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The Weak Layer Anticrack Model (WEAC) [1] is a tool for the analysis of snow slabs and the underlying weak layer, a system prone to release dry snow slab avalanches. Based on first-order shear deformation beam theory, it provides a closed-form solution for the deformation of the snowpack and the stress and energy release rate of the weak layer. Using a mixed-mode failure criterion for the weak layer, the model can predict anticrack nucleation preceding the release of an avalanche. In the current state, it allows unbounded vertical slab deformation. To limit this deformation to the collapse height of the weak layer, contact between the snow slab and the substratum must be considered. The present work proposes an extension of the model to take this effect into account. The propagation of a crack in the weak layer increases the deflection of the slab until it is finally in contact with the substratum. This corresponds to a change of boundary conditions and introduces a structural nonlinearity. This nonlinearity is handled by decomposing the nonlinear structural system of slab and weak layer into four linear subsystems, each of these applying to different scopes of crack lengths. For a given crack length, the subsystem to apply accordingly is evaluated by comparing the crack length at hand with the previously defined scopes. The subsystem constituted in this manner is then employed to calculate the energy release rate of a propagating anticrack and the stresses in the remaining intact weak layer. A comparison with a finite element reference model shows good agreement with the analytical model and, thus, validates the assumptions made. Parametric investigations on propagation saw tests address the effect of slab-substratum contact on the crack propagation conditions in snowpacks or experiments such as propagation saw tests. [1] Rosendahl, Philipp Laurens, & Weissgraeber, Philipp. (2021). Weak Layer Anticrack Nucleation Model (WEAC) (2.2.1). Zenodo. https://doi.org/10.5281/zenodo.6366666

Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on standing surface acoustic waves and transfer molecular specificity to image-based sorting using an efficient deep neural network. In addition to general performance, we demonstrate the utility of this method by sorting neutrophils from whole blood without labels.

The accurate measurement of elastic and fracture properties of snow is challenging but crucial for the modeling of avalanche events. We propose the combination of a closed-form model of the mechanical behavior of layered snowpacks with full-field displacement measurements of propagation saw tests (PSTs) for the identification of the elastic properties of all snow layers and of the fracture toughness of weak layers.The analytical model provides snow cover deformations, weak-layer stresses and energy release rates of cracks within the weak-layer for arbitrarily layered snowpacks. It can be used for real-time analyses of skier-loaded slopes and for stability tests such as the propagation saw test. Its real-time evaluation is particularly important for the present application.Full-field measurements of snow cover deformations during propagation saw tests can be obtained using digital image correlation. Recordings of a simple handheld camera suffice for the present application.The elastic material properties of each layer can then be obtained by fitting the modeled displacement field to the recorded field. The solution of this optimization problem requires many evaluations of the model with varied material parameters of all layers but finally yields the elastic properties of each layer of the snow cover.Finally, the model allows for the calculation of weak-layer fracture toughnesses using the above determined material properties and the critical crack length of the PST experiment. The results indicate an increasing slab stiffness and an increasing weak-layer fracture toughness throughout one winter season.

Cellular reprogramming is a dedifferentiation process during which cells continuously undergo phenotypical remodeling. Although the genetic and biochemical details of this remodeling are fairly well understood, little is known about the change in cell mechanical properties during the process. In this study, we investigated changes in the mechanical phenotype of murine fetal neural progenitor cells (fNPCs) during reprogramming to induced pluripotent stem cells (iPSCs). We find that fNPCs become progressively stiffer en route to pluripotency, and that this stiffening is mirrored by iPSCs becoming more compliant during differentiation towards the neural lineage. Furthermore, we show that the mechanical phenotype of iPSCs is comparable with that of embryonic stem cells. These results suggest that mechanical properties of cells are inherent to their developmental stage. They also reveal that pluripotent cells can differentiate towards a more compliant phenotype, which challenges the view that pluripotent stem cells are less stiff than any cells more advanced developmentally. Finally, our study indicates that the cell mechanical phenotype might be utilized as an inherent biophysical marker of pluripotent stem cells.

