Search Results (198)

This experiment aimed to investigate the effects of replacing alfalfa hay with Glycyrrhiza stem and leaf silage (moisture content: 45%) on rumen in vitro fermentation parameters, nutrient digestibility, and dynamic changes of microbial community composition. In vitro fermentation was conducted with 0% (control group G0A100), 50% (G50A50), and 100% (G100A0) alfalfa hay replaced by semi-dry silage of Glycyrrhiza stems and leaves with 45% moisture content for 72 h. Cumulative gas production (GP), fermentation parameters, microbial community composition at different time points, and post-fermentation nutrient digestibility were determined, with comprehensive evaluation by principal component analysis (PCA) and gray relational analysis (GRA). Results showed that GP of G50A50 and G100A0 was significantly higher than G0A100 at 3 h (p < 0.05), and that of G50A50 was significantly higher than the other two groups at 24 h (p < 0.05). pH of G50A50 was significantly lower than the other two groups at 3 h (p < 0.05). In vitro dry matter digestibility (IVDMD) at 24 h and 72 h, in vitro neutral detergent fiber digestibility (IVNDFD) at 12 h, and in vitro acid detergent fiber digestibility (IVADFD) at 12, 24 and 72 h of G0A100 and G50A50 were significantly higher than G100A0 (p < 0.05). PCA comprehensive scores ranked as G0A100 (0.170) > G50A50 (0.141) > G100A0 (−0.311). GRA comprehensive scores ranked as G50A50 (0.792) > G0A100 (0.756) > G100A0 (0.681). LEfSe analysis indicated distinct microbial biomarkers at 72 h, and KEGG functional profiles were highly consistent among groups. Under the experimental conditions, 50% Glycyrrhiza stem and leaf silage is recommended to replace alfalfa hay in dairy cow diets. Full article

The Longmaxi from the Anchang Syncline in northern Guizhou exhibits a high degree of thermal evolution of organic matter and significant variation in gas content. Because the synclinal is narrow, steep, and internally faulted, the mechanisms controlling shale gas preservation and escape remain poorly understood, complicating development planning and engineering design. Research on oil and gas migration and accumulation mechanisms in synclinal structures is therefore essential. To address this issue, three proportionally scaled strata—pure shale, gray shale, and sandy shale—were fabricated, and faults and artificial fractures with different displacements and inclinations were introduced. The simulation system consisted of two glass tanks (No. 1 and No. 2). Each tank had three rows of eight transmitting electrodes on one side, and a row of eight receiving electrodes on the opposite side. Tank 1 remained fixed, while Tank 2 could be hydraulically tilted up to 65° to simulate air and water migration under varying formation inclinations. A gas-water injection device was connected at the base. Gas was first injected slowly into the model. After injecting a measured volume (recorded via the flowmeter), the system was allowed to rest for 24–48 h to ensure uniform gas distribution. Water was then injected to displace the gas. During displacement, Tank 1 remained horizontal, and Tank 2 was inclined at a preset angle. An embedded monitoring program automatically recorded resistivity data from the 48 electrodes, and water-driven gas migration was analyzed through resistivity changes. A gas escape rate parameter (G_d), based on differences in gas saturation, was developed to quantify escape velocity. The simulation results show that gas escape increased with formation inclination. Beyond a critical angle, the escape rate slowed and approached a maximum. Faults and fractures significantly enhanced gas escape. Full article

