Search Results (9,218)

The diversity and abundance of the brain virome is an active field of investigation. However, how the brain virome relates to the presence of viruses outside of the nervous system remains unclear. The rationale for this study is that analyses across multiple biologically linked compartments within the same individuals provide an important opportunity to evaluate virome discordance and viral burden. To characterize viral prevalence and burden across anatomical compartments, we applied the targeted viral enrichment method ViroFind to matched postmortem brain (n = 66), cerebrospinal fluid (CSF; n = 24), and peripheral samples (spleen, peripheral blood mononuclear cells, and lymph nodes; n = 66) from individuals with and without human immunodeficiency virus (HIV) infection and substance use disorder (SUD) in the National NeuroAIDS Tissue Consortium. We detected nucleic acids from 27 viruses representing 12 taxa. Several viruses, including adenovirus, torque teno virus, Epstein–Barr virus, human herpesvirus 6 and 7, cytomegalovirus, parvovirus, and JC polyomavirus, showed significant inter-compartment differences in prevalence or burden. CSF exhibited lower overall viral diversity than brain or peripheral samples, whereas peripheral samples showed the highest viral burden. CNS viral detection was more likely when the same virus was also detected in the periphery. We also detected HBV and HCV in CNS samples despite them not being classically regarded as neurotropic. Broader virome profiling showed greater peripheral viral burden and diversity in HIV-positive than HIV-negative individuals, whereas SUD was not associated with overall viral burden differences. These findings highlight important cross-compartment differences in viral detection, including occurrence of occult HBV infection within the CNS, and support the value of CNS–periphery comparisons in virome studies. These findings can contribute to improved diagnosis and management of viral infections. Full article

Exosomes are small vesicles released by cells that have attracted growing interest as drug delivery vehicles, particularly for brain diseases, where getting therapeutics across the BBB remains a fundamental problem. While conventional platforms such as liposomes, polymeric nanoparticles, and viral vectors often suffer from immune clearance and poor brain accumulation, engineered exosomes leverage natural cellular transport mechanisms to cross the BBB, protect cargo from degradation, and enable biocompatible interactions with target cells. This review takes a mechanistic and translational look at how exosomes are being engineered for CNS disorders, with a particular focus on glioblastoma. We cover exosome biogenesis through ESCRT-dependent and ESCRT-independent pathways, and how the competition between Rab27-driven secretion and Rab7-driven lysosomal degradation determines how many exosomes a cell releases, which has direct consequences for therapeutic production. We then discuss cargo loading strategies, from genetic approaches where donor cells are engineered to package specific molecules during biogenesis to physical methods like electroporation and sonication applied to isolated vesicles, alongside surface modification techniques for directing exosomes toward specific cell types. In glioblastoma, engineered exosomes have shown real promise for delivering chemotherapeutics across the BBB, targeting glioma stem cells, enabling CRISPR-based gene editing, and functioning as combined treatment and imaging tools. Applications in stroke and neurodegenerative diseases, where engineered exosomes carrying microRNAs and neuroprotective cargo have produced encouraging preclinical results, are also discussed. Scalable manufacturing and consistent targeting remain the hardest unsolved problems, and we outline emerging approaches including bioreactor-based production, programmable cargo loading, and patient-specific exosome design that are beginning to address these gaps. Overall, the progress reviewed here suggests that engineered exosomes are moving from an interesting biological concept toward a practically viable platform for CNS drug delivery. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder traditionally defined by dopaminergic neuronal loss and Lewy body pathology; however, increasing evidence indicates that metabolic dysfunction contributes to both motor and non-motor manifestations of disease. While metabolomics studies in PD have largely focused on peripheral biofluids or subcortical brain regions, metabolic remodeling within cortical regions critical for cognition remains poorly characterized. Here, we applied LC-MS/MS-based untargeted metabolomics to post-mortem frontal cortex tissue from PD and neurologically normal control donors, with statistical models adjusted for age, sex, and post-mortem interval. A total of 893 metabolites were quantified, of which 234 exhibited significant differential abundance following false discovery rate correction. Pathway enrichment and network-based integration revealed coordinated metabolic remodeling characterized by predicted inhibition of β-alanine metabolism and pantothenate-dependent coenzyme A biosynthesis alongside activation of amino acid, vitamin B-dependent, cofactor-related, redox-associated, oxidative stress, and inflammatory pathways. Recurrent alterations in pantothenic acid, β-alanine-related intermediates, arginine- and histidine-derived metabolites, lumichrome, and vitamin B₆-associated species may reflect cortical metabolic perturbations associated with mitochondrial bioenergetic vulnerability and oxidative stress. Together, these findings indicate selective metabolic vulnerability in the PD frontal cortex rather than diffuse metabolic collapse. Full article

