AbstractSports coaches help athletes develop and improve their skills by assessing their ability to perform motion primitives that make up functional sports tasks. Sports coaching today is mostly done visually, which demands constant attention and can be imprecise. While sensors like electronic textiles and surface electromyography can measure muscle engagement, they are susceptible to movement artifacts and noise due to surface electrode issues. Therefore, the work reported here focuses on our development of self-adhesive, fabric-based sensors that can be directly affixed onto skin for monitoring skin-strains and distributed muscular engagement during functional movements. The vision is that these sensors can be readily used by sports coaches and individuals to better assess motion primitives and the execution of sports tasks. The approach integrates piezoresistive graphene nanosheet thin films with kinesiology tape (K-Tape). Because every location of the film is responsive to strains, electrodes can also be judiciously placed along the nanocomposite for distributed strain sensing. Nanocomposite or “Smart K-Tape” sensors were fabricated, and electromechanical tests were conducted to characterize their tensile, compressive, and cyclic sensing properties. Upon confirming their linearity, repeatability, stability, and high sensitivity, individuals wore Smart K-Tape sensors over different muscle groups as they performed prescribed exercise and stretching movements. The Smart K-Tapes outputted unique waveforms that revealed the speed and duration of muscular engagement through movement sequences. Furthermore, the region of muscular contraction could also be localized using each Smart K-Tape as a distributed strain sensor, which demonstrated promise as a convenient and quantitative motion primitive assessment tool relevant for sports coaching and athletic skills development.

It is estimated that more than 50% of adults over 80 will develop dementia, including Alzheimer's disease (AD), and the primary risk factor for dementia is aging. Aging provides the substrate for disease through increased inflammation and cellular dysfunction, which in turn sets the stage for neurodegenerative disease. In a previous study we validated replicative senescence, a model of cell senescence that permits the study of cells as they progress to senescence, in human coronary artery endothelial cells (HCAEC). Here, we tested the hypothesis that senescent endothelial cells, which accumulate with aging and release senescence-associated secretory phenotype (SASP) and extracellular vesicles, create a pro-inflammatory environment that adversely affects the viability and morphology of neurons, which are endpoints implicated in AD. We categorized the phenotypes of HCAEC by passage number and identified them as EP- early passage (non-senescent), ES- early senescence and LS- late senescence. HCAEC at these varying stages of senescence were co-cultured with LUHMES cells, a human neuronal cell line. Co-culturing HCAEC LS with LUHMES significantly decreased LUHMES viability, while co-culturing HCAEC ES with LUHMES decreased the number of neurites extended by LUHMES in 24h and decreased the length of LUHMES' neurites in 48h, when compared to LUHMES grown in the absence of HCAEC for the same period of time. HCAEC EP or LS co-cultured with LUHMES did not affect the number or length of the LUHMES' neurites, when compared to LUHMES grown in the absence of HCAEC. Using a cytokine array containing probes for 105 analytes, we detected 17 inflammatory mediators released by the co-cultures of HCAEC (EP, ES and LS) with LUHMES. Of these 17 mediators, 14 were also found at supernatants of HCAEC (EP, ES and LS) grown in the absence of LUHMES, and none of the analytes were detected in supernatants from LUHMES grown in the absence of HCAEC. Statistical analysis of the intensity of the positive reaction for inflammatory mediators in the array was run for all the 17 positive analytes, and only IL-8 and Serpin E1 release into the supernatants of the co-cultures were significantly increased in co-cultures of LUHMES and senescent HCAEC (ES or LS), when compared to the levels of the same mediators released by co-cultures of LUHMES and EP HCAEC. However, exposing LUHMES to IL-8 and Serpin E1, in the absence of HCAEC, did not affect LUHMES viability, the number or length of LUHMES' neurites or LUHMES' NF-kB activation. The results from the LUHMES and HCAEC co-cultures study supports a role for aging endothelial cells in the toxicity and morphological remodeling of the surrounding neurons, which may contribute to the development and progression of neurodegenerative diseases. However, our data exclude IL-8 and Serpin E1 as direct independent mediators of senescent HCAEC on neuronal cytotoxicity and neurite remodeling.

