Design, Analysis, and Experimental Results of Micromachined Single-structure Triaxis Vibratory Gyroscope with Advanced Coupling Mechanism

In this work, a novel micromachined monolithic triaxis gyroscope with an advanced anchor mechanism is designed and its structural characteristics are analyzed. Micromachined gyroscopes are usually packed in small packages, causing a high squeeze film damping effect that reduces the quality factor of out-of-plane vibration, resulting in lowered out-of-plane sensitivity. The proposed gyroscope has a four-mass single structure wherein the opposing masses vibrate in the opposite direction perpendicular to the direction they face, with the help of 'tree-shaped' coupling springs. The simulated driving and x-, y-, and z-axis sensing resonant frequencies are 19946, 20227, 20294, and 20361 Hz, respectively. Also, the prototype of the gyroscope was fabricated and tested. It showed a driving Q-factor of 106 and a scale factor of 7 mV/deg/s.11Ysciescopu

Mathematical Modeling and Simulation of Fatigue Muscle Fiber Mechanism

It is a common experience that we feel muscle pain after physical activities. A number of studies related to muscle fatigue had been conducted, but they mainly focused on biological and chemical mechanisms. In this study, we approached the fatigue muscle fiber mechanism by mathematical modeling and simulation on existing biological and chemical understanding. The aim of the research was to explain the process of generating muscle fatigue in a mathematical method. To generate an adequate mathematical muscle fatigue fiber model, we combined two mathematical models: muscle fiber and muscle fatigue models. The modified Huxley equation was mainly used in this study, which mathematically described the behavior of the muscle fiber mechanism. Then, we validated the generated mathematical model by data from previously performed by others in scientific researches. As a result, we found an integrated model that explained both muscle fiber mechanism and muscle fatigue action. The model was applied in computer simulation, and this model was in agreement with experimental data in scientific articles. The new muscle fatigue model was able to efficiently explain the muscle fatigue mechanism in muscle fiber

Modification of immune cell-derived exosomes for enhanced cancer immunotherapy: current advances and therapeutic applications

Abstract Cancer immunotherapy has revolutionized the approach to cancer treatment of malignant tumors by harnessing the body’s immune system to selectively target cancer cells. Despite remarkable advances, there are still challenges in achieving successful clinical responses. Recent evidence suggests that immune cell-derived exosomes modulate the immune system to generate effective antitumor immune responses, making them a cutting-edge therapeutic strategy. However, natural exosomes are limited in clinical application due to their low drug delivery efficiency and insufficient antitumor capacity. Technological advancements have allowed exosome modifications to magnify their intrinsic functions, load different therapeutic cargoes, and preferentially target tumor sites. These engineered exosomes exert potent antitumor effects and have great potential for cancer immunotherapy. In this review, we describe ingenious modification strategies to attain the desired performance. Moreover, we systematically summarize the tumor-controlling properties of engineered immune cell-derived exosomes in innate and adaptive immunity. Collectively, this review provides a comprehensive and intuitive guide for harnessing the potential of modified immune cell-derived exosome-based approaches, offering valuable strategies to enhance and optimize cancer immunotherapy

Qigong Exercise May Reduce Serum TNF-α Levels and Improve Sleep in People with Parkinson’s Disease: A Pilot Study

Background: Inflammatory cytokine levels are often elevated in people with Parkinson’s disease (PD). People with PD often experience sleep disturbances that significantly impact quality of life. Past studies suggest inflammatory cytokines may be associated with various symptoms of PD. Benefits of Qigong, a mind–body exercise, have been shown in different neurological conditions, but there is still a lack of clinical evidence in the PD population. Methods: Ten people with PD were recruited and randomly assigned into two groups receiving six weeks of Qigong (experimental group) or sham Qigong (control group) intervention. The levels of TNF-α, IL-1β, and IL-6 in subjects’ serum and sleep quality were measured before and after the intervention. Results: After the intervention, the serum level of TNF-α in the experimental group was significantly decreased in all subjects, while the level in the control group showed a trend to increase. Qigong exercise significantly improved sleep quality at night. There was a strong correlation between changes in the level of TNF-α and sleep quality. Conclusion: Qigong exercise decreased TNF-α level in people with PD and helped improve sleep quality. TNF-α may have a potential to influence the sleep quality in people with PD

Phosphonated Polymers with Fine-Tuned Ion Clustering Behavior: Toward Efficient Proton Conductors

We report the controlled synthesis, self-assembly, and ion transport properties of polystyrene bisphosphonate (PSbP) and polystyrene phosphonate (PSP) based polymers, revealing that ion clustering in PSbP (characterized by precisely determined phosphonate group location) was markedly suppressed compared to that in PSP despite the 2-fold higher phosphonic acid group concentration in the former. Moreover, confinement of PSbP chains to ordered nanoscale domains in PSbP-based block copolymers offered a platform for creating nearly homogeneous ionic phases with a radically decreased potential barrier to ion conduction. Notably, the decrease in the degree of polymerization of PSbP chain in the block copolymers by half (i.e., the lower acid group contents) led to 2-3 times improved anhydrous conductivity with incorporated ionic liquids, contrary to the results commonly reported for a range of acid-tethered polymers. Our work provides a first-time demonstration of well-defined self-assembled morphologies of bisphosphonate block copolymers, opening a new chapter in the development of highly conductive phosphonated polymers and thus being of importance to the field of polymer electrolytes.11Nsciescopu

Qigong Exercise May Reduce Serum TNF-α Levels and Improve Sleep in People with Parkinson’s Disease: A Pilot Study

