Chemische Charakterisierung und Spurenanalytik
Filtern
Erscheinungsjahr
- 2022 (128) (entfernen)
Dokumenttyp
- Zeitschriftenartikel (48)
- Vortrag (44)
- Posterpräsentation (25)
- Sonstiges (3)
- Buchkapitel (2)
- Beitrag zu einem Tagungsband (2)
- Forschungsdatensatz (2)
- Preprint (1)
- Forschungsbericht (1)
Schlagworte
- BAMline (9)
- ICP-MS (8)
- Imaging (6)
- Laser ablation (6)
- PFAS (6)
- Process Analytical Technology (6)
- Synchrotron (6)
- Fluorine (5)
- Mass Spectrometry (5)
- Mass spectrometry (5)
Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (93)
- 1.1 Anorganische Spurenanalytik (32)
- 6 Materialchemie (28)
- 1.4 Prozessanalytik (18)
- 1.6 Anorganische Referenzmaterialien (17)
- 1.7 Organische Spuren- und Lebensmittelanalytik (16)
- 4 Material und Umwelt (13)
- 1.8 Umweltanalytik (12)
- 6.3 Strukturanalytik (12)
- 6.6 Physik und chemische Analytik der Polymere (11)
Paper des Monats
- ja (1)
Prostate cancer (PCa) is one of the most common cancers in men. For detection and diagnosis of PCa, non-invasive methods, including magnetic resonance imaging (MRI), can reduce the risk potential of surgical intervention. To explore the molecular characteristics of the tumor, we investigated the applicability of ferumoxytol in PCa in a xenograft mouse model in two different tumor volumes, 500 mm3 and 1000 mm3. Macrophages play a key role in tumor progression, and they are able to internalize iron-oxide particles, such as ferumoxytol. When evaluating T2*-weighted sequences on MRI, a significant decrease of signal intensity between pre- and post-contrast images for each tumor volume (n = 14; p < 0.001) was measured. We, furthermore, observed a higher signal loss for a tumor volume of 500 mm3 than for 1000 mm3. These findings were confirmed by histological examinations and laser ablation inductively coupled plasma-mass spectrometry. The 500 mm3 tumors had 1.5% iron content (n = 14; sigma = 1.1), while the 1000 mm3 tumors contained only 0.4% iron (n = 14; sigma = 0.2). In vivo MRI data demonstrated a correlation with the ex vivo data (R2 = 0.75). The results of elemental analysis by inductively coupled plasma-mass spectrometry correlated strongly with the MRI data (R2 = 0.83) (n = 4). Due to its long retention time in the blood, biodegradability, and low toxicity to patients, ferumoxytol has great potential as a contrast agent for visualization PCa.
The most profound consequences of the presence of Ca–Mg carbonates (CaCO3–MgCO3) in the Earth’s upper mantle may be to lower the melting temperatures of the mantle and control the melt composition.
Low-degree partial melting of a carbonate-bearing mantle produces CO2-rich, silica-poor melts compositionally imposed by the melting relations of carbonates. Thus, understanding the melting relations in the CaCO3–MgCO3 system facilitates the interpretation of natural carbonate-bearing silicate systems.
We report the melting relations of the CaCO3–MgCO3 system and the partition coefficient of trace elements between carbonates and carbonate melt from experiments at high pressure (6 and 9 GPa) and temperature (1300–1800 ◦C) using a rocking multi-anvil press. In the absence of water, Ca–Mg carbonates are stable along geothermal gradients typical of subducting slabs. Ca–Mg carbonates (∼ Mg0.1–0.9Ca0.9–0.1CO3) partially melt beneath mid-ocean ridges and in plume settings. Ca–Mg carbonates melt incongruently, forming periclase crystals and carbonate melt between 4 and 9 GPa. Furthermore, we show that the rare earth element (REE) signature of Group-I kimberlites, namely strong REE fractionation and depletion of heavy REE relative to the primitive mantle, is resembled by carbonate melt in equilibrium with Ca-bearing magnesite and periclase at 6 and 9 GPa. This suggests that the dolomite–magnesite join of the CaCO3–MgCO3 system might be useful to approximate the REE signature of carbonate-rich melts parental to kimberlites.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
Isotope analysis is a tool for material research. For example, it may provide information about the provenance of a sample or changes in dynamic systems. Here is presented optical spectroscopy as an analytical alternative to mass spectrometry for isotope quantification based on the isotopic shift of atoms and diatomic molecules.
