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Eingeladener Vortrag
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Introduction: The influence of copper, iron and zinc concentrations on the formation of ß-amyloid plaques and neurofibrillary tangles in Alzheimer’s disease (AD) is widely discussed in the community. The results from human and animal studies so far are mixed with some studies showing a correlation and others not. From a number of studies, it is known that disease state and isotopic composition of essential elements can be coupled.
Aim: The aim of the study was to identify changes in element content and isotopic composition in two transgenic mouse models used in AD research compared to their genetic WT relatives and to establish whether element content and isotopic signature between different laboratories is comparable.
Methods: ß-amyloid (5xFAD) and tau overexpressing (L66) mice together with their matching wild-types were bred at dedicated facilities in accordance with the European Communities Council Directive (63/2010/EU). Serum and brain were sampled after sacrifice and the samples distributed among the participants of the study. The tissues were acid digested for total element determination and high-precision isotope ratio determination. Element content was determined by either sector-field or quadrupole-based inductively coupled plasma mass spectrometry (ICPMS). For the determination of isotope ratios multi-collector ICPMS was used.
Results: Total copper content was significantly higher for L66 and their matched WT compared to 5xFAD and WT. Brains of L66 mice contained more Fe in brain than their WT, Zn and Cu were not significantly different between L66 and WT. Whereas 5xFAD mice had a slightly lower Cu and slightly higher Zn concentration in brain compared to WT. The isotopic signature in brain of L66 mice for Fe was different from their controls, whereas Zn isotope ratios were influenced in 5xFAD mice compared to their WT . The Cu isotopic ratio did not seem to be influenced in either strain. In serum, the shifts were less pronounced.
Conclusion: Even though neither Tau-protein nor amyloid precursor protein are known to be metal-dependent / -containing proteins, the overexpression of both influences the Fe, Cu and Zn metabolism in brain and to some extent also in serum as can be seen not only using total element determination but probably more clearly studying the isotopic signature of Fe, Cu and Zn.
This presentation provides a short introduction to the Commission on Isotopic Abundances and Atomic Weights (CIAAW). It describes the role of the Commission and provides an insight into its work and the corresponding principal tasks. Finally, it provides the reader with the latest achievements and with the most recent publications.
Modular chemical production is a tangible implementation of the digital transformation of the specialty chemicals process industry. In particular, it enables acceleration of process development and thus faster time to market by flexibly interconnecting and orchestrating standardized physical modules and bringing them to life. For this purpose, specific (chemical) sensors of process analytics are needed, preferably without lengthy calibration or spectroscopic model development.
An excellent example of a "direct" analytical method is online nuclear magnetic resonance (NMR) spectroscopy. NMR spectroscopy meets the requirements of a direct analytical method because of the direct correlation between the signal area in the spectrum ("counting" the nuclear spins) and the analyte amount of substance concentrations. It is also extremely linear over the concentration range.
With the availability of compact benchtop NMR instruments, it is now possible to bring NMR spectroscopy directly into the field, in close proximity to specialized laboratory facilities, pilot plants, and even industrial-scale production facilities. The first systems are in TRL 8 (Qualified System with Proof of Functionality in the Field).
The presentation will discuss the many building blocks of online nuclear magnetic resonance spectroscopy, from flow cells to automated data analysis.
