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Paper des Monats
- ja (102)
Alternative Tools (AT) such as on-site test kits, on-site portable devices and continuous measuring devices, are useful to improve water quality assessment under EU directives, and water treatment processes, thus contributing to improving water management, as well as get insights on the dynamic of pollutants within water bodies. Although these tools have clear advantages (e.g. fast response allowing for real-time monitoring, ease-of-use, lower cost), they are perceived as less reliable than conventional analytical methods. Their alternative nature, innovative status, and non-standard operation mode require specific validation strategies that differ significantly from those of conventional analytical methods. Nevertheless, the validation of ATs, especially on-site test kits, portable devices and continuous measuring devices for water quality monitoring is crucial to support their acceptance, promote their use and make their application sustainable. In this paper, a validation procedure in 4 steps is proposed: (1) Comprehensive description of the AT; (2) Assessment of intrinsic metrological performance and operational factors within a single laboratory; (3) Assessment of inter-laboratory performances through an inter-laboratory comparison and, (4) Demonstration of the equivalence of results between the AT and a reference method. This paper discusses each step of the validation procedure, and examples to illustrate critical issues are provided.
Peptide pools consist of short amino acid sequences and have proven to be versatile tools in various research areas in immunology and clinical applications. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products which makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. Usually, this would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, worsening the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector at 214 nm for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF advanced, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein–Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length.
The non-steroidal anti-inflammatory drug (NSAID) diclofenac (DCF) is an important environmental contaminant occurring in surface waters all over the world, because, after excretion, it is not adequately removed from wastewater in sewage treatment plants. To be able to monitor this pollutant, highly efficient analytical methods are needed, including immunoassays. In a medical research project, monoclonal antibodies against diclofenac and its metabolites had been produced. Based on this monoclonal anti-DCF antibody, a new indirect competitive enzyme-linked immunosorbent assay (ELISA) was developed and applied for environmental samples. The introduction of a spacer between diclofenac and the carrier protein in the coating conjugate led to higher sensitivity. With a test midpoint of 3 mg L−1 and a measurement range of 1–30 mg L−1, the system is not sensitive enough for direct analysis of surface water. However, this assay is quite robust against matrix influences and can be used for wastewater. Without adjustment of the calibration, organic solvents up to 5%, natural organic matter (NOM) up to 10 mg L−1, humic acids up to 2.5 mg L−1, and salt concentrations up to 6 g L−1 NaCl and 75 mg L−1 CaCl2 are tolerated. The antibody is also stable in a pH range from 3 to 12. Cross-reactivity (CR) of 1% or less was determined for the metabolites 40-hydroxydiclofenac (40-OH-DCF), 5-hydroxydiclofenac (5-OH-DCF), DCF lactam, and other NSAIDs. Relevant cross-reactivity occurred only with an amide derivative of DCF, 6-aminohexanoic acid (DCF-Ahx), aceclofenac (ACF) and DCF methyl ester (DCF-Me) with 150%, 61% and 44%, respectively. These substances, however, have not been found in samples. Only DCF-acyl glucuronide with a cross-reactivity of 57% is of some relevance. For the first time, photodegradation products were tested for cross-reactivity. With the ELISA based on this antibody, water samples were analysed. In sewage treatment plant effluents, concentrations in the range of 1.9–5.2 mg L−1 were determined directly, with recoveries compared to HPLC-MS/MS averaging 136%.
Concentrations in lakes ranged from 3 to 4.4 ng L−1 and were, after pre-concentration, determined with an average recovery of 100%
Luminophore stained micro- and nanobeads made from organic polymers like polystyrene (PS) are broadly used in the life and material sciences as luminescent reporters, for bead-based assays, sensor arrays, printable barcodes, security inks, and the calibration of fluorescence microscopes and flow cytometers. Initially mostly prepared with organic dyes, meanwhile luminescent core/shell nanoparticles (NPs) like spherical semiconductor quantum dots (QDs) are increasingly employed for bead encoding. This is related to their narrower emission spectra, tuneability of emission color, broad wavelength excitability, and better photostability. However, correlations between particle architecture, morphology, and photoluminescence (PL) of the luminescent nanocrystals used for encoding and the optical properties of the NP-stained beads have been rarely explored. This encouraged us to perform a screening study on the incorporation of different types of luminescent core/shell semiconductor nanocrystals into polymer microparticles (PMPs) by a radical-induced polymerization reaction. Nanocrystals explored include CdSe/CdS QDs of varying CdS shell thickness, a CdSe/ZnS core/shell QD, CdSe/CdS quantum rods (QRs), and CdSe/CdS nanoplatelets (NPLs).
