Search Results (167)

Parkinson’s disease (PD), a progressive neurodegenerative disorder, imposes growing clinical and socioeconomic burdens worldwide. Despite landmark discoveries in dopamine biology and α-synuclein pathology, translating mechanistic insights into effective, personalized interventions remains elusive. Recent advances in molecular profiling, neuroimaging, and computational modeling have broadened the understanding of PD as a multifactorial systems disorder rather than a purely dopaminergic condition. However, critical gaps persist in diagnostic precision, biomarker standardization, and the translation of bench side findings into clinically meaningful therapies. This review critically examines the current landscape of PD research, identifying conceptual blind spots and methodological shortfalls across pathophysiology, clinical evaluation, trial design, and translational readiness. By synthesizing evidence from molecular neuroscience, data science, and global health, the review proposes strategic directions to recalibrate the research agenda toward precision neurology. Here I highlight the urgent need for interdisciplinary, globally inclusive, and biomarker-driven frameworks to overcome the fragmented progression of PD research. Grounded in the Accelerating Medicines Partnership-Parkinson’s Disease (AMP-PD) and the Parkinson’s Progression Markers Initiative (PPMI), this review maps shared biomarkers, open data, and patient-driven tools to faster personalized treatment. In doing so, it offers actionable insights for researchers, clinicians, and policymakers working at the intersection of biology, technology, and healthcare delivery. As the field pivots from symptomatic relief to disease modification, the road forward must be cohesive, collaborative, and rigorously translational, ensuring that laboratory discoveries systematically progress to clinical application. Full article

In modern vehicles, Autonomous Driving Systems (ADSs) are designed to operate partially or fully without human intervention. The ADS pipeline comprises multiple layers, including sensors, perception, localization, mapping, path planning, and control. The Robot Operating System (ROS) is a widely adopted framework that supports the modular development and integration of these layers. Among them, the path-planning and control layers remain particularly challenging due to several limitations. Classical path planners often struggle with non-smooth trajectories and high computational demands. Meta-heuristic optimization algorithms have demonstrated strong theoretical potential in path planning; however, they are rarely implemented in real-time ROS-based systems due to integration challenges. Similarly, traditional PID controllers require manual tuning and are unable to adapt to system disturbances. This paper proposes a ROS-based ADS architecture composed of eight integrated nodes, designed to address these limitations. The path-planning node leverages a meta-heuristic optimization framework with a cost function that evaluates path feasibility using occupancy grids from the Hector SLAM and obstacle clusters detected through the DBSCAN algorithm. A dynamic goal-allocation strategy is introduced based on the LiDAR range and spatial boundaries to enhance planning flexibility. In the control layer, a modified Pure Pursuit algorithm is employed to translate target positions into velocity commands based on the drift angle. Additionally, an adaptive PID controller is tuned in real time using the Differential Evolution (DE) algorithm, ensuring robust speed regulation in the presence of external disturbances. The proposed system is practically validated on a four-wheel differential drive robot across six scenarios. Experimental results demonstrate that the proposed planner significantly outperforms state-of-the-art methods, ranking first in the Friedman test with a significance level less than 0.05, confirming the effectiveness of the proposed architecture. Full article