The mechanical fingerprint of cells is inherently linked to the structure of the cytoskeleton and can serve as a label-free marker for cell homeostasis or pathologic states. How cytoskeletal composition affects the physical response of cells to external loads has been intensively studied with a spectrum of techniques, yet quantitative and statistically powerful investigations in the form of titration assays are hampered by the low throughput of most available methods. In this study, we employ real-time deformability cytometry (RT-DC), a novel microfluidic tool to examine the effects of biochemically modified F-actin and microtubule stability and nuclear chromatin structure on cell deformation in a human leukemia cell line (HL60). The high throughput of our method facilitates extensive titration assays that allow for significance assessment of the observed effects and extraction of half-maximal concentrations for most of the applied reagents. We quantitatively show that integrity of the F-actin cortex and microtubule network dominate cell deformation on millisecond timescales probed with RT-DC. Drug-induced alterations in the nuclear chromatin structure were not found to consistently affect cell deformation. The sensitivity of the high-throughput cell mechanical measurements to the cytoskeletal modifications we present in this study opens up new possibilities for label-free dose-response assays of cytoskeletal modifications.

Identification of different cell types is an indispensable part in biomedical research and clinical application. During the last decades, much attention was put onto molecular characterization and many cell types can now be identified and sorted based on established markers. The required staining process is a lengthy and costly treatment, which can cause alterations of cellular properties, contaminate the sample and therefore limit its subsequent use. A promising alternative to molecular markers is the label-free identification of cells using mechanical or morphological features. We introduce a microfluidic device for active label-free sorting of cells based on their bright field image supported by innovative real-time image processing and deep neural networks (DNNs). A microfluidic chip features a standing surface acoustic wave generator for actively pushing up to 100 cells/sec to a determined outlet for collection. This novel method is successfully applied for enrichment of lymphocytes, granulo-monocytes and red blood cells from human blood. Furthermore, we combined the setup with lasers and a fluorescence detection unit, allowing to assign a fluorescence signal to each captured bright-field image. Leveraging this tool and common molecular staining, we created a labelled dataset containing thousands of images of different blood cells. We used this dataset to train a DNN with optimized latency below 1 ms and used it to sort unstained neutrophils from human blood, resulting in a target concentration of 90%. The innovative approach to use deep learning for image-based sorting opens up a wide field of potential applications, for example label-free enrichment of stem-cells for transplantation.

The identification and separation of specific cells from heterogeneous populations is an essential prerequisite for further analysis or use. Conventional passive and active separation approaches rely on fluorescent or magnetic tags introduced to the cells of interest through molecular markers. Such labeling is time- and cost-intensive, can alter cellular properties, and might be incompatible with subsequent use, for example, in transplantation. Alternative label-free approaches utilizing morphological or mechanical features are attractive, but lack molecular specificity. Here we combine image-based real-time fluorescence and deformability cytometry (RT-FDC) with downstream cell sorting using standing surface acoustic waves (SSAW). We demonstrate basic sorting capabilities of the device by separating cell mimics and blood cell types based on fluorescence as well as deformability and other image parameters. The identification of blood sub-populations is enhanced by flow alignment and deformation of cells in the microfluidic channel constriction. In addition, the classification of blood cells using established fluorescence-based markers provides hundreds of thousands of labeled cell images used to train a deep neural network. The trained algorithm, with latency optimized to below 1 ms, is then used to identify and sort unlabeled blood cells at rates of 100 cells/sec. This approach transfers molecular specificity into label-free sorting and opens up new possibilities for basic biological research and clinical therapeutic applications.

Although label-free cell sorting is desirable for providing pristine cells for further analysis or use, current approaches lack molecular specificity and speed. Here, we combine real-time fluorescence and deformability cytometry with sorting based on standing surface acoustic waves and transfer molecular specificity to image-based sorting using an efficient deep neural network. In addition to general performance, we demonstrate the utility of this method by sorting neutrophils from whole blood without labels.

Stem cell mechanics, determined predominantly by the cell's cytoskeleton, plays an important role in different biological processes such as stem cell differentiation or migration. Several methods to measure mechanical properties of cells are currently available, but most of them are limited in the ability to screen large heterogeneous populations in a robust and efficient manner-a feature required for successful translational applications. With real-time fluorescence and deformability cytometry (RT-FDC), mechanical properties of cells in suspension can be screened continuously at rates of up to 1,000 cells/s-similar to conventional flow cytometers-which makes it a suitable method not only for basic research but also for a clinical setting. In parallel to mechanical characterization, RT-FDC allows to measure specific molecular markers using standard fluorescence labeling. In this chapter, we provide a detailed protocol for the characterization of hematopoietic stem and progenitor cells (HSPCs) in heterogeneous mobilized peripheral blood using RT-FDC and present a specific morpho-rheological fingerprint of HSPCs that allows to distinguish them from all other blood cell types.

