Search Results (1,120)

Background/Objectives: The spinal cord is a critical component of the central nervous system that transmits neural signals between the brain and the body’s peripheral regions through its nerve roots. Despite being partially protected by the vertebral column, the spinal cord remains highly vulnerable to trauma, tumors, infections, and degenerative or inflammatory disorders. These conditions can disrupt neural conduction, resulting in severe functional impairments, such as paralysis, motor deficits, and sensory loss. Therefore, accurate and comprehensive spinal cord segmentation is essential for characterizing its structural features and evaluating neural integrity. Methods: In this study, we propose a fully automated method for segmentation of the cervical spinal cord in sagittal magnetic resonance (MR) images. This method facilitates rapid clinical evaluation and supports early diagnosis. Our approach uses a Swin-Unet architecture, which integrates vision transformer blocks into the U-Net framework. This enables the model to capture both local anatomical details and global contextual information. This design improves the delineation of the thin, curved, low-contrast cervical cord, resulting in more precise and robust segmentation. Results: In experimental studies, the proposed Swin-Unet model (SWU1), which uses transformer blocks in the encoder layer, achieved Dice Similarity Coefficient (DSC) and Hausdorff Distance 95 (HD95) scores of 0.9526 and 1.0707 mm, respectively, for cervical spinal cord segmentation. These results confirm that the model can consistently deliver precise, pixel-level delineations that are structurally accurate, which supports its reliability for clinical assessment. Conclusions: The attention-enhanced Swin-Unet architecture demonstrated high accuracy in segmenting thin and complex anatomical structures, such as the cervical spinal cord. Its ability to generalize with limited data highlights its potential for integration into clinical workflows to support diagnosis, monitoring, and treatment planning. Full article

Background/Objectives: Patients with non-valvular heart failure frequently develop valvular disease. However, the prevalence of valvular disease across patients with different heart failure etiologies remains underexplored. This study aimed to investigate the burden of VHD among patients with non-valvular heart failure, and secondly evaluate its association with cardiopulmonary test. Methods: We analyzed data from patients with non-valvular heart failure (HF) who were evaluated as outpatients at the HF clinic between February 2020 and November 2024. Patients were categorized into three groups: coronary artery disease-related HF (CAD-HF), dilated cardiomyopathy (DCM), and other causes (e.g., hypertension, diabetes, and various cardiomyopathies). Demographic and clinical characteristics, as well as echocardiographic and cardiopulmonary exercise testing (CPET) results, were evaluated. Results: Among all groups mild mitral regurgitation (MR) was the most common valvular disease, followed by mild tricuspid regurgitation (TR). Patients with CAD-HF frequently had mild aortic regurgitation (AR) compared to DCM (23.6% vs. 14.9%, p = 0.05). In the CPET subgroup, which included 41 patients who consented to participate, in patients with moderate-to-severe VHD had significantly lower VO₂/HR (oxygen pulse), VO₂max, and OUES, indicating worsened functional capacity despite similar left ventricular ejection fraction. Hypertension and atrial fibrillation were independently associated with greater valvular disease severity on multivariable analysis. Conclusions: No significant differences in valvular disease between patients with DCM and CAD-HF were documented, apart from a higher prevalence of mild AR in the CAD-HF group. Patients with moderate-to-severe valvular regurgitation demonstrated worse cardiopulmonary performance, regardless of ejection fraction, highlighting the important role of CPET in evaluating the functional impact of valvular heart disease in this population. Full article

Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter in the vertebrate central nervous system, known for its role in promoting sleep, reducing anxiety, regulating blood pressure, and modulating stress, cognition, and behavior. Microbial fermentation offers an effective method for GABA production, with certain lactic acid bacteria (LAB) strains recognized as efficient producers. This study assessed the GABA-producing potential of 31 LAB strains, including isolates from traditional Bulgarian foods and plants. The strains were cultivated in an MRS medium supplemented with 1% monosodium glutamate (MSG), and GABA production was quantified using HPLC after derivatization with dansyl chloride. Most strains produced between 200 and 300 mg/L of GABA. However, Levilactobacillus brevis NCTC 13768 showed much higher productivity, reaching 3830.7 mg/L. To further evaluate its capacity, L. brevis NCTC 13768 was cultivated for 168 h in MRS medium with and without MSG. Without MSG, GABA production peaked at 371.0 mg/L during the late exponential phase. In contrast with MSG, GABA levels steadily increased, reaching 3333.6 mg/L after 168 h. RT-qPCR analyses of the glutamic acid decarboxylase (GAD) system showed that the genes of glutamate decarboxylase (gadB), glutamate-GABA antiporter (gadC), and transcriptional regulator (gadR) are significantly overexpressed when the culture reaches the late stationary phase of growth (96 h after the beginning of cultivation). These results identify L. brevis NCTC 13768 as a high-yield GABA producer, with potential applications in the production of fermented functional foods and beverages. Full article

The habitat landscape pattern of Mrs Hume’s pheasant in Jinzhongshan, northwestern Guangxi, was studied using field survey data and the LANDSAT satellite images by the ArcGIS 10.8 and Fragstats 3.3 software. The results showed that the Jinzhongshan region covers 38,716.6 hm², including 1708 patches and 11 landscape types. Although the area of farmland and village only occupies 10%, their number and density have led Jinzhongshan habitats to fragment. The degree of connection of suitable habitat was found to be relatively low, and seven landscape indices were below 0.5, which implied that the extent of habitat fragmentation in Jinzhongshan for Mrs Hume’s Pheasant is very high. The fragmentation index of Jinzhongshan Nature Reserve is 0.9887, landscape connectivity is 1.861, and AWS index is 425.3024. The broad-leaved forest, considered a matrix in the Jinzhongshan area, was the dominant landscape type controlling structure, function, and dynamic changes. The total suitable habitat of Mrs Hume’s pheasant (Syrmaticus humiae) was determined to be 29,552.3 hm², accounting for 76.3% of the total study area; the suitable habitat of Mrs Hume’s pheasant in Jinzhongshan Nature Reserve was determined to be 16,990.1 hm², accounting for 81.14% of the protected area. It is absolutely necessary and urgent to strengthen the management and protection of Mrs Hume’s pheasant’s habitat to control its fragmentation. Therefore, we have provided some useful advice, such as habitat restoration and corridor reconstruction, which are beneficial to the conservation of Mrs Hume’s pheasant in this sensitive region. Full article

Reperfusion therapy uses thrombolysis and clot removal to restore blood flow in the brain after stroke; however, three months after reperfusion therapy, roughly 46% of stroke patients become independent again. MiRNAs (micro RNA) regulate cerebral ischemia/reperfusion injury, and their transfer between cells via exosomes may differentially affect recipient cells. We examined serum exosomal miRNA levels, stroke treatments, and functional outcomes in stroke patients, and we explored the potential role of estimated differentially expressed miRNA (DEmiRNA) target genes in the brain’s reaction to reperfusion after ischemia. The patients in the study received aspirin or reperfusion therapy with either intravenous thrombolysis (rt-PA), mechanical thrombectomy (MT), or a combination of both (rt-PA/MT). Serum samples were collected from stroke patients on days 1 and 10 post-stroke. Serum exosomes’ miRNA was analyzed using qRT-PCR. We identified DEmiRNAs, estimated their targets, and performed enrichment analysis. Functional outcomes were assessed using the modified Rankin Scale (mRS) on days 10 and 90 post-stroke. Among studied treatments, only rt-PA/MT lowered DEmiRNA by day 10 vs. other groups. Specifically, patients with unfavorable mRS score exhibited decreased levels of miR-17, miR-20, miR-186 and miR-222 after combined stroke therapy. Functional analysis identified target genes and pathways associated with cytoskeleton remodeling, cell death, autophagy, inflammation, and dementia. In conclusion, unfavorable stroke outcomes following poor rt-PA/MT response could result from lower miRNA expression levels, thus activating cell death and neurodegenerative processes in brain. Full article