Identification of muscle-tendon force generation properties and muscle activities from physiological measurements, e.g., motion data and raw surface electromyography (sEMG), offers opportunities to construct a subject-specific musculoskeletal (MSK) digital twin system for health condition assessment and motion prediction. While machine learning approaches with capabilities in extracting complex features and patterns from a large amount of data have been applied to motion prediction given sEMG signals, the learned data-driven mapping is black-box and may not satisfy the underlying physics and has reduced generality. In this work, we propose a feature-encoded physics-informed parameter identification neural network (FEPI-PINN) for simultaneous prediction of motion and parameter identification of human MSK systems. In this approach, features of high-dimensional noisy sEMG signals are projected onto a low-dimensional noise-filtered embedding space for the enhancement of forwarding dynamics prediction. This FEPI-PINN model can be trained to relate sEMG signals to joint motion and simultaneously identify key MSK parameters. The numerical examples demonstrate that the proposed framework can effectively identify subject-specific muscle parameters and the trained physics-informed forward-dynamics surrogate yields accurate motion predictions of elbow flexion-extension motion that are in good agreement with the measured joint motion data.

The PD-L1 overexpression is an important event of immune escape and metastasis in triple-negative breast cancer (TNBC), but the molecular mechanism remains to be determined. Interferon gamma (IFNγ) represents a major driving force behind PD-L1 expression in tumor microenvironment, and histone deacetylase 2 (HDAC2) is required for IFN signaling. Here, we investigated the regulation of HDAC2 on the IFNγ-induced PD-L1 expression in TNBC cells. We found the HDAC2 and PD-L1 expression in TNBC was significantly higher than that in non-TNBC, and HDAC2 was positively correlated with PD-L1 expression. HDAC2 promoted PD-L1 induction by upregulating the phosphorylation of JAK1, JAK2, and STAT1, as well as the translocation of STAT1 to the nucleus and the recruitment of STAT1 to the PD-L1 promoter. Meanwhile, HDAC2 was recruited to the PD-L1 promoter by STAT1, and HDAC2 knockout compromised IFNγ-induced upregulation of H3K27, H3K9 acetylation, and the BRD4 recruitment in PD-L1 promoter. In addition, significant inhibition of proliferation, colony formation, migration, and cell cycle of TNBC cells were observed following knockout of HDAC2 in vitro. Furthermore, HDAC2 knockout reduced IFNγ-induced PD-L1 expression, lymphocyte infiltration, and retarded tumor growth and metastasis in the breast cancer mouse models. This study may provide evidence that HDAC2 promotes IFNγ-induced PD-L1 expression, suggesting a way for enhanced antitumor immunity when targeting the HDAC2 in TNBC.

Insight into, and measurements of, muscle contraction during movement may help improve the assessment of muscle function, quantification of athletic performance, and understanding of muscle behavior, prior to and during rehabilitation following neuromusculoskeletal injury. A self-adhesive, elastic fabric, nanocomposite, skin-strain sensor was developed and validated for human movement monitoring. We hypothesized that skin-strain measurements from these wearables would reveal different degrees of muscle engagement during functional movements. To test this hypothesis, the strain sensing properties of the elastic fabric sensors, especially their linearity, stability, repeatability, and sensitivity, were first verified using load frame tests. Human subject tests conducted in parallel with optical motion capture confirmed that they can reliably measure tensile and compressive skin-strains across the calf and tibialis anterior. Then, a pilot study was conducted to assess the correlation of skin-strain measurements with surface electromyography (sEMG) signals. Subjects did biceps curls with different weights, and the responses of the elastic fabric sensors worn over the biceps brachii and flexor carpi radialis (i.e., forearm) were well-correlated with sEMG muscle engagement measures. These nanocomposite fabric sensors were validated for monitoring muscle engagement during functional activities and did not suffer from the motion artifacts typically observed when using sEMGs in free-living community settings.

