Santiago D. Solares

Vesicle-cloaked virus clusters, or viral vesicles, represent an emerging pathogenic form of enteric viruses, exhibiting enhanced infectivity, environmental persistence, and resistance to disinfection compared to free viruses. Their unique vesicle architecture and mechanical properties likely play a critical role in maintaining structural integrity and shielding encapsulated virions from environmental stressors. Here, we employed atomic force microscopy to characterize the topography and viscoelasticity of viral vesicles from cell cultures, clinical stool, and municipal wastewater. When immobilized on a substrate, the vesicle height remained relatively consistent across origins, whereas the lateral size varied substantially. Viscoelastic properties, characterized by short-term stiffness, long-term stiffness, and dissipation coefficient, were comparable among norovirus, rotavirus, and coxsackievirus B3 vesicles derived from diverse host cells but differed significantly in vesicles isolated from stool and raw wastewater. These differences likely arise from interactions between environmental constituents and conditions in these matrices and the vesicle membranes. A clear decline in vesicle viscoelasticity was also observed during the wastewater treatment process. In summary, these results indicate that viral vesicle viscoelasticity is not a fixed intrinsic property but is strongly influenced by environmental conditions, with complex matrices reshaping the mechanical behavior, persistence, and associated environmental risks.

Material property viscoelastic inversion studies often rely on the continuous -time framework for Fourier analysis, which may not accurately represent real experimentally collected data. In this paper, we address the discrete and finite nature of viscoelastic functions obtained from experiments and discuss the impact of these characteristics on the frequency spectrum analysis. We derive equations for the Discrete-Time Fourier Transform (DTFT) of a discrete-finite stress relaxation signal corresponding to the relaxation of a generalized Maxwell model. Our analysis highlights the limitations of the traditional continuous -time framework in capturing the inherent features of real signals, which are discrete and finite in nature. This results in two phenomena: aliasing and spectral leakage. We present equations that consider these phenomena, allowing experimentalists to anticipate and account for aliasing and leakage when performing model fitting. The proposed discrete-finite approach provides a more accurate representation of real viscoelastic data, enabling researchers to make better-informed decisions in the analysis and interpretation of sample viscoelastic functions.

The paper presents an enhanced version of an arc electron source designed for air ionization applications in a self-neutralizing air-breathing plasma thruster. The arc electron source is specifically suited for the air-breathing plasma thruster, as it allows precise control of mean electron energy levels. This paper focuses on the ionization aspects of air-breathing thrusters through the development of axially magnetized arc electron sources. The sources consist of a circular and coaxial configuration of a metallic arc plasma source coupled with a positively biased grid to extract electrons and control mean electron energy. The average mean electron energy of electrons in the arc electron source is regulated by adjusting the bias voltage of the grid within the range of 0 V – 300 V. To investigate the behavior of ion current density and electron density concerning pressure and mean electron energy, the current probe and magnetic filter were utilized. It was demonstrated that the circular electron source leads to enhanced ionization of airflow by achieving plasma densities greater than 10¹⁸ m⁻³. By utilizing a high-speed camera for the circular arc electron source, the arc spot was seen to move azimuthally due to the magnetic field. Furthermore, scanning electron microscopy and a conductance measurement system were employed for the coaxial arc electron source to examine the deposition and conductance of the electron extraction grid. While the grid underwent deposition of about 600 microns, the conductance was observed to increase/saturate with time and bias voltage, indicating an electrically “self-healing material”.

Atomic force microscopy (AFM), developed in the early 1980s, has become a powerful characterization tool in micro- and nanoscale science. In the early 1990s, its relevance within biology and medicine research became evident, although its incorporation into healthcare applications remains relatively limited. Here, we briefly explore the reasons for this low level of technological adoption. We also propose a path forward for the incorporation of frequency-dependent nanomechanical measurements into integrated healthcare strategies that link routine AFM measurements with computer analysis, real-time communication with healthcare providers, and medical databases. This approach would be appropriate for diseases such as cancer, lupus, arteriosclerosis and arthritis, among others, which bring about significant mechanical changes in the affected tissues.

