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Now showing 1 - 10 of 27
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    Podosome-Driven Defect Development in Lamellar Bone under the Conditions of Senile Osteoporosis Observed at the Nanometer Scale
    (Washington, DC : ACS Publications, 2021) Simon, Paul; Pompe, Wolfgang; Bobeth, Manfred; Worch, Hartmut; Kniep, Rüdiger; Formanek, Petr; Hild, Anne; Wenisch, Sabine; Sturm, Elena
    The degradation mechanism of human trabecular bone harvested from the central part of the femoral head of a patient with a fragility fracture of the femoral neck under conditions of senile osteoporosis was investigated by high-resolution electron microscopy. As evidenced by light microscopy, there is a disturbance of bone metabolism leading to severe and irreparable damages to the bone structure. These defects are evoked by osteoclasts and thus podosome activity. Podosomes create typical pit marks and holes of about 300-400 nm in diameter on the bone surface. Detailed analysis of the stress field caused by the podosomes in the extracellular bone matrix was performed. The calculations yielded maximum stress in the range of few megapascals resulting in formation of microcracks around the podosomes. Disintegration of hydroxyapatite and free lying collagen fibrils were observed at the edges of the plywood structure of the bone lamella. At the ultimate state, the disintegration of the mineralized collagen fibrils to a gelatinous matrix comes along with a delamination of the apatite nanoplatelets resulting in a brittle, porous bone structure. The nanoplatelets aggregate to big hydroxyapatite plates with a size of up to 10 x 20 μm2. The enhanced plate growth can be explained by the interaction of two mechanisms in the ruffled border zone: the accumulation of delaminated hydroxyapatite nanoplatelets near clusters of podosomes and the accelerated nucleation and random growth of HAP nanoplatelets due to a nonsufficient concentration of process-directing carboxylated osteocalcin cOC. © 2021 The Authors. Published by American Chemical Society.
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    Fiber-based SORS-SERDS system and chemometrics for the diagnostics and therapy monitoring of psoriasis inflammatory disease in vivo
    (Washington, DC : Optica, 2021-1-28) Schleusener, Johannes; Guo, Shuxia; Darvin, Maxim E.; Thiede, Gisela; Chernavskaia, Olga; Knorr, Florian; Lademann, Jürgen; Popp, Jürgen; Bocklitz, Thomas W.
    Psoriasis is considered a widespread dermatological disease that can strongly affect the quality of life. Currently, the treatment is continued until the skin surface appears clinically healed. However, lesions appearing normal may contain modifications in deeper layers. To terminate the treatment too early can highly increase the risk of relapses. Therefore, techniques are needed for a better knowledge of the treatment process, especially to detect the lesion modifications in deeper layers. In this study, we developed a fiber-based SORS-SERDS system in combination with machine learning algorithms to non-invasively determine the treatment efficiency of psoriasis. The system was designed to acquire Raman spectra from three different depths into the skin, which provide rich information about the skin modifications in deeper layers. This way, it is expected to prevent the occurrence of relapses in case of a too short treatment. The method was verified with a study of 24 patients upon their two visits: the data is acquired at the beginning of a standard treatment (visit 1) and four months afterwards (visit 2). A mean sensitivity of ≥85% was achieved to distinguish psoriasis from normal skin at visit 1. At visit 2, where the patients were healed according to the clinical appearance, the mean sensitivity was ≈65%.
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    Monitoring excited-state relaxation in a molecular marker in live cells–a case study on astaxanthin
    (London : Royal Society of Chemistry (RSC), 2021) Yang, Tingxiang; Chettri, Avinash; Radwan, Basseem; Matuszyk, Ewelina; Baranska, Malgorzata; Dietzek, Benjamin
    Small molecules are frequently used as dyes, labels and markers to visualize and probe biophysical processes within cells. However, very little is generally known about the light-driven excited-state reactivity of such systems when placed in cells. Here an experimental approach to study ps time-resolved excited state dynamics of a benchmark molecular marker, astaxanthin, in live human cells is introduced. © The Royal Society of Chemistry 2021.
