In the last few decades, pharmaceuticals, credited with saving millions of lives, have emerged as a new class of environmental contaminant. These compounds can have both chronic and acute harmful effects on natural flora and fauna. The presence of pharmaceutical contaminants in ground waters, surface waters (lakes, rivers, and streams), sea water, wastewater treatment plants (influents and effluents), soils, and sludges has been well doccumented. A range of methods including oxidation, photolysis, UV-degradation, nanofiltration, reverse osmosis, and adsorption has been used for their remediation from aqueous systems. Many methods have been commercially limited by toxic sludge generation, incomplete removal, high capital and operating costs, and the need for skilled operating and maintenance personnel. Adsorption technologies are a low-cost alternative, easily used in developing countries where there is a dearth of advanced technologies, skilled personnel, and available capital, and adsorption appears to be the most broadly feasible pharmaceutical removal method. Adsorption remediation methods are easily integrated with wastewater treatment plants (WWTPs). Herein, we have reviewed the literature (1990-2018) illustrating the rising environmental pharmaceutical contamination concerns as well as remediation efforts emphasizing adsorption.

Pharmaceuticals of Emerging Concern in Aquatic Systems: Chemistry, Occurrence, Effects, and Removal Methods.

Analytical strategies for residue analysis of veterinary drugs and growth-promoting agents in food-producing animals - A review

Modern research in food science and nutrition is moving from classical methodologies to advanced analytical strategies in which MS-based techniques play a crucial role. In this context, Foodomics has been recently defined as a new discipline that studies food and nutrition domains through the application of advanced omics technologies in which MS techniques are considered indispensable. Applications of Foodomics include the genomic, transcriptomic, proteomic, and/or metabolomic study of foods for compound profiling, authenticity, and/or biomarker-detection related to food quality or safety; the development of new transgenic foods, food contaminants, and whole toxicity studies; new investigations on food bioactivity, food effects on human health, etc. This review work does not intend to provide an exhaustive revision of the many works published so far on food analysis using MS techniques. The aim of the present work is to provide an overview of the different MS-based strategies that have been (or can be) applied in the new field of Foodomics, discussing their advantages and drawbacks. Besides, some ideas about the foreseen development and applications of MS-techniques in this new discipline are also provided.

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Foodomics: MS‐based strategies in modern food science and nutrition

https://www.tandfonline.com/doi/pdf/10.1080/10406638.2014.918550

The Occurrence of 16 EPA PAHs in Food – A Review

Nitrofuran antibiotics, employed for the treatment of bacterial diseases in livestock production, were banned from use in the European Union (EU) in 1995 due to concerns about the carcinogenicity of their residues in edible tissue. This review provides an overview of nitrofuran toxicity, metabolism, and also specific aspects of legislation surrounding their prohibition. Special attention is devoted to semicarbazide - a nitrofuran metabolite and food contaminant. Analytical procedures for nitrofuran analysis in various matrices and validation require - List of abbreviations AHD = 1-aminohydantoin; AOZ = 3-amino-2-oxazolidinone; AMOZ = 3-amino-5-morpholino-methyl-1,3-oxa- zolidinone; CC α = decision limit; CC β = detection capability; EC = European Commission; EFSA = European Food Safety Authority; ELISA = enzyme linked immuno-adsorbent assay; ESI = electro-spray ionisation; EU = European Union; FTD = furaltadone; FZD = furazolidone; HPLC = high performance liquid chromatography; IC = inhibition concentration; LC = liquid chromatography; LOD = limit of detection; MS = mass spectrometry; NFT = nitrofurantoin; NFZ = nitrofurazone; NP = nitrophenyl; NPAHD = 3-(2-nitrobenzylidenamino)-2,4-imi- dazolidinedione); NPAMOZ = 5-(morpholinomethyl)-3-(2-nitrobenzylidenamino)-2-oxazolidinone); NPAOZ = (3-(2-nitrobenzylidenamino)-2-oxazolidinone); NPSEM = 3((2-nitrophenyl)methylene)-hydrazinecarboxamide; o-NBA = ortho-nitrobenzaldehyde; RASFF = Rapid Alert System for Food and Feed; SE = solvent extraction; SEM = semicarbazide; SPE = solid phase extraction; UV = ultraviolet

/pdf/nitrofuran-antibiotics-a-review-on-the-application-2ds1x3lvq2.pdf

Nitrofuran antibiotics: a review on the application, prohibition and residual analysis

Multi-method for the determination of antibiotics of different substance groups in milk and validation in accordance with Commission Decision 2002/657/EC.

A matrix-considering in-house validation concept for analytical methods is presented which takes into account the uncertainty due to matrix- and time-induced deviations. It is based on a variance component model for univariate quantitative measurement data that can be adapted to both screening and confirmation methods and to both zero-tolerance and threshold decisions. The model allows the calculation of critical concentrations for given α-errors and the calculation of the corresponding power function to evaluate the performance of an analytical method. The model is applied to a real-life validation experiment.

Assessment of detection methods in trace analysis by means of a statistically based in-house validation concept

Multi-residue method for non-steroidal anti-inflammatory drugs in plasma using high-performance liquid chromatography–photodiode-array detection: Method description and comprehensive in-house validation

The presented multi-method was developed for the confirmation of 37 antibiotic substances from the six antibiotic groups: macrolides, lincosamides, quinolones, tetracyclines, pleuromutilines and diamino-pyrimidine derivatives. All substances were analysed simultaneously in a single analytical run with the same procedure, including an extraction with buffer, a clean-up by solid-phase extraction, and the measurement by liquid chromatography tandem mass spectrometry in ESI+ mode. The method was validated on the basis of an in-house validation concept with factorial design by combination of seven factors to check the robustness in a concentration range of 5–50 μg kg−1. The honeys used were of different types with regard to colour and origin. The values calculated for the validation parameters—decision limit CCα (range, 7.5–12.9 μg kg−1), detection capability CCβ (range, 9.4–19.9 μg kg−1), within-laboratory reproducibility RSDwR (<20% except for tulathromycin with 23.5% and tylvalosin with 21.4 %), repeatability RSDr (<20% except for tylvalosin with 21.1%), and recovery (range, 92–106%)—were acceptable and in agreement with the criteria of Commission Decision 2002/657/EC. The validation results showed that the method was applicable for the residue analysis of antibiotics in honey to substances with and without recommended concentrations, although some changes had been tested during validation to determine the robustness of the method.

Validation of a multi-residue method for the determination of several antibiotic groups in honey by LC-MS/MS

The recently presented in-house validation concept developed on the basis of a variance component model is extended and optimised by basing it on a fractional factorial sampling scheme. The presented approach relies on a comprehensive mathematical model to assess simultaneously the in-house reproducibility and its components in addition to uncertainty-related performance characteristics like power functions and critical concentrations. The influence of individual factors and the corresponding uncertainties can be determined separately in a single experiment with optimum utilization of the generated data, in this way achieving a favourable ratio between costs and result.

Petra Gowik

Papers

Multi-method for the determination of antibiotics of different substance groups in milk and validation in accordance with Commission Decision 2002/657/EC.

Assessment of detection methods in trace analysis by means of a statistically based in-house validation concept

Multi-residue method for non-steroidal anti-inflammatory drugs in plasma using high-performance liquid chromatography–photodiode-array detection: Method description and comprehensive in-house validation

Validation of a multi-residue method for the determination of several antibiotic groups in honey by LC-MS/MS

A top-down in-house validation based approach for the investigation of the measurement uncertainty using fractional factorial experiments