In the context of critical challenges in curcumin-modified polyurethane synthesis—including limited curcumin bioavailability and suboptimal biodegradability/biocompatibility—a novel polyurethane material (Cur-PU) with good mechanical, shape memory, pH-responsive, and biocompatibility was synthesized via a one-pot, two-step synthetic protocol in which HO-PCL-OH served as the soft segment and curcumin was employed as the chain extender. The experimental results demonstrate that with the increase in Cur units, the crystallinity of the Cur-PU material decreases from 32.6% to 5.3% and that the intensities of the diffraction peaks at 2θ = 21.36°, 21.97°, and 23.72° in the XRD pattern gradually diminish. Concomitantly, tensile strength decreased from 35.5 MPa to 19.3 MPa, and Shore A hardness declined from 88 HA to 65 HA. These observations indicate that the sterically hindered benzene ring structure of Cur imposes restrictions on HO-PCL-OH crystallization, leading to lower crystallinity and retarded crystallization kinetics in Cur-PU. As a consequence, the material’s tensile strength and hardness are diminished. Except for the Cur-PU-3 sample, all other variants exhibited exceptional shape-memory functionality, with R_f and R_r exceeding 95%, as determined by three-point bending method. Analogous to pure curcumin solutions, Cur-PU solutions demonstrated pH-responsive chromatic transitions: upon addition of hydroxide ion (OH⁻) solutions at increasing concentrations, the solutions shifted from yellow-green to dark green and finally to orange-yellow, enabling sensitive pH detection across alkaline gradients. Hydrolytic degradation studies conducted over 15 weeks in air, UPW, and pH 6.0/8.0 phosphate buffer solutions revealed mass loss <2% for Cur-PU films. Surface morphological analysis showed progressive etching with the formation of micro-to-nano-scale pores, indicative of a surface-erosion degradation mechanism consistent with pure PCL. Biocompatibility assessments via L929 mouse fibroblast co-culture experiments demonstrated ≥90% cell viability after 72 h, while relative red blood cell hemolysis rates remained below 5%. Collectively, these findings establish Cur-PU as a biocompatible material with tunable mechanical properties, and pH responsiveness, underscoring its translational potential for biomedical applications such as drug delivery systems and tissue engineering scaffolds. Full article

In this paper, a hybrid flying robot that utilizes water thrust and aerial propeller actuation is proposed and analyzed, with the aim of applications in hazardous tasks in the marine field, such as firefighting, ship inspections, and search and rescue missions. For such tasks, existing solutions like drones and water-powered robots inherited fundamental limitations, making their use ineffective. For instance, drones are constrained by limited flight endurance, while water-powered robots struggle with horizontal motion due to the couplings between translational motions. The proposed hydro-aerodynamic hybrid actuation in this study addresses these significant drawbacks by utilizing water thrust for sustainable vertical propulsion and propeller-based actuation for more controllable horizontal motion. The characteristics and mathematical models of the proposed flying robots are presented in detail. A state feedback controller and a proportional–integral–derivative (PID) controller are designed and implemented in order to govern the proposed robot’s motion. In particular, a linear matrix inequality approach is also proposed for the former design so that a robust performance is ensured. Simulation studies are conducted where a purely water-powered flying robot using a nozzle rotation mechanism is deployed for comparison, to evaluate and validate the feasibility of the flying robot. Results demonstrate that the proposed system exhibits superior performance in terms of stability and tracking, even in the presence of external disturbances. Full article

