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Effect of additives on MWCNT dispersion and electrical percolation in polyamide 12 composites
The aim of this study was to decrease the electrical percolation threshold of multiwalled carbon nanotubes (MWCNTs) in a polyamide 12 matrix by the use of additives. Different kinds of additives were selected which either interact with the π-system of the MWCNTs (imidazolium based ionic liquid (IL) and perylene-3,4,9,10-tetracarboxylic dianhydride (PTCDA)) or improve the MWCNT wettability (cyclic butylene terephthalate, CBT). The composites were melt mixed using a DACA microcompounder. The electrical percolation threshold for PA12/MWCNT without additives, measured on compression molded plates, was found between 2.0 and 2.25 wt%. With all used additives, a significant reduction of the electrical percolation threshold could be achieved. Whereas the addition of IL and CBT resulted in MWCNT percolation at around 1.0 wt%, a slightly higher percolation threshold between 1.0 and 1.5 wt% was found for PTCDA as an additive. Interestingly, the electrical resistivity at higher loadings was decreased by nearly two decades when using CBT and one decade after application of PTCDA, whereas IL did not contribute to lower values in this range. In all cases macrodispersion as assessed by light microscopy was not improved and even worse as compared to non-modified composites. In summary, the results illustrate that these kinds of additives are able to improve the performance of PA12 based MWCNT nanocomposites.
Evolutionary design of explainable algorithms for biomedical image segmentation
An unresolved issue in contemporary biomedicine is the overwhelming number and diversity of complex images that require annotation, analysis and interpretation. Recent advances in Deep Learning have revolutionized the field of computer vision, creating algorithms that compete with human experts in image segmentation tasks. However, these frameworks require large human-annotated datasets for training and the resulting “black box” models are difficult to interpret. In this study, we introduce Kartezio, a modular Cartesian Genetic Programming-based computational strategy that generates fully transparent and easily interpretable image processing pipelines by iteratively assembling and parameterizing computer vision functions. The pipelines thus generated exhibit comparable precision to state-of-the-art Deep Learning approaches on instance segmentation tasks, while requiring drastically smaller training datasets. This Few-Shot Learning method confers tremendous flexibility, speed, and functionality to this approach. We then deploy Kartezio to solve a series of semantic and instance segmentation problems, and demonstrate its utility across diverse images ranging from multiplexed tissue histopathology images to high resolution microscopy images. While the flexibility, robustness and practical utility of Kartezio make this fully explicable evolutionary designer a potential game-changer in the field of biomedical image processing, Kartezio remains complementary and potentially auxiliary to mainstream Deep Learning approaches.
Super-Resolution STED Microscopy-Based Mobility Studies of the Viral Env Protein at HIV-1 Assembly Sites of Fully Infected T-Cells
The ongoing threat of human immunodeficiency virus (HIV-1) requires continued, detailed investigations of its replication cycle, especially when combined with the most physiologically relevant, fully infectious model systems. Here, we demonstrate the application of the combination of stimulated emission depletion (STED) super-resolution microscopy with beam-scanning fluorescence correlation spectroscopy (sSTED-FCS) as a powerful tool for the interrogation of the molecular dynamics of HIV-1 virus assembly on the cell plasma membrane in the context of a fully infectious virus. In this process, HIV-1 envelope glycoprotein (Env) becomes incorporated into the assembling virus by interacting with the nascent Gag structural protein lattice. Molecular dynamics measurements at these distinct cell surface sites require a guiding strategy, for which we have used a two-colour implementation of sSTED-FCS to simultaneously target individual HIV-1 assembly sites via the aggregated Gag signal. We then compare the molecular mobility of Env proteins at the inside and outside of the virus assembly area. Env mobility was shown to be highly reduced at the assembly sites, highlighting the distinct trapping of Env as well as the usefulness of our methodological approach to study the molecular mobility of specifically targeted sites at the plasma membrane, even under high-biosafety conditions.
