Human nails have recently become a sample of interest for toxicological purposes. Multiple studies have proven the ability to detect various analytes within the keratin matrix of the nail. The analyte of interest in this study is fentanyl, a highly dangerous and abused drug in recent decades. In this proof-of-concept study, ATR-FTIR was combined with machine learning methods, which are effective in detecting and differentiating fentanyl in samples, to explore whether nail samples are distinguishable from individuals who have used fentanyl and those who have not. PLS-DA and SVM-DA prediction models were created for this study and had an overall accuracy rate of 84.8% and 81.4%, respectively. Notably, when classification was considered at the donor level-i.e., determining whether the donor of the nail sample was using fentanyl-all donors were correctly classified. These results show that ATR-FTIR spectroscopy in combination with machine learning can effectively differentiate donors who have used fentanyl and those who have not and that human nails are a viable sample matrix for toxicology.

• Klíčová slova
• ATR–FTIR, PLS-DA, SVM-DA, fentanyl, fingernails, machine learning, toenails,
• MeSH
• fentanyl * analýza   izolace a purifikace   MeSH
• lidé MeSH
• nehty * chemie   MeSH
• spektroskopie infračervená s Fourierovou transformací metody   MeSH
• strojové učení * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Názvy látek
• fentanyl * MeSH

OBJECTIVE: To profile maternal plasma metabolome in spontaneous preterm birth. METHOD: In this retrospective case-control study, we have examined plasma of patient with preterm birth (between 22 and 36 weeks of pregnancy (n = 57)), with threatened preterm labor (between 23 and 36 weeks of pregnancy (n = 49)), and with term delivery (n = 25). Plasma samples were analysed using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF-MS) in positive and negative polarity modes. RESULTS: We found 168 differentially expressed metabolites that were significantly distinct between study groups. We determined 51 metabolites using publicly available databases that could be subdivided into one of the five groups: amino acids, fatty acids, lipids, hormones, and bile acids. PLS-DA models, verified by SVM classification accuracy, differentiated preterm birth and term delivery groups. CONCLUSIONS: Maternal plasma metabolites are different between term and preterm parturitions. Part of them may be related with preterm labor, while others may be affected by gestational age or the beginning of labor. Metabolite profile can classify preterm or term delivery groups raising the potential of metabolome as a biomarker to identify high-risk pregnancies. Metabolomic studies are also a tool to detect individual compounds that may be further tested in targeted researches.

• MeSH
• dospělí MeSH
• gestační stáří MeSH
• lidé MeSH
• mladý dospělý MeSH
• multivariační analýza MeSH
• předčasná porodní činnost krev   MeSH
• předčasný porod krev   MeSH
• retrospektivní studie MeSH
• studie případů a kontrol MeSH
• těhotenství MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• těhotenství MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH