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The field of wireless communication has witnessed tremendous advancements in the past few decades, leading to more pervasive and ubiquitous networks. Human bodies are continually exposed to electromagnetic radiation, but typically this does not impact the body as the radiation is non-ionizing and the waves carry low power. However, with progress in the sixth generation (6G) of wireless networks and the adoption of the spectrum above 100 GHz in the next few years, higher power radiation is needed to cover larger areas, exposing humans to stronger and more prolonged radiation. Also, water has a high absorption coefficient at these frequencies and could lead to thermal effects on the skin. Hence, there is a need to study the radiation effects on human tissues, specifically the photothermal effects. In this paper, we present a custom-built, multi-physics model to investigate electromagnetic wave propagation in human tissue and study its subsequent photothermal effects. The proposed finite-element model consists of two segments—the first one estimates the intensity distribution along the beam path, while the second calculates the increase in temperature due to the wave distribution inside the tissue. We determine the intensity variation in the tissue using the radiative transfer equation and compare the results with Monte Carlo analysis and existing analytical models. The intensity information is then utilized to predict the rise in temperature with a bio-heat transfer module, powered by Pennes’ bioheat equation. The model is parametric, and we perform a systematic photothermal analysis to recognize the crucial variables responsible for the temperature growth inside the tissue, particularly for terahertz and near-infrared optical frequencies. Our numerical model can serve as a benchmark for studying the high-frequency radiation effects on complex heterogeneous media such as human tissue.

In this work, we report a numerical flow-focused study of bead magnetophoresis inside a continuous-flow microchannel in order to provide a detailed analysis of bead motion and its effect on fluid flow. The numerical model involves a Lagrangian approach and predicts the bead separation from blood and their collection into a flowing buffer by the application of a magnetic field generated by a permanent magnet. The following scenarios are modelled: (i) one-way coupling wherein momentum is transferred from the fluid to beads, which are treated as point particles, (ii) two-way coupling wherein the beads are treated as point particles and momentum is transferred from the bead to the fluid and vice versa, and (iii) two-way coupling taking into account the effects of bead volume in fluid displacement. The results indicate that although there is little difference in the bead trajectories for the three scenarios, there is significant variation in the flow fields, especially when high magnetic forces are applied on the beads. Therefore, an accurate full flow-focused model that takes into account the effects of the bead motion and volume on the flow field should be solved when high magnetic forces are employed. Nonetheless, when the beads are subjected to medium or low magnetic forces, computationally inexpensive models can be safely employed to model magnetophoresis.

Microglia are immune cells, which densely populate the central nervous system (CNS), and play essential role in suppression of neurodegenerative diseases, clearance of debris after CNS trauma, as well as serve as the last line of immune defense in response to any potential threat by being activated to eliminate diverse pathogens ranging from bacteria to cancer. The activated microglia cells are commonly used as a diagnostic biomarker of diverse brain conditions, however detection and classification of microglia activated phenotypes is a cumbersome and imprecise procedure. Here, we report on development of optical assay for detection and quantitative analysis of activated microglia. In this study, we investigated overall changes in the metabolism of microglia cells during their activation by monitoring the signal from cellular proteins and lipids using label‐free coherent anti‐Stokes Raman scattering imaging. Our data demonstrate that the activation of microglia in the presence of bacterial liposaccharide is accompanied by intense upregulation of synthesis of proteins and lipids. We further propose that elevated intracellular content of these types of macromolecules can serve as early supplementary marker for identification of active microglia cells in the brain samples by Raman imaging techniques.