Stem cell mechanics, determined predominantly by the cell's cytoskeleton, plays an important role in different biological processes such as stem cell differentiation or migration. Several methods to measure mechanical properties of cells are currently available, but most of them are limited in the ability to screen large heterogeneous populations in a robust and efficient manner-a feature required for successful translational applications. With real-time fluorescence and deformability cytometry (RT-FDC), mechanical properties of cells in suspension can be screened continuously at rates of up to 1,000 cells/s-similar to conventional flow cytometers-which makes it a suitable method not only for basic research but also for a clinical setting. In parallel to mechanical characterization, RT-FDC allows to measure specific molecular markers using standard fluorescence labeling. In this chapter, we provide a detailed protocol for the characterization of hematopoietic stem and progenitor cells (HSPCs) in heterogeneous mobilized peripheral blood using RT-FDC and present a specific morpho-rheological fingerprint of HSPCs that allows to distinguish them from all other blood cell types.

Mechanical properties of cells can serve as a label-free marker of cell state and function and their alterations have been implicated in processes such as cancer metastasis, leukocyte activation, or stem cell differentiation. Over recent years, new techniques for single-cell mechanical characterization at high throughput have been developed to accelerate discovery in the field of mechanical phenotyping. One such technique is real-time deformability cytometry (RT-DC), a robust technology based on microfluidics that performs continuous mechanical characterization of cells in a contactless manner at rates of up to 1000 cells per second. This tremendous throughput allows for comparison of large sample numbers and precise characterization of heterogeneous cell populations. Additionally, parameters acquired in RT-DC measurements can be used to determine the apparent Young's modulus of individual cells. In this chapter, we present practical aspects important for the implementation of the RT-DC methodology, including a description of the setup, operation principles, and experimental protocols. In the latter, we describe a variety of preparation procedures for samples originating from different sources including 2D and 3D cell cultures as well as blood and tissue-derived primary cells, and discuss obstacles that may arise during their measurements. Finally, we provide insights into standard data analysis procedures and discuss the method's performance in light of other available techniques.

Mechanical properties of cells can serve as a label-free marker of cell state and function and their alterations have been implicated in processes such as cancer metastasis, leukocyte activation, or stem cell differentiation. Over recent years, new techniques for single-cell mechanical characterization at high throughput have been developed to accelerate discovery in the field of mechanical phenotyping. One such technique is real-time deformability cytometry (RT-DC), a robust technology based on microfluidics that performs continuous mechanical characterization of cells in a contactless manner at rates of up to 1000 cells per second. This tremendous throughput allows for comparison of large sample numbers and precise characterization of heterogeneous cell populations. Additionally, parameters acquired in RT-DC measurements can be used to determine the apparent Young's modulus of individual cells. In this chapter, we present practical aspects important for the implementation of the RT-DC methodology, including a description of the setup, operation principles, and experimental protocols. In the latter, we describe a variety of preparation procedures for samples originating from different sources including 2D and 3D cell cultures as well as blood and tissue-derived primary cells, and discuss obstacles that may arise during their measurements. Finally, we provide insights into standard data analysis procedures and discuss the method's performance in light of other available techniques.