Thereby, we focused on the applicability of these NPs for the polymerization synthesis approach used and quantified the preservation of the initial NP luminescence. The spectroscopic characterization of the resulting PMPs revealed the successful staining of the PMPs with luminescent CdSe/CdS QDs and CdSe/CdS NPLs. In contrast, usage of CdSe/CdS QRs and CdSe QDs with a ZnS shell did not yield luminescent PMPs. The results of this study provide new insights into structure–property relationships between NP stained PMPs and the initial luminescent NPs applied for staining and underline the importance of such studies for the performance optimization of NP-stained beads.
Fluorescent labels have strongly contributed to many advancements in bioanalysis, molecular biology, molecular imaging, and medical diagnostics. Despite a large toolbox of molecular and nanoscale fluorophores to choose from, there is still a need for brighter labels, e.g., for flow cytometry and fluorescence microscopy, that are preferably of molecular nature. This requires versatile concepts for fluorophore multimerization, which involves the shielding of dyes from other chromophores and possible quenchers in their neighborhood. In addition, to increase the number of readout parameters for fluorescence microscopy and eventually also flow cytometry, control and tuning of the labels’ fluorescence lifetimes is desired. Searching for bright multi-chromophoric or multimeric labels, we developed PEGylated dyes bearing functional groups for their bioconjugation and explored their spectroscopic properties and photostability in comparison to those of the respective monomeric dyes for two exemplarily chosen fluorophores excitable at 488 nm. Subsequently, these dyes were conjugated with anti-CD4 and anti-CD8 immunoglobulins to obtain fluorescent conjugates suitable for the labeling of cells and beads. Finally, the suitability of these novel labels for fluorescence lifetime imaging and target discrimination based upon lifetime measurements was assessed. Based upon the results of our spectroscopic studies including measurements of fluorescence quantum yields (QY) and fluorescence decay kinetics we could demonstrate the absence of significant dye-dye interactions and self-quenching in these multimeric labels. Moreover, in a first fluorescence lifetime imaging (FLIM) study, we could show the future potential of this multimerization concept for lifetime discrimination and multiplexing.
A reliable monitoring and oversight system is essential to guarantee the safe operation and eventual closure of radioactive waste disposal facilities. With recent technological advancements, there is now the capability to deploy distributed wireless sensor networks that are cost-effective and low in power consumption. Such networks are versatile, finding applications in several civil, environmental, and industrial sectors. This work presents a novel system and method for identifying and continuously monitoring the integrity of stored radioactive waste packages. The proposed approach, developed by the University of Pisa in the context of the H2020 European Project PREDIS, employs a network of wireless node devices, provided with solid-state micro-power radiation detectors tasked with the measurement of gamma-rays and thermal neutrons coming from within cemented waste drums. Collected data are automatically transmitted across the storage site via Long Range radio technology and forwarded to cloud-based or offline platforms, allowing for further visualization, data processing, and safe storage. The system highlights the feasibility of autonomously and passively gathering data from radioactive waste drums over extended distances (more than 250 m in non-line-of-sight conditions), decreasing the reliance
on portable or automated scanning mechanisms. In line with its capability for autonomous, long-range data collection, the system satisfies the requirement for structural integrity, containment, and confinement of packaging throughout both interim and long-term disposal of radioactive wastes, thereby playing a key role in reinforcing the safe management of radioactive waste.
