A green deep eutectic solvent based dispersive liquid-liquid microextraction for the quantitative analysis of 21 polychlorinated biphenyl metabolites in food of animal origin using injector port silylation-gas chromatography-tandem mass spectrometry.

An analytical method was developed for the quantitative determination of 21 polychlorinated biphenyls (PCBs) metabolites (17 were -OH, 1 -MeO, and 3 were MeSO2) in foods of animal origin using deep eutectic solvent (DES) based dispersive liquid-liquid microextraction followed by injector port silylation-gas chromatography-tandem mass spectrometry. The type of DES (thymol: camphor, 1:1 molar ratio) and optimum volume of DES (300 µL), pH (7.0), and disperser solvent (acetonitrile) were optimized to attain the maximum extraction efficiency. The limit of detection, limit of quantification, and percent recovery were found to be in the range of 0.12-0.23 ng/mL, 0.40-0.76 ng/mL, and 80.1-111.4%, respectively. The expanded uncertainty was observed to be in the range of 7.2-22.8% for the targeted analytes. The proposed method was applied to real food samples (milk, meat, fish, and egg) and the levels were found to be in the range of 0.64-32.14 ng/g. This is first of its kind method using green solvent based method for the analysis of PCB metabolites (-OH, MeO, and MeSO2) and will find extensive application in routine testing for foods of animal origin.

Experimental design of non-ionic hydrophobic DES-DLLME coupled with injector port silylation-GC-MS/MS for the quantitative determination of 13 bisphenols in food samples.

Non-ionic hydrophobic deep eutectic solvent based DLLME method with thymol and camphor (1:1 mole ratio) as extraction solvent and acetonitrile as disperser solvent was developed for the determination of 13 bisphenols (BPs) in food commodities by auto IPS-GC-MS/MS. Further, the influential parameters pH, vortex time, and volume of NIHDES for extraction of 13 BPs were optimized by employing the design of experiment. The LOQ and recoveries were observed to be 0.1 ng mL-1, and 77.8-109.2%, respectively. The expanded uncertainty was found to be 4.8-18.0% for the developed and validated method, which was applied to food commodities to determine 13 BPs and their levels were in the range of 0.01-1.24 ng mL-1 in liquid foods (milk, water, and beverages) and 0.29-3.25 ng g-1 in meat samples (goat, chicken, and fish). The present green analytical method is highly suitable for the rapid determination of 13 BPs in food commodities for routine analysis.

Understanding the metabolic perturbations in Carica papaya Linn. due to different ripening practices/agents using gas chromatography-mass spectrometry based metabolomics.

The study of fruit-ripening mechanism is vital as it plays a key role in the maintenance of fruit quality. Use of various xenobiotics for quick ripening has been shown to impact the quality of fruit, which in turn affect human health. In the present study, we made an attempt to understand the metabolic perturbations in Carica papaya Linn. (papaya), which has been ripened either by the ripening practice (room temperature process as control) and/or ripening agents (calcium carbide and ethylene) using gas chromatography-mass spectrometry (GC-MS) based metabolomics. The partial least squares-discriminant analysis has revealed significant alternations in 13 metabolites mainly sugars, amino acids, fatty acids, and organic acids as well as disturbances in five metabolic pathways due to different ripening practice/agents. The individual comparison of calcium carbide with control and ethylene with control has found 13 and 11 metabolites, respectively, which are common to the PLS-DA of three ripening groups. The GC-MS-based metabolomics has been able to predict the metabolic perturbations in papaya resulting from the ripening practice/agents. The findings from the present analysis has a wide application in food quality and will help to address safety concerns.

Evaluating the metabolic perturbations in Mangifera indica (mango) ripened with various ripening agents/practices through gas chromatography - mass spectrometry based metabolomics.

Mangifera indica L. (mango) is said to be the king of fruits due to its rich nutritional properties and mainly originates from the Indian sub-continent. The consumption pattern of the mangoes has increased drastically, due to which, many ripening practices/agents were used to make it ready-to-eat fruit or juice for the consumers. The fruit quality and metabolic composition are said to be altered due to different ripening agents/practices. The present communication mainly deals to understand the metabolic perturbations in mango fruits due to different ripening practices/agents (room temperature ripening, ethylene, and calcium carbide) using gas chromatography - mass spectrometry based metabolomics. The partial least square-discriminant analysis has found 16 differential metabolites for different ripening agents/practices which are belong to the classes of amino acids, fatty acids, sugars, and polyols. Four metabolic pathways were found to alter in the fruit metabolome due to different ripening agents/practices. Fructose, glucose, and galactose were found to be significantly up-regulated due to calcium carbide ripening in comparison to other ripening agents/practices. Overall findings from the present study advocates that mass spectrometry based metabolomics can be valuable tool to understand the fruit quality and safety with respect to consumer health.

Islet adaptation to obesity and insulin resistance in WNIN/GR-Ob rats.

WNIN/GR-Ob mutant rat is a novel animal model to study metabolic syndrome (obesity, insulin resistance, hyperinsulinemia, impaired glucose tolerance and cardiovascular diseases). We have investigated the islet characteristics of obese mutants at different age groups (1, 6 and 12 months) to assess the islet changes in response to early and chronic metabolic stress. Our data demonstrates altered islet cell morphology and function (hypertrophy, fibrotic lesions, vacuolation, decreased stimulation index, increased TNFα, ROS and TBARS levels) in mutants as compared to controls. Furthermore, network analysis (gene-gene interaction) studied in pancreas demonstrated increased inflammation as a key factor underlying obesity/metabolic syndrome in mutants. These observations pave way to explore this model to understand islet adaptation in response to metabolic syndrome.