Blood is arguably the most important bodily fluid and its analysis provides crucial health status information. A first routine measure to narrow down diagnosis in clinical practice is the differential blood count, determining the frequency of all major blood cells. What is lacking to advance initial blood diagnostics is an unbiased and quick functional assessment of blood that can narrow down the diagnosis and generate specific hypotheses. To address this need, we introduce the continuous, cell-by-cell morpho-rheological (MORE) analysis of diluted whole blood, without labeling, enrichment or separation, at rates of 1000 cells/sec. In a drop of blood we can identify all major blood cells and characterize their pathological changes in several disease conditions in vitro and in patient samples. This approach takes previous results of mechanical studies on specifically isolated blood cells to the level of application directly in blood and adds a functional dimension to conventional blood analysis., eLife digest When you are sick and go to the doctor, it is often not obvious what exactly is wrong — what is causing fever, nausea, shortness of breath or other symptoms. It is important to find this out quickly so that the right action can be taken. One of the first steps is to obtain a blood sample and to count how many of the different blood cells are present in it. This is called a complete blood count, and the information it provides has turned out to be surprisingly useful. A large number of certain white blood cells, for example, can show that the body is fighting an infection. But there might be several reasons why the number of white blood cells has increased, so this information alone is often not enough for a specific diagnosis. There are many hundreds of possible tests that can supplement the results of a complete blood count. These might identify bacteria or measure the concentrations of certain molecules in the blood, for example. But which test will give the important clue that reveals the source of the illness? This can be difficult to predict. Although each test helps to narrow down the final diagnosis they become increasingly expensive and time-consuming to perform, and rapid action is often important when treating a disease. Can we get more decisive information from the initial blood test by measuring other properties of the blood cells? Toepfner et al. now show that this is possible using a technique called real-time deformability cytometry. This method forces the blood cells in a small drop of blood to flow extremely rapidly through a narrow microfluidic channel while they are imaged by a fast camera. A computer algorithm can then analyze the size and stiffness of the blood cells in real-time. Toepfner et al. show that this approach can detect characteristic changes that affect blood cells as a result of malaria, spherocytosis, bacterial and viral infections, and leukemia. Furthermore, many thousands of blood cells can be measured in a few minutes — fast enough to be suitable as a diagnostic test. These proof-of-concept findings can now be used to develop actual diagnostic tests for a wide range of blood-related diseases. The approach could also be used to test which of several drugs is working to treat a certain medical condition, and to monitor whether the treatment is progressing as planned.

We introduce real-time deformability cytometry (RT-DC) for continuous cell mechanical characterization of large populations (100,000 cells) with analysis rates greater than 100 cells/s. RT-DC is sensitive to cytoskeletal alterations and can distinguish cell-cycle phases, track stem cell differentiation into distinct lineages and identify cell populations in whole blood by their mechanical fingerprints. This technique adds a new marker-free dimension to flow cytometry with diverse applications in biology, biotechnology and medicine.

Cell mechanical characterization has recently approached the throughput of conventional flow cytometers. However, this very sensitive, label-free approach still lacks the specificity of molecular markers. Here we combine real-time 1D-imaging fluorescence and deformability cytometry (RT-FDC) to merge the two worlds in one instrument — opening many new research avenues. We demonstrate its utility using sub-cellular fluorescence localization to identify mitotic cells and test for their mechanical changes in an RNAi screen.

Blood is arguably the most important bodily fluid and its analysis provides crucial health status information. A first routine measure to narrow down diagnosis in clinical practice is the differential blood count, determining the frequency of all major blood cells. What is lacking to advance initial blood diagnostics is an unbiased and quick functional assessment of blood that can narrow down the diagnosis and generate specific hypotheses. To address this need, we introduce the continuous, cell-by-cell morpho-rheological (MORE) analysis of whole blood, without labeling, enrichment or separation, at rates of 1,000 cells/sec. In a drop of blood we can identify all major blood cells and characterize their pathological changes in several disease conditions in vitro and in patient samples. This approach takes previous results of mechanical studies on specifically isolated blood cells to the level of application directly in whole blood and adds a functional dimension to conventional blood analysis.

The mechanical fingerprint of cells is inherently linked to the structure of the cytoskeleton and can serve as a label‐free marker for cell homeostasis or pathologic states. How cytoskeletal composition affects the physical response of cells to external loads has been intensively studied with a spectrum of techniques, yet quantitative and statistically powerful investigations in the form of titration assays are hampered by the low throughput of most available methods. In this study, we employ real‐time deformability cytometry (RT‐DC), a novel microfluidic tool to examine the effects of biochemically modified F‐actin and microtubule stability and nuclear chromatin structure on cell deformation in a human leukemia cell line (HL60). The high throughput of our method facilitates extensive titration assays that allow for significance assessment of the observed effects and extraction of half‐maximal concentrations for most of the applied reagents. We quantitatively show that integrity of the F‐actin cortex and microtubule network dominate cell deformation on millisecond timescales probed with RT‐DC. Drug‐induced alterations in the nuclear chromatin structure were not found to consistently affect cell deformation. The sensitivity of the high‐throughput cell mechanical measurements to the cytoskeletal modifications we present in this study opens up new possibilities for label‐free dose‐response assays of cytoskeletal modifications.