Perinatal mental illness affects up to 20% of new mothers worldwide, yet despite a growing research interest over the past decade, the etiology is still not fully understood, and clinical treatment guidelines remain inconsistent across countries and services. In this review, recent findings on neurobiological processes and evolutionary mechanisms, as they occur during the menstrual cycle, pregnancy, birth, postpartum and breastfeeding, are discussed. The intention is to raise awareness of physiological changes in pregnancy that might be relevant to the differential diagnosis and clinical treatment of perinatal psychiatric disorders such as depression, anxiety, PTSD after childbirth, bipolar relapse, postpartum psychosis, obsessive-compulsive symptoms, substance-use disorders, and suicidality. Areas addressed include the activities of the immune system, thyroid gland, cortisol, sleep and individual sensitivity to ovarian hormone fluctuations. Evolutionary biological mechanisms intended to sustain pregnancy and to ensure the survival of the newborn are assumed to have potent effects on the maternal brain. These non-pathological adaptations could provide grounds for a better understanding of risk factors and the etiology of perinatal mental illness. Full article

Major depressive disorder (MDD) is a complex and heterogeneous psychiatric disorder with a high prevalence. Neuroinflammation may define biologically distinct patient subgroups with different mechanisms, clinical phenotypes, and treatment responses. This narrative review integrates current evidence around three linked questions: how neuroinflammatory processes contribute to depression, how biomarkers can identify clinically relevant inflammatory phenotypes, and how these findings can inform anti-inflammatory treatment strategies. The major mechanisms discussed include microglial activation and neuroimmune signaling, hypothalamic–pituitary–adrenal axis dysregulation and glucocorticoid receptor resistance, kynurenine pathway alterations, and cytokine-driven impairment of neurogenesis and synaptic plasticity. These pathways interact with stress responses, neurotransmitter systems, and neuronal function, while their expression may vary according to sex, age, hormonal status, disease stage, and treatment exposure. These interconnected pathways may contribute to depressive symptoms by disrupting neurotransmitter systems and impairing neural plasticity. In addition, this review discusses several candidate biomarkers, including C-reactive protein (CRP), interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), brain-derived neurotrophic factor (BDNF) and transforming growth factor-β1 (TGF-β), which may support patient stratification, treatment prediction, and assessment of target engagement. Clinical trials of anti-inflammatory agents have shown inconsistent and generally modest effects in unselected MDD populations. By integrating mechanistic evidence with biomarker-guided therapeutic implications, this review aims to clarify how neuroinflammatory research may inform more precise and individualized treatment strategies for depression. Full article

Military burn pits used during post-9/11 U.S. military deployments functioned as uncontrolled combustion systems and were widely utilized to dispose of large volumes of outdoor waste by burning. Burn pits involved heterogeneous waste materials burned under variable temperature and oxygen conditions. These combustion environments generated complex, toxic, multipollutant airborne emission mixtures that included particulate matter (PM_2.5), polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). This narrative review synthesizes epidemiologic, experimental, and mechanistic evidence linking burn pit emissions to disruption of the lung–brain axis and adverse neurological outcomes. We specifically aim to address a critical gap in understanding how combustion-derived toxicants impact brain health and are associated with unfavorable neuropsychiatric outcomes, including increased risk of post-traumatic stress disorder (PTSD) and depression. Combustion-related exposures promote pulmonary inflammation and system-wide immune signaling that propagate to the central nervous system, contributing to neuroinflammation and dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis. These interconnected mechanisms are associated with toxic encephalopathy and related cognitive and mood disturbances, underscoring the need to integrate fire science with military and environmental health services research to better define the systemic and neurological consequences of acute and chronic fire-derived inhalation exposures. Full article