Background: Inflammatory cytokine levels are often elevated in people with Parkinson’s disease (PD). People with PD often experience sleep disturbances that significantly impact quality of life. Past studies suggest inflammatory cytokines may be associated with various symptoms of PD. Benefits of Qigong, a mind–body exercise, have been shown in different neurological conditions, but there is still a lack of clinical evidence in the PD population. Methods: Ten people with PD were recruited and randomly assigned into two groups receiving six weeks of Qigong (experimental group) or sham Qigong (control group) intervention. The levels of TNF-α, IL-1β, and IL-6 in subjects’ serum and sleep quality were measured before and after the intervention. Results: After the intervention, the serum level of TNF-α in the experimental group was significantly decreased in all subjects, while the level in the control group showed a trend to increase. Qigong exercise significantly improved sleep quality at night. There was a strong correlation between changes in the level of TNF-α and sleep quality. Conclusion: Qigong exercise decreased TNF-α level in people with PD and helped improve sleep quality. TNF-α may have a potential to influence the sleep quality in people with PD

The impact of advanced age on driving safety in older adults with medical conditions

Background: Adults aged 85 and older, often referred to as the oldest-old, are the fastest growing segment of the population. The rapidly increasing number of older adults with chronic and multiple medical conditions poses challenges regarding their driving safety. Objective: To investigate the effect of advanced age on driving safety in drivers with medical conditions. Methods: We categorized 3,425 drivers with pre-existing medical conditions into four age groups: middle-aged (55-64, n = 1,386), young-old (65-74, n = 1,013), old-old (75-84, n = 803), or oldest-old (85+, n = 223). All underwent a formal driving evaluation. The outcome measures included fitness-to-drive recommendation by the referring physician, comprehensive fitness-to-drive decision from an official driving evaluation center, history of motor vehicle crashes (MVCs), and history of traffic violations. Results: The oldest-old reported more cardiopulmonary and visual conditions, but reported less neurological conditions than the old-old. Compared with the middle-aged, the oldest-old were more likely to be considered unfit-to-drive by the referring physicians (odds ratio (OR) = 4.47, 95% confidence interval (CI) 2.20-9.10) and by the official driving evaluation center (OR = 2.74, 95% CI 1.87-4.03). The oldest-old reported more MVCs (OR = 2.79, 95% CI 1.88-4.12) compared to the middle-aged. Conclusion: Advanced age adversely affected driving safety outcomes. The oldest-old are a unique age group with common medical conditions known to interfere with safe driving. Driving safety strategies should particularly target the oldest-old since they are the fastest growing group and their increased frailty is associated with severe or fatal injuries due to MVCs

Pupillary Response to Cognitive Demand in Parkinson’s Disease: A Pilot Study

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author's publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Previous studies have shown that pupillary response, a physiological measure of cognitive workload, reflects cognitive demand in healthy younger and older adults. However, the relationship between cognitive workload and cognitive demand in Parkinson’s disease (PD) remains unclear. The aim of this pilot study was to examine the pupillary response to cognitive demand in a letter-number sequencing (LNS) task between 16 non-demented individuals with PD (age, median (Q1–Q3): 68 (62–72); 10 males) and 10 control participants (age: 63 (59–67); 2 males), matched for age, education, and Montreal Cognitive Assessment (MOCA) scores. A mixed model analysis was employed to investigate cognitive workload changes as a result of incremental cognitive demand for both groups. As expected, no differences were found in cognitive scores on the LNS between groups. Cognitive workload, exemplified by greater pupil dilation, increased with incremental cognitive demand in both groups (p = 0.003). No significant between-group (p = 0.23) or interaction effects were found (p = 0.45). In addition, individuals who achieved to complete the task at higher letter-number (LN) load responded differently to increased cognitive demand compared with those who completed at lower LN load (p < 0.001), regardless of disease status. Overall, the findings indicated that pupillary response reflects incremental cognitive demand in non-demented people with PD and healthy controls. Further research is needed to investigate the pupillary response to incremental cognitive demand of PD patients with dementia compared to non-demented PD and healthy controls. HIGHLIGHTS: - Pupillary response reflects cognitive demand in both non-demented people with PD and healthy controls - Although not significant due to insufficient power, non-demented individuals with PD had increased cognitive workload compared to the healthy controls throughout the testing - Pupillary response may be a valid measure of cognitive demand in non-demented individuals with PD - In future, pupillary response might be used to detect cognitive impairment in individuals with P

Classification of Parkinson\u27s disease and essential tremor based on balance and gait characteristics from wearable motion sensors via machine learning techniques: A data-driven approach

© 2020 The Author(s). Background: Parkinson\u27s disease (PD) and essential tremor (ET) are movement disorders that can have similar clinical characteristics including tremor and gait difficulty. These disorders can be misdiagnosed leading to delay in appropriate treatment. The aim of the study was to determine whether balance and gait variables obtained with wearable inertial motion sensors can be utilized to differentiate between PD and ET using machine learning. Additionally, we compared classification performances of several machine learning models. Methods: This retrospective study included balance and gait variables collected during the instrumented stand and walk test from people with PD (n = 524) and with ET (n = 43). Performance of several machine learning techniques including neural networks, support vector machine, k-nearest neighbor, decision tree, random forest, and gradient boosting, were compared with a dummy model or logistic regression using F1-scores. Results: Machine learning models classified PD and ET based on balance and gait characteristics better than the dummy model (F1-score = 0.48) or logistic regression (F1-score = 0.53). The highest F1-score was 0.61 of neural network, followed by 0.59 of gradient boosting, 0.56 of random forest, 0.55 of support vector machine, 0.53 of decision tree, and 0.49 of k-nearest neighbor. Conclusions: This study demonstrated the utility of machine learning models to classify different movement disorders based on balance and gait characteristics collected from wearable sensors. Future studies using a well-balanced data set are needed to confirm the potential clinical utility of machine learning models to discern between PD and ET