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Organisationseinheit der BAM
The formation of vesicles based on the self-assembly of amphiphilic poly(butadiene)-b-poly(ethylene oxide) (PB130-b-PEO66) block copolymer in water has been studied using THF as co-solvent. To obtain a highly controlled mixing process for the polymer/THF- and the water-phase, we employed micro mixers with different mixing geometries. The high impact of this preparation method on the self-assembling process was verified by TEM and DLS characterization of the obtained structures. Spherical micelles, vesicles and worm-like micelles were found depending on the parameters of mixing. By additional parameter adjustment in the vesicle regime, the size of the assembled vesicles was controlled between 45 and 100 nm. This demonstrates the continuous preparation of narrowly distributed vesicle structures with controlled sizes.
Performance assessment for GuidedWave (GW)-based Structural Health Monitoring (SHM) systems is of major importance for industrial deployment.
With conventional feature extraction methods like damage indices, pathbased probability of detection (POD) analysis can be realized. To achieve reliability quantification enough data needs to be available, which is rarely the case.
Alternatives like methods for performance assessment on system level are still in development and in a discussion phase. In this contribution, POD results using an Artificial Intelligence (AI)-based data analysis are compared with those delivered by conventional data analysis. Using an open-access dataset from Open Guided Wave platform, the possibility of performance assessment for GW-based SHM systems using AI-based data analysis is shown in detail. An artificial neural network (ANN) classifier is trained to detect artificial damage in a stiffened CFRP plate. As input for the ANN, classical damage indicators are used. The ANN is tested to detect damage at another position, whose inspection data were not previously used in training. The findings show very high detection capabilities without sorting any specific path but only having a global view of current damage metrics. The systematic evaluation of the ANN predictions with respect to specific damage sizes allows to compute a probability of correct identification versus flaw dimension, somehow equivalent to and compared with the results achieved through classic path-based POD analysis. Also, sensitive paths are detected by ANN predictions allowing for evaluation of maximal distances between path and damage position. Finally, it is shown that the prediction performance of the ANN can be improved significantly by combining different damage indicators as inputs.
Reliability assessment of Structural Health Monitoring (SHM) systems
poses new challenges pushing the research community to address many questions which are still open. For guided wave-based SHM it is not possible to evaluate the system performance without taking into account the target structure and applied system parameters. This range of variables would result in countless measurements.
Factors like environmental conditions, structural dependencies and wave characteristics demand novel solutions for performance analysis of SHM systems compared to those relying on classical non-destructive evaluation. Such novel approaches typically require model-assisted investigations which may not only help to explain and understand performance assessment results but also enable complete studies without costly experiments. Within this contribution, a multi input multi output approach using a sparse transducer array permanently installed on a composite structure to excite and sense guided waves is considered. Firstly, the method and the analysis of path-based performance assessment are presented considering an open-access dataset from the Open Guided Wave platform. Then, a performance analysis of a guided wave-based SHM system using Probability of Detection is presented. To explain some unexpected results, the model-assisted investigations are used to understand the physical phenomena of wave propagation in the test specimen including the interaction with damage. Finally, issues and future steps in SHM systems’ performance assessment and their development are discussed.
Objectives: Using a murine model of multiple sclerosis, we previously showed that repeated administration of gadopentetate dimeglumine led to retention of gadolinium (Gd) within cerebellar structures and that this process was enhanced with inflammation. This study aimed to compare the kinetics and retention profiles of Gd in inflamed and healthy brains after application of the macrocyclic Gd-based contrast agent (GBCA) gadobutrol or the linear GBCA gadopentetate. Moreover, potential Gd-induced neurotoxicity was investigated in living hippocampal slices ex vivo.
Materials and Methods: Mice at peak of experimental autoimmune encephalomyelitis (EAE; n = 29) and healthy control mice (HC; n = 24) were exposed to a cumulative dose of 20 mmol/kg bodyweight of either gadopentetate dimeglumine or gadobutrol (8 injections of 2.5 mmol/kg over 10 days). Magnetic resonance imaging (7 T) was performed at baseline as well as at day 1, 10, and 40 post final injection (pfi) of GBCAs. Mice were sacrificed after magnetic resonance imaging and brain and blood Gd content was assessed by laser ablation-inductively coupled plasma (ICP)-mass spectrometry (MS) and ICP-MS, respectively. In addition, using chronic organotypic hippocampal slice cultures, Gd-induced neurotoxicity was addressed in living brain tissue ex vivo, both under control or inflammatory (tumor necrosis factor α [TNF-α] at 50 ng/μL) conditions.
