Search Results (2,811)

Hydrogen internal combustion engines are a promising propulsion technology due to their zero-carbon emission potential and high efficiency. However, achieving stable mixture formation during direct hydrogen injection remains a key challenge affecting ignition stability and NO_x emissions. Although numerous studies address the combustion characteristics of hydrogen, only a limited number have examined the transient behavior of hydrogen/air mixing during the intake stroke, particularly its interaction with in-cylinder flow structures prior to ignition. This lack of detailed insight into early mixture stratification and jet-driven turbulence represents a significant research gap that currently limits further optimization of DI-H₂ICE systems. This study therefore deals with the numerical analysis of the process of mixing hydrogen with air in the combustion chamber of a direct hydrogen injection engine (DI-H₂ICE). A 3D CFD model of a hydrogen direct-injection engine was used to evaluate in-cylinder mixing during the intake and early compression strokes. Unlike most existing publications that focus primarily on combustion or emission formation, this work examines the mixing process from the beginning of the intake stroke and provides a new evaluation of the evolution of the hydrogen jet and its interaction with the piston-induced swirl as the crankshaft angle changes. The simulation covers the section from the exhaust top dead center (TDC) to the early compression phase, during which hydrogen is injected at a high pressure. The results show that the shape of the combustion chamber and the interaction of the hydrogen jet with the piston significantly affect the distribution of the equivalent ratio and the intensity of the swirl. Quantitative evaluation showed that the mixture remained lean overall throughout the cycle: typical hydrogen mass fractions in the cylinder ranged from 0.01 to 0.05, corresponding to equivalence ratios of φ = 0.35–1.81 (λ = 2.85–0.55). Only the core of the jet reached an instantaneous local mass fraction of 0.96, representing undiluted hydrogen and not a combustible mixture. No persistent zones with φ > 1 were detected, confirming that the chosen injection strategy prevents the formation of locally rich pockets. This study confirmed that a suitably selected injection configuration and combustion chamber geometry can significantly contribute to a uniform mixture distribution, a more stable combustion process, and lower NO_x production. The presented findings provide a methodological basis for improving mixture formation strategies in hydrogen engines and may support the development of efficient, zero-carbon powertrains in future mobility systems. Full article

The complexity of stroke pathophysiology, involving intricate neurovascular interactions and dynamic cellular responses, has long challenged the development of effective preclinical models. Traditional 2D cultures and animal models often fail to fully recapitulate human-specific features, limiting translational success. Emerging 3D systems, particularly brain assembloids and organ-on-a-chip platforms, are offering new opportunities to create more physiologically relevant stroke models. Assembloids, which integrate multiple brain-region-specific organoids, enable the study of interregional connectivity and complex cellular responses under ischemic conditions. Organ-on-a-chip platforms, by mimicking key tissue interfaces such as the blood–brain barrier and incorporating controlled fluid dynamics, enable a dynamic and highly customizable microenvironment with real-time monitoring capabilities. This review introduces and characterizes these two cutting-edge platforms (assembloids and organ-on-chip technologies), exploring their potential in stroke research while also discussing current challenges that need to be addressed for their broader adoption in translational applications. Full article

