Effects of sedentary behaviour and long-term regular Tai Chi exercise on dynamic stability control during gait initiation in older women.

Background: Sedentary behaviour has been associated with an increased risk of falls among older adults. Although gait initiation (GI) is a promising tool used to assess fall risk, it has yet to be quantitatively evaluated for dynamic stability in sedentary populations. Tai Chi exercise is believed to be effective in preventing falls in older adults, but its effect on GI stability has not been quantified. This study aims to compare the stability of GI in sedentary older individuals versus those who are long-term Tai Chi exercisers by using a quantitative approach. Methods: This study included 17 sedentary older women without exercise habits (age: 65.59 ± 3.66 years, average daily sitting time: 8.735 ± 1.847 h/day) and 19 older women who regularly engage in Tai Chi exercise (age: 65.58 ± 3.63 years, years of exercise: 9.84 ± 3.48 years). Every participant underwent five trials of self-paced GI walking tests. Eight cameras and four force plates were used to obtain kinematic and kinetic parameters. The trajectory of the centre of mass (CoM) and the position of the foot placement were recorded. The anterior-posterior (A-P) and medio-lateral (M-L) dynamic stability at the onset and end moments of the single-legged support was calculated using CoM and gait spatiotemporal parameters. The stepping dynamic stability and foot placement positions of both groups were compared. Results: The Tai Chi group had greater stability in the M-L directions at the swing leg's toe-off moment and in the M-L and A-P directions at the heel-strike moment, as well as significantly larger step length, step width and step speed during locomotion than sedentary older women. However, the stability in the A-P directions at the swing leg's toe-off moment and the foot inclination angle was not statistically different between the two groups. Conclusion: Long-term regular Tai Chi exercise can enhance the dynamic stability of GI in older women, and effectively improve their foot placement strategy during GI. The findings further confirm the negative effect of sedentary on the stability control of older women and the positive role of Tai Chi in enhancing their gait stability and reducing the risk of falls.

Temporally interfering electric fields brain stimulation in primary motor cortex of mice promotes motor skill through enhancing neuroplasticity.

Temporal interference (TI) electric field brain stimulation is a novel neuromodulation technique that enables the non-invasive modulation of deep brain regions, but few advances about TI stimulation effectiveness and mechanisms have been reported. Conventional transcranial alternating current stimulation (tACS) can enhance motor skills, whether TI stimulation has an effect on motor skills in mice has not been elucidated. In the present study, TI stimulation was proved to stimulating noninvasively primary motor cortex (M1) of mice, and that TI stimulation with an envelope wave frequency of 20 Hz (Δ f = 20 Hz) once a day for 20 min for 7 consecutive days significantly improved the motor skills of mice. The mechanism of action may be related to regulating of neurotransmitter metabolism, increasing the expression of synapse-related proteins, promoting neurotransmitter release, increasing dendritic spine density, enhancing the number of synaptic vesicles and the thickness of postsynaptic dense material, and ultimately enhance neuronal excitability and plasticity. It is the first report about TI stimulation promoting motor skills of mice and describing its mechanisms.

Spatial domain detection using contrastive self-supervised learning for spatial multi-omics technologies.

Recent advances in spatially-resolved single-omics and multi-omics technologies have led to the emergence of computational tools to detect or predict spatial domains. Additionally, histological images and immunofluorescence (IF) staining of proteins and cell types provide multiple perspectives and a more complete understanding of tissue architecture. Here, we introduce Proust, a scalable tool to predict discrete domains using spatial multi-omics data by combining the low-dimensional representation of biological profiles based on graph-based contrastive self-supervised learning. Our scalable method integrates multiple data modalities, such as RNA, protein, and H&E images, and predicts spatial domains within tissue samples. Through the integration of multiple modalities, Proust consistently demonstrates enhanced accuracy in detecting spatial domains, as evidenced across various benchmark datasets and technological platforms.

Optimisation of stable flight posture of ski jumping based on computational fluid dynamics simulation technology.