Neuroinflammation, mediated by microglia and astrocytes, is an abnormal immune reaction in central nervous system (CNS) disorders. Stimulation of TRPV1 has been found to enhance microglial activation, resulting in a pro-inflammatory response. Natural anthraquinones such as physcion and rhein are commonly found in rhubarb, a medicinal plant recognized for its dual role in culinary and therapeutic applications. The therapeutic potential and mechanisms of these anthraquinones remain largely unexplored. This research aims to examine how anthraquinones protect against neuroinflammation and delineate the underlying mechanisms in lipopolysaccharide (LPS)-mediated cellular and zebrafish models. Among the representative anthraquinone analogs, physcion and rhein showed potent functional inhibitory activity against the TRPV1 channel. The production of nitric oxide (NO) and secretion of pro-inflammatory factors triggered by LPS were significantly reduced in BV-2 cells through regulation of iNOS, IL-6, IL-1β, and TNF-α mRNA expression. Moreover, physcion and rhein inhibited calcium influx and exerted anti-neuroinflammatory effects, which were closely associated with the suppression of Ca²⁺/CAMKK2/AKT and the PI3K/AKT-mediated NF-κB activation pathways. Furthermore, physcion and rhein reduced LPS-driven neutrophil recruitment to the brain and ameliorated locomotor deficits in zebrafish larvae, with the restoration of IL-1β, IL-6, and TNF-α transcript levels to baseline. In conclusion, natural-derived anthraquinones from rhubarb, physcion and rhein, acted as functional inhibitors of TRPV1-mediated calcium dynamics and significantly reduced LPS-mediated neuroinflammation in microglial cells and zebrafish larvae, suggesting promise as therapeutics for neurological disorders. Full article

Neonatal seizures represent the most common neurological emergency in the neonatal period and arise within a uniquely immature and highly dynamic brain. Their recognition is challenging due to frequent electroclinical dissociation, with many seizures remaining purely electrographic and therefore detectable only through continuous electroencephalogram (cEEG) monitoring. This narrative review provides an integrated and updated overview of neonatal seizures, bridging developmental neurobiology, diagnostic challenges, etiological classification, and therapeutic strategies. The immature brain is characterized by an imbalance between excitation and inhibition, transient network architectures, and activity-dependent developmental processes, all of which contribute to the distinct electroclinical features of neonatal seizures. cEEG remains essential for accurate diagnosis and quantification of seizure burden, which may influence outcome. Etiology represents the primary determinant of prognosis, with hypoxic–ischemic encephalopathy (HIE), stroke, and genetic disorders among the most frequent causes. Advances in genetic testing have improved diagnostic precision and enabled targeted therapies in selected cases, supporting a precision medicine approach. Several key findings emerge from the current evidence base: (i) the neonatal brain is a developmentally constrained system in which excitation–inhibition imbalance, transient circuits and immature long-range connectivity shape an electroclinically distinct seizure phenotype; (ii) cEEG is the gold standard for detection and quantification of seizure burden, since the majority of neonatal seizures are electrographic-only and bedside clinical recognition systematically underestimates true seizure burden; (iii) etiology—chiefly HIE, stroke, and genetic causes—remains the strongest determinant of outcome, while seizure burden acts as an independent and potentially modifiable prognostic modifier; (iv) phenobarbital retains an evidence-based advantage in acute electrographic seizure control, whereas levetiracetam offers a favorable safety profile in the absence of robust long-term human neurotoxicity data; (v) rapid genomic diagnostics, artificial intelligence-assisted EEG analysis and multimodal neuromonitoring are converging toward a precision-neonatology framework, but their translation into routine practice requires validation, standardization, and equitable access. Future neonatal seizure care should extend beyond seizure control to the preservation and optimization of neurodevelopmental outcomes. Full article

