Similar Datasets
Project description:A new sorting protocol was used to identify and isolate different senescent cell types from damaged muscles of young and geriatric mice. Analysis revealed conservation of two universal senescence hallmarks (inflammation and fibrosis) across cell type, regeneration time, and aging, while cell identity traits were preserved. Senescent cells create an “aged-like” inflamed niche, mirroring inflammation-associated with aging (inflammaging), that arrests stem cell proliferation and regeneration.
2022-10-25 | GSE196612 | GEO
Project description:A new sorting protocol was used to identify and isolate different senescent cell types from damaged muscles of young and geriatric mice. Analysis revealed conservation of two universal senescence hallmarks (inflammation and fibrosis) across cell type, regeneration time, and aging, while cell identity traits were preserved. Senescent cells create an “aged-like” inflamed niche, mirroring inflammation-associated with aging (inflammaging), that arrests stem cell proliferation and regeneration.
2022-10-25 | GSE196611 | GEO
Project description:A new sorting protocol was used to identify and isolate different senescent cell types from damaged muscles of young and geriatric mice. Analysis revealed conservation of two universal senescence hallmarks (inflammation and fibrosis) across cell type, regeneration time, and aging, while cell identity traits were preserved. Senescent cells create an “aged-like” inflamed niche, mirroring inflammation-associated with aging (inflammaging), that arrests stem cell proliferation and regeneration.
2022-10-25 | GSE197017 | GEO
Project description:Given the heterogeneity of senescent cells, our knowledge of both the drivers and consequences of cellular senescence in tissues and organs remains limited, as is our understanding of how this process could be harnessed for human health. Here we identified five broad areas that would help propel the field forward.
| S-EPMC8364378 | biostudies-literature
Project description:During the recent decade, the periodontal attachment apparatus has become one of the premier areas of the body for the development of novel tissue-engineering strategies. In the present review, we describe a developmental biology approach to characterize current concepts in periodontal regeneration and to discuss strategies for future applications in periodontal therapies. To decipher the developmental make-up of the periodontal region, we have followed the path of the migratory neural crest, since it gives rise to periodontal progenitor tissues, which in turn are subjected to the influence of diverse craniofacial extracellular matrices and peptide growth factors. Based on this developmental perspective, we have conducted a systematic analysis of the factors, progenitor cells, and matrices used in current periodontal tissue-engineering approaches. We propose that the developmental history of a tissue is a highly instructive design template for the discovery of novel bioengineering tools and approaches.
| S-EPMC2749262 | biostudies-literature
Project description:Regenerating lost or damaged tissue is the primary goal of Tissue Engineering. 3D bioprinting technologies have been widely applied in many research areas of tissue regeneration and disease modeling with unprecedented spatial resolution and tissue-like complexity. However, the extraction of tissue architecture and the generation of high-resolution blueprints are challenging tasks for tissue regeneration. Traditionally, such spatial information is obtained from a collection of microscopic images and then combined together to visualize regions of interest. To fabricate such engineered tissues, rendered microscopic images are transformed to code to inform a 3D bioprinting process. If this process is augmented with data-driven approaches and streamlined with machine intelligence, identification of an optimal blueprint can become an achievable task for functional tissue regeneration. In this review, our perspective is guided by an emerging paradigm to generate a blueprint for regeneration with machine intelligence. First, we reviewed recent articles with respect to our perspective for machine intelligence-driven information retrieval and fabrication. After briefly introducing recent trends in information retrieval methods from publicly available data, our discussion is focused on recent works that use machine intelligence to discover tissue architectures from imaging and spectral data. Then, our focus is on utilizing optimization approaches to increase print fidelity and enhance biomimicry with machine learning (ML) strategies to acquire a blueprint ready for 3D bioprinting.