High-fidelity multimode fibre-based endoscopy for deep brain in vivo imaging
Progress in neuroscience relies on new techniques for investigating the complex dynamics of neuronal networks. An ongoing challenge is to achieve minimally invasive and high-resolution observations of neuronal activity in vivo inside deep brain areas. Recently introduced methods for holographic control of light propagation in complex media enable the use of a hair-thin multimode optical fibre as an ultranarrow imaging tool. Compared to endoscopes based on graded-index lenses or fibre bundles, this new approach offers a footprint reduction exceeding an order of magnitude, combined with a significant enhancement in resolution. We designed a compact and high-speed system for fluorescent imaging at the tip of a fibre, achieving a resolution of 1.18 ± 0.04 µm across a 50-µm field of view, yielding 7-kilopixel images at a rate of 3.5 frames/s. Furthermore, we demonstrate in vivo observations of cell bodies and processes of inhibitory neurons within deep layers of the visual cortex and hippocampus of anaesthetised mice. This study paves the way for modern microscopy to be applied deep inside tissues of living animal models while exerting a minimal impact on their structural and functional properties.
Vinculin binding angle in podosomes revealed by high resolution microscopy
Podosomes are highly dynamic actin-rich adhesive structures formed predominantly by cells of the monocytic lineage, which degrade the extracellular matrix. They consist of a core of F-actin and actin-regulating proteins, surrounded by a ring of adhesion-associated proteins such as vinculin. We have characterised the structure of podosomes in macrophages, particularly the structure of the ring, using three super-resolution fluorescence microscopy techniques: stimulated emission depletion microscopy, structured illumination microscopy and localisation microscopy. Rather than being round, as previously assumed, we found the vinculin ring to be created from relatively straight strands of vinculin, resulting in a distinctly polygonal shape. The strands bind preferentially at angles between 116° and 135°. Furthermore, adjacent vinculin strands are observed nucleating at the corners of the podosomes, suggesting a mechanism for podosome growth.
3D Quantification of Vascular-Like Structures in z Stack Confocal Images
Optical slice microscopy is commonly used to characterize the morphometric features of 3D cellular cultures, such as in vitro vascularization. However, the quantitative analysis of those structures is often performed on a single 2D maximum intensity projection image, limiting the accuracy of data obtained from 3D cultures. Here, we present a protocol for the quantitative analysis of z stack images, utilizing Fiji, Amira, and WinFiber3D. This protocol facilitates the in-depth examination of vascular-like structures within 3D cell culture models.
Bioactive secondary metabolites with multiple activities from a fungal endophyte
In order to replace particularly biohazardous nematocides, there is a strong drive to finding natural product-based alternatives with the aim of containing nematode pests in agriculture. The metabolites produced by the fungal endophyte Fusarium oxysporum 162 when cultivated on rice media were isolated and their structures elucidated. Eleven compounds were obtained, of which six were isolated from a Fusarium spp. for the first time. The three most potent nematode-antagonistic compounds, 4-hydroxybenzoic acid, indole-3-acetic acid (IAA) and gibepyrone D had LC50 values of 104, 117 and 134 μg ml−1, respectively, after 72 h. IAA is a well-known phytohormone that plays a role in triggering plant resistance, thus suggesting a dual activity, either directly, by killing or compromising nematodes, or indirectly, by inducing defence mechanisms against pathogens (nematodes) in plants. Such compounds may serve as important leads in the development of novel, environmental friendly, nematocides.
TRAIT2D: a Software for Quantitative Analysis of Single Particle Diffusion Data
Single particle tracking (SPT) is one of the most widely used tools in optical microscopy to evaluate particle mobility in a variety of situations, including cellular and model membrane dynamics. Recent technological developments, such as Interferometric Scattering microscopy, have allowed recording of long, uninterrupted single particle trajectories at kilohertz framerates. The resulting data, where particles are continuously detected and do not displace much between observations, thereby do not require complex linking algorithms. Moreover, while these measurements offer more details into the short-term diffusion behaviour of the tracked particles, they are also subject to the influence of localisation uncertainties, which are often underestimated by conventional analysis pipelines. we thus developed a Python library, under the name of TRAIT2D (Tracking Analysis Toolbox – 2D version), in order to track particle diffusion at high sampling rates, and analyse the resulting trajectories with an innovative approach. The data analysis pipeline introduced is more localisation-uncertainty aware, and also selects the most appropriate diffusion model for the data provided on a statistical basis. A trajectory simulation platform also allows the user to handily generate trajectories and even synthetic time-lapses to test alternative tracking algorithms and data analysis approaches. A high degree of customisation for the analysis pipeline, for example with the introduction of different diffusion modes, is possible from the source code. Finally, the presence of graphical user interfaces lowers the access barrier for users with little to no programming experience.