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Motivation: A precise diagnosis of atherosclerosis is of clinical importance, since cardiovascular disease remain one of the leading causes of death worldwide.
Goal(s): The goal of this study was to evaluate the feasibility of characterizing a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS4) using molecular magnetic resonance imaging in a preclnical model of atherosclerosis.
Approach: Molecular magnetic resonance imaging using a novel probe targeted against ADAMTS4 was used in a high-fat murine model.
Results: It was possible to image atherosclerotic lesions in a mouse model using an ADAMTS4- specific probe for magnetic resonance imaging.
Impact: Using molecular MRI targeting ADAMTS4 is a promising method for characterization of plaque composition and could possibly impact plaque vulnerability assessment in the diagnosis and treatment of atherosclerosis in patients.
Non‐targeted screenings (NTS) are essential tools in different fields, such as forensics, health and environmental sciences. NTSs often employ mass spectrometry (MS) methods due to their high throughput and sensitivity in comparison to, for example, nuclear magnetic resonance–based methods. As the identification of mass spectral signals, called annotation, is labour intensive, it has been used for developing supporting tools based on machine learning (ML). However, both the diversity of mass spectral signals and the sheer quantity of different ML tools developed for compound annotation present a challenge for researchers in maintaining a comprehensive overview of the field.In this work, we illustrate which ML‐based methods are available for compound annotation in non‐targeted MS experiments and provide a nuanced comparison of the ML models used in MS data analysis, unravelling their unique features and performance metrics. Through this overview we support researchers to judiciously apply these tools in their daily research. This review also offers a detailed exploration of methods and datasets to show gaps in current methods, and promising target areas, offering a starting point for developers intending to improve existing methodologies.
The gravimetric isotope mixture method is the primary method to determine absolute isotope ratios. This method, however, depends on the existence of suitable spike materials and knowledge of their purities. Determining the purity of the spikes can be tedious and labour-intensive. In this publication, an advancement of the gravimetric isotope mixture method, rendering the determination of the purity of the spike materials unnecessary, is presented. The advancement combines mass spectrometry and ion chromatography leading to an approach being independent of the purity of the spike materials. In the manuscript the mathematical background and the basic idea of the novel approach are described using a two-isotope system like copper or lithium.
Fenton-like processes using persulfate for oxidative water treatment and contaminant removal can be enhanced by the addition of redox-active biochar, which accelerates the reduction of Fe(III) to Fe(II) and increases the yield of reactive species that react with organic contaminants. However, available data on the formation of non-radical or radical species in the biochar/Fe(III)/persulfate system are inconsistent, which limits the evaluation of treatment efficiency and applicability in different water matrices. Based on competition kinetics calculations, we employed different scavengers and probe compounds to systematically evaluate the effect of chloride in presence of organic matter on the formation of major reactive species in the biochar/Fe(III)/persulfate system for the transformation of the model compound N,N‑diethyl-m-toluamide (DEET) at pH 2.5. We show that the transformation of methyl phenyl sulfoxide (PMSO) to methyl phenyl sulfone (PMSO2) cannot serve as a reliable indicator for Fe(IV), as previously suggested, because sulfate radicals also induce PMSO2 formation. Although the formation of Fe(IV) cannot be completely excluded, sulfate radicals were identified as the major reactive species in the biochar/Fe(III)/persulfate system in pure water. In the presence of dissolved organic matter, low chloride concentrations (0.1 mM) shifted the major reactive species likely to hydroxyl radicals. Higher chloride concentrations (1 mM), as present in a mining-impacted acidic surface water, resulted in the formation of another reactive species, possibly Cl2•−, and efficient DEET degradation. To tailor the application of this oxidation process, the water matrix must be considered as a decisive factor for reactive species formation and contaminant removal.
This dataset accompanies the following publication:
Hülagü, D., Tobias, C., Dao, R., Komarov, P., Rurack, K., Hodoroaba, V.-D., Towards 3D determination of the surface roughness of core-shell microparticles as a routine quality control procedure by scanning electron microscopy. Sci.Rep, 14, 17936 (2024), https://doi.org/10.1038/s41598-024-68797-7.
