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The presence of endocrine-disrupting compounds (EDCs) in water poses a significant threat to human and animal health, as recognized by regulatory agencies throughout the world. The Yeast Estrogen Screen (YES) assay is an excellent method to evaluate the presence of these compounds in water due to its simplicity and capacity to assess the bioaccessible forms/fractions of these compounds. In the presence of a compound with estrogenic activity, Saccharomyces cerevisiae cells, containing a lacZ reporter gene encoding the enzyme β-galactosidase, are induced, the enzyme is synthesised, and released to the extracellular medium. In this work, a YES-based approach encompassing the use of a lacZ reporter gene modified strain of S. cerevisiae, microcarriers as solid support, and a fluorescent substrate, fluorescein di-β-D-galactopyranoside, is proposed, allowing for the assessment of EDCs’ presence after only 2 h of incubation. The proposed method provided an EC50 of 0.17 ± 0.03 nM and an LLOQ of 0.03 nM, expressed as 17β-estradiol. The assessment of different EDCs provided EC50 values between 0.16 and 1.2 × 103 nM. After application to wastewaters, similar results were obtained for EDCs screening, much faster, compared to the conventional 45 h spectrophotometric procedure using a commercial kit, showing potential for onsite high-throughput screening of environmental contamination.
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%
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.
Various software products for the simulation of industrial X-ray radiography have been developed in recent years (e.g., aRTist 2, CIVA CT, Scorpius XLab, SimCT, Wilcore) and their application potential has been shown in numerous works. However, full systematic approaches to characterise a specific CT system for these simulation software products to obtain a truthful digital twin are still missing. In this contribution, we want to present two approaches to obtain realistic grey values in X-ray projections in aRTist 2 simulations based on measured projections. In aRTist 2, the displayed grey value of a pixel is based on the energy density incident on that pixel.
The energy density is calculated based on the X-ray tube spectrum, the attenuation between source and detector as well as an energy-dependent sensitivity curve of the detector. The first approach presented in this contribution uses the sensitivity curve as a free modelling parameter. We measured the signal response at different thicknesses of Al EN-AW6082 at different tube voltages (i.e., different tube spectra). We then regarded the grey values displayed by these projections as a data regression respectively an optimisation problem and obtained the sensitivity curve that is best able to reproduce the measured behaviour in aRTist 2. The resulting sensitivity curve does not necessarily hold physical meaning but is able to simulate the real system behaviour in the simulation software.
The second approach presented in this contribution is to estimate the sensitivity curve based on assumptions about the characteristics of the scintillation detector (e.g., scintillator material, scintillator thickness and signal processing characteristics). For this approach, a linear response function (linear relationship between the deposited energy per pixel and the resulting grey value) is assumed. If the detector characteristics, which affect the simulated deposited energy, are properly modelled, the slope and offset of the response function to match the measured grey values should be the same for different tube spectra. As the offset is constant and given by the grey values measured at no incident radiation, the slope is the remaining parameter to evaluate the success of the detector modelling. We therefore adapted the detector characteristics by changing the detector setup until the slope was nearly the same for all measured tube spectra. We are aware that the resulting parameters of the scintillator material and thickness might not be the real ones, but with those modelling parameters we are able to simulate realistic grey values in aRTist 2. Both of those approaches could potentially be a step forward to a full systematic approach for a digital twin of a real CT system in aRTist 2.
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.
Sacrifice Few to Save Many: Fire Protective Interlayers in Carbon- Fiber-Reinforced Laminates
(2024)
The fire protection of carbon-fiber-reinforced polymer (CFRP) laminates often relies on flame-retardant coatings, but in some applications, their efficacy may diminish upon direct fire exposure due to rapid pyrolysis. This study introduces an innovative approach by integrating protective interlayers within the laminate structure to enhance the fire resistance. Various materials, including ceramic composite WHIPOX, titanium foil, poly(etherimide) (PEI) foil, basalt fibers, rubber mat, and hemp fibers, were selected as protective interlayers. These interlayers were strategically placed within the laminate layout to form a sacrificial barrier, safeguarding the integrity of the composite. Bench-scale fire resistance tests were conducted, where fire (180 kW/m2) was applied directly to the one side of the specimen by a burner while a compressive load was applied at the same time. Results indicate significant prolongation of time to failure for CFRP laminates with protective interlayers, which is up to 10 times longer. This innovative approach represents a potential advance in fire protection strategies for CFRP laminates, offering improved resilience against fire-induced structural failure.
A systematic series of industrial-relevant polystyrene-based anion exchange resins that are functionalized with hydro- or fluorocarbon chains are compared regarding their adsorption behavior toward perfluorocarboxylic acids (PFCA) in respect to their charge, chain length, and type of chain. The results clearly show the dominance of electrostatic interactions in the adsorption process as uncharged adsorber materials showed no adsorption at all. In contrast, the charged adsorber materials showed in general a PFCA removal of 80% to 30% over the experiment depending on effluent fraction.
Unexpectedly, for perfluorobutanoic acid (PFBA) the highest removal rate is found with consistently >90%. Despite observing significant benefits in the adsorption of PFCA for fluoroalkylated adsorbers in comparison to their non-fluorinated counterparts, this effect of fluoroalkylation is comparatively small and can not be clearly attributed to fluorophilic interactions between the fluoroalkyl chains. These findings help clarifying that the introduction of fluorocarbon moieties in adsorber materials is not necessary in order to remove fluorocarbon molecules from the environment.
Relation of craze to crack length during slow crack growth phenomena in high‐density polyethylene
(2024)
The craze‐crack mechanism occurring in high‐density polyethylene (HDPE) causing slow crack growth and environmental stress cracking is investigated in detail with respect to the relation of crack length and the related craze zone. This is essential for the understanding of the resulting features of the formed fracture surface and their interpretation in the context of the transition from crack propagation to ductile shear deformation. It turns out that an already formed craze zone does not inevitably result in formation of a propagating crack, but could also undergo ductile failure. For the examination, the full notch creep test (FNCT) was employed with a subsequent advanced fracture surface analysis that was performed using various imaging techniques: light microscopy, laser scanning microscopy, scanning electron microscopy, and X‐ray micro computed tomography scan. FNCT specimens were progressively damaged for increasing durations under standard test conditions applying Arkopal, the standard surfactant solution, and biodiesel as test media were used to analyze the stepwise growth of cracks and crazes. From considerations based on well‐established fracture mechanics approaches, a theoretical correlation between the length of the actual crack and the length of the preceding craze zone was established that could be evidenced and affirmed by FNCT fracture surface analysis. Moreover, the yield strength of a HDPE material exposed to a certain medium as detected by a classic tensile test was found to be the crucial value of true stress to induce the transition from crack propagation due to the craze‐crack mechanism to shear deformation during FNCT measurements.
Highlights
- Progress of crack formation in high‐density polyethylene is analyzed by different imaging techniques
- Determined growth rates depend on distinction between craze zone and crack
- The ratio of the present crack to the anteceding craze zone is validated theoretically
- The transition from crack propagation to ductile shear deformation is identified
- An already formed craze zone may still fail by ductile mechanisms