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Autism Spectrum Disorder (ASD) is a complex and multifactorial neurodevelopmental condition whose pathogenesis remains only partially elucidated. Earlier accounts of oxidative stress in ASD often relied on the reductive paradigm of an imbalance between oxidants and antioxidants. In contrast, this narrative review, based on a systematic examination of 1102 publications indexed in scientific databases from 2002 to July 2025, reframes the discussion in terms of redox system dysfunction, a broader and more integrative construct. Here, reactive oxidant species, molecular targets, and reducing/antioxidant counterparts are considered elements of a dynamic circuitry whose maladaptation progressively undermines homeostasis. The sequence of events unfolds in three stages. The first is primary redox dysfunction, manifesting as alterations in metabolic, signaling, and defense pathways. From this disturbance, a second stage arises, marked by functional derailment of cellular compartments—from membranes and cytosol to organelles and nuclei—including mitochondrial and peroxisomal deficits. Ultimately, a third stage emerges, defined by neurodevelopmental alterations such as impaired neurotransmission, synaptic dysfunction, abnormal plasticity, morphogenetic defects, neuroinflammation, and gut–brain–microbiota disarrangements. This progression situates the redox system as a central hub at the interface between human cells and the microbiota, resonating with the ecological and evolutionary principles of the holobiont and the One Health framework. By weaving dispersed evidence into a coherent perspective, this review advances beyond previous analyses, offering a unifying paradigm that connects biochemical dysfunction to clinical heterogeneity in ASD and opens new directions for interdisciplinary research. Full article

Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by significant neurological plasticity in early childhood, where timely interventions like behavioral therapy, language training, and social skills development can mitigate symptoms. Contributions: We introduce a novel Multi-Atlas Guided Multi-View Contrast Learning (MAMVCL) framework for ASD classification, leveraging functional connectivity (FC) matrices from multiple brain atlases to enhance diagnostic accuracy. Methodology: The MAMVCL framework integrates imaging and phenotypic data through a population graph, where node features derive from imaging data, edge indices are based on similarity scoring matrices, and edge weights reflect phenotypic similarities. Graph convolution extracts global field-of-view features. Concurrently, a Target-aware attention aggregator processes FC matrices to capture high-order brain region dependencies, yielding local field-of-view features. To ensure consistency in subject characteristics, we employ a graph contrastive learning strategy that aligns global and local feature representations. Results: Experimental results on the ABIDE-I dataset demonstrate that our model achieves an accuracy of 85.71%, outperforming most existing methods and confirming its effectiveness. Implications: The proposed model demonstrates superior performance in ASD classification, highlighting the potential of multi-atlas and multi-view learning for improving diagnostic precision and supporting early intervention strategies. Full article

Glioblastoma multiforme (GBM) is an aggressive brain cancer characterized by highly invasive growth driven by glial-mesenchymal transition (GMT). Given the urgent need for effective therapies targeting this process, we aimed to discover potential GMT inhibitors using transcriptomic-based repurposing applied to both approved and experimental drugs. Deep bioinformatic analysis of transcriptomic data from GBM patient tumors and GBM cell lines with mesenchymal phenotype using gene set variation analysis (GSVA), weighted gene co-expression network analysis (WGCNA), reconstruction of GMT-related gene association networks, gene set enrichment analysis (GSEA), and the search for correlation with transcriptomic profiles of known GMT markers, revealed a novel 31-gene GMT signature applicable as relevant input data for the connectivity map-based drug repurposing study. Using this gene signature, a number of small-molecule compounds were predicted as potent anti-GMT agents. Further ranking according to their blood–brain barrier permeability, as well as structural and transcriptomic similarities to known anti-GBM drugs, revealed SP600125, vemurafenib, FG-7142, dibenzoylmethane, and phensuximide as the most promising for GMT inhibition. In vitro validation showed that SP600125, which is most closely associated with GMT-related hub genes, effectively inhibited TGF-β1- and chemical hypoxia-induced GMT in U87 GBM cells by reducing morphological changes, migration, vasculogenic mimicry, and mesenchymal marker expression. These results clearly demonstrate the applicability of connectivity mapping as a powerful tool to accelerate the discovery of effective GMT-targeting therapies for GBM and significantly expand our understanding of the antitumor potential of SP600125. Full article

