Urine 1H-NMR Metabolomics to Discriminate Neurocysticercosis Patients from Healthy Controls: An Exploratory Study.

The diagnosis of neurocysticercosis (NCC) is principally based on neuroimaging (magnetic resonance imaging or computed tomography), instrumentation that is scarcely available in the rural regions where Taenia solium transmission, primarily occurs due to poor sanitation conditions. Immunological assays for antigen or antibody detection complement the neuroimaging approach. However, no field-applicable assays to diagnose viable NCC or to guide the referral of cases for neuroimaging or for appropriate management are available. We performed an exploratory study on urine and serum samples using 1H-nuclear magnetic resonance (NMR)-based metabolomics to discriminate NCC patients (n = 14) from healthy control subjects (n = 22). Metabolic profiles demonstrated a discrimination between the urines of NCC patients and noninfected control subjects with a moderate predictive accuracy (R2 = 0.999, Q2 = 0.434). NMR metabolomics analysis has been proven useful in depicting biomarkers linked to other infectious diseases, various types of cancer, and other disorders. Our results, albeit preliminary, open a door to the development of better methods for detecting NCC through the identification of biomarkers participating in disturbed metabolic pathways.

NMR-based leaf metabolic profiling of V. planifolia and three endemic Vanilla species from the Peruvian Amazon.

The fruit of Vanilla planifolia is broadly preferred by the agroindustry and gourmet markets due to its refined flavor and aroma. Peruvian Vanilla has been proposed as a possible source for genetic improvement of existing Vanilla cultivars, but, little has been done to facilitate comprehensive studies of these and other Vanilla. Here, a nuclear magnetic resonance (NMR) metabolomic platform was developed to profile for the first time the leaves - organ known to accumulate vanillin putative precursors - of V. planifolia and those of Peruvian V. pompona, V. palmarum, and V. ribeiroi, with the aim to determine metabolic differences among them. Analysis of the NMR spectra allowed the identification of thirty-six metabolites, twenty-five of which were quantified. One-way ANOVA and post-hoc Tukey test revealed that these metabolites changed significantly among species, whilst multivariate-analyses allowed the identification of malic and homocitric acids, together with two vanillin precursors, as relevant metabolic markers for species differentiation.

Validated HPLC-Diode Array Detector Method for Simultaneous Evaluation of Six Quality Markers in Coffee.

Nicotinic acid, N-methylpyridinium ion, and trigonelline are well studied nutritional biomarkers present in coffee, and they are indicators of thermal decomposition during roasting. However, no method is yet available for their simultaneous determination. This paper describes a rapid and validated HPLC-diode array detector method for the simultaneous quantitation of caffeine, trigonelline, nicotinic acid, N-methylpyridinium ion, 5-caffeoylquinic acid, and 5-hydroxymethyl furfural that is applicable to three coffee matrixes: green, roasted, and instant. Baseline separation among all compounds was achieved in 30 min using a phenyl-hexyl RP column (250×4.6 mm, 5 µm particle size), 0.3% aqueous formic buffer (pH 2.4)-methanol mobile phase at a flow rate of 1 mL/min, and a column temperature at 30°C. The method showed good linear correlation (r2>0.9985), precision (less than 3.9%), sensitivity (LOD=0.023-0.237 µg/mL; LOQ=0.069-0.711 µg/mL), and recovery (84-102%) for all compounds. This simplified method is amenable for a more complete routine evaluation of coffee in industry.