Optimizing pavement maintenance and rehabilitation (M&R) strategies is essential, especially in developing countries with limited budgets. This study presents an integrated framework combining a deterioration prediction model and a genetic algorithm (GA)-based optimization model to plan cost-effective M&R strategies for flexible pavements, including asphalt concrete (AC) and double bituminous surface treatment (DBST). The GA schedules multi-year interventions by accounting for varied deterioration rates and budget constraints to maximize pavement performance. The optimization process involves generating a population of candidate solutions representing a set of selected road sections for maintenance, followed by fitness evaluation and solution evolution. A mixed Markov hazard (MMH) model is used to model uncertainty in pavement deterioration, simulating condition transitions influenced by pavement bearing capacity, traffic load, and environmental factors. The MMH model employs an exponential hazard function and Bayesian inference via Markov Chain Monte Carlo (MCMC) to estimate deterioration rates and life expectancies. A case study on Cambodia’s road network evaluates six budget scenarios (USD 12–27 million) over a 10-year period, identifying the USD 18 million budget as the most effective. The framework enables road agencies to access maintenance strategies under various financial and performance conditions, supporting data-driven, sustainable infrastructure management and optimal fund allocation. Full article

Background: The progression of cognitive decline is accelerated in older adults with sarcopenia, but the protective dietary factors have remained uncertain. Objective: This study aims to investigate the association between dietary factors and cognitive decline in older adults, and to explore the potential mediating effects of sarcopenic components. Methods: Data from the Mr. OS and Ms. OS cohort study in Hong Kong (N = 3146, aged ≥65 years) were used. Cognitive function was assessed based on the Mini-Mental State Examination (MMSE). Sarcopenic status was assessed according to the Asian Working Group for Sarcopenia 2019 updated consensus. Dietary protein intake and adherence to dietary patterns were assessed using a food frequency questionnaire. Linear regression was used to examine the associations between dietary factors and MMSE scores. Mediation analysis was conducted to identify the possible mediators in the diet–cognition associations. Results: Sarcopenia and its components were associated with baseline MMSE and MMSE changes. Positive associations were observed for plant protein intake (β = 0.79, 95% CI 0.24–1.35) and dietary patterns such as the Dietary Approaches to Stop Hypertension (DASH) diet (β = 0.14, 95% CI 0.02–0.26) and diets with lower Dietary Inflammatory Index (DII) scores (β = −0.18, 95% CI −0.26–−0.09) with better MMSE outcomes. Protective effects were more profound in participants with sarcopenia/severe sarcopenia. The effects of the DASH diet and DII were more profound in female participants, while higher adherence to the Mediterranean–DASH Intervention for Neurodegenerative Delay (MIND) diet was associated with an increment in MMSE score in male participants with sarcopenia. Handgrip strength and physical performance are significant mediators in the diet–cognition associations. Conclusions: The protective effects of healthy dietary patterns were beneficial, especially for participants with sarcopenia, while handgrip strength and walking speed potentially mediated the associations. Full article

Background/Objectives: Stroke remains a leading cause of disability in Japan, and early mobilization is an important strategy to prevent muscle atrophy and promote independence. However, the optimal intensity and duration of early rehabilitation remain unclear. This study aims to examine the association between rehabilitation dose during the acute phase of stroke and functional outcomes at 90 days post-onset. Methods: This multicenter prospective cohort study will enroll patients from twelve acute care hospitals across Japan, beginning in June 2026. Eligible patients are aged ≥ 18 years, expected to be hospitalized for ≥7 days, and initiated rehabilitation by day 2 after stroke onset. Rehabilitation dose will be quantified using the Mobilization Quantification Score (MQS). The primary outcome is functional status measured by the modified Rankin Scale (mRS) at 90 days. Secondary outcomes include muscle atrophy assessed by ultrasound, the Barthel Index, and physical performance measures. Subgroup analyses will evaluate how stroke severity modifies the dose–response relationship. Results: As this is a study protocol, results are not yet available. The study is designed to clarify the relationship between early rehabilitation dose and functional recovery after stroke. Conclusions: This is the first large-scale Japanese study to assess early stroke rehabilitation dosage using a standardized tool. Findings are expected to provide evidence for individualized, evidence-based mobilization strategies to optimize functional outcomes in stroke patients. Full article