Background: Recent research suggests that damage to right hemisphere regions homotopic to the left hemisphere language network affects language abilities to a greater extent than previously thought. However, few studies have investigated acute disruption of language after lesion to the right hemisphere. Here, we examined lesion correlates of acute speech deficits following left and right hemisphere ischemic stroke to clarify the neural architecture underlying early language dysfunction. Methods: We retrospectively analyzed 410 patients (225 left, 185 right hemisphere lesions) from the Stroke Outcome Optimization Project dataset. Presence and severity of speech deficits was measured using the National Institute of Health Stroke Scale Best Language subscore within 48 h of onset. Manual lesion masks were derived from clinical MRI scans and normalized to MNI space. Lesion-symptom mapping was conducted using voxelwise and region-of-interest analyses with permutation correction (5000 iterations; p < 0.05), controlling for total lesion volume. Results: Speech deficits were observed in 53.7% of the cohort (58.2% left, 48.1% right hemisphere lesions). In the full sample, the presence of speech deficits was associated with bilateral subcortical and perisylvian damage, including the external and internal capsules, insula, putamen, and superior fronto-occipital fasciculus. Severity of speech deficits localized predominantly to left hemisphere structures, with peak associations in the external capsule (Z = 6.39), posterior insula (Z = 5.64), and inferior fronto-occipital fasciculus (Z = 5.43). In the right hemisphere cohort, the presence and severity of speech deficits were linked to homologous regions, including the posterior insula (Z = 3.70) and external capsule (Z = 3.63), although with smaller effect sizes relative to the left hemisphere cohort. Right hemisphere lesions resulted in milder deficits despite larger lesion volumes compared with left hemisphere lesions. Conclusions: Acute speech impairment following right hemisphere stroke is associated with damage to a homotopic network encompassing perisylvian cortical and subcortical regions analogous to the dominant left hemisphere language network. These findings demonstrate that damage to the right hemisphere consistently results in acute speech deficits, challenging the traditional left-centric view of post-stroke speech impairment. These results have important implications for models of bilateral language representation and the neuroplastic mechanisms supporting language recovery. Full article

Background: Stroke is the leading cause of physical disability in adults in Catalonia. Despite this, there is a lack of evidence of physiotherapy interventions on functional capacity during the chronic phase of the pathology. This multicenter clinical trial will be conducted with a sample size of 75 participants. Objectives: The objective of the study is to evaluate the effectiveness of a therapeutic exercise program in physiotherapy using telerehabilitation to optimize functional recovery and quality of life in people with chronic stroke, and to determine its impact on adherence to the exercise program. Methods: This is a multicenter randomized controlled trial. Three parallel groups will be compared, and two will undergo the same type of therapy. A control group (CG) will perform conventional intervention in primary care. There will be two experimental groups; (EG1) will perform document-guided therapeutic exercises at home and (EG2) will perform therapeutic exercises at home guided by a telerehabilitation program. The outcomes to be measured are degree of independence of a person in their activities of daily living, assessed by the Barthel Index, motor function, muscle tone of the affected limbs, muscle strength of the affected limbs, balance, gait efficiency, perception of musculoskeletal pain, perception of fatigue, risk of falls, perception of quality of life, and the perception of perceived subjective change after treatment. These outcomes will be evaluated at baseline (T0), at ten weeks (T1) (end of the intervention), and at 18 weeks (T2). The study duration per patient will be 18 weeks (a ten-week intervention, followed by an eight-week intervention follow-up). The analysis will be performed using a mixed linear model (ANOVA 3X3) and significance level p < 0.05. Full article

Stroke-induced motor impairment necessitates objective and quantitative assessment tools for rehabilitation planning. In this study, a gesture-specific framework based on high-density surface electromyography (HD-sEMG) was developed to characterize neuromuscular dysfunction using eight macroscopic features and two microscopic motor unit decomposition features. HD-sEMG recordings were collected from stroke patients (n = 11; affected and unaffected sides) and healthy controls (n = 8; dominant side) during seven standardized hand gestures. Feature-level comparisons revealed hierarchical abnormalities, with the affected side showing significantly reduced activation/coordination relative to healthy controls, while the unaffected side exhibited intermediate deviations. For each gesture, dedicated K-nearest neighbors (KNN) models were constructed for clinical validation. For Brunnstrom stage classification, wrist extension yielded the best performance, achieving 92.08% accuracy and effectively discriminating severe (Stage 4), moderate (Stage 5), and mild (Stage 6) impairment as well as healthy controls. For fine motor recovery prediction, the thumb–index–middle finger pinch provided the optimal regression performance, predicting Upper Extremity Fugl–Meyer Assessment (UE-FMA) scores with R = 0.86 and RMSE = 3.24. These results indicate that gesture selection should be aligned with the clinical endpoint: wrist extension is most informative for gross recovery staging, whereas pinch gestures better capture fine motor control. Overall, the proposed HD-sEMG framework provides an objective approach for monitoring post-stroke recovery and supporting personalized rehabilitation assessment. Full article

