Influence of ECM Composition and Intracellular Calcium on Endothelial Biomechanics and Prediction of Cellular Stresses Using Machine Learning

Endothelial cells, which form the inner layer of the vasculature, constantly interact with their external microenvironment called the extracellular matrix (ECM) by exerting contractile cell-substrate stresses called tractions and cell-cell stresses called intercellular stresses. This cellular mechanosensing can become aberrant and act as a precursor for many vascular pathological and physiological processes such as cancer metastasis, atherosclerosis, cell differentiation, migration, and morphogenesis. Also, intracellular calcium signalling plays an important role in endothelial cell motility and in maintaining vascular tone. Alteration in ECM composition has been linked to several pathologies, in fact, a transition to a fibronectin-rich matrix from a type I collagen-rich and elastin-rich matrix in coronary artery disease, for example. However, the influence of ECM compositions and intracellular calcium levels on cell mechanics is not clearly understood. The first study will shed light on ECM composition and its influence on endothelial mechanical properties including traction, intercellular stresses, cell velocity, and various morphological parameters. The second study will enhance our knowledge on the role calcium signaling plays on cellular tractions. The final chapters will focus on the development and utilization of Machine Learning (ML) models for the predictions of tractions and intercellular stresses with morphological and pharmacological predictors, which to our knowledge is the first work in the field. The results yielded from this work will further our understanding of cellular mechanics at the mesoscale by: i) Identifying the role of specific ECM molecules in mechanical signaling, ii) Understanding the influence of transient calcium signaling on tractions, and iii) Providing a machine learning framework that can be used for the prediction of tractions and intercellular stresses as a dose dependent response to a drug that is known to influence cell mechanics. These findings will be beneficial to drug development studies and targeted drug therapy for treating various vascular-related pathologies

Rice endophytes and their potential applications

Endophytic microbial communities in crop plants are beginning to be explored. These microbes are either carried through seeds or establish colonization in the plants from soil based on chemotaxis of root exudates. Variability and diversity of endophytic bacteria and fungi have been observed in rice plants in different plant parts and growth stages. Genotypic variations are observed between Indica and Japonica. Pseudomonas, Bacillus, Streptomyces, Azospirillum, Azotobacter are some of the dominating genera of bacteria in internal tissues of rice plants. These endophytes provide benefits such as tolerance to abiotic stresses, defense against pest and diseases, nutrient solubilization and mobility. In addition, many metabolites are characterized from the endophytes that are useful in other branches of biotechnology including bioremediation. Complete characterization of microbiome of rice plants under various soil agro-climatic zones and understanding their population dynamics, co-occurrence and networking will help in identifying useful strains for developing new biofertilizers, plant growth promoting microbes and biopesticides

A model-based rear-end collision avoidance algorithm for heavy commercial road vehicles

Abstract A rear-end collision is one of the most frequent accidents occurring on roadways. In this paper, a model-based longitudinal collision avoidance algorithm is developed for heavy commercial road vehicles to avoid rear-end collisions. This paper focuses on the inclusion of the dynamics of the pneumatic brake system in the collision avoidance algorithm. The developed algorithm also considers the dynamic behaviour of the heavy vehicle during braking such as the dynamic load transfer, the dynamic brake force distribution between the wheels and the maximum traction available at the tyre-road interface. The pressure transients in the brake chamber are modelled as a linear first-order dynamic system with a time delay. Commercially available vehicle dynamic simulation software, TruckSim, is used for simulating the developed control algorithm for realistic traffic scenarios with different loading and road conditions. The results obtained from the simulations are compared with the experimental results obtained from a hardware-in-the-loop system and the simulation results are found to be promising

IL-4 Induces Metallothionein 3- and SLC30A4-Dependent Increase in Intracellular Zn2+ that Promotes Pathogen Persistence in Macrophages

SummaryAlternative activation of macrophages promotes wound healing but weakens antimicrobial defenses against intracellular pathogens. The mechanisms that suppress macrophage function to create a favorable environment for pathogen growth remain elusive. We show that interleukin (IL)-4 triggers a metallothionein 3 (MT3)- and Zn exporter SLC30A4-dependent increase in the labile Zn2+ stores in macrophages and that intracellular pathogens can exploit this increase in Zn to survive. IL-4 regulates this pathway by shuttling extracellular Zn into macrophages and by activating cathepsins that act on MT3 to release bound Zn. We show that IL-4 can modulate Zn homeostasis in both human monocytes and mice. In vivo, MT3 can repress macrophage function in an M2-polarizing environment to promote pathogen persistence. Thus, MT3 and SLC30A4 dictate the size of the labile Zn2+ pool and promote the survival of a prototypical intracellular pathogen in M2 macrophages