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Sanaei, P.

Publications and source records attributed to Sanaei, P..

2 recordsLinked to original sources

Modeling mucociliary mixing and transport at tissue scale

Mucociliary clearance is the primary defense mechanism in our respiratory system against aerosol pathogens and allergens. The rhythmic movement of cilia on airway-lining cells propels mucus flow, driving the movement of trapped particles. We want harmful particles, e.g., pathogens and allergens to be transported rapidly out of the airway and beneficial particles, e.g. vaccines and medicine, to stay and disperse. However, the impact of cilia density and distribution on mucociliary mixing and transport at the tissue scale remains poorly understood. We present three-dimensional (3D) simulations of mucociliary mixing and transport at the tissue scale. We investigate the influence of ciliary cluster spacing, metachronal wave, and ciliary density on mucus mixing and transport. Our findings reveal that: (i) cilia clusters produce swirls of mucus flow, their size scales with ciliary density; (ii) a single cilia cluster generates horizontal and upward transport with horizontal mixing; (iii) for three aligned cilia clusters, an optimal cluster spacing exists for achieving maximum horizontal transport; (iv) asynchronous beating among clusters enhances mixing but hinders transport; and (v) the diffusion of particles exhibits spatial inhomogeneity, leading to particle aggregation into discrete groups over time. These discoveries have implications for understanding particle distributions in the airway and contribute to drug delivery design considerations. Author summaryOur airways are exposed to various foreign particles, including allergens, pathogens, and aerosolized vaccines or medications. The mucus coating the airway surface traps these particles, and the beating cilia extending from the ciliated epithelial cells play a crucial role in propelling the flow of mucus to transport the particles out of the airway. This mucociliary clearance process is closely associated with the initiation and progression of airway tissue response, such as allergic responses, infections, and treatment effects. Changes in ciliated cell density or mucus production can significantly impact this process. Conversely, achieving a homogeneous distribution of aerosol drug particles within the airway is essential for optimizing treatment outcomes. We simulate cilia-mucus coupled flow to examine how the motion of cilia influences the transport and mixing of particles in the mucus. Our key findings suggest that an optimal spacing for ciliated cell clusters that enhances directional transport. Intriguingly, while the metachronal wave promotes mixing, it also tends to hinder the overall transport of particles.

systems biology↗

Dynamic Entrainment: A deep learning and data-driven process approach for synchronization in the Hodgkin-Huxley model

Resonance and synchronized rhythm are important phenomena and can be either constructive or destructive in dynamical systems in the nature, specifically in biology. There are many examples showing that the humans body organs must maintain their rhythm in order to function properly. For instance, in the brain, synchronized or desynchronized electrical activities can lead to neurodegenerative disorders such as Huntingtons disease. In this paper, we adopt a well known conductance based neuronal model known as Hodgkin-Huxley model describing the propagation of action potentials in neurons. Armed with the "data-driven" process alongside the outputs of the Hodgkin-Huxley model, we introduce a novel Dynamic Entrainment technique, which is able to maintain the system to be in its entrainment regime dynamically by applying deep learning approaches.

neuroscience↗