The fusion of physics and biology in early mammalian embryogenesis.

Biomechanics in embryogenesis is a dynamic field intertwining the physical forces and biological processes that shape the first days of a mammalian embryo. From the first cell fate bifurcation during blastulation to the complex symmetry breaking and tissue remodeling in gastrulation, mechanical cues appear critical in cell fate decisions and tissue patterning. Recent strides in mouse and human embryo culture, stem cell modeling of mammalian embryos, and biomaterial design have shed light on the role of cellular forces, cell polarization, and the extracellular matrix in influencing cell differentiation and morphogenesis. This chapter highlights the essential functions of biophysical mechanisms in blastocyst formation, embryo implantation, and early gastrulation where the interplay between the cytoskeleton and extracellular matrix stiffness orchestrates the intricacies of embryogenesis and placenta specification. The advancement of in vitro models like blastoids, gastruloids, and other types of embryoids, has begun to faithfully recapitulate human development stages, offering new avenues for exploring the biophysical underpinnings of early development. The integration of synthetic biology and advanced biomaterials is enhancing the precision with which we can mimic and study these processes. Looking ahead, we emphasize the potential of CRISPR-mediated genomic perturbations coupled with live imaging to uncover new mechanosensitive pathways and the application of engineered biomaterials to fine-tune the mechanical conditions conducive to embryonic development. This synthesis not only bridges the gap between experimental models and in vivo conditions to advancing fundamental developmental biology of mammalian embryogenesis, but also sets the stage for leveraging biomechanical insights to inform regenerative medicine.

A Mathematical Model of the Dynamics of Cytokine Expression and Human Immune Cell Activation in Response to the Pathogen Staphylococcus aureus.

Cell-based mathematical models have previously been developed to simulate the immune system in response to pathogens. Mathematical modeling papers which study the human immune response to pathogens have predicted concentrations of a variety of cells, including activated and resting macrophages, plasma cells, and antibodies. This study aims to create a comprehensive mathematical model that can predict cytokine levels in response to a gram-positive bacterium, S. aureus by coupling previous models. To accomplish this, the cytokines Tumor Necrosis Factor Alpha (TNF-α), Interleukin 6 (IL-6), Interleukin 8 (IL-8), and Interleukin 10 (IL-10) are included to quantify the relationship between cytokine release from macrophages and the concentration of the pathogen, S. aureus, ex vivo. Partial differential equations (PDEs) are used to model cellular response and ordinary differential equations (ODEs) are used to model cytokine response, and interactions between both components produce a more robust and more complete systems-level understanding of immune activation. In the coupled cellular and cytokine model outlined in this paper, a low concentration of S. aureus is used to stimulate the measured cellular response and cytokine expression. Results show that our cellular activation and cytokine expression model characterizing septic conditions can predict ex vivo mechanisms in response to gram-negative and gram-positive bacteria. Our simulations provide new insights into how the human immune system responds to infections from different pathogens. Novel applications of these insights help in the development of more powerful tools and protocols in infection biology.