Background: Common variable immunodeficiency is a heterogeneous disorder characterized by defects in antibody production and immune dysregulation, associated with infections and autoimmunity. Although structural and cognitive effects of CVID on the central nervous system have attracted attention in recent years, studies jointly addressing volumetric brain imaging and neurocognitive evaluation remain limited. Materials and Methods: In this retrospective cross-sectional study, 35 patients with common variable immunodeficiency and 40 age- and sex-matched healthy controls were evaluated. Cognitive performance was assessed in all participants using the Montreal Cognitive Assessment. High-resolution T1-weighted brain magnetic resonance imaging scans underwent automated segmentation using the volBrain platform, yielding quantitative volumetric measurements of cortical, subcortical, and cerebellar structures, as well as ventricles and cerebrospinal fluid. Intergroup comparisons were performed using independent t-tests and analysis of variance. Results: MoCA scores were significantly lower in patients with CVID. Volumetric analysis revealed prominent reductions in the volumes of total brain tissue, gray matter, cerebrum, cerebellum, limbic system, thalamus, and basal ganglia. Paralleling these findings, cerebrospinal fluid and lateral ventricle volumes were increased. Additional volume losses were detected in CVID patients with low MoCA scores. In CVID patients with autoimmunity, volume loss affected broader areas. Conclusions: CVID appears to be associated with structural brain changes and cognitive impairments. Chronic inflammation and immune dysregulation may contribute to these neurodegenerative processes. Regular neurocognitive monitoring and further prospective studies are warranted in patients with CVID. Full article

Background/Objectives: The rapid diffusion of generative AI has raised concerns about its potential influence on human cognition, particularly during creative work. This pilot study explored task-related associations between generative AI use and facial expression-derived indices that have previously been shown to correlate with gray matter volume in the default mode network (DMN) and central executive network (CEN). Methods: Thirty-three business professionals completed three AI-supported writing tasks involving concept generation, concept combination, and a mixed task. Results: The results showed a statistically robust reduction in the CEN-related facial expression index during the concept combination task, whereas no corrected changes were observed during concept generation or the mixed task. In addition, higher creative self-efficacy was associated with smaller reductions in the CEN-related index. Conclusions: Given the indirect nature of the facial expression measures, the absence of a control condition, and the exploratory design, these findings should be interpreted cautiously and primarily as hypothesis-generating. Future research using controlled designs and direct neuroimaging methods is needed to clarify the cognitive and neural mechanisms underlying AI-assisted creativity. Full article

Early and accurate diagnosis of Alzheimer’s disease is critical for effective clinical intervention, particularly in distinguishing it from mild cognitive impairment, a prodromal stage marked by subtle structural changes. In this study, we propose a hybrid deep learning ensemble framework for Alzheimer’s disease classification using structural magnetic resonance imaging. Gray and white matter slices are used as inputs to three pretrained convolutional neural networks: ResNet50, NASNet, and MobileNet, each fine-tuned through an end-to-end process. To further enhance performance, we incorporate a stacked ensemble learning strategy with a meta-learner and weighted averaging to optimally combine the base models. Evaluated on the Alzheimer’s Disease Neuroimaging Initiative dataset, the proposed method achieves state-of-the-art accuracy of 99.21% for Alzheimer’s disease vs. mild cognitive impairment and 91.02% for mild cognitive impairment vs. normal controls, outperforming conventional transfer learning and baseline ensemble methods. To improve interpretability in image-based diagnostics, we integrate Explainable AI techniques by Gradient-weighted Class Activation Mapping, which generates heatmaps and attribution maps that highlight critical regions in gray and white matter slices, revealing structural biomarkers that influence model decisions. These results highlight the framework’s potential for robust and scalable clinical decision support in neurodegenerative disease diagnostics. Full article

