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Chemical Profiling of Nyaope and Its Public Health Implications
Lufuno Ratshisusu1, Omphile E Simani1, Nakisani B Moyo2
1HIV and Hepatitis Research Unit, Department of Medical Virology, Sefako Makgatho Health Sciences University, Pretoria 0208, South Africa.
None:
Nyaope is a highly addictive street drug that is widely used in South Africa, particularly in urban and peri-urban settings. Although it is traditionally consumed by smoking, increasing injection use has raised serious public health concerns due to an elevated risk of bloodborne viral infections and other drug-related health complications. The composition of nyaope is highly variable, frequently adulterated, and continually evolving, thus highlighting the need for detailed chemical characterization to support forensic investigations and public health interventions. An exploratory study design was conducted using eight nyaope samples seized from six sites within the City of Tshwane Metropolitan Municipality that were provided by the South African Police Service Forensic Science Chemistry Laboratory (SAPS-FSCL). Samples were analyzed using Ultra-High-Performance Liquid Chromatography coupled to Quadrupole-Time-of-Flight Mass Spectrometry (UHPLC-qTOF-MS) operated in data-dependent acquisition mode under positive ionization. Raw data from the methanolic extracts of nyaope was converted to mzML format and processed using SIRIUS software for compound annotation based on isotope pattern ranking and fragmentation analysis. Chemical profiling revealed multiple opiate-related compounds, including noscapine, heroin, papaverine, and codeine. Molecular networking revealed chemically diverse yet structurally related metabolites consistent with a poppy-derived botanical origin. In addition, multiple synthetic pharmaceutical adulterants were detected. Notably, one sample contained formaline, a toxic rodenticide structurally related to protopine, highlighting the risk of misidentification using less advanced analytical approaches. This study demonstrates the value of advanced computational metabolomics, including molecular networking and machine-learning-assisted mass spectrometry interpretation, for comprehensive characterization of complex illicit drug mixtures. These approaches enhance forensic accuracy and support informed public health and law-enforcement responses.
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