Results: Neuroinflammation promoted a significant decrease in T1 relaxation times after multiple injections of both GBCAs as shown by quantitative T1 mapping of EAE brains compared with HC. This corresponded to higher Gd retention within the EAE brains at 1, 10, and 40 days pfi as determined by laser ablation-ICP-MS. In inflamed cerebellum, in particular in the deep cerebellar nuclei (CN), elevated Gd retention was observed until day 40 after last gadopentetate application (CN: EAE vs HC, 55.06 ± 0.16 μM vs 30.44 ± 4.43 μM). In contrast, gadobutrol application led to a rather diffuse Gd content in the inflamed brains, which strongly diminished until day 40 (CN: EAE vs HC, 0.38 ± 0.08 μM vs 0.17 ± 0.03 μM). The analysis of cytotoxic effects of both GBCAs using living brain tissue revealed an elevated cell death rate after incubation with gadopentetate but not gadobutrol at 50 mM. The cytotoxic effect due to gadopentetate increased in the presence of the inflammatory mediator TNF-α (with vs without TNF-α, 3.15% ± 1.18% vs 2.17% ± 1.14%; P = 0.0345).
Conclusions: In the EAE model, neuroinflammation promoted increased Gd retention in the brain for both GBCAs. Whereas in the inflamed brains, efficient clearance of macrocyclic gadobutrol during the investigated time period was observed, the Gd retention after application of linear gadopentetate persisted over the entire observational period. Gadopentetate but not gadubutrol appeared to be neurotoxic in an ex vivo paradigm of neuronal inflammation.
A modern day light microscope has evolved from a tool devoted to making primarily empirical observations to what is now a sophisticated, quantitative device that is an integral part of both physical and life science research. Nowadays, microscopes are found in nearly every experimental laboratory. However, despite their prevalent use in capturing and quantifying scientific phenomena, neither a thorough understanding of the principles underlying quantitative imaging techniques nor appropriate knowledge of how to calibrate, operate and maintain microscopes can be taken for granted. This is clearly demonstrated by the well-documented and widespread difficulties that are routinely encountered in evaluating acquired data and reproducing scientific experiments. Indeed, studies have shown that more than 70% of researchers have tried and failed to repeat another scientist’s experiments, while more than half have even failed to reproduce their own experiments1. One factor behind the reproducibility crisis of experiments published in scientific journals is the frequent underreporting of imaging methods caused by a lack of awareness and/or a lack of knowledge of the applied technique2,3. Whereas quality control procedures for some methods used in biomedical research, such as genomics (e.g., DNA sequencing, RNA-seq) or cytometry, have been introduced (e.g. ENCODE4), this issue has not been tackled for optical microscopy instrumentation and images. Although many calibration standards and protocols have been published, there is a lack of awareness and agreement on common Standards and guidelines for quality assessment and reproducibility5.
In April 2020, the QUality Assessment and REProducibility for instruments and images in Light Microscopy (QUAREP-LiMi) initiative6 was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models7,8, and tools9,10, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research.
This White Paper 1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; 2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of Stakeholders including, researchers, imaging scientists11, bioimage analysts, bioimage informatics developers, corporate partners, Funding agencies, standards organizations, scientific publishers, and observers of such; 3) outlines the current actions of the QUAREPLiMi initiative, and 4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC.
To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.