It contains SEM and AFM-in-SEM images of polystyrene (PS) core particles, polystyrene-iron oxide (PS/Fe3O4) core-shell particles, and polystyrene-iron oxide-silica (PS/Fe3O4/SiO2) core-shell-shell particles. Please refer to the publication and its supporting information for more details on the acquisition and contents of the dataset, as well as the GitHub repository at https://github.Com/denizhulagu/roughness-analysis-by-electron-microscopy.
The investigated particles were produced at BAM laboratories as previously described in:
Hülagü, D. et al. Generalized analysis approach of the profile roughness by electron microscopy with the example of hierarchically grown polystyrene–iron oxide–silica core–shell–shell particles. Adv. Eng. Mater. 24, 2101344, https://doi.org/10.1002/adem.202101344 (2022).
Tobias, C., Climent, E., Gawlitza, K. & Rurack, K. Polystyrene microparticles with convergently grown mesoporous silica shells as a promising tool for multiplexed bioanalytical assays. ACS Appl. Mater. Interfaces 13, 207, https://dx.doi.org/10.1021/acsami.0c17940 (2020).
Colloids provide manifold opportunities for targeted product design due to their tunable properties with respect to size, shape, composition, surface, and spectral characteristics. However, the determination of structure-property relationships is quite challenging as most particulate samples exhibit polydispersity of their disperse properties. Analytical ultracentrifugation (AUC) is a fractionating technique and highly accurate method for the multidimensional analysis of nanoparticles as it permits the differentiation of spectral information linked to hydro- and thermodynamic properties of the particles.
So far, characterization capabilities for fluorescent nanoparticles by AUC were limited, as the formerly commercially available fluorescence detector could not provide any spectral information. Using a multiwavelength emission detector developed in our group, it is possible to extract spectra of fluorescent particles and biomolecules alongside their sedimentation and diffusion coefficients within a single centrifugation experiment.
In our contribution, we will highlight that even narrowly distributed core/shell CdSe/CdS quantum dots still show size- and structure-dependent shifts of their fluorescence spectra, which can be resolved with our AUC system in an ensemble measurement. Thereby, we can link spectral changes of only a few nanometers to particle sizes retrieved with Angstrom size resolution. Single-particle measurements not only supported the results obtained with the AUC system but also provided deeper insights into the photophysical processes of individual QDs, clearly demonstrating the complementary nature of the techniques used. With our novel multiwavelength emission detector and the established extinction-based detector for AUC, a comprehensive platform for the holistic characterization of fluorescent colloids is now available.
The recently certified reference material (CRM) BAM-N012 as cubical iron oxide FeOx nanoparticles (NPs) of 8 nm area equivalent square edge length (ESL) and the RM candidate BAM-N013 as nearly spherical NPs of 22 nm size were analyzed in detail by electron microscopy (EM).
For the metrological characterization with SEM, STEM in SEM and TEM, the understanding of the imaging contrasts and sensitivities, and the correct interpretation of the (art)effects which are inherent to each detection mode is necessary.
The same sample areas with NPs deposited on a TEM grid were analyzed by two SEM acquisition modes, i. e. SE InLens and STEM in SEM using a dedicated transmission sample holder, and further, correlatively, analyzed with TEM.
With increasing kV, SE InLens shows increasing particle size (unless overcharging at the particle boundaries is filtered), as a known effect. For STEM-in-SEM the particle size decreases significantly and individual particles are identified easier (at 2 kV only a few single particles can be detected automatically).
❑ Documentation of the sample preparation and measurement conditions (including optimization process) is important for reproducibility.
❑ Plasma cleaning, analysis in the transmission mode at SEM is recommended for FeOx NPs.
❑ Selection of the threshold algorithm can significantly alter the reported ECD.