Background: Traumatic brain injury (TBI) and substance use disorder (SUD) frequently co-occur due to shared risk factors and a potentially bidirectional relationship. However, epidemiological patterns in rural populations remain understudied despite known disparities in access and outcomes. This study aimed to characterize the relationship between TBI and SUD in a rural Southwestern population, including demographic and clinical patterns of diagnostic sequencing. Methods: A retrospective observational study was conducted using electronic health records and trauma registry data (2022–2023) from a rural trauma center. Cohort one included 24,389 emergency department encounters with ICD-10 codes for TBI or SUD. Cohort two included 248 trauma registry patients with TBI and SUD diagnoses. Descriptive statistics and multinomial logistic regression models were used to evaluate diagnostic patterns and associated demographic factors. Results: Males were more likely to have co-occurring TBI and SUD (Relative Risk Ratio [RRR] = 1.35), while increasing age was associated with TBI-only diagnoses. Among patients with multiple visits and diagnoses, 16% had co-diagnoses, while 9% had sequential diagnoses. American Indian/Alaska Native patients had higher co-diagnosis risk compared to White patients (RRR = 2.21, p < 0.001). Higher blood alcohol concentration was associated with lower Glasgow Coma Scale scores (r = −0.15, p = 0.022), indicating greater severity. Conclusions: TBI and SUD frequently co-occur in rural populations, with notable disparities by sex and race/ethnicity. Emergency Departments are critical points of care for interventions such as screening for both substance use and head injury when either is suspected, and employing culturally responsive education and referral pathways upon discharge. Full article

Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder characterized by amyloid-β (Aβ) and the accumulation of tau in the brain, which triggers robust innate immune responses. Growing evidence indicates that neuroinflammation contributes to AD progression by overactivating microglia through the release of cytokines and chemokines. In general, chemokines can disrupt neuronal communication and promote blood–brain barrier permeability. Peripheral immune cells are mobilized into the brain by a gradient of chemokines. These processes link peripheral immune responses with substantial T-cell infiltration into the CNS parenchyma, leptomeninges and cerebrospinal fluid of both AD mice and AD patients. This finding underscores the relevance of the adaptive immune system, particularly T and B cells, in AD neuropathology. T-cell infiltration into the brain can influence amyloid clearance through chemokine signalling. However, chemokines play a critical role in AD by either promoting or suppressing disease progression. The infiltration of peripheral T and B cells into the brain parenchyma can exacerbate neuronal loss, yet it may also exert neuroprotective effects. Despite the presence of CD4⁺ and CD8⁺ T cells in postmortem brains of AD patients, debate continues about their role in AD brains, in terms of whether they are protective or detrimental. Understanding the complex role of chemokines in controlling innate and adaptive immune responses by modulating neuron–glia interactions (involving astrocytes and microglia) may provide novel therapeutic approaches for AD. Targeting chemokine signalling or treating with drugs that can prevent the recruitment of immune cells may be promising strategies for treating AD neuropathology. Therapies that prevent the overactivation of T cells in the brain could lead to protective strategies against AD. In fact, regulatory T cells (Tregs) could delay the onset of cognitive symptoms, because they suppress inflammation and slow the accumulation of Aβ plaques and p-Tau in the brain. Complementary strategies, such as photobiomodulation, nanoparticle, and T-cell-based approaches, could mitigate AD progression in patients. Full article