Performance Assessment for a Guided Wave-Based SHM System Applied to a Stiffened Composite Structure
(2022)
To assess the ability of structural health monitoring (SHM) systems, a variety of prerequisites and contributing factors have to be taken into account. Within this publication, this variety is analyzed for actively introduced guided wave-based SHM systems. For these systems, it is not possible to analyze their performance without taking into account their structure and their applied system parameters. Therefore, interdependencies of performance assessment are displayed in an SHM pyramid based on the structure and its monitoring requirements. Factors influencing the quality, capability and reliability of the monitoring system are given and put into relation with state-of-the-art performance analysis in a non-destructive evaluation. While some aspects are similar and can be treated in similar ways, others, such as location, environmental condition and structural dependency, demand novel solutions. Using an open-access data set from the Open Guided Waves platform, a detailed method description and analysis of path-based performance assessment is presented.The adopted approach clearly begs the question about the decision framework, as the threshold affects the reliability of the system. In addition, the findings show the effect of the propagation path according to the damage position. Indeed, the distance of damage directly affects the system performance. Otherwise, the propagation direction does not alter the potentiality of the detection approach despite the anisotropy of composites. Nonetheless, the finite waveguide makes it necessary to look at the whole paths, as singular phenomena associated with the reflections may appear. Numerical investigation helps to clarify the centrality of wave mechanics and the necessity to take sensor position into account as an influencing factor. Starting from the findings achieved, all the issues are discussed, and potential future steps are outlined.
Inflammatory bowel diseases (IBD) comprise mainly ulcerative colitis (UC) and Crohn´s disease (CD). Both forms present with a chronic inflammation of the (gastro) intestinal tract, which induces excessive changes in the composition of the associated extracellular matrix (ECM). In UC, the inflammation is limited to the colon, whereas it can occur throughout the entire gastrointestinal tract in CD. Tools for early diagnosis of IBD are still very limited and highly invasive and measures for standardized evaluation of structural changes are scarce. To investigate an efficient non-invasive way of diagnosing intestinal inflammation and early changes of the ECM, very small superparamagnetic iron oxide nanoparticles (VSOPs) in magnetic resonance imaging (MRI) were applied in two mouse models of experimental colitis: the dextran sulfate sodium (DSS)-induced colitis and the transfer model of colitis. For further validation of ECM changes and inflammation, tissue sections were analyzed by immunohistochemistry. For in depth ex-vivo investigation of VSOPs localization within the tissue, Europium-doped VSOPs served to visualize the contrast agent by imaging mass cytometry (IMC). VSOPs accumulation in the inflamed colon wall of DSS-induced colitis mice was visualized in T2* weighted MRI scans. Components of the ECM, especially the hyaluronic acid content, were found to influence VSOPs binding. Using IMC, colocalization of VSOPs with macrophages and endothelial cells in colon tissue was shown. In contrast to the DSS model, colonic inflammation could not be visualized with VSOP-enhanced MRI in transfer colitis. VSOPs present a potential contrast agent for contrast-enhanced MRI to detect intestinal inflammation in mice at an early stage and in a less invasive manner depending on hyaluronic acid content.
Per- and polyfuoroalkyl substances (PFAS) are emerging organic pollutants and can occur in surface and groundwater. To identify the degree of pollution in surface water with PFAS, often targeted HPLC–ESI–MS/MS has been employed in which commonly 30–40 compounds are analyzed. However, other PFAS and organofuorines remain undetected. We sampled surface water of the river Spree and the Teltow Canal in Berlin, Germany, which are afected by the efuent discharge of wastewater treatment plants. Here, we employed high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) for measuring extractable organofuorines (EOF) and compared in a mass balance approach the total fuorine to the identifed and quantifed PFAS from the targeted analysis. The analysis highlights that the EOF are in the range expected for an urban river system (Winchell et al. in Sci Total Environ 774, 2021). However, downstream of an efuent discharge, the EOF increased by one order of magnitude, e.g., 40.3 to 574 ng F L−1, along the Teltow Canal. From our target analytes, mostly short-chained perfuorinated carboxylic acids and sulfonates occur in the water, which however makes up less than 10% of the EOF. The increase in EOF in the Teltow Canal correlates well with the increase of perfuorohexanoic acid (PFHxA), indicating that PFHxA is characteristic for the discharged EOF but not responsible for the increase. Hence, it points to PFHxA precursor discharge. The study highlights that EOF screening using HR-CS-GFMAS is necessary to identify the full scale of pollution with regard to PFAS and other organofuorines such as pharmaceutical compounds from the efuent of WWTPs.