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    Scanning electron microscopy preparation of the cellular actin cortex: A quantitative comparison between critical point drying and hexamethyldisilazane drying
    (San Francisco, California, US : PLOS, 2021) Schu, Moritz; Terriac, Emmanuel; Koch, Marcus; Paschke, Stephan; Lautenschläger, Franziska; Flormann, Daniel A.D.
    The cellular cortex is an approximately 200-nm-thick actin network that lies just beneath the cell membrane. It is responsible for the mechanical properties of cells, and as such, it is involved in many cellular processes, including cell migration and cellular interactions with the environment. To develop a clear view of this dense structure, high-resolution imaging is essential. As one such technique, electron microscopy, involves complex sample preparation procedures. The final drying of these samples has significant influence on potential artifacts, like cell shrinkage and the formation of artifactual holes in the actin cortex. In this study, we compared the three most used final sample drying procedures: critical-point drying (CPD), CPD with lens tissue (CPD-LT), and hexamethyldisilazane drying. We show that both hexamethyldisilazane and CPD-LT lead to fewer artifactual mesh holes within the actin cortex than CPD. Moreover, CPD-LT leads to significant reduction in cell height compared to hexamethyldisilazane and CPD. We conclude that the final drying procedure should be chosen according to the reduction in cell height, and so CPD-LT, or according to the spatial separation of the single layers of the actin cortex, and so hexamethyldisilazane.
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    Research data management in agricultural sciences in Germany: We are not yet where we want to be
    (San Francisco, California, US : PLOS, 2022) Senft, Matthias; Stahl, Ulrike; Svoboda, Nikolai
    To meet the future challenges and foster integrated and holistic research approaches in agricultural sciences, new and sustainable methods in research data management (RDM) are needed. The involvement of scientific users is a critical success factor for their development. We conducted an online survey in 2020 among different user groups in agricultural sciences about their RDM practices and needs. In total, the questionnaire contained 52 questions on information about produced and (re-)used data, data quality aspects, information about the use of standards, publication practices and legal aspects of agricultural research data, the current situation in RDM in regards to awareness, consulting and curricula as well as needs of the agricultural community in respect to future developments. We received 196 (partially) completed questionnaires from data providers, data users, infrastructure and information service providers. In addition to the diversity in the research data landscape of agricultural sciences in Germany, the study reveals challenges, deficits and uncertainties in handling research data in agricultural sciences standing in the way of access and efficient reuse of valuable research data. However, the study also suggests and discusses potential solutions to enhance data publications, facilitate and secure data re-use, ensure data quality and develop services (i.e. training, support and bundling services). Therefore, our research article provides the basis for the development of common RDM, future infrastructures and services needed to foster the cultural change in handling research data across agricultural sciences in Germany and beyond.
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    Evolutionary design of explainable algorithms for biomedical image segmentation
    ([London] : Nature Publishing Group UK, 2023) Cortacero, Kévin; McKenzie, Brienne; Müller, Sabina; Khazen, Roxana; Lafouresse, Fanny; Corsaut, Gaëlle; Van Acker, Nathalie; Frenois, François-Xavier; Lamant, Laurence; Meyer, Nicolas; Vergier, Béatrice; Wilson, Dennis G.; Luga, Hervé; Staufer, Oskar; Dustin, Michael L.; Valitutti, Salvatore; Cussat-Blanc, Sylvain
    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.
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    Computational design and optimization of electro-physiological sensors
    ([London] : Nature Publishing Group UK, 2021) Nittala, Aditya Shekhar; Karrenbauer, Andreas; Khan, Arshad; Kraus, Tobias; Steimle, Jürgen
    Electro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.