Background/Objectives: Vitamin D is a nutrient-related secosteroid system with endocrine, paracrine, immunological, and neurodevelopmental actions relevant to nutritional psychiatry. Psychiatric research has often treated vitamin D either as a cross-sectional correlate of depression or as a non-specific supplement expected to act across heterogeneous diagnostic categories. This narrative review aimed to develop a more discriminating framework in which vitamin D is considered a lifespan neuroimmune and immunometabolic signal whose psychiatric relevance depends on developmental timing, biological context, and phenotype. Methods: Evidence was integrated from developmental epidemiology, neonatal dried-blood-spot studies, randomized trials, meta-analyses, Mendelian randomization studies, clinical guidelines, and mechanistic neuroscience. The review focuses on prenatal and neonatal 25-hydroxyvitamin D, vitamin D-binding protein, free and bioavailable vitamin D, vitamin D receptor signaling, immune and microglial pathways, neurotransmitter systems, neurotrophic signaling, mitochondrial function, oxidative stress, hypothalamic–pituitary–adrenal-axis regulation, and the gut–microbiota–immune–brain axis. Results: The available evidence does not support vitamin D as a universal treatment for psychiatric disorders. Instead, vitamin D deficiency and altered vitamin D biology appear most relevant in biologically and clinically defined risk states, including neurodevelopmental vulnerability, inflammatory depression, psychosis liability, severe mental illness with nutritional deprivation, metabolic comorbidity, and cognitive frailty. Mechanistic data support plausible links with cytokine biology, the tryptophan–kynurenine pathway, dopaminergic and serotonergic systems, stress regulation, and neuroimmune homeostasis. Conclusions: Vitamin D should be conceptualized in psychiatry as a context-dependent neuroimmune and immunometabolic signal rather than a generic psychotropic intervention. Future studies should prioritize biomarker-enriched, developmentally timed, nutrition-centered models of precision prevention and adjunctive care. Full article

Background/Objectives: Brain magnetic resonance imaging (MRI) is an important imaging modality for assessing neurological disorders. However, automatic multi-class MRI classification remains challenging because of visual similarity between disease categories, heterogeneous pathological patterns, class imbalance, and the need for reliable confidence estimation. This study aims to develop a comprehensive and well-calibrated deep learning framework for image-level brain MRI classification across multiple neurological categories. Methods: This paper introduces a new deep learning framework, MCND-ComputeNet++, for brain MRI classification into eight image-level categories using the MCND dataset, which comprises 16,400 two-dimensional brain MRI images belonging to eight diagnostic categories: AD-MildDemented, AD-ModerateDemented, AD-VeryMildDemented, BT-glioma, BT-meningioma, BT-pituitary, MS, and Normal. The proposed model uses a single pretrained EfficientNetV2-S backbone to extract hierarchical feature maps from three intermediate stages. These multi-level features are projected into a common latent space, spatially aligned, adaptively fused through learnable gated multi-scale fusion, further refined using convolutional processing, and aggregated using spatial attention pooling before classification. The training strategy combines class-balanced focal loss with label smoothing, MixUp/CutMix regularization, exponential moving average weight smoothing, warmup cosine learning-rate scheduling, temperature scaling, and test-time augmentation to improve generalization and calibration. The framework was evaluated using accuracy, precision, recall, macro-F1, macro-AUC, macro-average precision, expected calibration error, Brier score, bootstrap confidence intervals, ablation analysis, McNemar testing, and comparisons against standard pretrained baseline models. Results: MCND-ComputeNet++ achieved mean accuracy, macro-F1, macro-AUC, and macro-average precision values of 0.9738, 0.9771, 0.9993, and 0.9971, respectively, with narrow bootstrap confidence intervals indicating stable image-level performance. These findings should be interpreted as image-level/slice-level performance on MCND, because patient-level identifiers and subject-wise splitting were not available. These results outperformed most evaluated baselines, including ResNet50, DenseNet121, EfficientNetB0, EfficientNetV2-S with a standard classifier, Swin-Tiny, and ConvNeXt-Tiny, across several discrimination and calibration metrics. Compared with ConvNeXt-Tiny, the proposed model achieved higher macro-AUC and macro-average precision, together with a lower ECE and Brier score, suggesting improved image-level discrimination and confidence reliability. Compared with the EfficientNetV2-S standard classifier, accuracy increased from 0.9308 to 0.9738, while the Brier score decreased from 0.1045 to 0.0400. Conclusions: The results suggest that MCND-ComputeNet++ is a promising image-level brain MRI classification framework for the eight MCND categories. The proposed model integrates hierarchical feature extraction, shared latent projection, gated multi-scale fusion, convolutional refinement, spatial attention pooling, and calibrated inference within a unified architecture. However, because the current evaluation was conducted at the image/slice level without available patient-level identifiers, the findings should not be interpreted as patient-level clinical diagnostic validation. Further studies using subject-wise splitting, external multi-center datasets, 3D volumetric modeling, and multimodal clinical information are required to assess generalizability and potential clinical decision-support applicability. Full article

