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Multidimensional isotope profiling is a useful tool for the characterization of the provenance of active pharmaceutical ingredients (API). To evaluate this approach, samples of the nonsteroidal anti-inflammatory drug (NSAIDs) ibuprofen were collected from 32 manufactures and 13 countries, and carbon, hydrogen and oxygen isotope ratios were analyzed by elemental analyzer, chromium-filled elemental analyzer and high temperature conversion elemental analyzer (EA, Cr-EA and TC/EA) coupled to an isotope ratio mass spectrometry (IRMS). The range of isotope values of ibuprofen (δ(13)C: -33.2±0.1‰ to -27.4±0.1‰; δ(2)H: -121.4±1.5‰ to -41.2±0.8‰; and δ(18)O: -12.6±0.3‰ to 19.0±0.6‰) allowed characterization and distinction of 5 groups, which reflect synthetic pathways and/or use of different raw materials, as well as possible isotope fractionation during the synthesis reactions. This study highlights that multi isotope fingerprinting has potential for identification of sources, and provides a database of isotope composition of ibuprofen (δ(2)H, δ(13)C, δ(18)O) that might improve the tracing of origin, transport pathways and environmental fate of ibuprofen.
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http://dx.doi.org/10.1016/j.jpba.2015.07.030 | DOI Listing |
Anal Chim Acta
October 2025
State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan, 030006, China; Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China.
Background: In coal quality analysis, spectroscopic techniques such as near-infrared spectroscopy (NIRS) and X-ray fluorescence (XRF) offer rapid and non-destructive measurements, but differences between instruments and coal types may lead to the failure of established models. Given the complexity of coal, it is important to systematically evaluate the applicability of traditional calibration transfer methods, such as the Slope/Bias (S/B) method and Piecewise Direct Standardization (PDS). Meanwhile, machine learning algorithm such as Domain-Adversarial Neural Networks (DANN), have shown great potential in addressing data distribution differences between source and target domains, offering new possibilities for calibration transfer.
View Article and Find Full Text PDFEnviron Pollut
August 2025
African Centre of Excellence for Water and Environmental Research (ACEWATER), Redeemer's University, P.M.B 230, Ede, 232101, Osun State, Nigeria; Department of Chemical Sciences, Faculty of Natural Sciences, Redeemer's University, P.M.B 230, Ede, Osun State, Nigeria. Electronic address: unuabonahe@r
The present study was carried out to understand the spatial distribution of toxic heavy metals in aerosols from indoor environments in universities, elucidate the potential health implications and provide strategies for improved indoor air quality. Aerosols were characterized using SEM, Particle analyzer and BET Surface Area analyzer and quantification of heavy metals was carried out with ICP-MS. Characterization analysis indicates the samples are mainly made of elemental carbon while particle size of aerosols from the three indoor environments are consistent at ≈ 3.
View Article and Find Full Text PDFData Brief
October 2025
Dpto. de Prehistoria y Arqueología, Universidad de Sevilla, 41004, Seville, Spain.
This dataset includes the compositional information of = 1778 geoarchaeological samples of green phosphate minerals sourced from three major Iberian deposits with evidence of prehistoric mining: Aliste, Terena, and the Gavà Mines. It has been used to develop a data-driven framework that integrates portable X-ray fluorescence (p-XRF) analysis and machine learning (ML), to determine the provenance of archaeological artifacts based on its elemental composition. In addition, a mineralogical analysis by X-ray diffraction (XRD) of a subset ( = 249; n_Aliste = 122, n_Terena = 47, n_Gavà = 80) was conducted to complement the geochemical characterisation of the sample.
View Article and Find Full Text PDFInt J Biol Macromol
September 2025
Department of Biochemistry, ICMR-RMRIMS, Agamkuan, Patna 800007, India. Electronic address:
This study explores the use of green-synthesized chitosan-coated CuO nanoparticle (Ch-CuNs) for the sustainable removal of hexavalent chromium (Cr (VI)). Scanning electron microscope (SEM) analysis confirmed the formation of spherical nanoparticles, while energy dispersive X-ray analyzer (EDX) and elemental analysis verified the presence of Cr (VI) on the nanoparticle surface, indicating successful adsorption. Fourier Transform Infrared (FTIR) spectroscopy analysis identified functional groups on the nanoparticles that actively participated in Cr (VI) adsorption.
View Article and Find Full Text PDFHistopathology
August 2025
Division of Respiratory Medicine, Niigata University Medical and Dental Hospital, Niigata, Japan.
Aims: Giant cell interstitial pneumonia (GIP) is a rare type of interstitial lung disease (ILD) caused by hard metal dust. However, instances of GIP without clear exposure to hard metals have been documented. This study aimed to determine whether or not GIP is pathognomonic for hard metal lung disease (HMLD) using an electron probe micro-analyser (EPMA).
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