The stable flight posture that affects sports performance during flight is usually formed by the multiple angles of the athlete-ski posture. At present, research on the flight phase is mainly based on the single-factor impact analysis based on computational fluid dynamics simulation technology, but studies on the multi-factor coupling relationship of two or more factors is less. This study aims to determine the best optimal-level combination based on the simulation model of this work through comprehensive evaluation from the optimisation perspective of multi-factor coupling. Here, a refined model of the athlete-ski system with the characteristics of ski jumping was established. Reynolds time-averaged method was used for the simulation. A three-factor and five-level simulation test was conducted on the relative inclination between skis, the angle between the body and the ski and the ski V-angle through orthogonal experiment design. Our results show that the optimal-level combination of the relative inclination between skis of 120°, the angle between the body and the ski of 20°, and the ski V-angle of 30° is relatively best in terms of aerodynamic characteristics. Simulation results were similar to the results of the winter field data from video analysis, and the results were effective.

Key transition technology of ski jumping based on inertial motion unit, kinematics and dynamics.

BACKGROUND: The development and innovation of biomechanical measurement methods provide a solution to the problems in ski jumping research. At present, research on ski jumping mostly focuses on the local technical characteristics of different phases, but studies on the technology transition process are less. OBJECTIVES: This study aims to evaluate a measurement system (i.e. the merging of 2D video recording, inertial measurement unit and wireless pressure insole) that can capture a wide range of sport performance and focus on the key transition technical characteristics. METHODS: The application validity of the Xsens motion capture system in ski jumping was verified under field conditions by comparing the lower limb joint angles of eight professional ski jumpers during the takeoff phase collected by different motion capture systems (Xsens and Simi high-speed camera). Subsequently, the key transition technical characteristics of eight ski jumpers were captured on the basis of the aforementioned measurement system. RESULTS: Validation results indicated that the joint angle point-by-point curve during the takeoff phase was highly correlated and had excellent agreement (0.966 ≤ r ≤ 0.998, P < 0.001). Joint root-mean-square error (RMSE) differences between model calculations were 5.967° for hip, 6.856° for knee and 4.009° for ankle. CONCLUSIONS: Compared with 2D video recording, the Xsens system shows excellent agreement to ski jumping. Furthermore, the established measurement system can effectively capture the key transition technical characteristics of athletes, particularly in the dynamic changes of straight turn into arc in inrun, the adjustment of body posture and ski movement during early flight and landing preparation.

Effects of a Single Bout of Endurance Exercise on Brain-Derived Neurotrophic Factor in Humans: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

We aimed to investigate the impact of a single bout of endurance exercise on the brain-derived neurotrophic factor (BDNF) in humans and analyze how a single bout of endurance exercise impacts the peripheral BDNF types by age group. We performed a systematic literature review by searching PubMed, Elsevier, and Web of Science for studies that included a single bout of endurance exercise in the experimental group and other exercise types in the control group. Eight interventions were included in the study. Overall, a single bout of endurance exercise significantly increased BDNF expression (SMD = 0.30; 95% CI = [0.08, 0.52]; p = 0.001), which was confirmed in the serum BDNF (SMD = 0.30; 95% CI = [0.04, 0.55]; p < 0.001). A non-significant trend was observed in the plasma BDNF (SMD = 0.31; 95% CI = [−0.13, 0.76]; p = 0.017). The serum and plasma BDNF levels significantly increased regardless of age (SMD = 0.35; 95% CI = [0.11, 0.58]; p = 0.004; I2 = 0%). In conclusion, a single bout of endurance exercise significantly elevates BDNF levels in humans without neurological disorders, regardless of age. The serum BDNF is a more sensitive index than the plasma BDNF in evaluating the impact of a single bout of endurance exercise on the BDNF.

In vivo knee biomechanics during badminton lunges at different distances and different foot positions by using the dual fluoroscopic imaging system.

