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Warfarin als ein Vertreter der NSO-Hetereozyklen, ist seit den 1950er Jahren einer der bekanntesten Gerinnungshemmer. Beim Menschen wird es bis heute zur Vorbeugung von Thrombose und der Behandlung von Vorhofflimmern und Arrhythmie eingesetzt. Doch schon einige Jahre vor der FDA Zulassung als Medikament wurde es zur Bekämpfung von Nagetieren eingesetzt. Bis heute wurde es nur teilweise durch weitaus wirksamere antikoagulante Rodentizide (ARs) der zweiten Generation, sogenannte Superwarfarine, ersetzt. In der Fachliteratur finden sich zahlreiche Beispiele für sekundäre und tertiäre Vergiftung mit ARs bei Wildtieren und anderen Nichtzieltieren. Bisher ist relativ wenig über die Bioakkumulation, Persistenz und Toxizität von ARs und deren Transformationsprodukten (TPs) in der terrestrischen und aquatischen Umwelt, sowie der Nahrungskette bekannt.
Um Einblicke in mögliche Transformations- und Abbauprozesse von Warfarin zu erhalten und um Umwelteinflüsse zu simulieren, wurde es in einer elektrochemischen Reaktorzelle oxidativ umgesetzt und mittels Massenspektrometrie analysiert. Hinsichtlich der Wasseraufbereitung in Kläranlagen wurden technisch relevante Simulationsverfahren wie Chlorung, UV-Bestrahlung und Ozonung angewendet um potentielle Eliminierungswege aufzuklären. Gebildete Transformationsprodukte wurden daher mittels unterschiedlicher chromatografischer Verfahren getrennt, massenspektrometrisch analysiert und verglichen.
Extraction, chromatographic separation, and quantification of low-concentration organic compounds in complex matrices are core challenges for reference material producers and providers of calibration services. Evidence of successful participation in formal, relevant international comparisons is needed to document measurement capability claims made by national metrology institutes (NMIs) and designated institutes (DIs). To enable NMIs and DIs to update or establish their claims, in 2014 the Organic Analysis Working Group (OAWG) initiated CCQM-K95.1 "Low-Polarity Analytes in a Botanical Matrix: Polycyclic Aromatic Hydrocarbons (PAHs) in Tea". This was a follow-on comparison from CCQM-K95 which was completed in 2014.
The polycyclic aromatic hydrocarbons (PAHs) benz[a]anthracene (BaA) and benzo[a]pyrene (BaP) are considered priority pollutants by U.S. Environmental Protection Agency and are regulated contaminants in food, pose chromatographic separation challenges, and for which exist well-characterized measurement procedures and standard materials. BaA and BaP in a smoked tea were therefore selected as representative target measurands for CCQM-K95.1. Ten NMIs participated in CCQM-K95.1. The consensus summary mass fractions for the two PAHs are in the range of (50 to 70) ng/g with relative standard deviations of (6 to 10) %.
Successful participation in CCQM K95.1 demonstrates the following measurement capabilities in determining mass fraction of organic compounds, with molar mass of 100 g/mol to 500 g/mol and having polarity pKow −2, in a botanical matrix ranging in mass fraction from 10 ng/g to 1000 ng/g: (1) value assignment of primary reference standards (if in-house purity assessment carried out), (2) value assignment of single and/or multi-component organic solutions, (3) extraction of analytes of interest from the matrix, (4) cleanup and separation of analytes of interest from interfering matrix or extract components, and (5) separation and quantification using gas chromatography or liquid chromatography.
Solutions of organic analytes of known mass fraction are typically used to calibrate the measurement processes used to determine these compounds in matrix samples. Appropriate value assignments and uncertainty calculations for calibration solutions are critical for accurate measurements. Evidence of successful participation in formal, relevant international comparisons is needed to document measurement capability claims (CMCs) made by national metrology institutes (NMIs) and designated institutes (DIs). To enable NMIs and DIs to update or establish their claims, in 2015 the Organic Analysis Working Group (OAWG) sponsored CCQM-K131 "Low-Polarity Analytes in a Multicomponent Organic Solution: Polycyclic Aromatic Hydrocarbons (PAHs) in Acetonitrile".