Utilizing Aspergillus niger Fumonisin Amine Oxidase for the Electrochemical Detection of Fumonisin
(2023)
Fumonisins are a class of toxic secondary metabolites produced by various Fusarium species. The two most important producers of fumonisins are F. verticillioides and F. proliferatum but also Aspergillus niger is known to produce fumonisins. Most frequently they occur on maize, but also other grains can be contaminated with this group of mycotoxins. Exposure to fumonisins by dietary intake can have serious health effects on farm animals and also within humans. Thus, the European Commission sets legal limits for fumonisins in feed and foodstuffs. The detection of fumonisins is frequently performed in laboratories by chromatographic methods, which are costly and require trained personnel. Simplifying the analysis is therefore a major goal using portable detection systems. Electrochemical enzymatic biosensors offer great promise to meet this demand. Here we report for the first time an enzymatic fumonisin sensing approach with amperometric detection. For this purpose, an Aspergillus niger fumonisin amine oxidase (AnFAO) catalyzing the oxidative deamination of fumonisins, producing hydrogen peroxide, was recombinantly produced in E. coli. It was found that the specific activity of AnFAO using 20 μM Fumonisin B1 as substrate is higher than for 20 μM Fumonisin B2 with 0.122 U mg-1 and 0.058 U mg-1, respectively. It was possible to show a dependence of enzyme activity with enzyme – and substrate-concentration. For fumonisin B1 detection, the enzyme was coupled covalently to magnetic particles and the enzymatically produced H2O2 was detected amperometrically in a flow injection system using Prussian blue carbon electrodes. The developed method allows to quantify fumonisin B1 concentrations down to 1.5 µM and demonstrates that the recombinantly produced AnFAO was able to deaminate different concentrations of fumonisin even in immobilized form. Thus, this enzyme is well suited to develop an enzyme based electrochemical biosensor for fumonisin contaminated food and feed.
Per- and polyfluoroalkyl substances (PFASs) are a group of anthropogenic contaminates associated with persistent, bioaccumulative and toxic properties. Mostly, target-based approaches (e.g., LC-MS/MS) are utilized for the analysis of PFASs in the environment. Target approaches are limited to a few selected PFASs and therefore underestimate the total PFAS burden. Analytical approaches based on total fluorine for PFAS sum parameter analysis become increasingly important to indicate realistic PFAS pollution levels.
Recently high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) turned out to be 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 in the low µg F/L range. HR-CS-GFMAS analysis can be combined with the extractable organically bound fluorine (EOF) approach whereas PFASs are extracted from liquid or solid samples using organic solvents and/or solid phase extraction (SPE).
In this presentation the applicability of HR-CS-GFMAS for organic fluorine analysis in various environmental sample including (1) water samples, (2) soil samples and (3) plant samples is demonstrated.
(1) We investigated EOF concentrations in water bodies in Berlin, Germany and used additional PFAS target analysis for a PFAS mass balance approach. EOF concentrations were in the expected range for an urban river system. However, downstream of an effluent discharge, the EOF increased by one order of magnitude from 40 to 574 ng F/L. Target analysis determined mostly short-chained perfluorinated carboxylic acids and sulfonic acids, which however only made up less than 10% of the EOF. This study highlights that EOF screening using HR-CS-GFMAS is useful and advantageous compared to target analysis to identify pollution sites in urban water systems.
(2) For soil samples, we optimized a fast and simple PFAS extraction method for EOF determination. The developed extraction method consists of a liquid-solid extraction without any additional SPE for fluoride removal. We investigated different soil samples using the optimized method with and without an additional SPE clean-up step and revealed a drastic underestimation of EOF mass fractions using SPE. The optimized method is a valuable screening tool for fast PFAS monitoring.
(3) For plant samples, we conducted a study on the uptake and fate of PFASs in bean plants. For PFAS mass balancing HR-CS-GFMAS analysis was combined with LC-MS/MS analysis. PFASs were spiked as mixtures of known and unknown composition. Short-chained PFASs were determined with high mass fractions mainly in the fruits of the investigated plants while long-chained PFASs were mainly determined in roots. Overall, both methods indicate comparable results with target analysis being more reliable for known PFAS contamination and EOF/HR-CS-GFMAS analysis being more valuable to identify PFAS exposure of unknown composition.
The use of benchtop-NMR instruments is constantly increasing during the recent years. Advantages of being affordable, portable and easy-to-operate without the need for trained staff make them especially interesting for industrial applications in quality control. However, applications of NMR spectroscopy as an online PAT tool are still very rare but offer a huge potential for process optimization and control. A key task to exploit this potential is hardware field integration of the lab-instruments in a rough environment of a chemical plant. Additionally, developments in automation and data evaluation are mandatory to ensure a robust unattended operation with low maintenance requirements. Here, we show an approach of a fully automated analyzer enclosure considering explosion safety, field communication, as well as environmental conditions in the field.