Parkinson’s Disease (PD) is the fastest-growing neurological disorder, characterized by the degeneration of dopaminergic neurons. Treatments remain symptomatic, and objective biomarkers for therapeutic response are lacking. This review aims to evaluate the potential of Proton Magnetic Resonance Spectroscopy (¹H-MRS) to provide objective and reproducible biomarkers for monitoring treatment response in PD. This systematic review followed PRISMA guidelines. Articles were searched in PubMed, Web of Science, Scopus, and Embase, and studies employing ¹H-MRS to evaluate pharmacological treatments in PD were included, analyzing pre- and post-treatment changes. Six studies were included, investigating cannabinoids, dopamine agonists, monoamine oxidase B inhibitors, and levodopa. Key metabolites analyzed were N-acetylaspartate, Creatine, Choline, myo-Inositol, and Glx (glutamate+glutamine). Increases in NAA, a marker of neuronal integrity and mitochondrial function, suggested neuroprotective mechanisms of dopaminergic drugs, while stable Cho and mI levels, markers of membrane metabolism and inflammatory processes, suggested limited short-term responsiveness. This is the first systematic review evaluating ¹H-MRS for monitoring neurometabolic changes induced by pharmacological treatments in PD. Observed metabolite changes appear to reflect treatment mechanisms and potential neuroprotective properties. Findings suggest that ¹H-MRS may serve as an objective biomarker for assessing therapeutic efficacy and potential neuroprotective drug effects, although further studies are needed to confirm its clinical utility. Full article

Background/Objectives: Acute ischemic stroke (AIS) remains a major cause of morbidity and mortality worldwide. Although advanced imaging modalities, such as CT perfusion (CTP), are increasingly being used in clinical decision-making, the necessity and added value of perfusion imaging prior to intravenous thrombolysis (IVT) within early time windows remains uncertain. We aim to evaluate the safety and functional outcomes of IVT in AIS patients without perfusion deficits on CTP. We question the requirement of perfusion mismatch for IVT eligibility and hypothesize that IVT is safe and beneficial even in the absence of a perfusion deficit. Methods: A retrospective analysis was conducted using data from the Giessen Stroke Registry, focusing on AIS patients who underwent CTP imaging and received IVT between 01/2018 and 12/2020. Patients who underwent endovascular therapy were excluded. Clinical data, including demographics, National Institutes of Health Stroke Scale (NIHSS) scores, modified Rankin Scale (mRS) scores, and complications, were collected. Patients were dichotomized based on the presence of perfusion lesions and compared in terms of efficacy outcomes (i.e., NIHSS or mRS improvement during the hospital stay) and safety outcomes (i.e., post-thrombolytic hemorrhagic complications). Results: Of the 89 AIS patients with available CTP data who received IVT, 34 (38%) had a perfusion deficit and 55 (62%) did not. There were no significant differences between the groups in terms of hemorrhagic complications or functional outcomes at discharge (NIHSS and mRS). Clinical improvement from admission to discharge was similar in both groups. Conclusions: Our findings suggest that IVT is safe and clinically effective even in AIS patients without detectable perfusion deficits on CTP within the standard therapeutic window. These results support current guideline recommendations that do not mandate perfusion imaging for early presenters. Routine use of CTP in this context may be of limited clinical utility and could unnecessarily delay treatment or introduce additional risks in the first 4.5 h. Full article