Calcium isotope analysis can be an important tool for paleoclimate studies of the carbon cycle, as well in carbon capture technology, but its utility is limited by challenges using conventional mass spectrometry. We propose a new fast, precise, and high-throughput technology based on multiple complementary high-resolution spectroscopies analyzed by machine-learning.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer‐based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented
algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
Towards Unbiased Evaluation of Ionization Performance in LC-HRMS Metabolomics Method Development
(2022)
As metabolomics increasingly finds its way from basic science into applied and regulatory environments, analytical demands on nontargeted mass spectrometric detection methods continue to rise. In addition to improved chemical comprehensiveness, current developments aim at enhanced robustness and repeatability to allow long-term, inter-study, and meta-analyses. Comprehensive metabolomics relies on electrospray ionization (ESI) as the most versatile ionization technique, and recent liquid chromatography-high resolution mass spectrometry (LC-HRMS) instrumentation continues to overcome technical limitations that have hindered the adoption of ESI for applications in the past. Still, developing and standardizing nontargeted ESI methods and instrumental setups remains costly in terms of time and required chemicals, as large panels of metabolite standards are needed to reflect biochemical diversity. In this paper, we investigated in how far a nontargeted pilot experiment, consisting only of a few measurements of a test sample dilution series and comprehensive statistical analysis, can replace conventional targeted evaluation procedures. To examine this potential, two instrumental ESI ion source setups were compared, reflecting a common scenario in practical method development. Two types of feature evaluations were performed, (a) summary statistics solely involving feature intensity values, and (b) analyses additionally including chemical interpretation.
Results were compared in detail to a targeted evaluation of a large metabolite standard panel. We reflect on the advantages and shortcomings of both strategies in the context of current harmonization initiatives in the metabolomics field.
IsoCor
(2022)
Despite numerous advantages offered by hyphenation of chromatography and electrokinetic separation methods with multicollector (MC) ICP-MS for isotope analysis, the main limitation of such systems is the decrease in precision and increase in uncertainty due to generation of short transient signals. To minimize this limitation, most authors compare several isotope ratio calculation methods and establish a multi-step data processing routine based on the precision and accuracy of the methods. However, to the best of our knowledge, there is no universal data processing tool available that incorporates all important steps of the treatment of the transient signals. Thus, we introduce a data processing application (App) IsoCor that facilitates automatic calculation of isotope ratios from transient signals and eases selection of the most suitable method. The IsoCor App performs baseline subtraction, peak detection, mass bias correction, isotope ratio calculation and delta calculation. The feasibility and reliability of the App was proven by reproducing the results from isotope analysis of three elements (neodymium, mercury and sulfur) measured on-line via hyphenated systems. The IsoCor App provides trackability of the results to ensure quality control of the analysis.
Estrogens are endocrine disrupting chemicals and of high concerns due to demonstrated harmful effects on the environment and low effect levels. For monitoring and risk assessment, several estrogens were included in the "watch list" of the EU Water Framework Directive which sets very low environmental quality standard (EQS) levels for Estrone (E1) and 17β-Estradiol (E2) of 0.4 ng L−1 and for 17α-Ethinylestradiol (EE2) of 0.035 ng L−1 requiring sensitive detection methods, as well as extensive sample preparation. A sensitive, derivatization-free, isotope dilution calibration HPLC-MS/MS method for a panel of 5 selected estrogens (including the 3 estrogens of the EU WFD watchlist), and a procedure for the reproducible preparation of a representative whole water matrix including mineral water, humic acids and solid particulate matter are presented. These are used in a diligent comparison of classical solid phase extraction (SPE) on hydrophilic-lipophilic balanced (HLB) phase to SPE on an estrogen-specific molecularly imprinted polymer phase (MISPE) for ultra-trace levels of the analytes (1–10 ng L−1). Additionally, a two-step procedure combining HLB SPE disks followed by MISPE is evaluated. The tow-step procedure provides superior enrichment, matrix removal and sample throughput while maintaining comparable recovery rates to simple cartridge SPE. Estimated method quantification limits (MQLs) range from 0.109–0.184 ng L−1 and thus meet EQS-levels for E1 and E2, but not EE2. The representative whole water matrix provides a reproducible comparison of sample preparation methods and lays the foundation for a certified reference material for estrogen analysis. The presented method will serve as the basis for an extended validation study to assess its use for estrogen monitoring in the environment.
Per- and polyfluorinated alkyl substances (PFASs) are a group of several thousand individual compounds. Many PFASs are extremely persistent, bioaccumulative and toxic. The analysis of PFASs is challenging because of their various chemical and physical properties as well as the high number of compounds. Target-based approaches (e.g., LC-MS/MS) are limited to the availability of analytical grade standards and are not suitable for the analysis of new/unknown PFASs and transformation products. Therefore, PFAS sum parameter methods become increasingly important to indicate realistic PFAS pollution levels.
PFAS sum parameters display the proportion of organically bound fluorine that can either be extracted (EOF) or adsorbed to activated carbon (AOF). For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. High resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) is a sensitive and highly selective tool for fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification of c(F) 2.7 µg/L.
In the present work a HR-CS-GFMAS method for EOF analysis was utilized for suspended particulate matter (SPM) analysis in German rivers in time lines from 2005–2020. Therefore, time and spatial resolved trends were investigated. In addition, SPM samples were analyzed for the Σ41PFAS using target analysis based on UHPLC-HRMS. Overall, target analysis drastically underestimated the total PFAS burden in SPM of German rivers compared to the EOF HR-CS-GFMAS analysis. Using a fluorine mass balance approach, only 0.2% to 38.6% of the EOF was explainable using the Σ41PFAS determined with target analysis. Our study highlights the need to integrate PFAS sum parameters (e.g., EOF with HR-CS-GFMAS) in PFAS risk assessment strategies.