Skeletal stem cells (SSCs) are a sub-population of mesenchymal stromal cells (MSCs) present in bone marrow with multipotent differentiation potential. A current unmet challenge hampering their clinical translation remains the isolation of homogeneous populations of SSCs, in vitro, with consistent regeneration and differentiation capacities. Cell stiffness has been shown to play an important role in cell separation using microfluidic techniques such as inertial focusing or deterministic lateral displacement. Here we report that the mechanical properties of SSCs, and of a surrogate human osteosarcoma cell line (MG-63), differ significantly from other cell populations found in the bone marrow. Using real-time deformability cytometry, a recently introduced method for cell mechanical characterization, we demonstrate that both MG-63 and SSCs are stiffer than the three primary leukocyte lineages (lymphocytes, monocytes and granulocytes) and also stiffer than HL-60, a human leukemic progenitor cell line. In addition, we show that SSCs form a mechanically distinct sub-population of MSCs. These results represent an important step towards finding the bio-physical fingerprint of human SSCs that will allow their label-free separation from bone marrow with significant physiological and therapeutic implications.

Cell stiffness is a sensitive indicator of physiological and pathological changes in cells, with many potential applications in biology and medicine. A new method, real-time deformability cytometry, probes cell stiffness at high throughput by exposing cells to a shear flow in a microfluidic channel, allowing for mechanical phenotyping based on single-cell deformability. However, observed deformations of cells in the channel not only are determined by cell stiffness, but also depend on cell size relative to channel size. Here, we disentangle mutual contributions of cell size and cell stiffness to cell deformation by a theoretical analysis in terms of hydrodynamics and linear elasticity theory. Performing real-time deformability cytometry experiments on both model spheres of known elasticity and biological cells, we demonstrate that our analytical model not only predicts deformed shapes inside the channel but also allows for quantification of cell mechanical parameters. Thereby, fast and quantitative mechanical sampling of large cell populations becomes feasible.

Changes in cell function are often accompanied by alterations of the intrinsic cell structure particularly the cytoskeleton. This leads to distinct mechanical changes. For example, cells become softer during malignant transformation and stiffer during differentiation. Exploiting the mechanical phenotype of cells as an inherent, label-free marker requires a high-throughput and robust measurement technique. Here, we introduce real-time deformability cytometry (RT-DC) for mechanical single cell classification of heterogeneous cell populations at rates of several hundred cells per second in real-time. Performing RT-DC on primary human hematopoietic stem cells and mature blood cells we demonstrate its capability to detect lineage and source specific mechanical phenotypes. We also find that different stages of the cell cycle possess a unique mechanical fingerprint allowing the distinction between cells in G2 and M phase. In summary, RT-DC represents a novel flow cytometric approach that enables the translation of mechanical phenotyping from basic research into applications in biology and medicine.

Background: The use of video technology is an established method of training. As an extended video format, 360° videos expand the potential of conventional videos with immersive and interactive design possibilities and combine conventional video technology with immersive technologies in a resource-saving manner. In sports, 360° videos can be used as tactical training tools to support reflection and analysis and to illustrate movements. In particular, 360° videos can be used to create a recorded authentic learning environment to support observational, multi-perspective training. Approach: This paper presents the use of 360° video training for the observation and imitation of movement sequences in poomsae training in taekwondo (or kata training in karate), using the example of the Taegeuk II Jang poomsae. The successive four-step concept can not only be applied to poomsae training in Taekwondo, but can also be transferred to other predefined movement forms and choreographies. Purpose: By using playback media with different degrees of immersion, the movement sequence can be observed, imitated, and followed in successive steps to enable the feeling of participating in a digital training group. Conclusions: The possible applications of 360° video technology in sports are versatile and offer new, immersive possibilities for simple and accessible training design. Training processes that are predominantly done through observational and imitative learning can be accompanied or shifted to home training with the presented 360° video training concept. In particular, 360° videos are suitable for reflective and observational training due to the multiple perspectives provided by the 360° view, which remain to be evaluated.