The electrochemical biosensors based on poly(o-phenylenediamine) (PoPD) and acetylcholinesterase (AChE) and choline oxidase (ChO) enzymes were fabricated on carbon fibre (CF) substrate. The electropolymerized PoPD was used to reduce the interfering substances. The electrode assembly was completed by depositing functionalized carbon nano tubes (FCNTs) and Nafion (Naf). Amperometric detection of acetylcholine (ACh) and choline (Ch) were realized at an applied potential of +750 mV vs Ag/AgCl (saturated KCl). At pH 7.4, the final assembly, Naf-FCNTs/AChE-ChO((10:1))/PoPD/CF(Elip), was observed to have high sensitivity towards Ch (6.3±0.3 μA mM(-1)) and ACh (5.8±0.3 μA mM(-1)), linear range for Ch (K(M)=0.52±0.03 mM) and ACh (K(M)=0.59±0.07 mM), and for Ch the highest ascorbic acid blocking capacity (97.2±2 1mM AA). It had a response time of <5s and with 0.045 μM limit of detection. Studies on different ratio (ACh/Ch) revealed that 10:1, gave best overall response.
Meat is a rich source of energy that provides high-value animal protein, fats, vitamins, minerals and trace amounts of carbohydrates. Globally, different types of meats are consumed to fulfill nutritional requirements. However, the increasing burden on the livestock industry has triggered the mixing of high-price meat species with low-quality/-price meat. This work aimed to differentiate different meat samples on the basis of metabolites. The metabolic difference between various meat samples was investigated through Nuclear Magnetic Resonance spectroscopy coupled with multivariate data analysis approaches like principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA). In total, 37 metabolites were identified in the gluteal muscle tissues of cow, goat, donkey and chicken using 1H-NMR spectroscopy. PCA was found unable to completely differentiate between meat types, whereas OPLS-DA showed an apparent separation and successfully differentiated samples from all four types of meat. Lactate, creatine, choline, acetate, leucine, isoleucine, valine, formate, carnitine, glutamate, 3-hydroxybutyrate and α-mannose were found as the major discriminating metabolites between white (chicken) and red meat (chevon, beef and donkey). However, inosine, lactate, uracil, carnosine, format, pyruvate, carnitine, creatine and acetate were found responsible for differentiating chevon, beef and donkey meat. The relative quantification of differentiating metabolites was performed using one-way ANOVA and Tukey test. Our results showed that NMR-based metabolomics is a powerful tool for the identification of novel signatures (potential biomarkers) to characterize meats from different sources and could potentially be used for quality control purposes in order to differentiate different meat types.
To investigate the diagnostic accuracy of single-voxel proton magnetic resonance spectroscopy (SV (1)H MRS) by quantifying total choline-containing compounds (tCho) in differentiating malignant from benign lesions, and subsequently, to analyse the relationship of tCho levels in malignant breast lesions with their histopathological subtypes.