Driven by the shipping industry’s pressing need to reduce its environmental impact, methanol has emerged as a promising marine fuel. Methanol-diesel dual-fuel (DF) engines present a viable solution, yet their optimization is challenging due to complex, nonlinear interactions among operational parameters. This study develops an integrated simulation and data-driven framework for multi-objective optimization of a large-bore two-stroke marine DF engine. We first establish a high-fidelity 1D model in GT-POWER, rigorously validated against experimental data with prediction errors within 10% for emissions (NOx, CO, CO₂) and 3% for performance indicators. To address computational constraints, we implement a Polynomial Regression (PR) surrogate model that accurately captures engine response characteristics. The innovative Triple-Adaptive Chaotic Sparrow Search Algorithm (TAC-SSA) serves as the core optimization tool, efficiently exploring the parameter space to generate Pareto-optimal solutions that simultaneously minimize fuel consumption and emissions. The Entropy-Weighted TOPSIS (E-TOPSIS) method then identifies the optimal compromise solution from the Pareto set. At 75% load, the framework determines an optimal configuration: methanol substitution ratio (MSR) = 93.4%; crank angle at the beginning of combustion (CAB) = 2.15 °CA; scavenge air pressure = 1.70 bar; scavenge air temperature = 26.9 °C, achieving concurrent reductions of 7.1% in NOx, 13.3% in CO, 6.1% in CO₂, and 4.1% in specific fuel oil consumption (SFOC) relative to baseline operation. Full article

Background/Objectives: Secondary stroke prevention is a cornerstone of long-term recovery and healthy aging among older adults, yet adherence to preventive strategies remains suboptimal. This global systematic review aimed to synthesize evidence from randomized controlled trials evaluating interventions that support sustained secondary prevention in older adults after stroke. Methods: A systematic search of PubMed and Scopus databases was conducted up to April 2025, following PRISMA 2020 guidelines and registered in PROSPERO (CRD420251177501). Eligible studies included randomized controlled trials targeting adults aged 60 years or older and assessing pharmacological, behavioral, educational, rehabilitative, or technology-assisted interventions for stroke recurrence prevention. Data were narratively synthesized due to study heterogeneity, and methodological quality was appraised using the Cochrane RoB 2 tool. Results: Seventeen randomized trials involving approximately 17,000 participants met the inclusion criteria. Multicomponent programs integrating medication management, behavioral education, exercise, cognitive rehabilitation, and digital support consistently improved adherence, vascular risk control, and quality of life. Pharmacological strategies alone showed limited or transient benefits, underscoring the importance of patient education and sustained follow-up. Common barriers included low motivation, cognitive decline, and technological challenges, while key facilitators were personalized education, multidisciplinary coordination, and culturally adapted implementation. Conclusions: Effective secondary stroke prevention in older adults depends on integrated, person-centered models that combine education, behavioral reinforcement, and technology-assisted monitoring. Structured, continuous educational programs, embedded within rehabilitation and primary care, emerge as the most promising pathway to improve adherence, reduce recurrence, and promote active, autonomous aging. Full article