Background and Purpose: Hepatic encephalopathy (HE) is a neuropsychiatric syndrome associated with liver cirrhosis (LC) that often results in cognitive impairment. Minimal HE (mHE), a subtle form of the condition, significantly affects patients’ quality of life. Advanced imaging techniques, such as quantitative susceptibility mapping (QSM), provide new insights into the brain changes associated with HE. Materials and Methods: The study included 28 patients (17 with mHE and 11 without) with alcohol-induced LC and 25 healthy controls. MR imaging, including QSM, was utilized to assess microstructural tissue changes and iron deposition in the brain. Cognitive function was assessed through a neuropsychological test battery. QSM quantified magnetic susceptibility in deep gray matter, while enlarged perivascular spaces (EPVS) were evaluated using T2-weighted images. Statistical analyses, including non-parametric tests and linear regression, assessed differences in susceptibility and their correlation with cognitive performance and EPVS. Results: Significant differences in cognitive performance and brain susceptibility were observed between patients and controls. Patients exhibited lower susceptibility in the caudate nucleus with the accumbens (CNA); mHE patients, in particular, had a significant reduction in CNA susceptibility. Additionally, EPVS grade correlated positively with cognitive decline, suggesting that EPVS may play an essential role in the pathophysiology of mHE. Conclusions: This study demonstrates that QSM can detect subtle brain changes in LC patients, with decreased susceptibility in the CN (caudate nucleus) linked to cognitive impairment in mHE. The role of EPVS in HE warrants further investigation, as it may affect the efficacy of current diagnostic and therapeutic approaches. These findings highlight the potential of QSM to improve HE assessment. Full article

Mild cognitive impairment (MCI) and sarcopenia are prevalent age-related conditions that often coexist and share common mechanisms such as chronic inflammation, reduced neuroplasticity, and impaired muscle function. Resistance exercise training (RET) has emerged as a promising non-pharmacological strategy capable of addressing both physical and cognitive decline. The aim of this narrative review is to synthesize preclinical and clinical evidence on the effects of RET in older adults with MCI and sarcopenia, with a specific focus on its impact on neuroinflammation, cognitive performance and structural brain changes. At the molecular level, RET activates anabolic pathways, including PI3K/Akt/mTOR, enhances neurotrophic support via BDNF, NT-3, and IGF-1, and promotes hippocampal neurogenesis through exercise-induced myokines such as irisin and cathepsin B. RET also exerts immunomodulatory actions by shifting microglia toward anti-inflammatory M2 phenotypes, attenuating reactive astrogliosis, and supporting oligodendrocyte precursor cell differentiation, thereby improving myelin integrity. Neuroimaging studies consistently report preservation of hippocampal and precuneus gray matter, as well as improved white matter connectivity following RET. Clinically, RET has demonstrated significant and sustained improvements in executive function, memory, and global cognition, with effects persisting for up to 18 months. Collectively, RET represents a multifaceted intervention with the potential to delay progression from MCI to Alzheimer’s disease by integrating neuroprotective, anti-inflammatory, and anabolic effects. Standardization of RET protocols and identification of biomarkers of responsiveness are needed to optimize its role within multimodal dementia-prevention strategies. Full article

Background/Objectives: The cerebellum contributes to both motor and cognitive functions. As basketball requires the integration of these abilities, basketball athletes provide an ideal model for exploring cerebellar adaptations. This study aimed to examine multidimensional cerebellar adaptations in basketball athletes and their associations with physical performance. Methods: In this study, 55 high-level basketball athletes and 55 non-athletes matched for age and gender were recruited for multimodal magnetic resonance imaging data collection and physical fitness tests. We compared the structural and functional differences in the brain between the two groups and analyzed the correlations between regional brain indices and physical fitness test outcomes. Results: Basketball athletes exhibited increased gray matter volume in Crus I, alongside heightened ALFF signal in Crus I and improved regional homogeneity in Crus II and VII b compared to non-athletes. Diffusion kurtosis imaging analysis demonstrated that athletes perform elevated kurtosis fractional anisotropy and decreased radial kurtosis within the cerebellar cortex and peduncles, with cortical modifications mainly localized around Crus I and lobule VI. Notably, both kurtosis fractional anisotropy and the amplitude of low-frequency fluctuations displayed positive correlations with vertical jump performance, an indicator specific to basketball ability. Conclusions: Basketball athletes exhibit structural, microstructural, and functional cerebellar adaptations, especially in Crus I. These modifications involve regions associated with motor and cognitive representations within the cerebellum, and part of the indexes are linked to the athletes’ physical performance. This study enhances our understanding of cerebellar adaptive changes in athletes, providing new insights for future research aimed at fully elucidating the role of the cerebellum in these individuals. Full article

