Mathematical modelling and numerical simulations of actin dynamics in the eukaryotic cell

The aim of this article is to study cell deformation and cell movement by considering both the mechanical and biochemical properties of the cortical network of actin filaments and its concentration. Actin is a polymer that can exist either in fil- amentous form (F-actin) or in monometric form (G-actin) (Chen et al. 2000) and the filamentous form is arranged in a paired helix of two protofilaments (Ananthakrish- nan et al. 2006). By assuming that cell deformations are a result of the cortical actin dynamics in the cell cytoskeleton, we consider a continuum mathematical model that couples the mechanics of the network of actin filaments with its bio-chemical dy- namics. Numerical treatment of the model is carried out using the moving grid finite element method (Madzvamuse et al. 2003). Furthermore, by assuming slow deforma- tions of the cell, we use linear stability theory to validate the numerical simulation results close to bifurcation points. Far from bifurcation points, we show that the math- ematical model is able to describe the complex cell deformations typically observed in experimental results. Our numerical results illustrate cell expansion, cell contrac- tion, cell translation and cell relocation as well as cell protrusions. In all these results, the contractile tonicity formed by the association of actin filaments to the myosin II motor proteins is identified as a key bifurcation parameter

Development of a Dynamic Network Model to Identify Temporal Patterns of Structural Malformations in Zebrafish Embryos Exposed to a Model Toxicant, Tris(4-chlorophenyl)methanol

Embryogenesis is a well-coordinated process relying on precise cues and environmental signals that direct spatiotemporal embryonic patterning. Quite often, when one error in this process occurs, others tend to co-occur. We posit that investigating the co-occurrence of these abnormalities over time would yield additional information about the mode of toxicity for chemicals. Here, we use the environmental contaminant tris(4-chlorophenyl)methanol (TCPMOH) as a model toxicant to assess the relationship between exposures and co-occurrence of developmental abnormalities in zebrafish embryos. We propose a dynamic network modeling approach to study the co-occurrence of abnormalities, including pericardial edema, yolk sac edema, cranial malformation, spinal deformity, delayed/failed swim bladder inflation, and mortality induced by TCPMOH exposure. TCPMOH-exposed samples revealed increased abnormality co-occurrence when compared to controls. The abnormalities were represented as nodes in the dynamic network model. Abnormalities with high co-occurrence over time were identified using network centrality scores. We found that the temporal patterns of abnormality co-occurrence varied between exposure groups. In particular, the high TCPMOH exposure group experienced abnormality co-occurrence earlier than the low exposure group. The network model also revealed that pericardial and yolk sac edema are the most common critical nodes among all TCPMOH exposure levels, preceding further abnormalities. Overall, this study introduces a dynamic network model as a tool for assessing developmental toxicology, integrating structural and temporal features with a concentration response

Extraction and Analysis of Respiratory Motion Using a Comprehensive Wearable Health Monitoring System

Respiratory activity is an important vital sign of life that can indicate health status. Diseases such as bronchitis, emphysema, pneumonia and coronavirus cause respiratory disorders that affect the respiratory systems. Typically, the diagnosis of these diseases is facilitated by pulmonary auscultation using a stethoscope. We present a new attempt to develop a lightweight, comprehensive wearable sensor system to monitor respiration using a multi-sensor approach. We employed new wearable sensor technology using a novel integration of acoustics and biopotentials to monitor various vital signs on two volunteers. In this study, a new method to monitor lung function, such as respiration rate and tidal volume, is presented using the multi-sensor approach. Using the new sensor, we obtained lung sound, electrocardiogram (ECG), and electromyogram (EMG) measurements at the external intercostal muscles (EIM) and at the diaphragm during breathing cycles with 500 mL, 625 mL, 750 mL, 875 mL, and 1000 mL tidal volume. The tidal volumes were controlled with a spirometer. The duration of each breathing cycle was 8 s and was timed using a metronome. For each of the different tidal volumes, the EMG data was plotted against time and the area under the curve (AUC) was calculated. The AUC calculated from EMG data obtained at the diaphragm and EIM represent the expansion of the diaphragm and EIM respectively. AUC obtained from EMG data collected at the diaphragm had a lower variance between samples per tidal volume compared to those monitored at the EIM. Using cubic spline interpolation, we built a model for computing tidal volume from EMG data at the diaphragm. Our findings show that the new sensor can be used to measure respiration rate and variations thereof and holds potential to estimate tidal lung volume from EMG measurements obtained from the diaphragm

Spatial Heterogeneity of Excess Lung Fluid in Cystic Fibrosis: Generalized, Localized Diffuse, and Localized Presentations

Magnetic resonance (MR) imaging has demonstrated that CF subjects have a significantly higher lung density (e.g., fluid content) when compared with healthy control subjects, but, at present, there are no techniques to quantify the spatial presentation of these lung abnormalities. The excess fluid in MR lung images for CF subjects with mild (n = 4), moderate (n = 5), and severe (n = 4) disease and age- and sex-matched healthy controls (n = 13) in both the right and left lungs was identified and quantified using a thresholding-based image segmentation technique using healthy controls as a baseline. MR lung images were categorized into one of three spatial presentation groups based on their regional and global percent area of the lung covered by excess fluid (i.e., spatial distribution): (i) generalized for sparse, (ii) localized diffuse for a moderate focality, and (iii) localized for a strong focality. A total of 96% of the controls presented as generalized. CF subjects populated all three presentation groups and an individual’s right and left lungs did not always categorize identically. The developed metrics for categorization provide a quantification method to describe the spatial presentation of CF disease and suggests the heterogeneous nature of the disease

Spatial Heterogeneity of Excess Lung Fluid in Cystic Fibrosis: Generalized, Localized Diffuse, and Localized Presentations

Magnetic resonance (MR) imaging has demonstrated that CF subjects have a significantly higher lung density (e.g., fluid content) when compared with healthy control subjects, but, at present, there are no techniques to quantify the spatial presentation of these lung abnormalities. The excess fluid in MR lung images for CF subjects with mild (n = 4), moderate (n = 5), and severe (n = 4) disease and age- and sex-matched healthy controls (n = 13) in both the right and left lungs was identified and quantified using a thresholding-based image segmentation technique using healthy controls as a baseline. MR lung images were categorized into one of three spatial presentation groups based on their regional and global percent area of the lung covered by excess fluid (i.e., spatial distribution): (i) generalized for sparse, (ii) localized diffuse for a moderate focality, and (iii) localized for a strong focality. A total of 96% of the controls presented as generalized. CF subjects populated all three presentation groups and an individual’s right and left lungs did not always categorize identically. The developed metrics for categorization provide a quantification method to describe the spatial presentation of CF disease and suggests the heterogeneous nature of the disease