328 research outputs found

    BH3-only Protein Noxa Is a Mediator of Hypoxic Cell Death Induced by Hypoxia-inducible Factor 1α

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    Hypoxia is a common cause of cell death and is implicated in many disease processes including stroke and chronic degenerative disorders. In response to hypoxia, cells express a variety of genes, which allow adaptation to altered metabolic demands, decreased oxygen demands, and the removal of irreversibly damaged cells. Using polymerase chain reaction–based suppression subtractive hybridization to find genes that are differentially expressed in hypoxia, we identified the BH3-only Bcl-2 family protein Noxa. Noxa is a candidate molecule mediating p53-induced apoptosis. We show that Noxa promoter responds directly to hypoxia via hypoxia-inducible factor (HIF)-1α. Suppression of Noxa expression by antisense oligonucleotides rescued cells from hypoxia-induced cell death and decreased infarction volumes in an animal model of ischemia. Further, we show that reactive oxygen species and resultant cytochrome c release participate in Noxa-mediated hypoxic cell death. Altogether, our results show that Noxa is induced by HIF-1α and mediates hypoxic cell death

    Biomechanical Gait Variable Estimation Using Wearable Sensors after Unilateral Total Knee Arthroplasty

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    Total knee arthroplasty is a common surgical treatment for end-stage osteoarthritis of the knee. The majority of existing studies that have explored the relationship between recovery and gait biomechanics have been conducted in laboratory settings. However, seamless gait parameter monitoring in real-world conditions may provide a better understanding of recovery post-surgery. The purpose of this study was to estimate kinematic and kinetic gait variables using two ankle-worn wearable sensors in individuals after unilateral total knee arthroplasty. Eighteen subjects at least six months post-unilateral total knee arthroplasty participated in this study. Four biomechanical gait variables were measured using an instrumented split-belt treadmill and motion capture systems. Concurrently, eleven inertial gait variables were extracted from two ankle-worn accelerometers. Subsets of the inertial gait variables for each biomechanical gait variable estimation were statistically selected. Then, hierarchical regressions were created to determine the directional contributions of the inertial gait variables for biomechanical gait variable estimations. Selected inertial gait variables significantly predicted trial-averaged biomechanical gait variables. Moreover, strong directionally-aligned relationships were observed. Wearable-based gait monitoring of multiple and sequential kinetic gait variables in daily life could provide a more accurate understanding of the relationships between movement patterns and recovery from total knee arthroplasty

    Characteristic Analysis of the Built Environment of Ferry Terminals: A Case Study of Mokpo, South Korea

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    Ferry terminals are an essential facility for those frequently commuting between islands or towns ashore. Therefore, it is crucial to ensure a smooth and efficient flow of passengers and vehicles while guaranteeing safety and convenience at the ferry terminal. This study investigates and evaluates the walking path environment and determines the passengers’ walkability and walking satisfaction of ferry terminals in Korea. As a case study, to measure the passenger’s overall perception and satisfaction of the built environment of the ferry terminal, we conducted an importance–performance analysis for two ferry terminals located in Mokpo city of Korea. The segments of the poor built environment in terms of walking were found. Furthermore, the ANOVA and t-test results confirmed that the satisfaction level of the built environment varied by age and residential location of passengers. There was a significant difference in satisfaction between the groups (age and residential location) in the walking path segments while embarking and disembarking the ferry. Passengers’ perceptions and walking satisfaction were different depending on the features of the built environment, including public transport accessibility, layout, distance, and surface condition of the walking path of the ferry terminal. As a limitation of the study, the case study was conducted only in the Mokpo region due to the impact of COVID-19, and the sample survey was also conducted in a short period of time. In addition, further studies are needed on the generalization of passengers’ walkability in ferry terminals

    Machine Learning Approach for Automated Detection of Irregular Walking Surfaces for Walkability Assessment with Wearable Sensor

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    The walkability of a neighborhood impacts public health and leads to economic and environmental benefits. The condition of sidewalks is a significant indicator of a walkable neighborhood as it supports and encourages pedestrian travel and physical activity. However, common sidewalk assessment practices are subjective, inefficient, and ineffective. Current alternate methods for objective and automated assessment of sidewalk surfaces do not consider pedestrians’ physiological responses. We developed a novel classification framework for the detection of irregular walking surfaces that uses a machine learning approach to analyze gait parameters extracted from a single wearable accelerometer. We also identified the most suitable location for sensor placement. Experiments were conducted on 12 subjects walking on good and irregular walking surfaces with sensors attached at three different locations: right ankle, lower back, and back of the head. The most suitable location for sensor placement was at the ankle. Among the five classifiers trained with gait features from the ankle sensor, Support Vector Machine (SVM) was found to be the most effective model since it was the most robust to subject differences. The model’s performance was improved with post-processing. This demonstrates that the SVM model trained with accelerometer-based gait features can be used as an objective tool for the assessment of sidewalk walking surface conditions
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