The range of observable time-dependent mechanical behavior in AFM FD experiments is limited by sampling frequency 1/Δtand duration of the experimentt_f. One should choose parameters that encompass both the minimum and maximum material relaxation times.

Force–distance curve experiments are commonly performed in atomic force microscopy (AFM) to obtain the viscoelastic characteristics of materials, such as the storage and loss moduli or compliances. The classic methods used to obtain these characteristics consist of fitting a viscoelastic material model to the experimentally obtained AFM data. Here, we demonstrate a new method that utilizes the modified discrete Fourier transform to approximate the storage and loss behavior of a material directly from the data, without the need for a fit. Additionally, one may still fit a model to the resulting storage and loss behavior if a parameterized description of the material is desired. In contrast to fitting the data to a model chosen a priori, departing from a model-free description of the material's frequency behavior guides the selection of the model, such that the user may choose the one that is most appropriate for the particular material under study. To this end, we also include modified Fourier domain descriptions of commonly used viscoelastic models.

Countless biophysical studies have sought distinct markers in the cellular mechanical response that could be linked to morphogenesis, homeostasis, and disease. Here, an iterative-fitting methodology visualizes the time-dependent viscoelastic behavior of human skin cells under physiologically relevant conditions. Past investigations often involved parameterizing elastic relationships and assuming purely Hertzian contact mechanics, which fails to properly account for the rich temporal information available. We demonstrate the performance superiority of the proposed iterative viscoelastic characterization method over standard open-search approaches. Our viscoelastic measurements revealed that 2D adherent metastatic melanoma cells exhibit reduced elasticity compared to their normal counterparts—melanocytes and fibroblasts, and are significantly less viscous than fibroblasts over timescales spanning three orders of magnitude. The measured loss angle indicates clear differential viscoelastic responses across multiple timescales between the measured cells. This method provides insight into the complex viscoelastic behavior of metastatic melanoma cells relevant to better understanding cancer metastasis and aggression.

Viscoelastic characterization of materials at the micro- and the nanoscale is commonly performed with the aid of force–distance relationships acquired using atomic force microscopy (AFM). The general strategy for existing methods is to fit the observed material behavior to specific viscoelastic models, such as generalized viscoelastic models or power-law rheology models, among others. Here we propose a new method to invert and obtain the viscoelastic properties of a material through the use of the Z-transform, without using a model. We present the rheological viscoelastic relations in their classical derivation and their z-domain correspondence. We illustrate the proposed technique on a model experiment involving a traditional ramp-shaped force–distance AFM curve, demonstrating good agreement between the viscoelastic characteristics extracted from the simulated experiment and the theoretical expectations. We also provide a path for calculating standard viscoelastic responses from the extracted material characteristics. The new technique based on the Z-transform is complementary to previous model-based viscoelastic analyses and can be advantageous with respect to Fourier techniques due to its generality. Additionally, it can handle the unbounded inputs traditionally used to acquire force–distance relationships in AFM, such as ramp functions, in which the cantilever position is displaced linearly with time for a finite period of time.

Countless biophysical studies have sought distinct markers in the cellular mechanical response that could be linked to morphogenesis, homeostasis, and disease. Here, a novel iterative-fitting methodology is used to investigate the viscoelastic behavior at multiple relaxation times of human skin cells under physiologically relevant conditions. Past investigations often involved parameterizing linear elastic relationships and assuming purely Hertzian contact mechanics. However, linear elastic treatment fails to capture and properly account for the rich temporal information available in datasets. We demonstrate the performance superiority of the proposed iterative viscoelastic characterization method over standard open-search approaches. Our viscoelastic measurements revealed that 2D adherent metastatic melanoma cells exhibit reduced elasticity compared to normal counterparts—melanocytes and fibroblasts, whereas are significantly less viscous than only fibroblasts over timescales spanning three orders of magnitude. Interestingly, melanocytes are stiffer than melanoma cells, while being the less viscous cells measured. The measured loss angle indicates clear differential viscoelastic responses across multiple timescales between the measured cells. We propose the use of viscoelastic properties at multiple timescales as a mechanical biomarker of diseases. Altogether, this method provides new insight into the complex viscoelastic behavior of metastatic melanoma cells relevant to better understanding cancer metastasis aggression.