Extracellular matrix modulates T cell clearance of malignant cells in vitro
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
SEARCH · Search NASA
Results for “collagen”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
On the regeneration of fish scales: structure and mechanical behavior
Fish scales serve as a dermal armor that provides protection from physical injury. Owing to a number of outstanding properties, fish scales are inspiring new concepts for layered engineered materials and next-generation flexible armors. Although past efforts have primarily focused on the structure and mechanical behavior of ontogenetic scales, the structure–property relationships of regenerated scales have received limited attention. In the present study, common carp ( Cyprinus carpio ) acquired from the wild were held live in an aquatic laboratory at 10°C and 20°C. Ontogenetic scales were extracted from the fish for analysis, as well as regenerated scales after approximately 1 year of development and growth. Their microstructure was characterized using microscopy and Raman spectroscopy, and the mechanical properties were evaluated in uniaxial tension to failure under hydrated conditions. We note the strength, strain to fracture and toughness of the regenerated scales were significantly lower than those of ontogenetic scales from the same fish, regardless of the water temperature. Scales that regenerated at 20°C exhibited significantly higher strength, strain to fracture and toughness than those regenerated at 10°C. The regenerated scales exhibited a highly mineralized outer layer, but no distinct limiting layer or external elasmodine; they also possessed a significantly lower number of plies in the basal layer than the ontogenetic scales. The results suggest that a mineralized layer develops preferentially during scale regeneration with the topology needed for protection, prior to the development of other qualities.
59 BASIC BIOLOGICAL SCIENCES↗
Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array
While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo , functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a “bottom-up” 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.
3D culture↗