A LC-MS/MS method for determination of clenbuterol enantiomers in animal tissues and its application to the enantioselective distribution in Bama mini-pigs

OBJECTIVES

To establish and validate a simple and reliable analytical method for separation and determination of clenbuterol enantiomers (R-(-)-clenbuterol & S-(+)-clenbuterol) in animal tissues, and apply it to the enantioselective distribution of clenbuterol in Bama mini-pigs.

METHODS

A LC-MS/MS analytical method was developed and validated in positive multiple reaction monitoring mode with electrospray ionization. After perchloric acid deproteinization, samples were pretreated only by one step liquid-liquid extraction using tert-butyl methyl ether under strong alkaline condition. Teicoplanin was used as chiral selector and 10 mM ammonium formate methanol solution was used as mobile phase. The optimized chromatographic separation conditions were completed in 8 min. Two chiral isomers in 11 edible tissues from Bama mini-pigs were investigated.

RESULTS

R-(-)-clenbuterol and S-(+)-clenbuterol can be baseline separated and accurately analyzed with a linear range of 5-500 ng/g. Accuracies ranged from -11.9-13.0% for R-(-)-clenbuterol and -10.2-13.2% for S-(+)-clenbuterol, intra-day and inter-day precisions were between 0.7 and 6.1% for R-(-)-clenbuterol and 1.6-5.9% for S-(+)-clenbuterol. R/S ratios in edible tissues of pigs were all significantly lower than 1.

CONCLUSIONS

The analytical method has good specificity and robustness in determination of R-(-)-clenbuterol and S-(+)-clenbuterol in animal tissues, and can be used as a routine analysis method for food safety and doping control. There is a significant difference in R/S ratio between pig feeding tissues and pharmaceutical preparations (racemate with R/S ratio of 1), which makes it possible to identify the source of clenbuterol in doping control and investigation.

Determination of clenbuterol at trace levels in raw gelatin powder and jellies using ultra-high-performance liquid chromatography coupled to triple quadrupole mass spectrometry

Clenbuterol is present in animal tissues and organs and, therefore, potentially present in gelatin derived from animal sources. The objective of this study was to develop a method for identify an quantify traces of clenbuterol in gelatin and jellies. The clenbuterol calibration curve showed linearity in the range of 20-1000 pg mL^-1. The detection and quantification limits were 5 pg g^-1 and 10 pg g^-1, respectively. The recovery of the analyte ranged from 93.4 to 98.7% with an intra-day RSD% (n = 4) of 1.25%-3.25%, and an inter-day RSD% (n = 12) of 0.5%-2.25%, with good linearity (R² = 0.99). The method developed and validated was successfully applied in 54 gelatin samples, 57.4% of which showed clenbuterol. This UHPLC-MS/MS method combines high sensitivity with good selectivity and short chromatographic run time.

Detection of clenbuterol residues in beef sausages and its enantiomeric analysis using UHPLC-MS/MS. A risk of unintentional doping in sport field

Clenbuterol (Clb) can be present in Mexico often but not all over the world in animal tissues and organs, therefore, potentially is derived from animal sources as well. The aims of this study were to develop and validate a method for detecting traces of clenbuterol in beef sausages. A calibration curve showed linearity in the range of 20–500 pg ml⁻¹. The limit of detection (LOD) and lower limit of quantification (LLOQ) were 5 and 10 pg g⁻¹, respectively. The analyte recovery was from 95.70% to 100.40% with an intraday relative standard deviation (RSD%) of 0.99%–2.10% and an interday RSD% of 0.54%–2.34%, R² = 0.9998. The methodology developed was applied successfully in 15 samples of beef sausage, and 73.3% of the samples tested contained racemic clenbuterol in concentrations between 30 and 471 pg g⁻¹. The UHPLC–MS/MS method developed combines high sensitivity with good selectivity and short chromatographic run time. Additionally, the enantiomeric analysis of clenbuterol performed in beef sausages showed a 59% for R‐(−)‐Clb and 41% for S‐(+)‐Clb. The presence of clenbuterol in beef sausages could represent a risk of unintentional doping in sport field, because the clenbuterol is a banned substance included in the World Anti‐Doping Agency's (WADA) list of prohibited substances.

[Separation and determination of clenbuterol enantiomers by ultra-performance convergence chromatography]

Clenbuterol enantiomers differ greatly in their bioactivities. By optimizing the conditions for chromatographic separation and method validation, ultra-performance convergence chromatography (UPC2) was adopted to separate the enantiomers of clenbuterol. Standard solutions of (+)-clenbuterol and (-)-clenbuterol were stored at -18 ℃ for 1, 3, 5, 7, 14, 30, and 60 d, and then, their stability was monitored. The impacts of different chromatographic columns, cosolvents, system backpressure, and chromatographic column temperature on the separation of the two enantiomers were investigated. Acquity Trefoil AMY1 (150 mm×3.0 mm, 2.5 μm) was used for separation, and CO2-0.5% (v/v) ammonium acetate was used as the mobile phase. Gradient elution at a flow rate of 2.0 mL/min was adopted. The detection wavelength was set to 241 nm, and the injection volume was set to 10 μL. The backpressure was set to 13.8 MPa, and the column temperature was maintained at 40 ℃. The two enantiomers showed good linear relationships in the range of 1.0 to 20.0 mg/L with correlation coefficients greater than 0.9997. The limits of detection (LODs, S/N=3) of (+)-clenbuterol and (-)-clenbuterol were both 0.5 mg/L. The relative standard deviation (RSD, n=6) for the peak area of the 10.0 mg/L mixed standard working solution with six replicate injections ranged from 0.65% to 0.76%. The effectiveness and practicability of this method were demonstrated by using it to detect standard clenbuterol racemate. The (+)-clenbuterol and (-)-clenbuterol contents were 5.6 mg/L and 5.5 mg/L, respectively, in the standard clenbuterol racemates, as determined by the external standard method of quantification. The detection results suggested that the content ratio of (+)-clenbuterol and (-)-clenbuterol was close to 1.02∶1.00, which is consistent with the literature data. The established method has the advantages of rapid analysis, good separation effect, and low consumption of organic solvents, and it is suitable for the separation of clenbuterol enantiomers. This method can also provide technical support for the separation of other chiral drugs, analysis of the effects of chiral drugs, and assessment of product quality.

Squaring Things Up With R2: What it is, What it Can (and cannot) Tell You

The coefficient of correlation (r) and the coefficient of determination (R2 or r2) have long been used in analytical chemistry, bioanalysis and forensic toxicology as figures demonstrating linearity of the calibration data in method validation. We clarify here what these two figures are and why they should not be used for this purpose in the context of model fitting for prediction. R2 evaluates whether the data are better explained by the regression model used than by no model at all (i.e., a flat line of slope = 0 and intercept $\bar y$), and to what degree. Hopefully, in the context of calibration curves, the fact that a linear regression better explains the data than no model at all should not be a point of contention. Upon closer examination, a series of restrictions appear in the interpretation of these coefficients. They cannot indicate whether the dataset at hand is linear or not, because they assume that the regression model used is an adequate model for the data. For the same reason, they cannot disprove the existence of another functional relationship in the data. By definition, they are influenced by the variability of the data. The slope of the calibration curve will also change their value. Finally, when heteroscedastic data are analyzed, the coefficients will be influenced by calibration levels spacing within the dynamic range, unless a weighted version of the equations is used. With these considerations in mind, we suggest to stop using r and R2 as figures of merit to demonstrate linearity of calibration curves in method validations. Of course, this does not preclude their use in other contexts. Alternative paths for evaluation of linearity and calibration model validity are summarily presented.