Classification of Mass Spectral Data to Assist in the Identification of Novel Synthetic Cannabinoids.

Detection and characterization of newly synthesized cannabinoids (NSCs) is challenging due to the lack of availability of reference standards and chemical data. In this study, a binary classification system was developed and validated using partial least square discriminant analysis (PLS-DA) by utilizing readily available mass spectral data of known drugs to assist in the identification of previously unknown NCSs. First, a binary classification model was developed to discriminate cannabinoids and cannabinoid-related compounds from other drug classes.

Transmission Infrared Microscopy and Machine Learning Applied to the Forensic Examination of Original Automotive Paint.

Alternate least squares (ALS) reconstructions of the infrared (IR) spectra of the individual layers from original automotive paint were analyzed using machine learning methods to improve both the accuracy and speed of a forensic automotive paint examination. Twenty-six original equipment manufacturer (OEM) paints from vehicles sold in North America between 2000 and 2006 served as a test bed to validate the ALS procedure developed in a previous study for the spectral reconstruction of each layer from IR line maps of cross-sectioned OEM paint samples. An examination of the IR spectra from an in-house library (collected with a high-pressure transmission diamond cell) and the ALS reconstructed IR spectra of the same paint samples (obtained at ambient pressure using an IR transmission microscope equipped with a BaF cell) showed large peak shifts (approximately 10 cm) with some vibrational modes in many samples comprising the cohort.

Synthesis and Characterization of -Isopropylacrylamide Microspheres as pH Sensors.

Swellable polymer microspheres that respond to pH were prepared by free radical dispersion polymerization using -isopropylacrylamide (NIPA), ,-methylenebisacrylamide (MBA), 2,2-dimethoxy-2-phenylacetylphenone, -tert-butylacrylamide (NTBA), and a pH-sensitive functional comonomer (acrylic acid, methacrylic acid, ethacrylic acid, or propacrylic acid). The diameter of the microspheres was between 0.5 and 1.

Analysis of gentisic acid and related renal cell carcinoma biomarkers using reversed-phase liquid chromatography with water-rich mobile phases.

The problem of longer retention times using water-rich mobile phases in reversed phase liquid chromatography (RPLC) has been addressed using hydrophobic alcohols such as butanol in very low quantities (approximately 0.1%) as the organic modifier. Advantages of water-rich mobile phases in RPLC for the separation of water-soluble and weakly retained compounds are improved separation of congeners and better tuning of RPLC separations.