Background: Lunges are common in badminton. Distance and foot position affect knee joint loadings under lunges, which are closely related to knee injury incidence. Investigations involving dynamic knee motion in vivo, kinetics, and muscle activation in lunges, especially during lunges of different distances and foot positions, are instrumental for understanding knee performance and injury risks of players. Methods: A total of 10 experienced badminton athletes (10 females; height, 164.5 ± 5.0 cm; weight, 59.3 ± 6.0 kg; and age, 22 ± 1.0 years) were recruited. By using a high-speed dual fluoroscopic imaging system, Qualisys motion capture system, Kistler force plate, and Delsys electromyography simultaneously, data were collected during players' 1.5 times leg length lunge, the maximum lunge, and the maximum lunge while the foot rotated externally. Magnetic resonance and dual fluoroscopic imaging techniques were used to analyze the in vivo knee kinematics. Results: Compared with the 1.5 times leg length lunge, knee flexion for the maximum lunge increased significantly (p < 0.05). The anterior-posterior ground reaction force (GRF) and vertical GRF of the maximum lunge were significantly higher than those of the 1.5 times leg length lunge. During the two different foot position lunges with the maximum distance, the posterior translation of knee joint was larger (p < 0.05) when the foot rotated externally than the normal maximum lunge. Moreover, the anterior-posterior GRF and vertical GRF increased significantly when the foot rotated externally. Significant differences were observed in valgus-varus rotation torque and internal-external rotation torque of the knee joint under the two distance lunges and two foot position lunges (p < 0.05). No significant difference was found in knee muscle activation during the two distance lunges and during the two foot position lunges. Conclusion: High knee torque and compressive loadings with increasing lunge distance may cause knee injuries in badminton. When lunging in the external foot rotation under the maximum distance, high quadriceps force and posterior tibia translation force could result in knee injuries among badminton players.

Research advances in the application of metabolomics in exercise science.

Exercise training can lead to changes in the metabolic composition of an athlete's blood, the magnitude of which depends largely on the intensity and duration of exercise. A variety of behavioral, biochemical, hormonal, and immunological biomarkers are commonly used to assess an athlete's physical condition during exercise training. However, traditional invasive muscle biopsy testing methods are unable to comprehensively detect physiological differences and metabolic changes in the body. Metabolomics technology is a high-throughput, highly sensitive technique that provides a comprehensive assessment of changes in small molecule metabolites (molecular weight <1,500 Da) in the body. By measuring the overall metabolic characteristics of biological samples, we can study the changes of endogenous metabolites in an organism or cell at a certain moment in time, and investigate the interconnection and dynamic patterns between metabolites and physiological changes, thus further understanding the interactions between genes and the environment, and providing possibilities for biomarker discovery, precise training and nutritional programming of athletes. This paper summaries the progress of research on the application of exercise metabolomics in sports science, and looks forward to the future development of exercise metabolomics, with a view to providing new approaches and perspectives for improving human performance, promoting exercise against chronic diseases, and advancing sports science research.

The Path Planning of Mobile Robot by Neural Networks and Hierarchical Reinforcement Learning.

Existing mobile robots cannot complete some functions. To solve these problems, which include autonomous learning in path planning, the slow convergence of path planning, and planned paths that are not smooth, it is possible to utilize neural networks to enable to the robot to perceive the environment and perform feature extraction, which enables them to have a fitness of environment to state action function. By mapping the current state of these actions through Hierarchical Reinforcement Learning (HRL), the needs of mobile robots are met. It is possible to construct a path planning model for mobile robots based on neural networks and HRL. In this article, the proposed algorithm is compared with different algorithms in path planning. It underwent a performance evaluation to obtain an optimal learning algorithm system. The optimal algorithm system was tested in different environments and scenarios to obtain optimal learning conditions, thereby verifying the effectiveness of the proposed algorithm. Deep Deterministic Policy Gradient (DDPG), a path planning algorithm for mobile robots based on neural networks and hierarchical reinforcement learning, performed better in all aspects than other algorithms. Specifically, when compared with Double Deep Q-Learning (DDQN), DDPG has a shorter path planning time and a reduced number of path steps. When introducing an influence value, this algorithm shortens the convergence time by 91% compared with the Q-learning algorithm and improves the smoothness of the planned path by 79%. The algorithm has a good generalization effect in different scenarios. These results have significance for research on guiding, the precise positioning, and path planning of mobile robots.

Adaptation of semi-continuous anaerobic sludge digestion to humic acids.

