Search Results
Thermal activation of catalytic microjets in blood samples using microfluidic chips
We demonstrate that catalytic microjet engines can out-swim high complex media composed of red blood cells and serum. Despite the challenge presented by the high viscosity of the solution at room temperature, the catalytic microjets can be activated at physiological temperature and, consequently, self-propel in diluted solutions of blood samples. We prove that these microjets self-propel in 10× diluted blood samples using microfluidic chips.
A new human adipocyte model with PTEN haploinsufficiency
Few human cell strains are suitable and readily available as in vitro adipocyte models. We used resected lipoma tissue from a patient with germline phosphatase and tensin homolog (PTEN) haploinsufficiency to establish a preadipocyte cell strain termed LipPD1 and aimed to characterize cellular functions and signalling pathway alterations in comparison to the established adipocyte model Simpson-Golabi-Behmel-Syndrome (SGBS) and to primary stromal-vascular fraction cells. We found that both cellular life span and the capacity for adipocyte differentiation as well as adipocyte-specific functions were preserved in LipPD1 and comparable to SGBS adipocytes. Basal and growth factor-stimulated activation of the PI3 K/AKT signalling pathway was increased in LipPD1 preadipocytes, corresponding to reduced PTEN levels in comparison to SGBS cells. Altogether, LipPD1 cells are a novel primary cell model with a defined genetic lesion suitable for the study of adipocyte biology. © 2020, © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Effects of new beta-type Ti-40Nb implant materials, brain-derived neurotrophic factor, acetylcholine and nicotine on human mesenchymal stem cells of osteoporotic and non osteoporotic donors
Introduction Treatment of osteoporotic fractures is still challenging and an urgent need exists for new materials, better adapted to osteoporotic bone by adjusted Young’s modulus, appropriate surface modification and pharmaceuticals. Materials and methods Titanium-40-niobium alloys, mechanically ground or additionally etched and titanium-6-alu-minium-4-vanadium were analyzed in combination with brain-derived neurotrophic factor, acetylcholine and nicotine to determine their effects on human mesenchymal stem cells in vitro over 21 days using lactate dehydrogenase and alkaline phosphatase assays, live cell imaging and immunofluorescence microscopy. Results Cell number of human mesenchymal stem cells of osteoporotic donors was increased after 14 d in presence of ground titanium-40-niobium or titanium-6-aluminium-4-vanadium, together with brain-derived neurotrophic factor. Cell number of human mesenchymal stem cells of non osteoporotic donors increased after 21 d in presence of titanium-6-aluminium-4-vanadium without pharmaceuticals. No significant increase was measured for ground or etched titanium-40-niobium after 21 d. Osteoblast differentiation of osteoporotic donors was significantly higher than in non osteoporotic donors after 21 d in presence of etched, ground titanium-40-niobium or titanium-6-aluminium-4-vanadium accompanied by all pharmaceuticals tested. In presence of all alloys tested brain-derived neurotrophic factor, acetylcholine and nicotine increased differentiation of cells of osteoporotic donors and accelerated it in non osteoporotic donors. Conclusion We conclude that ground titanium-40-niobium and brain-derived neurotrophic factor might be most suitable for subsequent in vivo testing.
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.
Computational tissue staining of non-linear multimodal imaging using supervised and unsupervised deep learning
Hematoxylin and Eosin (H&E) staining is the 'gold-standard' method in histopathology. However, standard H&E staining of high-quality tissue sections requires long sample preparation times including sample embedding, which restricts its application for 'real-time' disease diagnosis. Due to this reason, a label-free alternative technique like non-linear multimodal (NLM) imaging, which is the combination of three non-linear optical modalities including coherent anti-Stokes Raman scattering, two-photon excitation fluorescence and second-harmonic generation, is proposed in this work. To correlate the information of the NLM images with H&E images, this work proposes computational staining of NLM images using deep learning models in a supervised and an unsupervised approach. In the supervised and the unsupervised approach, conditional generative adversarial networks (CGANs) and cycle conditional generative adversarial networks (cycle CGANs) are used, respectively. Both CGAN and cycle CGAN models generate pseudo H&E images, which are quantitatively analyzed based on mean squared error, structure similarity index and color shading similarity index. The mean of the three metrics calculated for the computationally generated H&E images indicate significant performance. Thus, utilizing CGAN and cycle CGAN models for computational staining is beneficial for diagnostic applications without performing a laboratory-based staining procedure. To the author's best knowledge, it is the first time that NLM images are computationally stained to H&E images using GANs in an unsupervised manner.