Machine learning-assisted equivalent circuit identification for dielectric spectroscopy of polymers
(2024)
Polymers have become indispensable across fields of application, and understanding their structure–property relationships and dynamic behaviour is essential for performance optimization. Polymer membranes, particularly ion exchange membranes, play a crucial role in renewable energy conversion technologies, fuel cells, solar energy conversion, and energy storage. In this context, broadband dielectric spectroscopy (BDS) offers a powerful, non-destructive approach to investigate the electrical response and relaxation dynamics of polymers. These properties are investigated by parametrizing the system’s impedance response in terms of a network of circuit elements, i.e. the electrical equivalent circuit (EEC), whose impedance resembles the one of the system under investigation. However, the determination of the EEC from BDS data is challenging due to system complexity, interdependencies of circuit elements, and researcher biases. In this work, we propose a novel approach that incorporates a convolutional neural network (CNN) model to predict the EEC topology. By reducing user bias and enhancing data analysis, this approach aims to make BDS accessible to both experienced users and those with limited expertise. We show that the combination of machine learning and BDS provides valuable insights into the dynamic behaviour of polymer membranes, thus facilitating the design and characterization of tailored polymers for various applications. We also show that our model outperforms state-of-the-art machine learning methods with a top-5 accuracy of around 80% for predicting the circuit topology and a parameter fitting error as low as 0.05%.
Barriers to transitioning to a circular bio-based economy: Findings from an industrial perspective
(2024)
The transition from a linear fossil-based to a circular bio-based economy represents an opportunity and a suitable pathway for achieving several sustainable development goals. However, the transition is a complex process since it requires transformative policies, purposeful innovation, access to finance, risk-taking capacity as well as new and sustainable business models and markets. Accordingly, the first step in this transition process is the identification of barriers that are hampering the transition to a sustainable circular bio-based economy. With this motivation in mind, this study reviews grey literature to identify barriers focusing on four critical sectors facing major challenges within the current linear economy and requiring a sustainable transition most urgently: construction, chemicals, plastics, and textile sectors. Employing an adapted STEEP methodology (Social, Technological, Economical, Environmental, Political), a total of 193 different barriers have been identified and clustered under six categories: cultural, technical, economic, environmental, governance, and structural. Regardless of the sector, cultural and structural barriers are identified as the most prominent; the lack of incentives for consumer behaviour change and lack of stakeholder collaboration were the most cited barriers among the literature records. From a value chain perspective, most of the barriers are related to the material processing and product manufacturing stage. Finally, potential solutions, extracted from the grey literature, are proposed to fill the gaps and overcome the identified barriers. Many of the identified barriers are common across the four investigated sectors, indicating the solutions or measures can be applicable in a wider perspective to promote the transition in the right direction.
Self-healing polymers have been developed to improve durability and reduce costs associated with maintenance during service. The addition of thermoplastics to thermosets to produce mendable polymers appears as a promising selfhealing technique. In this study, poly (ethylene-co-methacrylic acid) (EMAA) was added to epoxy resin and the effects of EMAA addition on epoxy properties were evaluated. Specimens with two different contents of thermoplastic and particles sizes were manufactured. A two-level full factorial experimental design was used to evaluate the effect of particle size and particle content on properties of epoxy modified with addition of EMAA. Tensile tests and dynamic mechanical analysis (DMA) were used and the evaluated responses were tensile strength, modulus of elasticity, and glass transition temperature (Tg). X-ray computed tomography (XCT) was used to investigate particle size and concentration after manufacturing. It was found that the particle concentration has greater effects on stress–strain behavior of epoxy while Tg was not significantly affected by neither of the analyzed entrance variables.
Recent publications indicate that the order of electrochemical anodization (before or after the laser processing step) plays an important role for the response of bone-forming osteoblasts—an effect that can be utilized for improving permanent dental or removable bone implants. For exploring these different surface functionalities, multimethod morphological, structural, and chemical characterizations are performed in combination with electrochemical pre- and postanodization for two different characteristic microspikes covered by nanometric laser-induced periodic surface structures on Ti–6Al–4V upon irradiation with near-infrared ps-laser pulses (1030 nm wavelength, ≈1 ps pulse duration, 67 and 80 kHz pulse repetition frequency) at two distinct sets of laser fluence and beam scanning parameters. This work involves morphological and topographical investigations by scanning electron microscopy and white light interference microscopy, structural material examinations via X-ray diffraction, and micro-Raman spectroscopy, as well as near-surface chemical analyses by X-ray photoelectron spectroscopy and hard X-ray photoelectron spectroscopy. The results allow to qualify the mean laser ablation depth, assess the spike geometry and surface roughness parameters, and provide new detailed insights into the near-surface oxidation that may affect the different cell growth behavior for pre- or postanodized medical implants.