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Biology subjects

Savvidou, M.

Publications and source records attributed to Savvidou, M..

2 recordsLinked to original sources

Progressive matrix stiffening of tyramine-modified silk fibroin hydrogels governs stage-specific pulmonary fibroblast activation

Fibrosis is a progressive and often fatal pathological process characterized by excessive extracellular matrix deposition, tissue stiffening, and irreversible organ dysfunction. Effective antifibrotic therapies remain limited by the lack of in vitro models that recapitulate the full spectrum of fibrotic disease progression. Here, we leverage tyramine-modified silk fibroin (SF-TA) hydrogels to investigate normal human lung fibroblasts (NHLF) responses to progressively stiffening environments relevant to pulmonary fibrosis. Two hydrogel formulations with distinct stiffening profiles over 14 days were prepared: a gradual-stiffening 0% SF-TA formulation reaching [~]20 kPa, and a rapidly stiffening 50% SF-TA formulation reaching [~]60 kPa. NHLFs were cultured on both formulations, with and without TGF{beta} (5 ng/mL), for 14 days and assessed for viability, metabolic activity, cytokine and collagen secretion, cytoskeletal organization, and mechanotransductive gene expression. The 0% SF-TA hydrogels drove sustained fibroblast proliferation and elevated secretion of IL-6, IL-8, and MCP-1, consistent with early inflammatory fibrosis. The 50% SF-TA hydrogels induced a metabolic plateau without senescence, suppressed inflammatory cytokine secretion, and, in the presence of TGF{beta}, led to significant upregulation of ACTA2 and CTGF, alongside -SMA stress fiber incorporation, consistent with established myofibroblast persistence. Both conditions produced comparable secreted collagen output by day 14. Together, these findings establish dynamically stiffening SF-TA hydrogels as a tunable platform for investigating stage-dependent fibroblast activation and mechanobiological progression in fibrosis.

bioengineering↗

Multi-modal, Label-free, Optical Mapping of Cellular Metabolic Function and Oxidative Stress in 3D Engineered Brain Tissue Models

Brain metabolism is essential for the function of organisms. While established imaging methods provide valuable insights into brain metabolic function, they lack the resolution to capture important metabolic interactions and heterogeneity at the cellular level. Label-free, two-photon excited fluorescence imaging addresses this issue by enabling dynamic metabolic assessments at the single-cell level without manipulations. In this study, we demonstrate the impact of spectral imaging on the development of rigorous intensity and lifetime label-free imaging protocols to assess dynamically metabolic functions over time in 3D engineered brain tissue models comprised of human induced neural stem cells, astrocytes, and microglia. Specifically, we rely on multi-wavelength spectral imaging to identify the excitation/emission profiles of key cellular fluorophores within human brain cells, including NAD(P)H, LipDH, FAD, and lipofuscin. These enable the development of methods to mitigate lipofuscins overlap with NAD(P)H and flavin autofluorescence to extract reliable optical metabolic function metrics from images acquired at two excitation wavelengths over two emission bands. We present fluorescence intensity and lifetime metrics reporting on redox state, mitochondrial fragmentation, and NAD(P)H binding status in neuronal monoculture and the triculture systems to highlight the functional impact of metabolic interactions between different cell types. Our findings reveal significant metabolic differences between neurons and glial cells, shedding light on metabolic pathway utilization, including the glutathione pathway, OXPHOS, glycolysis, and fatty acid oxidation. Collectively, our studies establish a label-free, non-destructive approach to assess the metabolic function and interactions among different brain cell types relying on endogenous fluorescence and illustrate the complementary nature of the information that is gained by combining intensity and lifetime-based images. Such methods can improve understanding of physiological brain function and dysfunction that occurs at the onset of cancers, traumatic injuries and neurodegenerative diseases.

bioengineering↗