Introduction: Substance use disorders (SUDs) pose a significant public health challenge, with current treatments often exhibiting limited effectiveness and high relapse rates. Transcranial direct current stimulation (tDCS), a noninvasive neuromodulation technique that delivers low-intensity direct current via scalp electrodes, has shown promise in various psychiatric and neurological conditions. In SUDs, tDCS may help to modulate key neurocircuits involved in craving, executive control, and reward processing, potentially mitigating compulsive drug use. However, the precise neurobiological mechanisms by which tDCS exerts its therapeutic effects in SUDs remain only partly understood. This review addresses that gap by synthesizing evidence from clinical studies that used neuroimaging (fMRI, fNIRS, EEG) and blood-based biomarkers to elucidate tDCS’s mechanisms in treating SUDs. Methods: A targeted literature search identified articles published between 2008 and 2024 investigating tDCS interventions in alcohol, nicotine, opioid, and stimulant use disorders, focusing specifically on physiological and neurobiological assessments rather than purely behavioral outcomes. Studies were included if they employed either neuroimaging (fMRI, fNIRS, EEG) or blood tests (neurotrophic and neuroinflammatory markers) to investigate changes induced by single- or multi-session tDCS. Two reviewers screened titles/abstracts, conducted full-text assessments, and extracted key data on participant characteristics, tDCS protocols, neurobiological measures, and clinical outcomes. Results: Twenty-seven studies met the inclusion criteria. Across fMRI studies, tDCS—especially targeting the dorsolateral prefrontal cortex—consistently modulated large-scale network activity and connectivity in the default mode, salience, and executive control networks. Many of these changes correlated with subjective craving, attentional bias, or extended time to relapse. EEG-based investigations found that tDCS can alter event-related potentials (e.g., P3, N2, LPP) linked to inhibitory control and salience processing, often preceding or accompanying changes in craving. One fNIRS study revealed enhanced connectivity in prefrontal regions under active tDCS. At the same time, two blood-based investigations reported the partial normalization of neurotrophic (BDNF) and proinflammatory markers (TNF-α, IL-6) in participants receiving tDCS. Multi-session protocols were more apt to drive clinically meaningful neuroplastic changes than single-session interventions. Conclusions: Although significant questions remain regarding optimal stimulation parameters, sample heterogeneity, and the translation of acute neural shifts into lasting behavioral benefits, this research confirms that tDCS can induce detectable neurobiological effects in SUD populations. By reshaping activity across prefrontal and reward-related circuits, modulating electrophysiological indices, and altering relevant biomarkers, tDCS holds promise as a viable, mechanism-based adjunctive therapy for SUDs. Rigorous, large-scale studies with longer follow-up durations and attention to individual differences will be essential to establish how best to harness these neuromodulatory effects for durable clinical outcomes. Full article

Severe acute respiratory syndrome coronavirus 2 has undergone several mutations since 2020, and novel variants continue to emerge to this day. The immune escape ability of the emerging mutants is enhanced and results in robust transmissibility. The neutralizing ability of the antibodies produced in the human body during previous infections is decreased against some of these mutants, which poses a severe challenge to the preventive and therapeutic effectiveness of vaccines and antibody drugs. The nucleocapsid protein is one of the main structural proteins of the coronavirus and plays an important role in the life cycle of the novel coronavirus. This protein is one of the key targets for drug development, and the first major step in drug development is to obtain pure nucleocapsid proteins. However, since nucleocapsid proteins have a nucleic acid-binding function and automatically undergo liquid–liquid phase separation and agglomeration, the purification of full-length nucleocapsids is challenging. In this context, a set of easy-to-operate processes was developed in this study for the purification of nucleocapsid proteins. Finally, a pure full-length nucleocapsid protein without nucleic acid contamination was obtained, which exhibited significantly enhanced accessibility for structural and functional virological studies, vaccine development, and related research applications. Further, the nucleic acid-binding domain of the nucleocapsid protein was targeted, and potential severe acute respiratory syndrome coronavirus 2 inhibitors were identified using virtual screening and biolayer interferometry technology. Notably, the eukaryotically expressed nucleocapsid protein demonstrated a significantly greater binding affinity for Light Green SF Yellowish (K_D = 119.7 nM) compared to that demonstrated by its prokaryotic counterpart (K_D = 19.9 × 10³ nM). The findings of this study suggest the importance of considering both protein source and post-translational modifications of the target proteins to be used in drug screening workflows. Therefore, this compound not only represents a novel therapeutic candidate for COVID-19 but also a critical tool for elucidating antiviral mechanisms. Full article

Biofilms are complex microbial communities encased within a self-produced extracellular matrix, which plays a critical role in chronic infections and antimicrobial resistance. These enhance pathogen survival and virulence by protecting against host immune defenses and conventional antimicrobial treatments, posing substantial challenges in clinical contexts such as device-associated infections and chronic wounds. Secondary metabolites derived from medicinal plants, such as alkaloids, tannins, flavonoids, phenolic acids, and essential oils, have gained attention as promising agents against biofilm formation, microbial virulence, and antibiotic resistance. These natural compounds not only limit microbial growth and biofilm development but also disrupt communication between bacteria, known as quorum sensing, which reduces their ability to cause disease. Through progress in nanotechnology, various nanocarriers such as lipid-based systems, polymeric nanoparticles, and metal nanoparticles have been developed to improve the solubility, stability, and cellular uptake of phytochemicals. In addition, the synergistic use of plant-based metabolites with conventional antibiotics or antifungal drugs has shown promise in tackling drug-resistant microorganisms and revitalizing existing drugs. This review comprehensively discusses the efficacy of pure secondary metabolites from medicinal plants, both as individuals and in nanoformulated forms or in combination with antimicrobial agents, as alternative strategies to control biofilm-forming pathogens. The molecular mechanisms underlying their antibiofilm and antivirulence activities are discussed in detail. Lastly, the current pitfalls, limitations, and emerging directions in translating these natural compounds into clinical applications are critically evaluated. Full article