Temperature sensitivity is still a limitation of benchtop-NMR instruments in flow applications. Recent developments of manufacturers allow for limited operation at static temperature levels, however, a dynamic system for continuous operation is still not available. Using a prototype system offering a larger bore, active temperature shielding studies with thermostated air were performed evaluating the performance.
Automated data evaluation of NMR spectra using a modular indirect hard modeling (IHM) approach showed good results and flexibility. A second data analysis approach based on artificial neural networks (ANN) was evaluated.Therefore, amount of data was augmented to be sufficient for training. The results show comparable performance, while improving the calculation time tremendously, offering new ways to simultaneously evaluating large numbers of different models.
Anhand von Beispielen wird in diesem Vortrag ein möglicher ganzheitlicherer Ansatz für die Digitalisierung und den Einsatz maschinengestützter Prozesse bei der Herstellung von Spezialchemikalien und Arzneimitteln durch die Einführung integrierter und vernetzter Systeme und Prozesse skizziert. Ein aktueller Ansatz und ein Beispiel in diesem Vortrag sind flexible und modulare chemische Produktionseinheiten, die Mehrzweckanlagen nutzen, um verschiedene hochwertige Produkte mit kurzen Stillstandszeiten zwischen den Kampagnen herzustellen und die Markteinführungszeit für neue Produkte zu verkürzen.
Als zweites Beispiel wird kurz die Testplattform Wasserstofftankstelle vorgestellt, die als moderne Anlage der Prozessindustrie betrachtet werden kann, vergleichbar mit einer Anlage aus der chemischen oder pharmazeutischen Industrie. An ihr lassen sich alle derzeit entlang der Digitalen Transformation diskutierten Konzepte implementieren, um sie zu standardisieren und zu validieren. Dazu gehören Konzepte zur Konnektivität von Sensoren und Aktoren aus der Feldebene in höhere Ebenen der Automatisierung oder zur Einbringung zusätzlicher Sensoren oder Sensornetzwerke, die zunehmend flexibler gestaltet werden soll, die sichere und nachvollziehbare Parametrierung von Automatisierungskomponenten – vielleicht aus einem digitalen Abbild (Verwaltungsschale bzw. „Digitaler Zwilling“) heraus, Konzepte zur vorausschauenden Wartung („Predictive Maintenance“), Konzepte zu digitalen Entscheidungsprozessen, Zertifikaten und Signaturen oder der zunehmende Einsatz von komplexen Auswertungsalgorithmen und Applikationen in der Feldebene („Embedded Computing“) oder der „Kante“ zu Cloudbasierten Systemen der Informationstechnik („Edge-Computing“).
Die beiden Beispiele sollen aktuelle Entwicklungsachsen des industriellen Messwesens im Rahmen der industriellen Automation aufzeigen, in denen Messwerte, deren Messunsicherheiten und Kontextinformationen eine wichtige Rolle einnehmen.
Per- und polyfluorierte Alkylverbindungen (PFAS) sind eine Substanzklasse bestehend aus mehreren tausenden Einzelverbindungen. Unter PFAS zählen alle Verbindungen, die mindestens eine perfluorierte Methyl- (-CF3) oder Methylen-Gruppe (-CF2-) besitzen.[1] Somit zählt auch ein großer Teil der fluorierten Medikamente, Pflanzenschutzmittel oder Biozide in die PFAS-Substanzklasse. Aufgrund der Persistenz, Bioakkumulation in Nahrungsketten, Toxizität und der ubiquitären Verbreitung von PFAS zählen sie zu den „emerging pollutants“.[2] Die PFAS-Analytik ist wegen ihrer vielfältigen physikalisch-chemischen Eigenschaften und der sehr hohen Anzahl an PFAS eine große Herausforderung. Da es für viele Anwendungen noch ungewiss ist, welche PFAS verwendet werden, wie sie in die Umwelt gelangen und welche Transformations- bzw. Abbauprodukte entstehen, stoßen analytische Ansätze, die nur auf Einzelsubstanzen abzielen, hier an ihre Grenzen. PFAS-Summenparameter-Methoden, die darauf abzielen ein möglichst vollständiges Abbild der PFAS-Belastungssituation widerzuspiegeln, werden daher immer wichtiger.