Polycyclic aromatic hydrocarbons (PAHs) result from combustion sources and are ubiquitous in environmental samples. The PAH congeners, benz[a]anthracene (BaA), benzo[a]pyrene (BaP), and naphthalene (Nap) were selected as the target analytes for CCQM-K131. These targets span the volatility range of PAHs found in environmental samples and include potentially problematic chromatographic separations. Nineteen NMIs participated in CCQM-K131. The consensus summary mass fractions for the three PAHs are in the range of (5 to 25) μg/g with relative standard deviations of (2.5 to 3.5) %.
Successful participation in CCQM-K131 demonstrates the following measurement capabilities in determining mass fraction of organic compounds of moderate to insignificant volatility, molar mass of 100 g/mol up to 500 g/mol, and polarity pKow < −2 in a multicomponent organic solution ranging in mass fraction from 100 ng/g to 100 μg/g: (1) value assignment of primary reference standards (if in-house purity assessment carried out), (2) value assignment of single and/or multi-component organic solutions, and (3) separation and quantification using gas chromatography or liquid chromatography.
High spatially resolved quantitative bioimaging of CdSe/ZnS Quantum Dots uptake in two kinds of cells is investigated combining laser ablation inductively coupled plasma mass spectrometry and the spatially resolved analysis of dried pL-droplets from a solution with a known concentration of Quantum Dots. Single cells and dried pL-droplets are morphologically characterized by Atomic Force Microscopy. A number concentration of CdSe/ZnS QDs between 3.5 104 and 48 104 is estimated to be uptaken by several selected single cells, after being incubated in the presence of a QDs suspension added to a standard cell culture medium. Mono-elemental bioimaging at subcellular resolution seems to show a higher number concentration of the CdSe/ZnS QDs in the cytosol around the cell nucleus.
An alternative method for lithium isotope amount ratio analysis based on a combination of high-resolution atomic absorption spectrometry and spectral data analysis by machine learning (ML) is proposed herein. It is based on the well-known isotope shift of approximately 15 pm for the electronic transition 22P←22S at around the wavelength of 670.8 nm, which can be measured by the state-of-the-art high-resolution continuum source graphite furnace atomic absorption spectrometry. For isotope amount ratio analysis, a scalable tree boosting ML algorithm (XGBoost) was employed and calibrated using a set of samples with 6Li isotope amount fractions, ranging from 0.06 to 0.99 mol mol–1, previously determined by a multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS). The calibration ML model was validated with two certified reference materials (LSVEC and IRMM-016). The procedure was applied toward the isotope amount ratio determination of a set of stock chemicals (Li2CO3, LiNO3, LiCl, and LiOH) and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. The results of these determinations were compared with those obtained by MC-ICP-MS and found to be metrologically comparable and compatible. The residual bias was −1.8‰, and the precision obtained ranged from 1.9 to 6.2‰. This precision was sufficient to resolve naturally occurring variations, as demonstrated for samples ranging from approximately −3 to +15‰. To assess its suitability to technical applications, the NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification. The results obtained were metrologically compatible with each other.
The therapeutic dose of lithium (Li) compounds, which are widely used for the treatment of psychiatric and hematologic disorders, is close to its toxic level; therefore, drug monitoring protocols are mandatory. Herein, we propose a fast, simple, and low-cost analytical procedure for the traceable determination of Li concentration in human serum, based on the monitoring of the Li isotope dilution through the partially resolved isotope shift in its electronic transition around 670.80 nm using a commercially available high-resolution continuum source graphite furnace atomic absorption spectrometer. With this technique, serum samples only require acidic digestion before analysis. The procedure requires three measurements—an enriched 6Li spike, a mixture of a certified standard solution and spike, and a mixture of the sample and spike with a nominal 7Li/6Li ratio of 0.82. Lanthanum has been used as an internal spectral standard for wavelength correction. The spectra are described as the linear superposition of the contributions of the respective isotopes, each consisting of a spin-orbit doublet, which can be expressed as Gaussian components with constant spectral position and width and different relative intensity, reflecting the isotope ratio in the sample. Both the spectral constants and the correlation between isotope ratio and relative band intensity have been experimentally obtained using commercially available materials enriched with Li isotopes. The Li characteristic mass (mc) obtained corresponds to 0.6 pg. The procedure has been validated using five human serum certified reference materials. The results are metrologically comparable and compatible to the certified values. The measurement uncertainties are comparable to those obtained by the more complex and expensive technique, isotope dilution mass spectrometry.
