Mathematical Modeling of Tuberculosis Granuloma Activation

Comparative pathogenicity of Nocardia seriolae in Nile tilapia (Oreochromis niloticus), milkfish (Chanos chanos) and Asian seabass (Lates calcarifer)

Nocardiosis, caused by Nocardia seriolae, has been a prominent disease in Southeast Asian aquaculture in the last three decades. This granulomatous disease reported in various fish species is responsible for significant economic losses. This study investigated the pathogenicity of N. seriolae in three cultured species in Taiwan: Nile tilapia (omnivore), milkfish (herbivore) and Asian seabass (carnivore). Administration of an infective dose of 1 × 106 CFU/ fish in tilapia, seabass and milkfish demonstrated mortalities of 100%, 90% and 75%, respectively. Additionally, clinical signs namely, granuloma and lesions displayed varying intensities between the groups and pathological scores. Polymerase chain reaction (PCR) amplification specific for N. seriolae was confirmed to be positive (432 bp) using NS1/NG1 primers. Post-mortem lesions revealed the absence of granulomas in tilapia and milkfish and their presence in the seabass. Interestingly, the gut in tilapia showed an influx of eosinophils suggesting its role during the acute stages of infection. However, post-challenge, surviving milkfish exhibited granulomatous formations, while surviving seabass progressed toward healing and tissue repair within sampled tissues. Overall, in conclusion, these results demonstrate the versatility in the immunological ability of individual Perciformes to contain this pathogen as a crucial factor that influences its degree of susceptibility.

A novel nonlocal partial differential equation model of endothelial progenitor cell cluster formation during the early stages of vasculogenesis

The formation of new vascular networks is essential for tissue development and regeneration, in addition to playing a key role in pathological settings such as ischemia and tumour development. Experimental findings in the past two decades have led to the identification of a new mechanism of neovascularisation, known as cluster-based vasculogenesis, during which endothelial progenitor cells (EPCs) mobilised from the bone marrow are capable of bridging distant vascular beds in a variety of hypoxic settings in vivo. This process is characterised by the formation of EPC clusters during its early stages and, while much progress has been made in identifying various mechanisms underlying cluster formation, we are still far from a comprehensive description of such spatio-temporal dynamics. In order to achieve this, we propose a novel mathematical model of the early stages of cluster-based vasculogenesis, comprising of a system of nonlocal partial differential equations including key mechanisms such as endogenous chemotaxis, matrix degradation, cell proliferation and cell-to-cell adhesion. We conduct a linear stability analysis on the system and solve the equations numerically. We then conduct a parametric analysis of the numerical solutions of the one-dimensional problem to investigate the role of underlying dynamics on the speed of cluster formation and the size of clusters, measured via appropriate metrics for the cluster width and compactness. We verify the key results of the parametric analysis with simulations of the two-dimensional problem. Our results, which qualitatively compare with data from in vitro experiments, elucidate the complementary role played by endogenous chemotaxis and matrix degradation in the formation of clusters, suggesting chemotaxis is responsible for the cluster topology while matrix degradation is responsible for the speed of cluster formation. Our results also indicate that the nonlocal cell-to-cell adhesion term in our model, even though it initially causes cells to aggregate, is not sufficient to ensure clusters are stable over long time periods. Consequently, new modelling strategies for cell-to-cell adhesion are required to stabilise in silico clusters. We end the paper with a thorough discussion of promising, fruitful future modelling and experimental research perspectives.

Multiscale modeling in disease

Multiscale computational modeling aims to connect the complex networks of effects at different length and/or time scales. For example, these networks often include intracellular molecular signaling, crosstalk, and other interactions between neighboring cell populations, and higher levels of emergent phenomena across different regions of tissues and among collections of tissues or organs interacting with each other in the whole body. Recent applications of multiscale modeling across intracellular, cellular, and/or tissue levels are highlighted here. These models incorporated the roles of biochemical and biomechanical modulation in processes that are implicated in the mechanisms of several diseases including fibrosis, joint and bone diseases, respiratory infectious diseases, and cancers.

Special Issue on “Biological Networks”

Networks of coordinated interactions among biological entities govern a myriad of biological functions that span a wide range of both length and time scales—from ecosystems to individual cells, and from years (e.g., the life cycle of periodical cicadas) to milliseconds (e.g., allosteric enzymeregulation[...]