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Biomolecular adsorption has great significance in medical, environmental, and technological processes. Understanding adsorption equilibrium and binding kinetics is essential for advanced process implementation. This requires identifying intrinsic determinants that predict optimal adsorption properties at bio–hybrid interfaces. Solid-binding peptides (SBPs) have targetable intrinsic properties involving peptide–peptide and peptide–solid interactions, which result in high-affinity material-selective binding. Atomic force microscopy investigations confirmed this complex interplay of multi-step peptide assemblies in a cooperative modus. Yet, most studies report adsorption properties of SBPs using non-cooperative or single-step adsorption models. Using non-cooperative kinetic models for predicting cooperative self-assembly behavior creates an oversimplified view of peptide adsorption, restricting implementing SBPs beyond their current use. To address these limitations and provide insight into surface-level events during self-assembly, a novel method, the Frequency Response Cooperativity model, was developed. This model iteratively fits adsorption data through spectral analysis of several time-dependent kinetic parameters. The model, applied to a widely used gold-binding peptide data obtained using a quartz crystal microbalance with dissipation, verified multi-step assembly. Peak deconvolution of spectral plots revealed distinct differences in the size and distribution of the kinetic rates present during adsorption across the concentrations. This approach provides new fundamental insights into the intricate dynamics of self-assembly of biomolecules on surfaces. 

Diabetes is one of the leading causes of death globally. Currently, the donor pancreas is the only source of human islets, placing extreme constraints on supply. Hence, it is imperative to develop renewable islets for diabetes research and treatment. To date, extensive efforts have been made to derive insulin-secreting cells from human pluripotent stem cells with substantial success. However, the in vitro generation of functional islet organoids remains a challenge due in part to our poor understanding of the signaling molecules indispensable for controlling differentiation pathways towards the self-assembly of functional islets from stem cells. Since this process relies on a variety of signaling molecules to guide the differentiation pathways, as well as the culture microenvironments that mimic in vivo physiological conditions, this review highlights extracellular matrix proteins, growth factors, signaling molecules, and microenvironments facilitating the generation of biologically functional pancreatic endocrine cells from human pluripotent stem cells. Signaling pathways involved in stepwise differentiation that guide the progression of stem cells into the endocrine lineage are also discussed. The development of protocols enabling the generation of islet organoids with hormone release capacities equivalent to native adult islets for clinical applications, disease modeling, and diabetes research are anticipated.