Balayssac Stéphane, Assemat Gaëtan, Danoun Saïda, Malet-Martino Myriam, Gilard Véronique
Laboratoire Softmat, CNRS UMR 5623, Université de Toulouse, F-31062 Toulouse, France.
Laboratoire SPCMIB, CNRS UMR 5068, Université de Toulouse, F-31062 Toulouse, France.
Molecules. 2025 May 6;30(9):2060. doi: 10.3390/molecules30092060.
This study investigates the potential of H and C NMR for the characterization and classification of anabolic androgenic steroids (AASs) in various formulations. First, twenty AAS formulations, including tablets, capsules, and injectable solutions, were analyzed using H NMR for the qualitative identification and quantification of active compounds. The results revealed discrepancies between the labeled and detected substances in several samples, highlighting issues related to product mislabeling and potential health risks. Then, twelve oil-based injectable formulations were examined using C NMR, demonstrating its effectiveness in differentiating and quantifying closely related steroid structures that cannot be discriminated with H NMR. A chemometric approach from C NMR data, based on a principal component analysis (PCA) and hierarchical cluster analysis (HCA), enabled the classification of samples and the identification of key active ingredients.
本研究调查了氢核磁共振（H NMR）和碳核磁共振（C NMR）在表征和分类各种制剂中的合成代谢雄激素类固醇（AASs）方面的潜力。首先，使用H NMR对二十种AAS制剂进行分析，包括片剂、胶囊和注射溶液，以对活性化合物进行定性鉴定和定量分析。结果显示，几个样品中标记物质与检测到的物质之间存在差异，突出了与产品标签错误相关的问题以及潜在的健康风险。然后，使用C NMR对十二种油基注射制剂进行了检查，证明了其在区分和定量无法用H NMR区分的密切相关类固醇结构方面的有效性。基于主成分分析（PCA）和层次聚类分析（HCA）的C NMR数据化学计量学方法能够对样品进行分类并识别关键活性成分。
