As the use of head-mounted displays (HMDs) becomes increasingly common, concerns about visual fatigue in virtual reality (VR) environments have grown, as HMDs are known to induce greater fatigue than traditional 2D displays. To enable timely mitigation of this issue, it is essential to predict subjective visual fatigue in real time from continuously monitored objective measures. To address this need, we designeda passive HMD-based video-viewing experiment that manipulated motion (high/low) and brightness (high/low) to induce varying levels of visual fatigue and aimed to predict dynamic visual fatigue using eye-tracking data. Fifty-two participants took part in the study, providing continuous and post-task fatigue ratings while their eye movements were recorded as they watched video content in VR. Based on the recorded data, we developed a temporal attention based deep learning model that predicts fatigue 10 s ahead using a 30-second window of eye-related metrics.The proposed BiGRU-Attn model achieved competitive predictive performance—a mean absolute error (1.156), root mean square error (1.253), and two-point ordinal accuracy of 91% under leave-one-subject-out cross-validation–indicating that the predictive signal resides primarily in the eye-tracking features. Moreover, explainable feature importance analysis converged on the number of blinks (NB) as the single most informative ocular signal across zero-order correlation, Integrated Gradients, and feature ablation, with fixation duration (FD) emerging as a supporting contributor through temporal multivariate interactions. These findings demonstrate that eye-tracking data alone can predict dynamic visual fatigue duringpassive HMD-based video viewing and highlight the potential for a real-time fatigue prediction system that can enable timely application of fatigue reduction techniques.
Focused ultrasound (FUS) generates acoustic forces that activate cellular mechanotransduction, including calcium signaling via mechanosensitive ion channels, and modulates nanoparticle behavior through physical and chemical perturbations. These coupled effects have been leveraged to enhance anti-cancer drug delivery and reshape tumor transport dynamics. Integration of FUS with nanodrug systems enables coordinated modulation of vascular permeability, intratumoral distribution, and tumor microenvironment (TME) remodeling. Advanced cancer-on-a-chip platforms provide physiologically relevant in vitro models for systematically evaluating these multiscale interactions under controlled conditions. Together, these elements form an integrated framework linking FUS-induced physicochemical mechanisms to biological responses, nanoparticle behavior, and chip-based evaluation. This review presents the biological and transport-associated roles of FUS in cancer therapy, discusses its integration with nanodrug systems to modulate TME dynamics, and highlights the application of cancer-on-a-chip technologies to assess FUS-mediated transport modulation and nanodrug performance in preclinical settings.
Abstract While much is known about the effects of the chemical microenvironment on cellular metabolism, mechanical cues have emerged as critical stimuli of intracellular metabolic pathways. Mechanical signals from the extracellular matrix (ECM), neighboring cells, and the microenvironment intersect with key regulators of cellular metabolism, often leading to changes in fundamental cell behaviors, including cell proliferation and migration. Here, we review recent work that has uncovered a role for mechanical cues from microenvironmental factors on cellular metabolism. We discuss how cell–ECM interactions and forces such as shear, tension, and compression affect cellular metabolic requirements and energy production. Importantly, mechanometabolism shapes both physiological homeostasis and pathological states, and further investigation has implications for understanding tissue function and disease progression and uncovering potential therapeutic strategies.
We review the key observations and theories relevant to the origin and evolution of the Galilean satellites. Key observations include: the potentially undifferentiated nature of Callisto; the increasing ice fraction with semi-major axis; the present-day existence of the Laplace resonance; the potential resurfacing of Ganymede mid-way through its evolution; and the metal-enriched nature of Jupiter’s envelope. The most widely accepted theory for the formation of the satellites is the so-called “starved disk” model, although newer alternatives including decretion disks and pebble accretion have also been proposed. Models that allow slow satellite formation in a cold disk are preferred, based on the density progression and Callisto’s apparent differentiation state. Major model uncertainties include the angular momentum distribution of the material infalling to the circumplanetary disk, the source of the solids, and the thermal and viscosity structure of the disk. We identify six outstanding questions, some of which will be answered by JUICE, Europa Clipper and Tianwen-4. A major difficulty in answering some questions is overprinting of primordial characteristics by later events.
Kimberlites allow exceptional insights deep into cratons by rapidly bringing to the surface well-preserved mantle fragments from a broad depth range. Water, mainly dissolved as hydroxyl, OH, is a key parameter for craton long-term stability as it affects viscosity and melting properties. We report here a multi-disciplinary (FTIR, Mössbauer, XANES, EPMA, LA-ICPMS) study of 17 harzburgite and dunite xenoliths from the Jagersfontein mine (Kaapvaal, South Africa) that are typical residues of high-degree melting (Mg# 92–94) and display minimum metasomatic interaction with the kimberlite as evidenced using trace elements. Thermobarometry yields 742–887 °C and 30-37.5 kbar for the equilibrium conditions of garnet free peridotites and 674–1084 °C and 27–51 kbar for garnet bearing peridotites. Oxygen fugacity, expressed as ΔlogfO2 relative to the FMQ buffer, varies between − 1.32 and − 0.29 ± 0.5 in the Cr-spinel bearing peridotites and between − 2.87 and − 0.57 ± 0.5 in garnet peridotites. OH content ([OH]) in the bulk rock varies between 29 and 99 ppm wt. H2O. Considering the low evidences of metasomatic interactions within the peridotites and the OH equilibrium between minerals, we suggest that the hydrogen content within the xenoliths remained pristine for billions of years. The [OH] decrease with depth can be explained by melting or, because bulk [OH] and ΔlogfO2 decrease with increasing depth, by a change in speciation from oxidized H2O to reduced H2 in line with thermodynamic modelling of fluid-saturated and undersaturated peridotite. Still, despite our efforts we did not observe H2 in the samples.