Background and Objectives: Stroke is widely recognised for its physical consequences. However, cognitive and emotional impairments, such as depression, anxiety, and vascular cognitive impairment (VCI), are often under-recognised and under-treated. Our study aimed to identify and characterise cognitive and emotional sequelae in patients hospitalised for acute ischemic stroke. Materials and Methods: We conducted a cross-sectional study involving 73 patients within seven days of an acute ischemic stroke. Patients were assessed using the National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), Montreal Cognitive Assessment (MoCA), Hachinski Ischemic Score (HIS), and the Clinical Assessment of Depression (CAD) questionnaire, which includes four subscales (Depressed Mood (DM), Anxiety/Worry, Disinterest, and Physical Fatigue). K-means clustering was applied to ten standardised clinical and psychometric variables. In addition, multiple linear regression was performed to determine independent predictors of cognitive and affective outcomes, with MoCA and CAD-DM as dependent variables. Results: Three distinct patient profiles emerged: (1) Mild Impairment Profile, characterised by minimal cognitive or emotional symptoms; (2) Depressive Profile, marked by elevated emotional symptom scores despite mild physical impairment; and (3) Vascular Cognitive Impairment Profile, comprising older patients with the most severe cognitive and functional deficits. ANOVA confirmed significant differences between groups in NIHSS, mRS, MoCA, HIS, and CAD scores, but not for age or education. Linear regression revealed that older age (β = –0.10, p = 0.012) and higher NIHSS at discharge (β = –0.72, p = 0.020) predicted lower MoCA scores, whereas years of education (β = 0.58, p = 0.013) predicted better cognition (R² = 0.29). No demographic or clinical factors predicted depressive symptoms (all p > 0.29). Conclusions: Our study highlights the heterogeneity of post-stroke outcomes. Neuropsychiatric impairments may be present even in patients with minimal physical deficits and require targeted evaluation and management. Full article

Background: Hemiplegic cerebral palsy (HCP) is a motor dysfunction disorder resulting from perinatal developmental brain injury, predominantly impairing upper limb function in children. Nonetheless, there has been insufficient research on the brain activation patterns and inter-brain coordination mechanisms of HCP children when performing motor control tasks, especially in contrast to children with typical development(CD). Objective: This cross-sectional study employed functional near-infrared spectroscopy (fNIRS) to systematically compare the cerebral blood flow dynamics and brain network characteristics of HCP children and CD children while performing upper-limb mirror training tasks. Methods: The study ultimately included 14 HCP children and 28 CD children. fNIRS technology was utilized to record changes in oxygenated hemoglobin (HbO) signals in the bilateral prefrontal cortex (LPFC/RPFC) and motor cortex (LMC/RMC) of the subjects while they performed mirror training tasks. Generalized linear model (GLM) analysis was used to compare differences in activation intensity between HCP children and CD children in the prefrontal cortex and motor cortex. Finally, conditional Granger causality (GC) analysis was applied to construct a directed brain network model, enabling directional analysis of causal interactions between different brain regions. Results: Brain activation: HCP children showed weaker LPFC activation than CD children in the NMR task (t = −2.032, p = 0.049); enhanced LMC activation in the NML task (t = 2.202, p = 0.033); and reduced RMC activation in the MR task (t = −2.234, p = 0.031). Intragroup comparisons revealed significant differences in LMC activation between the NMR and NML tasks (M = −1.128 ± 2.764, t = −1.527, p = 0.025) and increased separation in RMC activation between the MR and ML tasks (M = −1.674 ± 2.584, t = −2.425, p = 0.031). Cortical effective connectivity: HCP group RPFC → RMC connectivity was weaker than that in CD children in the NMR/NML tasks (NMR: t = −2.491, p = 0.018; NML: t = −2.386, p = 0.023); RMC → LMC connectivity was weakened in the NMR task (t = −2.395, p = 0.022). Conclusions: This study reveals that children with HCP exhibit distinct abnormal characteristics in both cortical activation patterns and effective brain network connectivity during upper limb mirror training tasks, compared to children with CD. These characteristic alterations may reflect the neural mechanisms underlying motor control deficits in HCP children, involving deficits in prefrontal regulatory function and compensatory reorganization of the motor cortex. The identified fNIRS indicators provide new insights into understanding brain dysfunction in HCP and may offer objective evidence for research into personalized, precision-based neurorehabilitation intervention strategies. Full article

