Background: Motion capture and analyzing systems are essential for understanding locomotion. However, the existing devices are too cumbersome and can be used indoors only. A newly-developed wearable motion capture and measurement system with multiple sensors and ultrasound imaging was introduced in this study. Methods: In ten healthy participants, the changes in muscle area and activity of gastrocnemius, plantarflexion and dorsiflexion of right leg during walking were evaluated by the developed system and the Vicon system. The existence of significant changes in a gait cycle, comparison of the ankle kinetic data captured by the developed system and the Vicon system, and test-retest reliability (evaluated by the intraclass correlation coefficient, ICC) in each channel’s data captured by the developed system were examined. Results: Moderate to good test-retest reliability of various channels of the developed system (0.512 ≤ ICC ≤ 0.988, p < 0.05), significantly high correlation between the developed system and Vicon system in ankle joint angles (0.638R ≤ 0.707, p < 0.05), and significant changes in muscle activity of gastrocnemius during a gait cycle (p < 0.05) were found. Conclusion: A newly developed wearable motion capture and measurement system with ultrasound imaging that can accurately capture the motion of one leg was evaluated in this study, which paves the way towards real-time comprehensive evaluation of muscles and joint motions during different activities in both indoor and outdoor environments.

Hepatocellular carcinoma (HCC), accounting for 90% of primary liver cancer, is a lethal malignancy that is tightly associated with chronic hepatitis B virus (HBV) infection. HBV encodes a viral onco-protein, transactivator protein X (HBx), which interacts with proteins of hepatocytes to promote oncogenesis. Our current study focused on the interaction of HBx with a transcription factor, hypoxia-inducible factor-1α (HIF-1α), which is stabilized by low O2 condition (hypoxia) and is found to be frequently overexpressed in HCC intra-tumorally due to poor blood perfusion. Here, we showed that overexpression of HBx by tetracycline-inducible systems further stabilized HIF-1α under hypoxia in HBV-negative HCC cell lines. Reversely, knockdown of HBx reduced HIF-1α protein stabilization under hypoxia in HBV-positive HCC cell lines. More intriguingly, overexpression of HBx elevated the mRNA and protein expression of a family of HIF-1α target genes, the lysyl oxidase (LOX) family in HCC. The LOX family members function to cross-link collagen in the extracellular matrix (ECM) to promote cancer progression and metastasis. By analyzing the collagens under scanning electron microscope, we found that collagen fibers were significantly smaller in size when incubated with conditioned medium from HBx knockdown HCC cells as compared to control HCC cells in vitro. Transwell invasion assay further revealed that less cells were able to invade through the matrigel which was pre-treated with conditioned medium from HBx knockdown HCC cells as compared to control HCC cells. Orthotopic and subcutaneous HCC models further showed that knockdown of HBx in HCC cells reduced collagen crosslinking and stiffness in vivo and repressed HCC growth and metastasis. Taken together, our in vitro and in vivo studies showed the HBx remodeled the ECM through HIF-1α/LOX pathway to promote HCC metastasis.

The physical microenvironment is a critical mediator of tumor behavior. However, detailed biological and mechanistic insight is lacking. The present study reveals the role of chemotherapy‐enriched CD133+ liver cancer stem cells (CSCs) with THBS2 deficiency. This subpopulation of cells contributes to a more aggressive cancer and functional stemness phenotype in hepatocellular carcinoma (HCC) by remodeling the extracellular matrix (ECM) through the regulation of matrix metalloproteinase (MMP) activity, collagen degradation, and matrix stiffness. The local soft spots created by these liver CSCs can enhance stemness and drug resistance and provide a route of escape to facilitate HCC metastasis. Interestingly, a positive feed‐forward loop is identified where a local soft spot microenvironment in the HCC tumor is enriched with CD133 expressing cells that secrete markedly less ECM‐modifying THBS2 upon histone H3 modification at its promoter region, allowing the maintenance of a localized soft spot matrix. Clinically, THBS2 deficiency is also correlated with low HCC survival, where high levels of CSCs with low THBS2 expression in HCC are associated with decreased collagen fiber deposits and an invasive tumor front. The findings have implications for the treatment of cancer stemness and for the prevention of tumor outgrowth through disseminated tumor cells.

Background: Available methods for studying muscle dynamics, including electromyography (EMG), mechanomyography (MMG) and M-mode ultrasound, have limitations in terms of spatial resolution. Methods: This study developed a novel method/protocol of two-dimensional mapping of muscle motion onset using ultrafast ultrasound imaging, i.e., sono-mechano-myo-graphy (SMMG). The developed method was compared with the EMG, MMG and force outputs of tibialis anterior (TA) muscle during ankle dorsiflexion at different percentages of maximum voluntary contraction (MVC) force in healthy young adults. Results: Significant differences between all pairwise comparisons of onsets were identified, except between SMMG and MMG. The EMG onset significantly led SMMG, MMG and force onsets by 40.0 ± 1.7 ms (p < 0.001), 43.1 ± 5.2 ms (p < 0.005) and 73.0 ± 4.5 ms (p < 0.001), respectively. Muscle motion also started earlier at the middle aponeurosis than skin surface and deeper regions when viewed longitudinally (p < 0.001). No significant effect of force level on onset delay was found. Conclusions: This study introduced and evaluated a new method/protocol, SMMG, for studying muscle dynamics and demonstrated its feasibility for muscle contraction onset research. This novel technology can potentially provide new insights for future studies of neuromuscular diseases, such as multiple sclerosis and muscular dystrophy.

(1) Background: Ultrasound provides a radiation-free and portable method for assessing swallowing. Hyoid bone locations and displacements are often used as important indicators for the evaluation of swallowing disorders. However, this requires clinicians to spend a great deal of time reviewing the ultrasound images. (2) Methods: In this study, we applied tracking algorithms based on deep learning and correlation filters to detect hyoid locations in ultrasound videos collected during swallowing. Fifty videos were collected from 10 young, healthy subjects for training, evaluation, and testing of the trackers. (3) Results: The best performing deep learning algorithm, Fully-Convolutional Siamese Networks (SiamFC), proved to have reliable performance in getting accurate hyoid bone locations from each frame of the swallowing ultrasound videos. While having a real-time frame rate (175 fps) when running on an RTX 2060, SiamFC also achieved a precision of 98.9% at the threshold of 10 pixels (3.25 mm) and 80.5% at the threshold of 5 pixels (1.63 mm). The tracker’s root-mean-square error and average error were 3.9 pixels (1.27 mm) and 3.3 pixels (1.07 mm), respectively. (4) Conclusions: Our results pave the way for real-time automatic tracking of the hyoid bone in ultrasound videos for swallowing assessment.