Plasma-MDS, a metadata schema for plasma science with examples from plasma technology
A metadata schema, named Plasma-MDS, is introduced to support research data management in plasma science. Plasma-MDS is suitable to facilitate the publication of research data following the FAIR principles in domain-specific repositories and with this the reuse of research data for data driven plasma science. In accordance with common features in plasma science and technology, the metadata schema bases on the concept to separately describe the source generating the plasma, the medium in which the plasma is operated in, the target the plasma is acting on, and the diagnostics used for investigation of the process under consideration. These four basic schema elements are supplemented by a schema element with various attributes for description of the resources, i.e. the digital data obtained by the applied diagnostic procedures. The metadata schema is first applied for the annotation of datasets published in INPTDAT—the interdisciplinary data platform for plasma technology. © 2020, The Author(s).
Antimicrobial Efficacy of Two Surface Barrier Discharges with Air Plasma against In Vitro Biofilms
The treatment of infected wounds is one possible therapeutic aspect of plasma medicine. Chronic wounds are often associated with microbial biofilms which limit the efficacy of antiseptics. The present study investigates two different surface barrier discharges with air plasma to compare their efficacy against microbial biofilms with chlorhexidine digluconate solution (CHX) as representative of an important antibiofilm antiseptic. Pseudomonas aeruginosa SG81 and Staphylococcus epidermidis RP62A were cultivated on polycarbonate discs. The biofilms were treated for 30, 60, 150, 300 or 600 s with plasma or for 600 s with 0.1% CHX, respectively. After treatment, biofilms were dispensed by ultrasound and the antimicrobial effects were determined as difference in the number of the colony forming units by microbial culture. A high antimicrobial efficacy on biofilms of both plasma sources in comparison to CHX treatment was shown. The efficacy differs between the used strains and plasma sources. For illustration, the biofilms were examined under a scanning electron microscope before and after treatment. Additionally, cytotoxicity was determined by the MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay with L929 mouse fibroblast cell line. The cell toxicity of the used plasma limits its applicability on human tissue to maximally 150 s. The emitted UV irradiance was measured to estimate whether UV could limit the application on human tissue at the given parameters. It was found that the UV emission is negligibly low. In conclusion, the results support the assumption that air plasma could be an option for therapy of chronic wounds.
Complement activation by carbon nanotubes and its influence on the phagocytosis and cytokine response by macrophages
Carbon nanotubes (CNTs) have promised a range of applications in biomedicine. Although influenced by the dispersants used, CNTs are recognized by the innate immune system, predominantly by the classical pathway of the complement system. Here, we confirm that complement activation by the CNT used continues up to C3 and C5, indicating that the entire complement system is activated including the formation of membrane-attack complexes. Using recombinant forms of the globular regions of human C1q (gC1q) as inhibitors of CNT-mediated classical pathway activation, we show that C1q, the first recognition subcomponent of the classical pathway, binds CNTs via the gC1q domain. Complement opsonisation of CNTs significantly enhances their uptake by U937 cells, with concomitant downregulation of pro-inflammatory cytokines and up-regulation of anti-inflammatory cytokines in both U937 cells and human monocytes. We propose that CNT-mediated complement activation may cause recruitment of cellular infiltration, followed by phagocytosis without inducing a pro-inflammatory immune response. From the Clinical Editor: This study highlights the importance of the complement system in response to carbon nanontube administration, suggesting that the ensuing complement activation may cause recruitment of cellular infiltration, followed by phagocytosis without inducing a pro-inflammatory immune response.