Background: A deregulated aldosterone (Aldo)–mineralocorticoid receptor (MR) pathway is linked to cardiovascular disease (CVD), including hypertension and heart failure. Despite the association of elevated plasma Aldo levels with cardiac stress, inflammation, myocardial fibrosis, and cardiac remodeling, the underlying mechanisms remain elusive. Methods: To study the impact of Aldo–MR pathway overactivation on cardiac health, a novel mouse model with AAV9-mediated MR overexpression and Aldo administration via subcutaneous osmotic pumps was generated. Echocardiographic analyses, transcriptome sequencing, and loss-of-function experiments of an identified lead candidate gene were performed. Additionally, cardiac tissue samples from human patients with end-stage heart failure were analyzed in the study. Results: Mice with an overactivated Aldo–MR pathway exhibited increased neutrophil gelatinase-associated lipocalin (NGAL) expression, cardiac dysfunction, hypertrophy, and fibrosis. Transcriptomics identified prostaglandin D₂ synthase (Ptgds) as a novel downstream effector of the cardiac Aldo–MR pathway. SiRNA-mediated inhibition of Ptgds in primary cardiomyocytes reduced NGAL levels and the hypertrophic impact of Aldo, suggesting a role in mediating Aldo-induced cardiac pathologies. Elevated expression of PTGDS was observed in hiPSC-CMs treated with the pro-hypertrophic cytokine leukemia inhibitory factor (LIF) and in end-stage heart failure patients, ascertaining its importance in cardiac disease settings. Conclusions: PTGDS is a newly identified mediator of Aldo–MR-induced cardiac remodeling and may represent a potential therapeutic target for CVD. Full article

Accurate detection and counting of rice ears serve as a critical indicator for yield estimation, but the complex conditions of paddy fields limit the efficiency and precision of traditional sampling methods. We propose REU-YOLO, a model specifically designed for UAV low-altitude remote sensing to collect images of rice ears, to address issues such as high-density and complex spatial distribution with occlusion in field scenes. Initially, we combine the Additive Block containing Convolutional Additive Self-attention (CAS) and Convolutional Gated Linear Unit (CGLU) to propose a novel module called Additive-CGLU-C2F (AC-C2f) as a replacement for the original C2f in YOLOv8. It can capture the contextual information between different regions of images and improve the feature extraction ability of the model, introduce the Dropblock strategy to reduce model overfitting, and replace the original SPPF module with the SPPFCSPC-G module to enhance feature representation and improve the capacity of the model to extract features across varying scales. We further propose a feature fusion network called Multi-branch Bidirectional Feature Pyramid Network (MBiFPN), which introduces a small object detection head and adjusts the head to focus more on small and medium-sized rice ear targets. By using adaptive average pooling and bidirectional weighted feature fusion, shallow and deep features are dynamically fused to enhance the robustness of the model. Finally, the Inner-PloU loss function is introduced to improve the adaptability of the model to rice ear morphology. In the self-developed dataset UAVR, REU-YOLO achieves a precision (P) of 90.76%, a recall (R) of 86.94%, an mAP_0.5 of 93.51%, and an mAP_0.5:0.95 of 78.45%, which are 4.22%, 3.76%, 4.85%, and 8.27% higher than the corresponding values obtained with YOLOv8 s, respectively. Furthermore, three public datasets, DRPD, MrMT, and GWHD, were used to perform a comprehensive evaluation of REU-YOLO. The results show that REU-YOLO indicates great generalization capabilities and more stable detection performance. Full article

Metabolic imaging is undergoing a fundamental transformation. Traditionally confined to static representations of metabolite distribution through modalities such as PET, MRS, and MSOT, imaging has offered only partial glimpses into the dynamic and systemic nature of metabolism. This Perspective envisions a shift toward dynamic metabolic intelligence—an integrated framework where real-time imaging is fused with physics-informed models, artificial intelligence, and wearable data to create adaptive, predictive representations of metabolic function. We explore how novel technologies like hyperpolarized MRI and time-resolved optoacoustics can serve as dynamic inputs into digital twin systems, enabling closed-loop feedback that not only visualizes but actively guides clinical decisions. From early detection of metabolic drift to in silico therapy simulation, we highlight translational pathways across oncology, cardiology, neurology, and space medicine. Finally, we call for a cross-disciplinary effort to standardize, validate, and ethically implement these systems, marking the emergence of a new paradigm: metabolism as a navigable, model-informed space of precision medicine. Full article