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    Reply to Burgess et al: Catastrophic climate risks are neglected, plausible, and safe to study
    (Washington, DC : National Acad. of Sciences, 2022) Kemp, Luke; Xu, Chi; Depledge, Joanna; Ebi, Kristie L.; Gibbins, Goodwin; Kohler, Timothy A.; Rockström, Johan; Scheffer, Marten; Schellnhuber, Hans Joachim; Steffen, Will; Lenton, Timothy M.
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    PDA Indolylmaleimides Induce Anti-Tumor Effects in Prostate Carcinoma Cell Lines Through Mitotic Death
    (Lausanne : Frontiers Research Foundation, 2021) Schille, Jan Torben; Nolte, Ingo; Beck, Julia; Jilani, Daria; Roolf, Catrin; Pews-Davtyan, Anahit; Rolfs, Arndt; Henze, Larissa; Beller, Matthias; Brenig, Bertram; Junghanss, Christian; Schütz, Ekkehard; Murua Escobar, Hugo
    Castrate resistant prostate cancer in men shares several characteristics with canine prostate cancer (PCa). Due to current insufficient therapies, evaluating novel therapeutic agents for late-stage PCa is of considerable interest for both species. PDA indolylmaleimides showed anticancer effects in several neoplastic cell lines. Herein, a comparative characterization of PDA-66 and PDA-377 mediated effects was performed in human and canine PCa cell lines, which is also the first detailed characterization of these agents on cells derived from solid tumors in general. While PDA-377 showed only weak growth inhibition on human PCa cell lines, PDA-66 inhibited proliferation and induced apoptosis in human and canine cell lines with concentrations in the low micromolar range. Morphological characterization and whole transcriptome sequencing revealed that PDA-66 induces mitotic death through its microtubule-depolymerizing ability. PDA-66 appears to be a worthwhile anti-mitotic agent for further evaluation. The similarities in cellular and molecular response observed in the cell lines of both origins form a solid basis for the use of canine PCa in vivo models to gain valuable interchangeable data to the advantage of both species.
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    Breast Cancer Stem Cell–Derived Tumors Escape from γδ T-cell Immunosurveillance In Vivo by Modulating γδ T-cell Ligands
    (Philadelphia, Pa. : AACR, 2023) Raute, Katrin; Strietz, Juliane; Parigiani, Maria Alejandra; Andrieux, Geoffroy; Thomas, Oliver S.; Kistner, Klaus M.; Zintchenko, Marina; Aichele, Peter; Hofmann, Maike; Zhou, Houjiang; Weber, Wilfried; Boerries, Melanie; Swamy, Mahima; Maurer, Jochen; Minguet, Susana
    There are no targeted therapies for patients with triple-negative breast cancer (TNBC). TNBC is enriched in breast cancer stem cells (BCSC), which play a key role in metastasis, chemoresistance, relapse, and mortality. γδ T cells hold great potential in immunotherapy against cancer and might provide an approach to therapeutically target TNBC. γδ T cells are commonly observed to infiltrate solid tumors and have an extensive repertoire of tumor-sensing mechanisms, recognizing stress-induced molecules and phosphoantigens (pAgs) on transformed cells. Herein, we show that patient-derived triple-negative BCSCs are efficiently recognized and killed by ex vivo expanded γδ T cells from healthy donors. Orthotopically xenografted BCSCs, however, were refractory to γ δ T-cell immunotherapy. We unraveled concerted differentiation and immune escape mechanisms: xenografted BCSCs lost stemness, expression of γ δ T-cell ligands, adhesion molecules, and pAgs, thereby evading immune recognition by γ δ T cells. Indeed, neither promigratory engineered γ δ T cells, nor anti–PD-1 checkpoint blockade, significantly prolonged overall survival of tumor-bearing mice. BCSC immune escape was independent of the immune pressure exerted by the γ δ T cells and could be pharmacologically reverted by zoledronate or IFNα treatment. These results pave the way for novel combinatorial immunotherapies for TNBC.