Publikationen

Adhesion between an elastic body and a smooth, rigid substrate can lead to large tensile stresses between them. However, most macroscopic objects are microscopically rough, which strongly suppresses adhesion. A fierce debate has unfolded recently as to whether local or global parameters determine the crossover between small and large adhesion. Here, we report simulations revealing that the dependence of the pull-off force Fn on the surface energy γ does not only have two regimes of high and low adhesion but up to four regimes. They are related to contacts, which at the moment of rupture consist of (i) the last individual Hertzian-shaped contact, in which is linear in γ, (ii) a last meso-scale, individual patches with super-linear scaling, (iii) many isolated contact patches with extremely strong scaling, and (iv) a dominating largest contact patch, for which the pull-off stress is no longer negligible compared to the maximum, microscopic pull-off stress. Regime (iii) can be seen as a transition domain. It is located near the point where the surface energy is half the elastic energy per unit area in conformal contact. A criterion for the transition between regimes (i) and (ii) appears difficult to grasp.

Adherens junctions (AJs) allow cell contact to inhibit epithelial migration yet also permit epithelia to move as coherent sheets. How, then, do cells identify which contacts will inhibit locomotion? Here, we show that in human epithelial cells this arises from the orientation of cortical flows at AJs. When the leader cells from different migrating sheets make head-on contact with one another, they assemble AJs that couple together oppositely directed cortical flows. This applies a tensile signal to the actin-binding domain (ABD) of α-catenin, which provides a clutch to promote lateral adhesion growth and inhibit the lamellipodial activity necessary for migration. In contrast, AJs found between leader cells in the same migrating sheet have cortical flows aligned in the same direction, and no such mechanical inhibition takes place. Therefore, α-catenin mechanosensitivity in the clutch between E-cadherin and cortical F-actin allows cells to interpret the direction of motion via cortical flows and signal for contact to inhibit locomotion.

The adhesion of a rigid substrate and an adhered straight cylindrical punch with a non-homogeneous elastic modulus is analyzed. The stress distributions are obtained along the interface for various elastic modulus gradients. The calculations are performed in the commercial finite element software Abaqus using a user material (UMAT) subroutine to control the dependence of Young’s modulus on the radial position. The UMAT code is shared in the paper. The results reveal that the decreasing elastic modulus toward the perimeter of the punch can be used to significantly reduce the normal stress magnitudes in the singularity domain, which leads to stronger adhesion. The increase in the adhesion strength is characterized numerically. The effect of Poisson’s ratio is also analyzed.

While viscoelastic, adhesive contact rupture of simple indenters is well studied, contact formation has received much less attention. Here, we present simulations of the formation of contact between various power law indenters and an adhesive, viscoelastic foundation. For all investigated indenters, we find that the macroscopic relaxation time τ scales approximately with 1/ρ1.8, where ρ is the range of adhesion. The prolongation of contact formation with Tabor parameter is rationalized by the increased dissipation that short-range adhesion causes on a moving crack.

Bioinspired fibrillar adhesives have been proposed for novel gripping systems with enhanced scalability and resource efficiency. Here, we propose an in-situ optical monitoring system of the contact signatures, coupled with image processing and machine learning. Visual features were extracted from the contact signature images recorded at maximum compressive preload and after lifting a glass object. The algorithm was trained to cope with several degrees of misalignment and with unbalanced weight distributions by off-center gripping. The system allowed an assessment of the picking process for objects of various mass (200, 300, and 400 g). Several classifiers showed a high accuracy of about 90 % for successful prediction of attachment, depending on the mass of the object. The results promise improved reliability of handling objects, even in difficult situations.