The understanding of sustainability is shifting from that of a purely environmental dimension to one that includes social concerns. Combined with the growing customer interest in livestock husbandry practices, this study investigates the assessment of animal welfare as a socially influenced impact category for the life cycle assessment (LCA) of pig farming. The weighting of animal welfare impacts is based on a quantitative approach using a set of indicators derived from an expert survey using the Analytic Hierarchy Process (AHP). The aim is to develop an easy-to-implement score that translates the characteristics of several animal welfare indicators into a comparable value. To demonstrate the feasibility of the weighting part of the framework, a case study is conducted with nine experts in the fields of animal husbandry, agricultural sciences, and veterinary medicine. The case study results show that the main criteria of single animal observation and feed intake are the most relevant factors, at 30.6%, followed by operation-specific parameters at 23.9% and husbandry conditions at 14.9%. This case study highlights that animal losses (13.9%) significantly influence the impact category, while access to outdoor areas (1.4%) is less important. The overall conclusion is that an animal health-centered approach is preferable when assessing animal welfare. Full article

This study investigates the synergistic effects of integrating ozone nanobubbles (generated via a pure oxygen-fed reactor with nanobubble-diffusing air stones) and biofloc technology (BFT) on water quality optimization, pathogenic load reduction, and growth performance enhancement in Pacific white shrimp (Penaeus vannamei) prenursery aquaculture systems. Four treatments were tested: a clear water control (CW), ozonated clear water (CW + O), biofloc (FLOC), and biofloc with ozone (FLOC + O). The FLOC + O group significantly improved water quality, reducing total ammonia nitrogen (TAN) by 61%, nitrite nitrogen (NO₂⁻-N) by 78% compared to CW, and total suspended solids (TSS) by 21% compared to FLOC (p = 0.0015). Ozone application (maintained above 0.3 mg/L, 15 min/day) demonstrated robust pathogen suppression, achieving a sharp reduction in Muscle Necrosis Virus (MNV), a 99.5% inhibition of Vibrio spp. (from 228,885 to 107 CFU/mL), and the clearance of Epistylis spp., as determined via optical microscope. These enhancements directly translated to superior biological outcomes, with the FLOC + O group exhibiting an 82% survival rate (vs. 40% in CW) and 13% higher final body weight (11.65 mg vs. 10.32 mg in CW). The integration of ozone and BFT also accelerated larval development and improved the Zoea II to Mysis I metamorphosis success rate. By maintaining stable microbial communities and reducing organic waste, the combined system lowered the water exchange frequency by 40% and eliminated the need for prophylactic antibiotics. These results demonstrate that ozone–BFT integration effectively addresses key challenges in shrimp prenursery—enhancing disease resistance, optimizing water conditions, and improving growth efficiency. The technology offers a sustainable strategy for the intensive prenursery of Pacific white shrimp, balancing ecological resilience with production scalability. Full article