Unmanned underwater vehicles (UUVs) capable of agile, high-speed maneuvering in complex environments require propulsion systems that can dynamically modulate three-dimensional forces. The California sea lion (Zalophus californianus) provides an exceptional biological model, using its foreflippers to achieve rapid turns and powerful propulsion. However, the specific kinematic mechanisms that govern instantaneous force generation from its powerful foreflippers remain poorly quantified. This study experimentally characterizes the time-varying thrust and lift produced by a bio-robotic sea lion foreflipper to determine how flipper twist, sweep, and phase overlap modulate propulsive forces. A three-degree-of-freedom bio-robotic flipper with a simplified, low-aspect-ratio planform and single compliant hinge was tested in a circulating flow tank, executing parameterized power and paddle strokes in both isolated and combined-phase trials. The time-resolved force data reveal that the propulsive stroke functions as a tunable hybrid system. The power phase acts as a force-vectoring mechanism, where the flipper’s twist angle reorients the resultant vector: thrust is maximized in a broad, robust range peaking near 45°, while lift increases monotonically to 90°. The paddle phase operates as a flow-insensitive, geometrically driven thruster, where twist angle (0° optimal) regulates thrust by altering the presented surface area. In the full stroke, a temporal-phase overlap governs thrust augmentation, while the power-phase twist provides robust steering control. Within the tested inertial flow regime (Re ≈ 10⁴–10⁵), this control map is highly consistent with propulsion dominated by geometric momentum redirection and impulse timing, rather than circulation-based lift. These findings establish a practical, experimentally derived control map linking kinematic inputs to propulsive force vectors, providing a foundation for the design and control of agile, bio-inspired underwater vehicles. Full article

Neurological disorders and cardiovascular disease (CVD) remain leading causes of global morbidity and mortality and often coexist, in part through shared mechanisms of chronic inflammation and oxidative stress. Neuroinflammatory signaling, including microglial activation, cytokine release, and impaired autonomic regulation, contributes to endothelial dysfunction, atherosclerosis, hypertension, and stroke, while cardiac and metabolic disturbances can reciprocally exacerbate brain pathology. Increasing evidence shows that several antidiabetic agents exert pleiotropic anti-inflammatory and antioxidant effects that extend beyond glycemic control. Metformin, SGLT2 inhibitors, DPP-4 inhibitors, and GLP-1 receptor agonists modulate key pathways such as AMPK, NF-κB, Nrf2 activation, and NLRP3 inflammasome suppression, with demonstrated vascular and neuroprotective actions in preclinical models. Clinically, GLP-1 receptor agonists and SGLT2 inhibitors reduce major cardiovascular events, improve systemic inflammatory markers, and show emerging signals for cognitive benefit, while metformin and DPP-4 inhibitors exhibit supportive but less robust evidence. This review synthesizes molecular, preclinical, and clinical data across drug classes, with particular emphasis on GLP-1 receptor agonists, and highlights outstanding translational questions including blood–brain barrier penetration, biomarker development, optimal patient selection, and timing of intervention. We propose a unified framework to guide future trials aimed at leveraging antidiabetic therapies such as DDP-4 anti-inflammatory and antioxidant interventions for neurological and cardiovascular diseases. Full article

Acute injuries to the central nervous system (CNS) share a rapid disruption of arousal, autonomic stability, and neuroimmune balance. Among the neuromodulatory systems affected, the orexin (hypocretin) network is uniquely positioned at the intersection of wakefulness, autonomic control, and motivated behavior. Experimental evidence across ischemic, hemorrhagic, traumatic, and systemic models shows that orexin signaling is sharply suppressed during the early post-injury collapse and gradually recovers as arousal circuits and homeostatic functions stabilize. Controlled enhancement of orexinergic tone has been found to improve arousal state, modulate inflammatory responses, and support behavioral engagement, although these effects are highly dependent on timing, receptor subtype, and physiological context. This review synthesizes evidence from ischemia, hemorrhagic stroke, traumatic brain and spinal cord injury, and systemic inflammatory states, and examines the conceptual and translational rationale for targeting orexin pathways. We summarize available pharmacological, peptide-based, neuromodulatory, and physiological strategies to boost orexinergic tone, highlighting the growing development of selective OX₂ agonists and experimental approaches to enhance endogenous orexin activity. By integrating findings across etiologies within a timing-aware framework, this review addresses a gap in the current literature, which has largely treated these injuries in isolation. While clinical testing in acute CNS injury has not yet been performed, the mechanistic convergence across etiologies suggests that orexinergic modulation may offer a phase-sensitive means to stabilize arousal and support recovery. Taken together, orexin emerges as a state-dependent integrator whose modulation could complement existing therapies by linking early arousal stabilization with longer-term motivational and functional recovery. Full article