Consuming fast food draws consumers’ attention to emerging issues related to such consumption. Namely, the consumption of fast food affects environmental sustainability, healthy living, and other sustainable activities. The main objective of this study is to explore how environmental awareness, healthy living, and sustainability-oriented fast-food stimuli may influence neurophysiological response patterns during food-related cognitive processing. Eighteen voluntary subjects, aged 19 to 53 years, who frequently consume fast food and have no physical or mental disorders, took part in the experiment. An experiment was conducted in which data were collected using Electroencephalography (EEG) and analyzed with WinEEG. The waves detected from brain activity signals were digitally converted to data using WinEEG. The resulting digital data was further analyzed using Detrended Fluctuation Analysis, Neural Networks (NN) algorithms, and K Nearest Neighbors (k-NN) algorithms. Herewith, the findings suggest that fast-food-related visuals associated with healthy living may elicit stronger patterns of cognitive engagement among participants. The findings provide exploratory insights into implicit cognitive engagement associated with healthy-living and sustainability-related fast-food stimuli. Additionally, the discussion helps in understanding sustainability-oriented food perception and consumer neuroscience research. Full article

Photonic imaging technologies have profoundly transformed neuro-ophthalmic diagnostics by enabling non-invasive visualization of neurodegenerative processes at the retinal level. This review examines how advanced light-based modalities provide unprecedented insights into the structural, physiologic, and biologic relationships between the eye and brain in conditions such as optic neuritis, multiple sclerosis, and glaucoma. Optical coherence tomography has emerged as an essential tool for quantifying thinning of the retinal nerve fiber layer and ganglion cell layer, serving as reliable biomarkers of axonal loss and disease progression across multiple sclerosis subtypes and optic neuropathies. Detection of apoptosing retinal cells imaging enables real-time visualization of retinal ganglion cell apoptosis preceding irreversible structural damage, offering a critical window for early intervention in various neurodegenerative conditions, in particular, glaucoma. Two-photon microscopy with adaptive optics enables subcellular-resolution imaging of retinal neurons, microvascular dynamics, and inflammatory processes in vivo, facilitating the characterization of neurodegenerative mechanisms at unprecedented spatial scales and redefining neuro-ophthalmology by positioning the retina as an accessible extension of the central nervous system. This review critically examines how established and investigational photonic imaging modalities may support earlier disease detection, longitudinal monitoring, and biomarker development in neuro-ophthalmic and neurodegenerative disorders, with potential implications for more timely and targeted management strategies. Full article

Background: Atopic dermatitis is a chronic inflammatory skin disease characterized by epidermal barrier dysfunction and immune dysregulation, whereas major depressive disorder is a common psychiatric condition with a substantial impact on quality of life; increasing attention has been given to oxidative and nitrosative stress as a potential biological link between these disorders. Methods: This narrative review synthesizes current evidence on molecular biomarkers of oxidative and nitrosative stress in AD and MDD and examines shared mechanisms within the skin–brain axis. Results: Across both conditions, studies consistently report increased markers of lipid peroxidation (e.g., malondialdehyde, 4-hydroxynonenal), oxidative DNA damage (8-hydroxy-2′-deoxyguanosine), and nitrosative stress, alongside impaired antioxidant defenses, particularly involving glutathione; these alterations are closely associated with chronic inflammation, cytokine signaling, mitochondrial dysfunction, and dysregulation of neuroimmune and hypothalamic–pituitary–adrenal axis pathways. Conclusions: Although the available evidence is heterogeneous and largely based on cross-sectional studies, limiting causal inference, the findings support a biologically plausible link between AD and depression mediated by shared redox pathways and highlight the need for further longitudinal and mechanistic research. Full article