Background: Retinal microvascular changes may serve as biomarkers for disease activity in multiple sclerosis (MS). This study evaluated macular and peripapillary vascular plexus densities using optical coherence tomography angiography (OCTA) in patients with relapsing MS (RMS) and healthy controls (HCs), exploring their association with disease activity based on the NEDA-3 concept. Methods: In a cross-sectional study, 117 RMS patients and 37 HCs underwent OCTA imaging. Parameters analyzed included superficial vascular plexus (SVP), deep vascular plexus (DVP), foveal avascular zone (FAZ), and radial peripapillary capillary (RPC) density. Images with artifacts were excluded. Associations between OCTA metrics and demographic, clinical, and MRI volumetrics, as well as NEDA-3 status, were evaluated using multivariate generalized estimating equations. Receiver operating characteristic (ROC) curves assessed predictive capacity. Results: Compared to HCs, MS eyes with prior optic neuritis showed significantly lower SVP density (p < 0.05). DVP and FAZ parameters did not differ between groups. SVP and DVP densities correlated with age, disease duration, relapse history, and MRI volumetrics, including gray matter and whole brain volume. SVP density predicted NEDA-3 status (AUC = 0.82), while DVP also showed predictive value (AUC = 0.64). FAZ FD (Foveal density) was associated with gray matter and whole brain atrophy (AUC = 0.62–0.61). Conclusions: Retinal vascular alterations correlate with clinical and MRI measures in MS. Reduced SVP and DVP densities may serve as markers of recent disease activity, and FAZ metrics reflect neurodegeneration. OCTA may be a valuable non-invasive tool for monitoring MS progression. Full article

The Kavokta deposit in Russia contains gray and black dolomite-type nephrite, which is in high demand commercially. Although the fact that black nephrite has been found in several deposits, the reasons for its color are not well understood. The present study aims to identify the localization and mineral composition of gray and black nephrite, and to determine the reasons for its dark coloration. The mineral composition of nephrite was studied using a scanning electron microscope with energy-dispersive microanalysis (SEM-EDX) and X-ray phase analysis. Also, the isotopic composition of carbon in graphite in nephrite and in carbonates associated with nephrite in the surrounding strata was determined. The gray–black color in most samples from the southeastern part of the Kavokta deposit (lodes 17 and 28 of the nephrite-bearing zone 4 of the Medvezhy section and lode 6-1 of the nephrite-bearing zone 6 of the Levoberezhny section) is due to the presence of graphite. Syngenetic graphite formed both by the organic matter buried in dolomites and by the decomposition of carbon dioxide that is released during decarbonation under the influence of deep-seated hydrogen. The color of nephrite also depends on the iron content, changing from white to light green as the iron content increases. The gray color of tremolite–diopside nephrite is due to the development of chlorite aggregates that replace diopside and/or tremolite. The gray-green to black color of the nephrite in the northwestern part of the Kavokta deposit (lode 1 of the nephrite-bearing zone 1 of the Prozrachny section) is due to the high iron content in the tremolite–actinolite at the contact with the epidote–tremolite skarn formed after amphibolite. The identified patterns of black nephrite localization can be used in the process of geological exploration of similar deposits elsewhere in Russia and abroad. Full article