Nanostructured earth abundant metal catalysts that mediate important chemical reactions with high efficiency and selectivity are of great interest. This study introduces a synthesis protocol for nanostructured earth abundant metal catalysts. Three components, an inexpensive metal precursor, an easy to synthesize N/C precursor, and a porous support material undergo pyrolysis to give the catalyst material in a simple, single synthesis step. By applying this catalyst synthesis, a highly active cobalt catalyst for the general and selective hydrogenation of aromatic heterocycles could be generated. The reaction is important with regard to organic synthesis and hydrogen storage. The mild reaction conditions observed for quinolines permit the selective hydrogenation of numerous classes of N-, O- and S-heterocyclic compounds such as: quinoxalines, pyridines, pyrroles, indoles, isoquinoline, aciridine amine, phenanthroline, benzofuranes, and benzothiophenes.

Background: Due to COVID-19, pandemic preparedness emerges as a key imperative, necessitating new approaches to accelerate development of reagents against infectious pathogens. Methods: Here, we developed an integrated approach combining synthetic, computational and structural methods with in vitro antibody selection and in vivo immunization to design, produce and validate nature-inspired nanoparticle-based reagents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).
Results: Our approach resulted in two innovations: (i) a thermostable nasal vaccine called ADDoCoV, displaying multiple copies of a SARS-CoV-2 receptor binding motif derived epitope and (ii) a multivalent nanoparticle superbinder, called Gigabody, against SARS-CoV-2 including immune-evasive variants of concern (VOCs). In vitro generated neutralizing nanobodies and electron cryo-microscopy established authenticity and accessibility of epitopes displayed by ADDoCoV. Gigabody comprising multimerized nanobodies prevented SARS-CoV-2 virion attachment with picomolar EC50. Vaccinating mice resulted in antibodies cross-reacting with VOCs including Delta and Omicron.
Conclusion: Our study elucidates Adenovirus-derived dodecamer (ADDomer)-based nanoparticles for use in active and passive immunization and provides a blueprint for crafting reagents to combat respiratory viral infections.

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 dif-
ficult 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 flex-
ibility, speed, and functionality to this approach. We then deploy Kartezio to
solve a series of semantic and instance segmentation problems, and demon-
strate its utility across diverse images ranging from multiplexed tissue histo-
pathology images to high resolution microscopy images. While the flexibility,
robustness and practical utility of Kartezio make this fully explicable evolu-
tionary designer a potential game-changer in the field of biomedical image
processing, Kartezio remains complementary and potentially auxiliary to
mainstream Deep Learning approaches.

Ionic liquids (ILs) represent an important class of liquids considered for a broad range of applications such as lubrication, catalysis, or as electrolytes in batteries. It is well-known that in the case of charged surfaces, ILs form a pronounced layer structure that can be easily triggered by an externally applied electrode potential. Information about the time required to form a stable interface under varying electrode potentials is of utmost importance in many applications. For the first time, probing of relaxation times of ILs by friction force microscopy is demonstrated. The friction force is extremely sensitive to even subtle changes in the interfacial configuration of ILs. Various relaxation processes with different time scales are observed. A significant difference dependent on the direction of switching the applied potential, i.e., from a more cation-rich to a more anion-rich interface or vice versa, is found. Furthermore, variations in height immediately after the potential step and the presence of trace amounts of water are discussed as well.

The presence of mechanoreceptors in glabrous skin allows humans to discriminate textures by touch. The amount and distribution of these receptors defines our tactile sensitivity and can be affected by diseases such as diabetes, HIV-related pathologies, and hereditary neuropathies. The quantification of mechanoreceptors as clinical markers by biopsy is an invasive method of diagnosis. We report the localization and quantification of Meissner corpuscles in glabrous skin using in vivo, non-invasive optical microscopy techniques. Our approach is supported by the discovery of epidermal protrusions which are co-localized with Meissner corpuscles. Index fingers, small fingers, and tenar palm regions of ten participants were imaged by optical coherence tomography (OCT) and laser scan microscopy (LSM) to determine the thickness of the stratum corneum and epidermis and to count the Meissner corpuscles. We discovered that regions containing Meissner corpuscles could be easily identified by LSM with an enhanced optical reflectance above the corpuscles, caused by a protrusion of the strongly reflecting epidermis into the stratum corneum with its weak reflectance. We suggest that this local morphology above Meissner corpuscles has a function in tactile perception.