In this poster for the SCIX Conference, we apply an analytical procedure based on the monitoring of the lithium isotope through the partially resolved isotope shift in the electronic transition 22P<-22S around wavelength 670.80 nm using high-resolution continuum source atomic absorption spectrometer (HR-CS-AAS) in combination with machine learning (ML) for the determination of Li Isotope ratio analysis.
Glow discharge optical emission spectroscopy (GD-OES) is a technique for the analysis of solids such as metals, semiconductors, and ceramics. A low-pressure glow discharge plasma is applied in this system, which ‘sputters’ and promotes the sample atoms to a higher energy state. When the atoms return to their ground state, they emit light with characteristic wavelengths, which a spectrometer can detect. Thus, GD-OES combines the advantages of ICP-OES with solid sampling techniques, which enables it to determine the bulk elemental composition and depth profiles. However, direct solid sampling methods such as glow-discharge spectroscopy require reference materials for calibration due to the strong matrix effect.
Reference materials are essential when the accuracy and reliability of measurement results need to be guaranteed to generate confidence in the analysis. These materials are frequently used to determine measurement uncertainty, validate methods, suitability testing, and quality assurance. In addition, they guarantee that measurement results can be compared to recognized reference values. Unfortunately, the availability of certified reference materials suited to calibrate all elements in different matrix materials is limited. Therefore various calibration strategies and the preparation of traceable matrix-matched calibration standards will be discussed.
Machine learning is an essential component of the growing field of data science. Through statistical methods, algorithms are trained to make classifications or predictions, uncovering key insights within data mining projects. Therefore, it was tried in our work to combine GD-OES with machine learning strategies to establish a new and robust calibration model, which can be used to identify the elemental composition and concentration of metals from a single spectrum. For this purpose, copper reference materials from different manufacturers, which contain various impurity elements, were investigated using GD-OES. The obtained spectra information are evaluated with different algorithms (e.g., gradient boosting and artificial neural networks), and the results are compared and discussed in detail.
An alternative method for lithium isotope analysis by using high-resolution atomic absorption spectrometry (HR-CS-AAS) is proposed herein. This method is based on monitoring the isotope shift of approximately 15 pm for the electronic transition 22P←22S at around the wavelength of 670.8 nm, which can be measured by state-of-the-art HR-CS-AAS. Isotope analysis can be used for (i) the traceable determination of Li concentration and (ii) isotope amount ratio analysis based on a combination of HR-CS-AAS and spectral data analysis by machine learning (ML).
In the first case, the Li spectra are described as the linear superposition of the contributions of the respective isotopes, each consisting of a spin-orbit doublet, which can be expressed as Gaussian components with constant spectral position and width and different relative intensity, reflecting the isotope ratio in the sample. Precision was further improved by using lanthanum as internal spectral standard. The procedure has been validated using human serum-certified reference materials. The results are metrologically comparable and compatible with the certified values.
In the second case, for isotope amount ratio analysis, a scalable tree boosting ML algorithm (XGBoost) was employed and calibrated using a set of samples with 6Li isotope amount fractions ranging from 0.06 to 0.99 mol mol−1. The training ML model was validated with certified reference materials. The procedure was applied to the isotope amount ratio determination of a set of stock chemicals and a BAM candidate reference material NMC111 (LiNi1/3Mn1/3Co1/3O2), a Li-battery cathode material. These determinations were compared with those obtained by MC-ICP-MS and found to be metrologically comparable and compatible. The residual bias was −1.8‰, and the precision obtained ranged from 1.9‰ to 6.2‰. This precision was sufficient to resolve naturally occurring variations. The NMC111 cathode candidate reference material was analyzed using high-resolution continuum source atomic absorption spectrometry with and without matrix purification to assess its suitability for technical applications. The results obtained were metrologically compatible with each other.