Anaerobic digestion (AD) is a technology for recovering chemical energy as methane from excess sludge/waste. Unfortunately, humic acids (HA) contained in excess sludge can have the effects of inhibiting the efficiency of energy conversion. Based on a batch experiment, the impact of HA on a semi-continuous AD process was sequentially investigated, with the impact on the associated enzymes and microorganisms being measured. The results of this semi-continuous experiment indicate that the inhibition of the microbial community increased with an increased HA:VSS ratio. Long-term cultivation did not result in the adaption of methane production to the presence of HA. Moreover, at HA:VSS = 20%, the strongest inhibition (74.3%) on energy conversion efficiency was observed in the semi-continuous experiment, which was two-fold higher than that recorded in the batch experiment. This is attributed to serious and irreversible inhibition of both acidogenic and methanogenic microorganisms, as well as the physical-chemical reactions between HA and the associated enzymes which, it was concluded, were the dominant mechanisms of inhibition in the batch experiment.

Macroporous microbeads containing apatite-modified mesoporous bioactive glass nanofibres for bone tissue engineering applications.

Mesoporous bioactive glass (MBG) has a greater surface area and pore volume than conventional BG. Hence, MBG is useful as a drug delivery carrier. Previously, MBG has been fabricated as dense or porous blocks. Compared to blocks, microbeads have a greater flexibility to fill different-shaped cavities with close packing. Moreover, fibrous materials have proven to increase cell attachment and differentiation because they mimic the three-dimensional structure of the natural extracellular matrix (ECM). Macroporous materials possess porous structures with interconnecting channels that allow the invasive growth of cells and capillaries. Hence, the aim of this study was to fabricate macroporous microbeads containing MBG nanofibres (MMBs). We used poly(methyl methacrylate) (PMMA) microspheres as the macroporous template in the process and removed the PMMA microspheres after the calcination treatment. Scanning electron microscopy imaging showed multiple pores on the surface of the MMBs, and a micro-computed tomography image showed the presence of pores throughout the entire microbead. The cellular attachment of MG63 osteoblast-like cells was considerably higher on the MMBs than on glass beads after culturing for 4 h. However, the cell viability greatly decreased after culturing for 1 day. We speculated that the release of a high concentration of calcium ions from the MMBs decreased the cell viability. To improve the cell viability, we modified the MMBs by immersing the MMBs in a simulated body fluid to fabricate a thin apatite layer on the surface of the MMBs. The apatite-modified MMBs (Ap-MMB) decreased the release of calcium ions and improved the cell viability. In an animal study, the bone defect in the control group did not recover. In contrast to the control group, the Ap-MMBs in the defect were nearly filled with new bone. The results show that the Ap-MMBs have great potential in osteogenesis for bone tissue engineering.

Preparation of Nanofibrous Structure of Mesoporous Bioactive Glass Microbeads for Biomedical Applications.

A highly ordered, mesoporous (pore size 2~50 nm) bioactive glass (MBG) structure has a greater surface area and pore volume and excellent bone-forming bioactivity compared with traditional bioactive glasses (BGs). Hence, MBGs have been used in drug delivery and bone tissue engineering. MBGs can be developed as either a dense or porous block. Compared with a block, microbeads provide greater flexibility for filling different-shaped cavities and are suitable for culturing cells in vitro. In contrast, the fibrous structure of a scaffold has been shown to increase cell attachment and differentiation due to its ability to mimic the three-dimensional structure of natural extracellular matrices. Hence, the aim of this study is to fabricate MBG microbeads with a fibrous structure. First, a sol-gel/electrospinning technique was utilized to fabricate the MBG nanofiber (MBGNF) structure. Subsequently, the MBGNF microbeads (MFBs) were produced by an electrospraying technology. The results show that the diameter of the MFBs decreases when the applied voltage increases. The drug loading and release profiles and mechanisms of the MFBs were also evaluated. MFBs had a better drug entrapment efficiency, could reduce the burst release of tetracycline, and sustain the release over 10 days. Hence, the MFBs may be suitable drug carriers. In addition, the cellular attachment of MG63 osteoblast-like cells is significantly higher for MFBs than for glass microbeads after culturing for 4 h. The nanofibrous structure of MFBs could provide an appropriate environment for cellular spreading. Therefore, MFBs have great potential for use as a bone graft material in bone tissue engineering applications.