| S-EPMC6967031 | biostudies-literature
Project description:The relationship between plant traits and species relative abundance along environmental gradients can provide important insights on the determinants of community structure. Here we bring extensive data on six key traits (specific leaf area (SLA), seed mass, seed germination rate, height, leaf proline content and photosynthesis rate) to test trait-abundance relationships in a successional chronosequence of subalpine meadow plant communities. Our results show that in late-successional meadows, abundant species had higher values for seed mass, seed germination rate, and SLA, but had lower values for height, photosynthesis rate, and leaf proline content than rarer species. The opposite patterns of trait-abundance relationships were observed for early-successional meadows. Observations of strong trait convergence and divergence in these successional communities lend greater support for niche processes compared to neutral community assembly. We conclude that species' niches that determine plant growth (plant height and photosynthesis rate), carbon balance (SLA, photosynthesis rate), regeneration (seed mass and seed germination rate), and abiotic stress resistance (leaf proline content) under different environmental conditions have strong influence on species relative abundance in these sub-alpine meadow communities during succession.
| S-EPMC7048279 | biostudies-literature
Project description:Lymph node stromal cells (LNSCs) closely regulate immunity and self-tolerance, yet key aspects of their biology remain poorly elucidated. Here, comparative transcriptomic analyses of mouse LNSC subsets demonstrated the expression of important immune mediators, growth factors and previously unknown structural components. Pairwise analyses of ligands and cognate receptors across hematopoietic and stromal subsets suggested a complex web of crosstalk. Fibroblastic reticular cells (FRCs) showed enrichment for higher expression of genes relevant to cytokine signaling, relative to their expression in skin and thymic fibroblasts. LNSCs from inflamed lymph nodes upregulated expression of genes encoding chemokines and molecules involved in the acute-phase response and the antigen-processing and antigen-presentation machinery. Poorly studied podoplanin (gp38)-negative CD31(-) LNSCs showed similarities to FRCs but lacked expression of interleukin 7 (IL-7) and were identified as myofibroblastic pericytes that expressed integrin ?(7). Together our data comprehensively describe the transcriptional characteristics of LNSC subsets.
| S-EPMC3366863 | biostudies-literature
Project description:The application of multiphoton microscopy in the field of biomedical research and advanced diagnostics promises unique insights into the pathophysiology of inflammatory skin diseases. In the present study, we combined multiphoton-based intravital tomography (MPT) and fluorescence lifetime imaging (MPT-FLIM) within the scope of a clinical trial of atopic dermatitis with the aim of providing personalised data on the aetiopathology of inflammation in a non-invasive manner at patients' bedsides. These 'optical biopsies' generated via MPT were morphologically analysed and aligned with classical skin histology. Because of its subcellular resolution, MPT provided evidence of a redistribution of mitochondria in keratinocytes, indicating an altered cellular metabolism. Two independent morphometric algorithms reliably showed an even distribution in healthy skin and a perinuclear accumulation in inflamed skin. Moreover, using MPT-FLIM, detection of the onset and progression of inflammatory processes could be achieved. In conclusion, the change in the distribution of mitochondria upon inflammation and the verification of an altered cellular metabolism facilitate a better understanding of inflammatory skin diseases and may permit early diagnosis and therapy.
| S-EPMC4804294 | biostudies-literature
Project description:While considerable progress has been made towards understanding the complex processes and pathways that regulate human wound healing, regenerative medicine has been unable to develop therapies that coax the natural wound environment to heal scar-free. The inability to induce perfect skin regeneration stems partly from our limited understanding of how scar-free healing occurs in a natural setting. Here we have investigated the wound repair process in adult axolotls and demonstrate that they are capable of perfectly repairing full thickness excisional wounds made on the flank. In the context of mammalian wound repair, our findings reveal a substantial reduction in hemostasis, reduced neutrophil infiltration and a relatively long delay in production of new extracellular matrix (ECM) during scar-free healing. Additionally, we test the hypothesis that metamorphosis leads to scarring and instead show that terrestrial axolotls also heal scar-free, albeit at a slower rate. Analysis of newly forming dermal ECM suggests that low levels of fibronectin and high levels of tenascin-C promote regeneration in lieu of scarring. Lastly, a genetic analysis during wound healing comparing epidermis between aquatic and terrestrial axolotls suggests that matrix metalloproteinases may regulate the fibrotic response. Our findings outline a blueprint to understand the cellular and molecular mechanisms coordinating scar-free healing that will be useful towards elucidating new regenerative therapies targeting fibrosis and wound repair.
| S-EPMC3317654 | biostudies-literature