Hair analysis, a reliable and non-invasive method to evaluate the contamination by clenbuterol

Simple and Sensitive Analysis of Clenbuterol in Urine Matrices by UHPLC-MS/MS Method with Online-SPE Sample Preparation

Clenbuterol is one of the most misused anabolic agents in professional sports. Therefore, the monitoring of clenbuterol in body fluids such as human urine is related to the development of rapid, selective and sensitive analytical methods that produce reliable results. In this work, these requirements were met by a two-dimensional separation method based on online solid-phase extraction coupled with ultra-high performance liquid chromatography–tandem mass spectrometry (SPE–UHPLC–MS/MS). The developed method provides favorable performance parameters, and it is characterized by minimum manual steps (only dilution and the addition of an internal standard) in the sample preparation. A limit of quantification (LOQ) of 0.1 ng/mL, excellent linearity (0.9999), remarkable precision (1.26% to 8.99%) and high accuracy (93.1% to 98.7%) were achieved. From a practical point of view, the analytical performance of the validated SPE–UHPLC–MS/MS method was demonstrated on blinded spiked urine samples from ten healthy volunteers. The estimated concentrations of clenbuterol were in accordance with their corresponding nominal values, as supported by the precision and accuracy data (relative standard deviation ≤5.4%, relative error ≤11%). The fulfillment of the World Anti-Doping Agency’s screening and confirmation criteria indicates that the proposed method is suitable for implementation in routine use in toxicologic and antidoping laboratories. Due to its high orthogonality and separation efficiency, the SPE–UHPLC–MS/MS method should also be easily adapted to the separation of structurally related compounds (such as clenbuterol metabolites). Thus, future antidoping applications could also include monitoring of clenbuterol metabolites, providing a longer detection widow.

Utilization of Wool Integral Lipids to Determine Milk Fat Content in Suffolk Down Ewes

The identification of higher fat content in ewe milk during lactation can help to improve the nutritional value and quality of the derived dairy products. In this study, we characterized fatty acids from the wool of Suffolk ewes at two time points during lactation and assessed whether they were related to milk fat content through discriminant analysis and, thus, could be potentially used to identify ewes with a high fat content. Eighty single-bearing Suffolk ewes of similar body weight, body score, and age were selected for this study. The overall fat contents of milk and wool were determined, as well as the fatty acids in the wool. The wool fat content was 1.14% on average. The proportions of wool fatty acids were 65.82% saturated, 21.70% monounsaturated, and 12.48% polyunsaturated fatty acids. The wool fatty acid concentrations of C18:1n9c, C18:2n6c, and C22:2 were higher in ewes whose milk had a high fat content at both time points. Moreover, the levels of these fatty acids were positively correlated with milk fat content. Discriminant analyses using C18:1n9c and C18:2n6c were the best candidates for the prediction of high milk fat content, with an accuracy of 87.50%. The wool fatty acids C18:1n9c and C18:2n6c could potentially be used to determine the milk fat content of ewes.

A new potentiometric platform: Antibody cross-linked graphene oxide potentiometric immunosensor for clenbuterol determination

An immunosensor is based on the signal measurement obtained upon the reaction of an antibody antigen complex. It plays a significant role in various fields such as environmental analysis, production monitoring, drug detection or screening, veterinary medicine, and animal food. In this study, an antibody crosslinked graphen oxide (GO)-based potentiometric sensor has been developed for fast, simple, and economical detection of clenbuterol. In this context, the photosensitive amino acid bound GO platform is synthesized and used for the preparation of electrode material. Then, polymeric structure is characterized by infrared spectroscopy, and the performance of immunonano platform prepared by potentiometric sensor is evaluated. The effect of pH, response time, selectivity, and sensitivity is investigated. Under the optimized conditions, a simple and rapid method for the determination of clenbuterol from milk sample is established by immuno-potentiometric sensor. The detection limit has found to be 0.87 × 10^-9 mmol L^-1 for this immuno-potentiometric sensor. This immuno-potentiometric sensor has optimum pH at 7.0, a wide linear response (1.0 × 10^-2 to 1.0 × 10^-9 mmol L^-1 ), rapid response time (2 Min) and 36 weeks operational lifetime.

Detection of azithromycin residue in broiler feathers by liquid chromatography-tandem mass spectrometry

In the study, a sensitive and reproducible method for the quantitative analysis of azithromycin in broiler feather samples by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed. Feather samples were rinsed after being wrapped in medical gauze, then chopped and then added to 5% (v/v) ammonia in methanol solution for ultrasonic extraction. The extract was purified by the combination of commercial polymeric microparticles (Oasis MCX) and Fe₃O₄ nanoparticles. The LC separation was performed on an Agilent Eclipse plus C18 column. Multiple reaction monitoring was used for the selective detection of azithromycin. The good linearity curve of azithromycin in feather sample was in the range from 1.0 μg kg^-1 to 100.0 μg kg^-1 with 0.9935 of correlation coefficient. And the limit detection and limit of quantification was 0.5 μg kg^-1 and 2.0 μg kg^-1 in spiked feather samples. The recoveries of azithromycin were 85.2-94.7% with the relative standard deviation less than 10%. The established method is simple, rapid, sensitive and specific, and could meet the need of government and enterprises to monitor the illegal use of azithromycin in livestock and poultry breeding.

Development of Polyclonal Antibody against Clenbuterol for Immunoassay Application

Development of an immunoassay for clenbuterol (CLB) detection required an anti-CLB antibody as an important bioreceptor. In this study, we report our work on production and purification of a rabbit-derived polyclonal anti-CLB antibody. The antibody was then purified by nProtein A Sepharose affinity column and the antibody purity was confirmed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis. The activities of purified antibody were evaluated based on high antibody titer determined from enzyme-linked immunosorbent assay (ELISA). The sensitivity and selectivity of this antibody was evaluated and exhibits negligible cross-reactivity to antibiotics other than β-agonist families. Evaluation of the antibody as bioreceptor in immunoassay was performed using direct competitive ELISA and exhibited linear calibration plot (R² = 0.9484). The antibody was used to detect the content of CLB in spiked milk samples and the recovery of more than 92% indicating significant performance as bioreceptor for the development of a rapid and simple immunoassay.

Ultratrace LC-MS/MS analysis of segmented calf hair for retrospective assessment of time of clenbuterol administration in Agriforensics

In agriforensics, time of administration is often debated when illegal drug residues, such as clenbuterol, are found in frequently traded cattle. In this proof-of-concept work, the feasibility of obtaining retrospective timeline information from segmented calf tail hair analyses has been studied. First, an ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) hair analysis method was adapted to accommodate smaller sample sizes and in-house validated. Then, longitudinal 1 cm segments of calf tail hair were analyzed to obtain clenbuterol concentration profiles. The profiles found were in good agreement with calculated, theoretical positions of the clenbuterol residues along the hair. Following assessment of the average growth rate of calf tail hair, time of clenbuterol administration could be retrospectively determined from segmented hair analysis data. The data from the initial animal treatment study (n = 2) suggest that time of treatment can be retrospectively estimated with an error of 3-17 days.