Background: Larger brains are believed to rely more heavily on intra-hemispheric than inter-hemispheric processing, which may lead to a proportionally reduced callosal size. Methods: To test this hypothesis, we used T1-weighted magnetic resonance images from a large population sample (n = 38,034). The sample was drawn from the UK Biobank and included 19,947 females and 18,087 males, aged between 44 and 83 years (mean ± SD: 64 ± 7.72 years). Linear modelling was used to assess the relationship between proportional callosal volume and total intracranial volume, with sex, age, and handedness included as covariates and interaction terms. Results: We observed a significant negative relationship between proportional callosal volume and total brain volume, such that larger brains had proportionally smaller corpora callosa. Conclusion: These findings support the hypothesis that increasing brain size is associated with reduced inter-hemispheric connectivity, potentially due to conduction constraints that promote greater intra-hemispheric processing in larger brains. Full article

Traumatic brain injury (TBI) results in a cascade of neuropathological events, which can significantly disrupt synaptic integrity. This review explores the acute, subacute and chronic phases of synaptic dysfunction and loss in trauma which commence post-TBI, and their contribution to the subsequent neurological sequelae. Central to these disruptions is the loss of dendritic spines and impaired synaptic plasticity, which compromise neuronal connectivity and signal transmission. During the acute phase of TBI, mechanical injury triggers presynaptic glutamate secretion and Ca²⁺ ion-mediated excitotoxic injury, accompanied by cerebral edema, mitochondrial dysfunction and the loss of the mushroom-shaped architecture of the dendritic spines. The subacute phase is marked by continued glutamate excitotoxicity and GABAergic disruption, along with neuroinflammatory pathology and autophagy. In the chronic phase, long-term structural remodeling and reduced synaptic densities are evident. These chronic alterations underlie persistent cognitive and memory deficits, mood disturbances and the development of post-traumatic epilepsy. Understanding the phase-specific progression of TBI-related synaptic dysfunction is essential for targeted interventions. Novel therapeutic strategies primarily focus on how to effectively counter acute excitotoxicity and neuroinflammatory cascades. Future approaches may benefit from boosting synaptic repair and modulating neurotransmitter systems in a phase-specific manner, thereby mitigating the long-term impact of TBI on neuronal function. Full article

Alcohol-associated liver disease (ALD) includes a spectrum from steatosis and steatohepatitis to cirrhosis and hepatocellular carcinoma driven by oxidative stress, immune activation, and systemic inflammation. Ethanol metabolism through alcohol dehydrogenase, aldehyde dehydrogenase, and cytochrome P450 2E1 generates reactive oxygen and nitrogen species, leading to mitochondrial dysfunction, hepatocellular injury, and activation of inflammatory and fibrogenic pathways. Beyond hepatic effects, ALD engages the gut–liver–brain axis, where microbial dysbiosis, blood–brain barrier disruption, and neuroinflammation contribute to cognitive impairment and cerebrovascular risk. The emerging concept, metabolic dysfunction-associated steatotic liver disease and increased alcohol intake (MetALD), presents the synergistic impact of alcohol and metabolic comorbidities, enhancing oxidative injury and fibrosis. This review summarizes key mechanisms connecting oxidative stress to multisystem pathology and highlights the need for precision therapies targeting redox imbalance, immune dysregulation, and gut–brain–liver interactions to improve outcomes in ALD and MetALD. Full article

Canine distemper virus (CDV) is a serious and often fatal disease caused by Morbillivirus canis, which affects domestic dogs and wild carnivores, with case-fatality rates reaching up to 47%. The hemagglutinin (H) protein mediates viral adsorption and shows high genetic variability, making it a valuable molecular marker. This study aimed to detect and characterize the H gene of CDV strains from 14 dogs with fatal neurological disease in the Brazilian states of Mato Grosso and Rondônia. Brain tissue was tested via RT-PCR for the nucleocapsid gene, and positive samples were amplified for the H gene. Ten complete H-gene sequences were obtained. Phylogenetic analysis revealed two distinct clusters within the South America I/Europe lineage: one related to strains from Uruguay and Argentina (with residues 530G/549Y) and another related to Brazilian strains (530S/549Y). One sequence (MT8) showed an intermediate position in the haplotype network but clustered phylogenetically with Uruguay/Argentina-related strains. Most sequences carried 530S/549Y, a pattern linked to altered SLAM receptor usage in wildlife. These findings demonstrate the co-circulation of two CDV clusters in Central–Western Brazil, their regional and international genetic connectivity, and amino acid substitutions potentially influencing host adaptation and antigenicity. Full article