Background: Despite effective antiretroviral therapy, HIV-associated neurocognitive disorders (HANDs) remain prevalent, highlighting the need for sensitive biomarkers of early brain alterations. Trace-weighted diffusion spectroscopic imaging offers a non-invasive means to assess microstructural changes in brain metabolites in a single shot by measuring apparent diffusion coefficients (ADCs) of total N-acetylaspartate (tNAA), total creatine (tCr), total choline (tCho), and water. Methods: In this study, we used trace-weighted single-shot diffusion-weighted radial echo-planar spectroscopic imaging (DW-RESPI) to investigate metabolite diffusion and relative concentrations in the brains of people living with HIV (PLWH). Using a 3T MRI scanner, we studied 16 PLWH and 15 healthy controls (HCs), and we collected two sets of data with low and high b-values from which metabolite ADCs were computed. Metabolite ratios were derived from the low b-value spectra. A brief neuropsychological assessment evaluated attention, executive function, and memory in a subset of subjects. Cognitive and affective performance was quantified using domain-specific deficit scores, as well as depression and anxiety assessments, offering a comprehensive evaluation of neurobehavioral function. In the male subgroup (N = 15) of PLWH, we calculated the correlations between ADC values and neuropsychological domain scores. Results: tNAA, tCr, tCho, and water ADC values were significantly elevated in multiple gray and white matter regions in PLWH compared to HC, with the most pronounced differences observed in the superior precuneus, anterior cingulate cortex, and corona radiata. Notably, regional ADC values and metabolite ratios showed significant correlations with neuropsychological domain scores. Conclusions: These findings indicate the potential of metabolite and water diffusion metrics as biomarkers for HIV-associated microstructural brain alterations and cognitive impairment. However, the small sample size and preliminary nature of this data warrant further investigation to validate these findings. Full article

A 9.4T brain MRI is the highest resolution MRI scanner in the public market. It offers submillimeter brain imaging with exceptional anatomical detail, making it one of the most powerful tools for detecting subtle structural changes associated with neurological conditions. Current segmentation models are optimized for lower-field MRI (1.5T–3T), and they struggle to perform well on 9.4T data. In this study, we present the GA-MS-UNet++, the world’s first deep learning-based model specifically designed for 9.4T brain MRI segmentation. Our model integrates multi-scale residual blocks, gated skip connections, and spatial channel attention mechanisms to improve both local and global feature extraction. The model was trained and evaluated on 12 patients in the UltraCortex 9.4T dataset and benchmarked against four leading segmentation models (Attention U-Net, Nested U-Net, VDSR, and R2UNet). The GA-MS-UNet++ achieved a state-of-the-art performance across both evaluation sets. When tested against manual, radiologist-reviewed ground truth masks, the model achieved a Dice score of 0.93. On a separate test set using SynthSeg-generated masks as the ground truth, the Dice score was 0.89. Across both evaluations, the model achieved an overall accuracy of 97.29%, precision of 90.02%, and recall of 94.00%. Statistical validation using the Wilcoxon signed-rank test (p < 1 × 10⁻⁵) and Kruskal–Wallis test (H = 26,281.98, p < 1 × 10⁻⁵) confirmed the significance of these results. Qualitative comparisons also showed a near-exact alignment with ground truth masks, particularly in areas such as the ventricles and gray–white matter interfaces. Volumetric validation further demonstrated a high correlation (R² = 0.90) between the predicted and ground truth brain volumes. Despite the limited annotated data, the GA-MS-UNet++ maintained a strong performance and has the potential for clinical use. This algorithm represents the first publicly available segmentation model for 9.4T imaging, providing a powerful tool for high-resolution brain segmentation and driving progress in automated neuroimaging analysis. Full article

Background: The voxel-based specific regional analysis system for Alzheimer’s disease (VSRAD) allows quantitative evaluation of the degree of an individual’s brain atrophy through statistical comparison of brain magnetic resonance imaging (MRI) of their brain to a normative database of healthy Japanese individuals. Currently, the VSRAD is used in routine clinical practice in the diagnosis of Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB). Recent studies using VSRAD have explored its utility in the assessment of brain atrophy associated with various conditions, including diabetes, oral health status, and olfactory dysfunction. This review summarizes the principles of the VSRAD and its foundational method, voxel-based morphometry (VBM), and their clinical and research applications. Methods: This narrative review was conducted by performing a literature search of PubMed to identify articles regarding VBM and the VSRAD that were published between 2005 and 2025. Results: VSRAD yields four indices for quantifying the severity and extent of gray matter atrophy, especially in the medial temporal lobe. Studies have demonstrated its high diagnostic accuracy in distinguishing among AD, mild cognitive impairment (MCI), and DLB. Furthermore, it is correlated with neuropsychological test scores and has been applied to evaluate brain changes associated with diabetes, olfactory dysfunction, and physical inactivity. Motion-corrected MR images, which utilize AI techniques, have also been validated using VSRAD-derived metrics. Conclusions: Quantifying brain atrophy using the VSRAD allows objective evaluation and facilitates the investigation of its association with various diseases. Specifically, VSRAD can be considered a useful adjunctive tool for diagnosing AD and DLB. Full article

