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Prominent fluctuations, heterogeneity, and cooperativity dominate the dynamics of the cytoskeleton as well as the dynamics of the cellular collective. Such systems are out of equilibrium, disordered, and remain poorly understood. To explain these findings, here we consider a unifying mechanistic rubric that imagines these systems as comprising phases of soft condensed matter in proximity to a glass or jamming transition, with associated transitions between solid-like versus liquid-like phases. At the scale of the cytoskeleton, data suggest that intermittent dynamics, kinetic arrest and dynamic heterogeneity represent meso-scale features of glassy protein-protein interactions that link underlying biochemical events to integrative cellular behaviors such as crawling, contraction, and remodeling. At the scale of the multicellular collective, jamming has the potential to unify diverse biological factors that previously had been considered mostly as acting separately and independently. Although a quantitative relationship between intra- and intercellular dynamics is still lacking, glassy dynamics and jamming offer insights linking the mechanobiology of cell to human physiology and pathophysiology.

To investigate the effects of Trypanosoma cruzi on the mechanical properties of infected host cells, cytoskeletal stiffness and remodeling dynamics were measured in parasite-infected fibroblasts. We find that cell stiffness decreases in a time-dependent fashion in T. cruzi-infected human foreskin fibroblasts without a significant change in the dynamics of cytoskeletal remodeling. In contrast, cells exposed to T. cruzi secreted/released components become significantly stiffer within two hours of exposure and exhibit increased remodeling dynamics. These findings represent the first direct mechanical data to suggest a physical picture in which an intact, stiff, and rapidly remodeling cytoskeleton facilitates early stages of T. cruzi invasion and parasite retention, followed by subsequent softening and disassembly of the cytoskeleton to accommodate intracellular replication of parasites. We further suggest that these changes occur through protein kinase A and inhibition of the Rho/Rho kinase signaling pathway. In the context of tissue infection, changes in host cell mechanics could adversely affect the function of the infected organs, and may play an important role on the pathophysiology of Chagas' disease.

Acoustic rhinometry (AR) evaluates the geometry of the nasal cavity with acoustic reflections and provides information about nasal cross-sectional areas (CSA) and nasal volume within a given distance. The accuracy of the information obtained by AR was compared with that of magnetic resonance imaging (MRI) of the nasal cavity. Five healthy subjects were evaluated with AR and the MRI before and after the application of a long-acting nasal decongestant spray, to eliminate possible interference of the nasal cycle with both measurement techniques. The MRI images of 2 mm coronal sections of the nasal cavity were traced by three independent observers and the CSAs were calculated by computer-aided imaging digitization, to be compared with the calculated CSAs obtained with the AR at the corresponding distance from the nasal tip. Digitized data from the MRI images were also used to calculate the nasal volume within the first 6 cm from the nasal tip and compared with the AR volume measurements. The interobserver variation of digitized MRI data predecongestant and postdecongestant was not significant. The correlations of CSA and volume measurements between the AR and MRI were high (0.969) after the application of the decongestant. The correlation between the AR and MRI measurements before the decongestant was low (0.345). This may have been the result of interference of the nasal cycle during the long MRI measurements (1 hour) or other unknown factors. We conclude that AR measurements of nasal CSAs and volumes provide accurate information when compared with the MRI of the decongested nasal airway. (Otolaryngol Head Neck Surg 1997;117:349-54.)

The sections in this article are: 1 Modeling the Respiratory System as a Linear System 1.1 Models 1.2 Elemental Equations 1.3 Sinusoidal Forcing and Complex Impedance 1.4 Continuity and Compatibility Conditions 1.5 General Formulation of System Models 1.6 System Functions 1.7 Equivalent Circuits 1.8 Distributed-Parameter Models 2 History 3 Experimental Methods 3.1 Equipment 3.2 Inputs and Data Processing 3.3 Upper Airway Variability and Shunt 4 Frequency Responses Below 100 HZ 4.1 Total Respiratory System 4.2 Input Impedance Forcing at the Airway Opening 4.3 Transfer Impedance Forcing at the Chest 4.4 Transfer Impedance Forcing at the Mouth 4.5 Pressure and Flow Transfer Functions 4.6 Lung Impedance 4.7 Chest Wall Impedance 4.8 Airway Impedance 5 Frequency Responses Above 100 HZ 5.1 Wave Propagation in the Airways 5.2 Input Impedance Forcing at the Airway Opening 5.3 Pressure Transfer Functions 5.4 Airway Area by Acoustic Reflections 6 Clinical Applications 6.1 Pulmonary Function in Children 6.2 Obstructive Lung Diseases 6.3 Restrictive Lung Diseases 6.4 Miscellaneous Lung Diseases