Background: Inflammatory bowel disease (IBD) is associated with systemic inflammation and potential cardiovascular complications. This meta-analysis evaluates long-term cardiovascular risks in IBD. Methods: Electronic databases were searched for studies examining cardiovascular, cerebrovascular, and thromboembolic risks in IBD. Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were pooled using a random-effects model. Results: Fifty-three studies comprising 1,406,773 patients were analyzed. IBD was linked to increased risk of ischemic heart disease (aHR 1.25; p = 0.001) myocardial infarction (aHR 1.25; p = 0.01), acute coronary syndrome (aHR 1.43; p < 0.00001), heart failure (aHR 1.24; p < 0.00001), atrial fibrillation (aHR 1.20; p < 0.00001), and stroke (aHR 1.13; p < 0.00001). Elevated risks were also observed for peripheral arterial disease (aHR 1.41; p < 0.00001), diabetes mellitus (aHR 1.40; p < 0.00001), venous thromboembolism (aHR 1.98; p < 0.00001), deep vein thrombosis (aHR 2.85; p = 0.0004), and pulmonary embolism (aHR 1.98; p = 0.03). Importantly, IBD was associated with increased cardiovascular (aHR 1.14; p = 0.03) and all-cause mortality (aHR 1.53; p < 0.00001). Conclusions: IBD patients face higher risk for adverse cardiovascular outcomes, thromboembolic disease, and mortality, necessitating early cardiovascular risk assessment and targeted interventions in this population. Full article

Background/Objectives: This study aimed to evaluate the ability of ChatGPT-5, a multimodal large language model, to perform automated ASPECTS assessment on non-contrast CT (NCCT) in patients with acute ischemic stroke. Methods: This retrospective, single-center study included 199 patients with anterior circulation AIS who underwent baseline NCCT before reperfusion therapy between November 2020 and February 2025. Each NCCT was evaluated by two human readers and by ChatGPT-5 using four representative images (two ganglionic and two supraganglionic). Interobserver agreement was measured with the intraclass correlation coefficient (ICC), and prognostic performance was analyzed using multivariable logistic regression and receiver operating characteristic (ROC) analysis for 3-month functional independence (mRS ≤ 2). Results: ChatGPT-5 demonstrated good-to-excellent agreement with expert consensus (ICC = 0.845; 95% CI, 0.792–0.884; κ = 0.79). ChatGPT-ASPECTS were independently associated with 3-month functional independence (OR = 1.28 per point; p = 0.004), comparable to consensus-ASPECTS (OR = 1.31; p = 0.003). Prognostic discrimination was similar between ChatGPT-5 and consensus scoring (AUC = 0.78 vs. 0.80; p = 0.41). Conclusions: ChatGPT-5 achieved high reliability and strong prognostic validity in automated ASPECTS assessment without task-specific training. These findings highlight the emerging potential of large language models for quantitative image interpretation, though clinical implementation will require multicenter validation and regulatory approval. Full article

In response to the personalized and precise rehabilitation needs for motor injuries and stroke associated with population aging, this study proposes a design method for an intelligent rehabilitation trainer that integrates Bayesian information gain (BIG) and axis matching techniques. Grounded in the biomechanical characteristics of the human ankle joint, the design fully draws upon biomimetic principles, constructing a 3-PUU-R hybrid serial–parallel bionic mechanism. By mimicking the dynamic variation of the ankle’s instantaneous motion axis and its balance between stiffness and compliance, a three-dimensional digital model was developed, and multi-posture human factor simulations were conducted, thereby achieving a rehabilitation process more consistent with natural human movement patterns. Natural randomized disability grade experimental data were collected for 100 people to verify the validity of the design results. On this basis, a Bayesian information gain framework was established by quantifying the reduction of uncertainty in rehabilitation outcomes through characteristic parameters, enabling the dynamic optimization of training strategies for personalized and precise ankle rehabilitation. The rehabilitation process was modeled as a problem of uncertainty quantification and information gain optimization. Prior distributions were constructed using surface EMG (electromyography) signals and motion trajectory errors, and mutual information was used to drive the dynamic adjustment of training strategies, ultimately forming a closed-loop control architecture of “demand perception–strategy optimization–execution adaptation.” This innovative integration of probabilistic modeling and cross-joint bionic design overcomes the limitations of single-joint rehabilitation and provides a new paradigm for the development of intelligent rehabilitation devices. The deep integration mechanism-based dynamic axis matching and Bayesian information gain holds significant theoretical value and engineering application prospects for enhancing the effectiveness of neural plasticity training. Full article

