. repens (white clover) and L. perenne (perennial ryegrass) were sown in the pots and grown under greenhouse conditions (temperature 25/18 °C day/night, relative humidity 60/80% day/night and a photosynthetic photon flux density of 400 µmol photon m(-2) s(-1)) for 5 months. A parallel set of unplanted pots was also included. Concentrations of n-alkanes in soil were determined as an indicator of diesel degradation. Seedling germination, plant growth, maximal photochemical efficiency of photosystem II (F(v)/F(m)), pigment composition and lipophylic antioxidant content were determined to assess the impacts of diesel on the studied plants. Soil microbial community characteristics, such as enzyme and community-level physiological profiles, were also determined and used to calculate the soil quality index (SQI). The presence of plants had a stimulatory effect on soil microbial activity. L. perenne was far more tolerant to diesel contamination than T. repens. Diesel contamination affected soil microbial characteristics, although its impact was less pronounced in the rhizosphere of L. perenne. Rhizoremediation with T. repens and L. perenne resulted in a similar reduction of total n-alkanes concentration. However, values of the soil microbial parameters and the SQI showed that the more tolerant species (L. perenne) was able to better maintain its rhizosphere characteristics when growing in diesel-contaminated soil, suggesting a better soil health. We concluded that plant tolerance is of crucial importance for the recovery of soil health during rhizoremediation of contaminated soils.

Sensitive determination of triazines in underground waters using stir bar sorptive extraction directly coupled to automated thermal desorption and gas chromatography-mass spectrometry.

An automated thermal desorption-gas chromatography-mass spectrometry method for the determination of triazin herbicides in aqueous solution with excellent sensitivity was developed. The method is based on the use of stir bar sorptive extraction. The main parameters such as extraction time, sample volume, the addition of salt and organic modifiers, desorption temperature, desorption flow and desorption time which affect the efficiency of the proposed methodology are fully discussed. The proposed method is sensitive and shows a good linearity within a range of 10-10000 ng L(-1) with correlation coefficients higher than 0.998. Quantitation limits are, in all cases, below the limits accepted by European legislation for human waters consumption and ranging between 11.3 ng L(-1) and 0.7 ng L(-1). The repetitivity, expressed as a relative standard deviation, has values of lower than 8% for all analytes. Using this method, determination of 10 triazines in underground water samples was successfully performed. The average concentrations obtained in the analysis of the spiked samples at two different levels of concentration correspond to mean recoveries ranging from 94.4+/-5.1% to 106.0+/-6.3% for a significance level of 0.05.

Stereoselective determination of demethyl- and didemethyl-citalopram in rat plasma and brain tissue by liquid chromatography with fluorescence detection using precolumn derivatization.

A rapid and sensitive HPLC enantioselective method with fluorescence detection was developed to determine (-)-(R) and (+)-(S) enantiomers of the metabolites of citalopram, demethyl- and didemethyl-citalopram in plasma and brain tissue. This assay involves pre-column chiral derivatization with (-)-(R)-1-(1-naphthyl)ethyl isocyanate followed by separation on a normal-phase silica column. The developed liquid-liquid extraction procedure permits quantitative determination of analytes with recoveries ranged between 81 and 88% with intra- and inter-day relative standard deviations less than 10.5%. Linearity was obtained over the concentration range 5-1000 ng/mL and 100-10,000 ng/g for spiked drug-free plasma and brain tissue, respectively, with detection limits lower than 2.1 ng/mL and 42.8 ng/g.

Solid-phase microextraction coupled with high performance liquid chromatography using on-line diode-array and electrochemical detection for the determination of fenitrothion and its main metabolites in environmental water samples.

The aim of this study was to develop a methodology for the analysis of the insecticide fenitrothion and its two main environmental metabolites, fenitrooxon and 3-methyl-4-nitrophenol. For this purpose, a solid-phase microextraction (SPME) method coupled to high performance liquid chromatography (LC) was optimized. Two on-line detectors, diode array (DAD) and direct current amperometrical (DCAD) were used in order to determine sensitivity and selectivity. The effects of the extraction parameters, including exposure and desorption time, pH, temperature, salt concentration and desorption mode on the extraction efficiency were studied. A satisfactory reproducibility for extractions from samples at 20 ppb-level with RSD < 12.5% (n = 10) was obtained. The calibration graphs were linear in the range of 10-1000 microg l(-1) and detection limits for the target compounds were between 1.2 and 11.8 microg l(-1) depending on which detector was used. The method was applied for determining fenitrothion and both its metabolites in river waters which run through forest areas near to aerial application of the pesticide.

Optimization and validation of a method of analysis for fenitrothion and its main metabolites in forestry air samples using sorbent tubes with thermal desorption cold trap injection and gas chromatography-mass spectrometry.

An analytical methodology using thermal-desorption cold trap (TCT) and GC-MS was developed for the determination of the insecticide fenitrothion and its main metabolites, 3-methyl-4-nitrophenol and fenitrooxon, in forestry atmospheres. The sampled atmosphere was pumped through a glass tube containing 100 mg of Tenax adsorbent at a flow rate of 50 ml min(-1). Adsorption/thermal desorption and breakthrough experiments were performed to test the ability to quantitatively trap the compounds. The detection limits of method for these compounds ranged between 1.6 and 2.1 ng m(-3). This methodology was developed to evaluate the persistence of fenitrothion in forest atmospheres after treatment. Spray application at 21.5 mg active ingredient m(-2) resulted in atmosphere levels of the insecticide of 78.3 ng m(-3) (after 2 h of application). Within 2-4 days following treatment, the presence of fenitrooxon fell to 50-55%. During this period residues of metabolites began to appear, disappearing 19 days later.

Perfil de las competencias profesionales del diplomado en nutrición humana y dietética / Profile of profesional skills and abilities of the graduate in nutrition and dietetics

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Coupling solid-phase microextraction and high-performance liquid chromatography for direct and sensitive determination of halogenated fungicides in wine.

A solid-phase microextraction (SPME) method coupled to high-performance liquid chromatography with diode array detection (HPLC-DAD) for the analysis of six organochlorine fungicides (nuarimol, triadimenol, triadimefon, folpet, vinclozolin and penconazole) in wine was developed. For this purpose, polydimethylsiloxane-divinylbenzene-coated fibers were utilized and all factors affecting throughput, precision, and accuracy of the SPME method were investigated and optimized. These factors include: matrix influence, extraction and desorption time, percentage of ethanol, pH, salt effect and desorption mode. The performed analytical procedure showed detectability ranging from 4 to 27 microg l(-1) and precision from 2.4 to 14.2% (as intra-day relative standard deviation, RSD) and 4.7-25.7% (as inter-day RSD) depending on the fungicide. The results demonstrate the suitability of the SPME-HPLC-DAD method to analyze these organochlorine fungicides in red wine.

Multimembrane carbon fiber microelectrodes for amperometric determination of serotonin in human urine.

An electrochemical sensor for the determination of serotonin in urine was prepared using Ni(II)-phthalocyanine and Nafion to modify the surface of a 4 mm length carbon fiber microelectrode. The resultant sensor was found to improve the response towards this neuronal amine versus the microelectrode without the polymer films. Different polymerization conditions, as well as different conditioning solutions and buffer systems, were investigated in order to optimize the response of the electrodes. Square wave voltammetry (SWV) is proposed as a direct method for determination of serotonin in human urine, after a solid-liquid extraction process. The proposed method enables a detection limit for serotonin of 0.80 +/- 0.04 microgram L-1 to be achieved at a reduction potential of 0.35 V, with an overall prediction error of 2.2% and recoveries of 93%.