The pursuit of a comprehensive understanding of human consciousness, which includes the subjective experience of perception, is a long-standing endeavor. A multitude of disciplines have sought to elucidate and define consciousness, with a particular emphasis on its etiology. What is the cause of consciousness? One particularly eye-opening idea is that humans attempt to identify the source of consciousness by leveraging their own consciousness, as if something is attempting to elucidate itself. Strikingly, the results of brain-imaging experiments indicate that the brain processes a considerable amount of information outside conscious awareness of the organism in question. Perhaps, the vast majority of decision making, thinking, and planning processes originate from non-conscious brain processes. Nevertheless, consciousness is a fascinating phenomenon, and its intrinsic nature is both intriguing and challenging to ascertain. In the end, it is not necessarily given that consciousness, in particular the phenomenon of perception as the subjective experience it is, is a tangible function or process in the first place. This is why it must be acknowledged that this theoretical paper is not in a position to offer a definitive solution. However, it does present an interesting new concept that may at least assist future research and potential investigations in achieving a greater degree of elucidation. The concept is founded upon a physical (mathematical) phenomenon known as stochastic resonance. Without delving into the specifics, it is relatively straightforward to grasp one of its implications, which is employed here to introduce a novel direction regarding the potential for non-conscious information within the human brain to become conscious through the introduction of noise. It is noteworthy that this phenomenon can be visualized through a relatively simple approach that is provided in the frame of this paper. It is demonstrated that a completely white image is transformed into an image depicting clearly recognizable content by the introduction of noise. Similarly, information in the human brain that is processed below the threshold of consciousness could become conscious within a neural network by the introduction of noise. Thereby, the noise (neurophysiological energy) could originate from one or more of the well-known activating neural networks, with their nuclei being located in the brainstem and their axons connecting to various cortical regions. Even though stochastic resonance has already been introduced to neuroscience, the innovative nature of this paper is a formal introduction of this concept within the framework of consciousness, including higher-order perception phenomena. As such, it may assist in exploring novel avenues in the search for the origins of consciousness and perception in particular. Full article

Microgravity exposure during spaceflight has been linked to cognitive impairments, including deficits in attention, executive function, and spatial memory. Both space missions and ground-based analogs—such as head-down bed rest, dry immersion, and hindlimb unloading—consistently demonstrate that altered gravity disrupts brain structure and neural plasticity. Neuroimaging data reveal significant changes in brain morphology, functional connectivity, and cerebrospinal fluid dynamics. At the cellular level, simulated microgravity impairs synaptic plasticity, alters dendritic spine architecture, and compromises neurotransmitter release. These changes are accompanied by dysregulation of neuroendocrine signaling, decreased expression of neurotrophic factors, and activation of oxidative stress and neuroinflammatory pathways. Molecular and omics-level analyses further point to mitochondrial dysfunction and disruptions in key signaling cascades governing synaptic integrity, energy metabolism, and neuronal survival. Despite these advances, discrepancies across studies—due to differences in models, durations, and endpoints—limit mechanistic clarity and translational relevance. Human data remain scarce, emphasizing the need for standardized, longitudinal, and multimodal investigations. This review provides an integrated synthesis of current evidence on the cognitive and neurobiological effects of microgravity, spanning behavioral, structural, cellular, and molecular domains. By identifying consistent patterns and unresolved questions, we highlight critical targets for future research and the development of effective neuroprotective strategies for long-duration space missions. Full article

Background: Adolescents with autism spectrum disorder (ASD) display distinct neurodevelopmental trajectories marked by atypical neural activation and white matter maturation compared to neurotypical peers. Introduction: While improvements in face recognition and cognitive skills occur during childhood and adolescence, individuals with ASD often experience a plateau in these areas as they transition to adulthood, impacting daily living, executive function, social cognition, and emotional awareness. Results: Neuroimaging studies reveal altered white matter growth and connectivity in brain regions associated with social processing, which may underlie these functional challenges. Intellectual disability further compounds developmental difficulties by limiting foundational abilities and slowing progress. Discussion: The multifaceted and persistent service needs spanning legal, educational, vocational, health, and psychosocial domains highlight the necessity for coordinated, individualized, and family-centered approaches, particularly during the transition to adulthood. Advances in research integrating genetic, neurobiological, and behavioral data hold potential for refining diagnostic subgroups and personalizing interventions. Conclusion: Continued advocacy and innovation in service delivery are essential to address gaps in adult support systems and enhance long-term outcomes for individuals with ASD. Full article