The establishment of a linear seismic response analysis model that considers ground rotation effects and eccentric torsion informed the investigation of the linear response characteristics of coupled lateral–torsional vibration, considering eccentricity and ground rotation, after which the lateral–torsional coupling linear response pattern of special-shaped column structures is examined. The results show that the torsion angle of a floor is equal to the sum of the interlayer torsion angle caused by eccentric torsion and the pure torsion angle caused by ground rotation, respectively. The natural vibration frequency of the structure considering ground rotation effects is a function of relative eccentricity; the period ratio of translation to torsion caused by ground rotation; and the period ratio of translation to torsion when considering only eccentric torsion. When the translation to torsion period ratio, considering eccentric torsion, is greater than 1.0, the torsional amplitude increases remarkably, but the first-order participation mode is considerably higher under the same conditions. The natural vibration characteristics, translational response, torsional response, and seismic force distribution are obtained for special-shaped columns by conducting the shaking table test on steel-reinforced concrete (SRC) frame structures. After comparative analysis, the maximum ratio of the maximum torsional displacement of the bottom layer of the structure to the horizontal displacement in the X direction is 0.0007. The maximum ratio of the base shear force to the theoretical base shear force of the structure without considering coupling is 0.93. The maximum ratio of the measured shear force of the special-shaped column to the theoretical shear force without considering coupling is 0.65. This indicates that ground rotation has a significant amplification effect on structural response. The research results provide a reference for the seismic design of special-shaped column structures. Full article

The human gastrointestinal (GI) track host trillions of microorganisms that secrete molecules, including extracellular vesicles (EVs) and extracellular condensates (ECs) that may affect physiological and patho-physiological activities in the host. However, efficient protocols for the isolation of pure and functional GI-derived EVs|ECs is lacking. Here, we describe the use of high-resolution particle purification liquid chromatography (PPLC) gradient-bead-column integrated with polyvinylpolypyrrolidone (PVPP)-mediated extraction of impurities to isolate EVs from colonic content (ColEVs). PVPP facilitates the isolation of pure, non-toxic, and functionally active ColEVs that were internalized by cells and functionally activate HIV LTR promoter. ColEVs isolated without PVPP have a reductive effect on MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) without living cells, suggesting that ColEVs contain reductases capable of catalyzing the reduction of MTT to formazan. The assessment of the origin of ColEVs reveals that they are composed of both bacteria and host particles. This protocol requires ~12 h (5 h preprocessing, 7 h isolation) to complete and should be used to purify EVs from sources contaminated with microbial agents to improve rigor. This protocol provides a robust tool for researchers and clinicians investigating GI-derived EVs and the translational use of GI-derived EVs for diagnostic and therapeutic use. Additionally, GI-derived EVs may serve as a window into the pathogenesis of diseases. Full article

Background/Objectives: Human-driven selection has shaped modern horse breeds into highly specialized athletes, particularly in racing. Arabian horses, renowned for their endurance, provide an excellent model for studying molecular adaptations to exercise. This study aimed to identify genes commonly influenced by physical exertion in the gluteus medius muscle and whole blood of Arabian horses during their first year of race training. Methods: RNA sequencing of sixteen pure-breed Arabian horses was used to analyze transcriptomic changes at three key training stages. Differentially expressed genes (DEGs) were identified to explore their role in endurance and metabolic adaptation. Results: Seven genes—RCHY1, PIH1D1, IVD, FABP3, ANKRD2, USP13, and CRYAB—were consistently deregulated across tissues and training periods. These genes are involved in muscle remodeling, metabolism, oxidative stress response, and protein turnover. ANKRD2 was associated with mechanosensing and muscle adaptation, FABP3 with fatty acid metabolism, and USP13 with ubiquitination-related pathways crucial for muscle recovery and energy regulation. The transcriptomic overlap between muscle and blood suggests potential systemic biomarkers for athletic performance and endurance. Conclusions: Our findings highlight the importance of multi-tissue transcriptomic profiling in understanding exercise-induced molecular adaptations. The identified genes warrant further investigation as potential molecular markers for monitoring training progression and athletic potential in endurance horses. This study contributes to the growing field of equine sports genetics and may offer translational insights into human sports performance. Full article