Purpose: Focal cortical dysplasia (FCD) is a common developmental malformation disease of the cerebral cortex. Although mounting evidence has suggested that FCD lesions have variable locations and topographies throughout the cortex, few studies have explored consistencies in structural connectivity among different lesion types. In this study, we analyzed microscopic structural changes via lesion analysis and explored structural changes in nonlesion regions across the brain. Methods: Diffusion tensor imaging (DTI) and magnetization transfer imaging were used to compare FCD lesions and contralateral normal appearing gray/white matter (cNAG/WM). Voxel-based morphometry was calculated for 28 children with FCD and 34 sex- and age-matched healthy participants. DTI indices of the FCD and healthy control groups were analyzed via the tract-based spatial statistic method to evaluate the microstructure abnormalities of WM fiber tracts in individuals with FCD. Results: In terms of FCD lesions, compared with those of the cNAG, the fractional anisotropy (FA) values were decreased, and the mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values were increased; the magnetization transfer ratios were also decreased. In terms of whole-brain changes due to FCD, compared with the healthy control group, the FCD group showed a decrease in the volume of the right hippocampus and left anterior cingulate cortex. FCD patients had lower FA values, higher MD values, lower AD values, and mainly increased RD values in relation to WM microstructure. Conclusions: Microstructural abnormalities outside lesion regions may be related to injury to the epileptic network, and the identification of such abnormalities may complement diagnoses of FCD in pediatric patients. Full article

In recent years, research has focused on biomarkers as key tools to predict clinical outcomes and guide therapeutic decisions in Multiple Sclerosis (MS). MicroRNAs (miRs)—small non-coding RNA molecules that regulate gene expression at the post-transcriptional level—have emerged as promising biomarkers in MS due to their accessibility in biological fluids. This study investigates the role of specific serum miRs mainly involved in immune response regulation as potential prognostic biomarkers in MS, focusing on young patients with recent diagnosis. The study had a prospective design, involving a cohort of patients followed in the Hub and Spoke MS network of Verona province. Fifty-one patients (33F) aged 18–40 years with recent MS diagnosis (≤2 years; 45 relapsing-remitting, 6 primary progressive) were consecutively enrolled. At baseline, serum samples were collected for miR analysis alongside clinical-demographic and MRI data, including T2 lesion volume, normalized brain volume (NBV), gray matter volume, white matter volume (WMV) calculated at baseline and annual percentage brain volume change (PBVC) and occurrence of new T2 or gadolinium-enhancing (Gd+) lesions on follow-up scans. Candidate miRs were chosen based on their potential biological role in MS pathogenesis reported in the literature. miRs assays were done using real-time PCR and expressed as a ratio relative to a normalizer (i.e., miR-425-5p). Levels of miR-34a-5p were significantly higher in patients with Gd+ lesions (p < 0.001) and correlated to lower NBV (rho = −0.454, p = 0.001) and WMV (rho = −0.494, p < 0.001). Conversely, miR-140-5p exhibited a protective effect against occurrence of new T2 or Gd+ lesions over time (HR 0.43; IC 95% 0.19–0.99; p = 0.048). Additionally, miR-30b-5p correlated directly with PBVC (adjusted rho = −0.646; p < 0.001). These findings support the potential of serum miR-34a-5p, miR-140-5p, and miR-30b-5p as markers of disease activity and progression in patients with recently diagnosed MS. Full article