Introduction
Glacier ice algae, mainly Ancylonema alaskanum and Ancylonema nordenskiöldi, bloom on Greenland Ice Sheet bare ice surfaces. They significantly decrease surface albedo due to their purple-brown pigmentation, thus increasing melt. Little is known about their metabolic adaptation and factors controlling algal growth dynamics and pigment formation. A challenge in obtaining such data is the necessity of melting samples, which delays preservation and introduces bias to metabolomic analysis. There is a need to evaluate the physiological response of algae to melting and establish consistent sample processing strategies for metabolomics of ice microbial communities.
Objectives
To address the impact of sample melting procedure on metabolic characterization and establish a processing and analytical workflow for endometabolic profiling of glacier ice algae.
Methods
We employed untargeted, high-resolution mass spectrometry and tested the effect of sample melt temperature (10, 15, 20 °C) and processing delay (up to 49 h) on the metabolome and lipidome, and complemented this approach with cell counts (FlowCam), photophysiological analysis (PAM) and diversity characterization.
Results and Conclusion
We putatively identified 804 metabolites, with glycerolipids, glycerophospholipids and fatty acyls being the most prominent superclasses ( 50% of identified metabolites). Among the polar metabolome, carbohydrates and amino acid-derivatives were the most abundant. We show that 8% of the metabolome is affected by melt duration, with a pronounced decrease in betaine membrane lipids and pigment precursors, and an increase in phospholipids. Controlled fast melting at 10 °C resulted in the highest consistency, and is our recommendation for future supraglacial metabolomics studies.
One remaining handicap for spatially resolved elemental quantification in biological samples is the lack of a suitable internal standard (IS) that can be reliably measured across both calibration standards and samples. In this work, multielement quantitative intracellular imaging of cells tagged with lanthanide nanoparticles containing key lanthanides, e.g., Eu and Ho, is described using a novel strategy that uses the ratio of IS elements and LA-ICP-TOFMS analysis. To achieve this, an internal standard layer is deposited onto microscope slides containing either gelatin calibration standards or Euand Ho-tagged cell samples. This IS layer contains both gallium (Ga) and indium (In).
Monitoring either element as an IS individually showed significant variability in intensity signal between sample or standards prepared across multiple microscope slides, which is indicative of the difficulties in producing a homogeneous film at intracellular resolution.
However, normalization of the lanthanide signal to the ratio of the IS elements improved the calibration correlation coefficients from 0.9885 to 0.9971 and 0.9805 to 0.9980 for Eu and Ho, respectively, while providing a consistent signal to monitor the ablation behavior between standards and samples. By analyzing an independent quality control (QC) gelatin sample spiked with Eu and Ho, it was observed that without normalization to the IS ratio the concentrations of Eu and Ho were highly biased by approximately 20% in comparison to the expected values.
Similarly, this overestimation was also observed in the lanthanide concentration distribution of the cell samples in comparison with
the normalized data.
AbstractRecently, we have developed an algorithm to quantitatively evaluate the roughness of spherical microparticles using scanning electron microscopy (SEM) images. The algorithm calculates the root-mean-squared profile roughness (RMS-RQ) of a single particle by analyzing the particle’s boundary. The information extracted from a single SEM image yields however only two-dimensional (2D) profile roughness data from the horizontal plane of a particle. The present study offers a practical procedure and the necessary software tools to gain quasi three-dimensional (3D) information from 2D particle contours recorded at different particle inclinations by tilting the sample (stage). This new approach was tested on a set of polystyrene core-iron oxide shell-silica shell particles as few micrometer-sized beads with different (tailored) surface roughness, providing the proof of principle that validates the applicability of the proposed method. SEM images of these particles were analyzed by the latest version of the developed algorithm, which allows to determine the analysis of particles in terms of roughness both within a batch and across the batches as a routine quality control procedure. A separate set of particles has been analyzed by atomic force microscopy (AFM) as a powerful complementary surface analysis technique integrated into SEM, and the roughness results have been compared.