Spatial representation is a core element of spatial cognition in orienteering, but the visual-spatial neural modulation mechanisms underlying spatial representations with differently oriented maps have not yet been systematically elucidated. This study recruited 67 orienteering athletes as participants and employed a single-factor (map orientation: normal vs. rotated) between-subjects experimental design. Eye-tracking and functional near-infrared spectroscopy (fNIRS) techniques were used simultaneously to collect behavioral, eye movement, and brain activity data, investigating the effects of map orientation on visual attention and brain activity characteristics during terrain symbol representation processing in orienteering athletes. The results revealed that compared to the normal orientation, the rotated orientation led to significantly decreased task accuracy, significantly prolonged reaction times, and significantly increased saccade amplitude and pupil diameter. Brain activation analysis showed that the rotated orientation elicited significantly higher activation levels in the right dorsolateral prefrontal cortex (R-DLPFC), bilateral parietal lobe cortex (L-PL, R-PL), right temporal lobe (R-TL), and visual cortex (VC) compared to the normal orientation, along with enhanced functional connectivity. Correlation analysis revealed that under normal map orientation, accuracy was positively correlated with both saccade amplitude and pupil diameter; accuracy was positively correlated with activation in the R-DLPFC; saccade amplitude was positively correlated with activation in the R-DLPFC and R-PL; and pupil diameter was positively correlated with activation in the R-DLPFC. Under rotated map orientation, accuracy was positively correlated with saccade amplitude and pupil diameter, and pupil diameter was positively correlated with activation in both the L-PL and R-PL. The results indicate that map orientation significantly influences the visual search patterns and neural activity characteristics of orienteering athletes, impacting task performance through the coupling mode of visual-neural activity. 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

Chronic inflammation conducts an irreplaceable role in the aging process. More importantly, the impact is particularly significant in scenarios involving cardiac arrest and cardiopulmonary resuscitation (CA/CPR), where elderly individuals are inclined to suffer from more severe inflammatory injuries when compared to younger counterparts. Network pharmacology demonstrated a tight correlation between epicatechin (EC), aging, and the NRG1-NF-κB signaling pathway. With an aim to investigate whether EC suppressing inflammatory aging and alleviating post-CA/CPR brain injury is associated with the inhibition of the NRG1-NF-κB pathway, we established a model of naturally aged 21-month-old rats subjected to CA/CPR. A network pharmacology method was employed to pinpoint possible pathways that connect EC to neuroinflammation associated with aging. Sixty rats were randomly divided into three groups for feeding: a control group (pure water) and EC groups (EC was administered by gavage at doses of 1 mg/kg and 2 mg/kg respectively from the 12th month). Those groups underwent a CA/CPR procedure. At 24-h post-resuscitation, neurological scores, cortical pathology staining and assessments of neural injury were conducted. Expression levels of NRG1-NF-κB pathway-relevant inflammatory factors and proteins underwent systematic investigation by carrying out ELISA, RT-PCR, and Western blotting. In comparison with the 21-month-old groups treated with water, the 21-month-old groups treated with EC at 1 mg/kg and 2 mg/kg demonstrated decreased β-galactosidase staining, aging-correlated proteins and pro-inflammatory factors and NF-κB pathway-relevant proteins, as well as reinforced NRG1-ErbB4 expression. EC lessened inflammatory aging and mitigates post-CA/CPR brain injury in aged rats, associated with the inhibition of the NRG1-NF-κB pathway. 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/Objectives: Chronic stress is associated with long-lasting alterations in brain function, particularly affecting the dynamic interactions between large-scale neural networks during stress and recovery. In this study, we compared changes in brain functional connectivity between states of stress induction and recovery in individuals with chronic stress and investigate the effects of chronic stress on functional brain networks. Methods: We used functional magnetic resonance imaging and ROI-to-ROI analysis to analyze functional connectivity in chronic stress (n = 36). The participants performed the Montreal Imaging Stress Task followed by a recovery phase. Results: The results showed that during the stress induction phase, connectivity between the salience and dorsal attention networks increased, demonstrating enhanced attention and emotional regulation. In contrast, during the recovery phase, connectivity between the default mode and the frontoparietal networks increased, demonstrating cognitive and emotional recovery after stress. Notably, we found that salience network activation continued during the recovery phase, suggesting that individuals with chronic stress may exhibit a continual state of alertness even after stress. Conclusions: Thus, our findings show that chronic stress can lead to the reconstruction of functional networks during the stress response and recovery, contributing to our understanding of the neurobiological correlates of stress-related impairment. Full article