Background: Left atrial appendage (LAA) closure is an alternative to oral anticoagulants (OAC) for stroke prevention in atrial fibrillation (AF), but comparative evidence remains inconsistent. This study systematically evaluates the efficacy and safety of LAA closure versus OAC in AF patients. Methods: We systematically searched PubMed, EmBase, Cochrane Library, and Web of Science for randomized controlled trials (RCTs) and propensity score-matched (PSM) studies published up to 30 September 2025. Treatment effects were estimated using relative risks (RR) with 95% confidence intervals (CI), and a random-effects model was applied for all analyses. Results: Fifteen studies (17,116 AF patients) were included, comprising 4 RCTs, 3 prospective PSM studies, and 8 retrospective PSM studies. Compared with OAC, LAA closure significantly reduced the composite endpoint (RR: 0.79; 95% CI: 0.66–0.95; p = 0.010), all-cause mortality (RR: 0.58; 95% CI: 0.49–0.69; p < 0.001), and cardiovascular mortality (RR: 0.55; 95% CI: 0.44–0.67; p < 0.001). Risks of any stroke (RR: 1.06; 95% CI: 0.86–1.31; p = 0.555), ischemic stroke (RR: 1.00; 95% CI: 0.85–1.17; p = 0.972), hemorrhagic stroke (RR: 0.96; 95% CI: 0.54–1.70; p = 0.879), and major bleeding (RR: 0.84; 95% CI: 0.67–1.04; p = 0.112) were not significantly different between groups. Conclusions: In AF patients, LAA closure significantly reduces mortality and a composite clinical endpoint compared to OAC, with similar risks of stroke and major bleeding. It is a favorable alternative for patients unsuitable for long-term anticoagulation. Full article

Background: This study explored the correlation between lateral ventricle volume asymmetry and cerebral blood flow (CBF). Methods: A retrospective review of 94 patients who underwent CT perfusion (CTP) and standard brain imaging was conducted. Lateral ventricle volumes and CBF across 13 vascular-based regions of interest (ROIs) were measured. Cerebral artery stenosis was identified using magnetic resonance angiography (MRA) and digital subtraction angiography (DSA). Paired t-tests, Pearson’s correlation, logistic regression, and Cox models were used to assess the relationships between lateral ventricle asymmetry, CBF differences, and their associations with cerebral artery stenosis and the risk of stroke during follow-up. Results: 94 patients were included (mean age: 60.7 years). CBF was significantly lower on the side of the larger lateral ventricle in regions supplied by the anterior cerebral artery (ACA) (Mean relative value ± SD, % = 112.3 ± 32.5, p-value = 0.0016) and middle cerebral artery (MCA) (Mean relative value ± SD, % = 123.1 ± 57.8, p-value = 0.0004). A moderate correlation was observed between lateral ventricle volume asymmetry and CBF differences across the entire cohort. Significant associations were identified between CBF differences in specific ROIs and the presence of cerebral artery stenosis (MCA: aOR = 1.026, 95% CI: 1.004–1.048, p-value = 0.019). Conclusions: Lateral ventricle asymmetry is associated with reduced CBF in specific brain regions, particularly those supplied by the ACA. CBF differences in regions supplied by the PCA are linked to increased risk of subsequent stroke during follow-up. Full article