Huntington’s disease (HD) is a progressive neurodegenerative disorder characterized by motor, cognitive, and psychiatric symptoms. While traditionally viewed through the lens of neuronal dysfunction, emerging evidence highlights the critical role of endothelial dysfunction in HD pathogenesis. This review provides a comprehensive overview of endothelial dysfunction in HD, drawing on findings from both animal models and human studies. Key features of endothelial dysfunction in HD include impaired angiogenesis, altered cerebral blood flow, compromised neurovascular coupling and cerebrovascular reactivity, and increased blood–brain barrier permeability. Genetic factors such as the mutant huntingtin protein, peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), Brain-derived neurotrophic factor (BDNF), and the adenosine A2A receptor (ADORA2A) interact to influence endothelial function in complex ways. Various therapeutic approaches targeting endothelial dysfunction, including antioxidants, nitric oxide enhancers, calcium channel blockers, statins, and metformin, have shown promise in preclinical HD models but face translational challenges, particularly regarding optimal timing of intervention and patient stratification. The implications of these findings suggest that reconceptualizing HD as a neurovascular disorder, rather than purely neuronal, could lead to more effective treatment strategies. Future research priorities should include: (1) developing validated vascular biomarkers for disease progression, (2) advancing neuroimaging techniques to monitor endothelial dysfunction in real-time. These directions will be crucial for bridging the current gap between preclinical promise and clinical success in vascular-targeted HD therapeutics. Full article

Motor impairments resulting from neurological disorders, such as strokes or spinal cord injuries, often impair hand and finger mobility, restricting a person’s ability to grasp and perform fine motor tasks. Brain plasticity refers to the inherent capability of the central nervous system to functionally and structurally reorganize itself in response to stimulation, which underpins rehabilitation from brain injuries or strokes. Linking voluntary cortical activity with corresponding motor execution has been identified as effective in promoting adaptive plasticity. This study introduces NeuroFlex, a motion-intent-controlled soft robotic glove for hand rehabilitation. NeuroFlex utilizes a transformer-based deep learning (DL) architecture to decode motion intent from motor imagery (MI) EEG data and translate it into control inputs for the assistive glove. The glove’s soft, lightweight, and flexible design enables users to perform rehabilitation exercises involving fist formation and grasping movements, aligning with natural hand functions for fine motor practices. The results show that the accuracy of decoding the intent of fingers making a fist from MI EEG can reach up to $85.3\%$, with an average AUC of 0.88. NeuroFlex demonstrates the feasibility of detecting and assisting the patient’s attempted movements using pure thinking through a non-intrusive brain–computer interface (BCI). This EEG-based soft glove aims to enhance the effectiveness and user experience of rehabilitation protocols, providing the possibility of extending therapeutic opportunities outside clinical settings. Full article

Human–computer interaction (HCI) with three-dimensional (3D) Building Information Modelling/Model (BIM) is the crucial ingredient to enhancing the user experience and fostering the value of BIM. Current BIMs mostly use keyboard, mouse, or touchscreen as media for HCI. Using these hardware devices for HCI with BIM may lead to space constraints and a lack of visual intuitiveness. Somatosensory interaction represents an emergent modality of interaction, e.g., gesture interaction, which requires no equipment or direct touch, presents a potential approach to solving these problems. This paper proposes a computer-vision-based gesture interaction system for BIM. Firstly, a set of gestures for BIM model manipulation was designed, grounded in human ergonomics. These gestures include selection, translation, scaling, rotation, and restoration of the 3D model. Secondly, a gesture understanding algorithm dedicated to 3D model manipulation is introduced in this paper. Then, an interaction system for 3D models based on machine vision and gesture recognition was developed. A series of systematic experiments are conducted to confirm the effectiveness of the proposed system. In various environments, including pure white backgrounds, offices, and conference rooms, even when wearing gloves, the system has an accuracy rate of over 97% and a frame rate maintained between 26 and 30 frames. The final experimental results show that the method has good performance, confirming its feasibility, accuracy, and fluidity. Somatosensory interaction with 3D models enhances the interaction experience and operation efficiency between the user and the model, further expanding the application scene of BIM. Full article