Laboratoire Softmat, Université de Toulouse, CNRS UMR 5623, Université Toulouse III-Paul Sabatier, 31062 Toulouse, France.
Laboratoire SPCMIB, Université de Toulouse, CNRS UMR 5068, Université Toulouse III-Paul Sabatier, 31062 Toulouse, France.
Molecules. 2024 May 1;29(9):2086. doi: 10.3390/molecules29092086.
Recently, benchtop nuclear magnetic resonance (NMR) spectrometers utilizing permanent magnets have emerged as versatile tools with applications across various fields, including food and pharmaceuticals. Their efficacy is further enhanced when coupled with chemometric methods. This study presents an innovative approach to leveraging a compact benchtop NMR spectrometer coupled with chemometrics for screening honey-based food supplements adulterated with active pharmaceutical ingredients. Initially, fifty samples seized by French customs were analyzed using a 60 MHz benchtop spectrometer. The investigation unveiled the presence of tadalafil in 37 samples, sildenafil in 5 samples, and a combination of flibanserin with tadalafil in 1 sample. After conducting comprehensive qualitative and quantitative characterization of the samples, we propose a chemometric workflow to provide an efficient screening of honey samples using the NMR dataset. This pipeline, utilizing partial least squares discriminant analysis (PLS-DA) models, enables the classification of samples as either adulterated or non-adulterated, as well as the identification of the presence of tadalafil or sildenafil. Additionally, PLS regression models are employed to predict the quantitative content of these adulterants. Through blind analysis, this workflow allows for the detection and quantification of adulterants in these honey supplements.
最近,利用永磁体的台式核磁共振(NMR)光谱仪已成为多功能工具,在食品和制药等各个领域都有应用。当与化学计量学方法结合使用时,其效果会进一步增强。本研究提出了一种创新方法,利用紧凑型台式 NMR 光谱仪与化学计量学相结合,对含有活性药物成分的蜂蜜类食品补充剂进行筛查。
最初,使用 60MHz 台式光谱仪分析了法国海关查获的 50 个样本。研究发现 37 个样本中含有他达拉非,5 个样本中含有西地那非,1 个样本中含有氟班色林与他达拉非的混合物。在对样本进行全面定性和定量表征后,我们提出了一种化学计量学工作流程,利用 NMR 数据集对蜂蜜样本进行高效筛查。该流水线利用偏最小二乘判别分析(PLS-DA)模型,能够对掺假或非掺假样本进行分类,并识别他达拉非或西地那非的存在。此外,还采用 PLS 回归模型来预测这些掺杂物的定量含量。
通过盲分析,该工作流程可以检测和定量这些蜂蜜补充剂中的掺杂物。