965 research outputs found

    Insights from Multimodal Preclinical Imaging in Immunocompetent Nude Mice

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    Hydrogels based on gelatin have evolved as promising multifunctional biomaterials. Gelatin is crosslinked with lysine diisocyanate ethyl ester (LDI) and the molar ratio of gelatin and LDI in the starting material mixture determines elastic properties of the resulting hydrogel. In order to investigate the clinical potential of these biopolymers, hydrogels with different ratios of gelatin and diisocyanate (3-fold (G10_LNCO3) and 8-fold (G10_LNCO8) molar excess of isocyanate groups) were subcutaneously implanted in mice (uni- or bilateral implantation). Degradation and biomaterial-tissue- interaction were investigated in vivo (MRI, optical imaging, PET) and ex vivo (autoradiography, histology, serum analysis). Multimodal imaging revealed that the number of covalent net points correlates well with degradation time, which allows for targeted modification of hydrogels based on properties of the tissue to be replaced. Importantly, the degradation time was also dependent on the number of implants per animal. Despite local mechanisms of tissue remodeling no adverse tissue responses could be observed neither locally nor systemically. Finally, this preclinical investigation in immunocompetent mice clearly demonstrated a complete restoration of the original healthy tissue

    Disentangling Aliveness, Naturalness and Greenness

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    The \u3cem\u3eChlamydomonas\u3c/em\u3e Genome Reveals the Evolution of Key Animal and Plant Functions

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    Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella

    Adaptive sparse sampling for quasiparticle interference imaging

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    Quasiparticle interference imaging (QPI) offers insight into the band structure of quantum materials from the Fourier transform of local density of states (LDOS) maps. Their acquisition with a scanning tunneling microscope is traditionally tedious due to the large number of required measurements that may take several days to complete. The recent demonstration of sparse sampling for QPI imaging showed how the effective measurement time could be fundamentally reduced by only sampling a small and random subset of the total LDOS. However, the amount of required sub-sampling to faithfully recover the QPI image remained a recurring question. Here we introduce an adaptive sparse sampling (ASS) approach in which we gradually accumulate sparsely sampled LDOS measurements until a desired quality level is achieved via compressive sensing recovery. The iteratively measured random subset of the LDOS can be interleaved with regular topographic images that are used for image registry and drift correction. These reference topographies also allow to resume interrupted measurements to further improve the QPI quality. Our ASS approach is a convenient extension to quasiparticle interference imaging that should remove further hesitation in the implementation of sparse sampling mapping schemes

    Adaptive Sparse Sampling for Quasiparticle Interference Imaging

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    Quasiparticle interference imaging (QPI) offers insight into the band structure of quantum materials from the Fourier transform of local density of states (LDOS) maps. Their acquisition with a scanning tunneling microscope is traditionally tedious due to the large number of required measurements that may take several days to complete. The recent demonstration of sparse sampling for QPI imaging showed how the effective measurement time could be fundamentally reduced by only sampling a small and random subset of the total LDOS. However, the amount of required sub-sampling to faithfully recover the QPI image remained a recurring question. Here we introduce an adaptive sparse sampling (ASS) approach in which we gradually accumulate sparsely sampled LDOS measurements until a desired quality level is achieved via compressive sensing recovery. The iteratively measured random subset of the LDOS can be interleaved with regular topographic images that are used for image registry and drift correction. These reference topographies also allow to resume interrupted measurements to further improve the QPI quality. Our ASS approach is a convenient extension to quasiparticle interference imaging that should remove further hesitation in the implementation of sparse sampling mapping schemes.Comment: 10 pages, 5 figure

    Disturbed brain energy metabolism in a rodent model of DYT-TOR1A dystonia

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    DYT-TOR1A (DYT1) dystonia, characterized by reduced penetrance and suspected environmental triggers, is explored using a “second hit” DYT-TOR1A rat model. We aim to investigate the biological mechanisms driving the conversion into a dystonic phenotype, focusing on the striatum's role in dystonia pathophysiology. Sciatic nerve crush injury was induced in ∆ETorA rats, lacking spontaneous motor abnormalities, and wild-type (wt) rats. Twelve weeks post-injury, unbiased RNA-sequencing was performed on the striatum to identify differentially expressed genes (DEGs) and pathways. Fenofibrate, a PPARα agonist, was introduced to assess its effects on gene expression. 18F-FDG autoradiography explored metabolic alterations in brain networks. Low transcriptomic variability existed between naïve wt and ∆ETorA rats (17 DEGs). Sciatic nerve injury significantly impacted ∆ETorA rats (1009 DEGs) compared to wt rats (216 DEGs). Pathway analyses revealed disruptions in energy metabolism, specifically in fatty acid β-oxidation and glucose metabolism. Fenofibrate induced gene expression changes in wt rats but failed in ∆ETorA rats. Fenofibrate increased dystonia-like movements in wt rats but reduced them in ∆ETorA rats. 18F-FDG autoradiography indicated modified glucose metabolism in motor and somatosensory cortices and striatum in both ∆ETorA and wt rats post-injury. Our findings highlight perturbed energy metabolism pathways in DYT-TOR1A dystonia, emphasizing compromised PPARα agonist efficacy in the striatum. Furthermore, we identify impaired glucose metabolism in the brain network, suggesting a potential shift in energy substrate utilization in dystonic DYT-TOR1A rats. These results contribute to understanding the pathophysiology and potential therapeutic targets for DYT-TOR1A dystonia
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