The subseasonal features of the annual trends of runoff and other associated hydroclimatic variables in the upper Colorado River basin (UCRB) are examined using multiple data sets from in situ observations, reanalysis, and modeling for early spring (February, March, and April), given that about 58% of annual mean runoff decline from 1980 to 2018 stem from its decreases in the three months. Our analysis suggests that the strong annual trends of hydroclimatic variables in March are more statistically significant than other two months. While recent observational studies attribute the decline of runoff for either annual total or cool and warm seasons to regional warming and precipitation decrease, we suggested, for the first time, that a larger decreasing trend of the runoff in March is caused by the declining cloud optical depth which induces further decrease in precipitation and additional increase in temperature on top of climatic warming. The extra warming can reduce available water resource in the basin likely by enhancing evaporation in March. The recent cloud suppression likely results from stronger subsidence and larger moisture flux divergence over southwestern United States because of abnormal circulation patterns in varying climate, in turn leading to drier atmosphere which is unfavorable for cloud formation/development over the UCRB region. The cloud influence on the runoff in March in the UCRB revealed in this study implies the importance of understanding subseasonal variations of hydroclimate in the changing climate, as well as a need of future studies on the response of circulation patterns to climate change at subseasonal level and its implication on local hydroclimate.

Many countries and regions across the globe broke their surface temperature records in recent years. Recent crippling heat waves swept across the Earth, further sparking concerns about the impending arrival of “tipping points” later in the 21st century. This study analyzes observed global surface temperature trends in three target latitudinal regions: the Arctic Circle, Tropics, and the Antarctic Circle. We show that global warming is accelerating unevenly across the planet, with the Arctic warming at more than three times the average rate of our world. We also analyzed the reliability of latitude-dependent surface temperature simulations from a suite of Coupled Model Intercomparison Project Phase 6 (CMIP6) models and their multi-model mean (MMM) by comparing their outputs to observational data sets. We selected the best-performing models based on their statistical abilities to reproduce historical, latitude-dependent values adapted from these data sets. The surface temperature projections were calculated from ensemble simulations of the Shared Socioeconomic Pathway 2–4.5 (SSP2–4.5) by the selected CMIP6 models. We estimate the calendar years of when surface temperatures will increase by 1.5, 2.0, and 2.5°C relative to the preindustrial period, both globally and in the three target regions. Our results reaffirm a dramatic, upward trend in projected surface temperatures, with unprecedented acceleration in the Arctic Circle, which could lead to catastrophic consequences across the Earth. Further studies are necessary to determine the most efficient solutions to reduce global warming acceleration and maintain a low SSP, both globally and regionally.

Wearable sensors that measure parameters associated with physical activity and bodily motions have been regarded as an indispensable tool for assessing personal wellness. Recent advances in nanocomposite strain sensors have been successfully used for monitoring skin strains and other strain-derived physiological parameters. This study complements the existing body of work and presents a flexible, self-adhering, fabric-based wearable sensor for measuring skin strains and human motions. Graphene nanosheet thin films are directly spray-coated onto kinesiology tape (K-Tape) to obtain a self-adhering strain sensor of high sensitivity and linearity. Their stable sensing performance and high repeatability are verified, while human subject tests confirm that they adequately capture muscle engagement during functional movements. In addition, densely distributed strain monitoring can be achieved using an electrical impedance tomography measurement approach and algorithm. Spatial strain sensing is successfully demonstrated using a single strip of piezoresistive K-Tape, as well as when a K-Tape network or mesh pattern is formed. The results show promise for using graphene K-Tape meshes to measure how specific major muscle groups engage during different physical activities.