Neuroscience最新文献

Major Depressive Disorder (MDD) poses significant health risks, yet diagnosis lacks objective biomarkers. This systematic review synthesizes functional Magnetic Resonance Imaging (fMRI) studies (2020-2025, n = 52) on functional connectivity (FC) in MDD. We found robust FC alterations within and between core networks (Default Mode, Salience, Central Executive), linked to rumination, emotion dysregulation, and cognitive deficits. These alterations varied with suicidal ideation, comorbidities, childhood trauma, and biological sex. Treatments (antidepressants, rTMS, ECT) demonstrated distinct normalization effects on specific networks. This review consolidates evidence for MDD as a "network interaction disorder," moving beyond single-network foci. It highlights the translational potential of fMRI-based FC for refining diagnosis, personalizing treatment, and provides a novel integrative framework for future research.

Meditation is a widely recognized practice that enhances mental well-being and cognitive function. Despite advances in EEG meditation neuroscience, challenges persist in extracting robust and interpretable features from complex, non-stationary EEG signals. Existing classification methods often rely on limited feature sets and traditional machine learning approaches. These methods lack comprehensive integration of advanced time-frequency analysis, deep learning, and modern nature-inspired optimization techniques. To address this gap, we introduce a hybrid EEG-based theta-band meditation classification framework that combines Harris Hawks Optimization (HHO) and the Arithmetic Optimization Algorithm (AOA) to tune the parameters of a Convolutional Neural Network (CNN). EEG signals are pre-processed and converted into time-frequency images using the Stockwell Transform (S-transform). These images are fed into the proposed HHO-AOA-CNN framework, where HHO explores and AOA exploits to achieve effective hyper-parameter optimization. The optimized CNN is then used to classify EEG data into three categories: Vipassana (VIP), Isha Shoonya (IS), and Control (CTR). Experimental results demonstrate that the hybrid model outperforms standalone HHO-CNN, AOA-CNN, and baseline CNN models. The proposed approach achieves an accuracy of 94.20%, indicating strong classification performance. Additionally, statistical measures such as best, worst, average fitness, and standard deviation confirm the stability and robustness of the hybrid optimizer.

This study explores the anatomical distribution of Angiotensin-(Ang)-(1-7) fusion protein within the central nervous system of the novel transgenic rat model (TG7371). The Ang-(1-7)/Mas pathway of the renin-angiotensin system (RAS) plays a key role in cardiovascular regulation and influences higher brain functions, including cognition and emotion. TG7371 expresses a transgenic Ang-(1-7)-producing fusion protein which resulted in a hypotensive phenotype. Here, we assessed the expression of Ang-(1-7) fusion mRNA and protein in primary cortical cells from neonates and identified their distribution in the brain of adult rats using qPCR, WB, ISH, and immunolabeling. In neonates, Ang-(1-7) mRNA was mainly found in proliferating cells, whereas in adults, it was primarily identified in GFAP-positive astrocytes. The Ang-(1-7) fusion protein, however, was predominantly found in neurons, including GABAergic interneurons and specific pyramidal cells. High protein levels were particularly noted in cardiovascular control regions like the medulla, as well as in other non-cardiovascular areas. TG7371 displayed twofold increase in brain levels of Ang-(1-7) compared to Ang II vs. Control, which remained unchanged, alongside significant changes in the expression of RAS components and nNOS. These findings indicate that the Ang-(1-7) fusion protein modulates the GABA-nNOS-NO-pathway, contributing to the low blood pressure phenotype of these rats, and promotes a mode of astrocytes-neurons-communication. The widespread expression of the fusion protein in the brain also suggests a potential role in modulating mood, cognition, and neurological disorders. Overall, TG7371 presents a valuable model to explore the long-term cardiovascular and neurobehavioral effects of Ang-(1-7), highlighting promising therapeutic implications and neural crosstalk.

Microglial phagocytosis is essential for neurological recovery after intracerebral hemorrhage (ICH). Using single-cell RNA sequencing, we compared microglial responses in murine and human ICH and identified striking species-specific temporal patterns. Murine microglia exhibited a sustained enhancement of phagocytic activity, whereas human microglia showed only a transient increase followed by a decline and persistent inflammation. To identify genes associated with phagocytic differences, we evaluated five machine learning models and selected XGBoost as the best-performing model. This analysis identified Tlr2 in mice and CLEC7A in humans as genes associated with microglial phagocytic status. Inferred transcription factor activity analysis further revealed stronger phagocytosis- and inflammation-associated transcriptional activity in murine phagocytic microglial subclusters, whereas human microglia were predominantly characterized by inflammation-associated transcription factors. Consistent with these results, Tlr2 expression was markedly increased at day 14 in single-cell data, and immunostaining confirmed its colocalization with IBA1⁺ microglia and upregulation at days 3 and 7 after ICH. Together, our findings demonstrate that integrating single-cell RNA sequencing with machine learning facilitates the identification of phagocytosis-associated genes and reveals both conserved and divergent patterns of microglial phagocytosis, providing new insights into species-specific responses to ICH.

δ-catenin (also known as CTNND2) functions as an anchor for the glutamatergic AMPA receptor (AMPARs) to regulate synaptic activity in excitatory synapses. Alteration in the gene coding δ-catenin has been implicated in many neurological disorders. Some of these genetic alterations exhibit a profound loss of δ-catenin functions in excitatory synapses. We have shown that δ-catenin deficiency induced by the homozygous δ-catenin knockout (KO) and autism-associated missense glycine 34 to serine (G34S) mutation significantly alters AMPAR-mediated synaptic activity in cortical neurons and disrupts social behavior in mice. Importantly, many genetic disorders are caused by haploinsufficiency. Indeed, δ-catenin haploinsufficiency contributes to severe autism and learning disabilities in humans. However, previous studies have used only homozygous δ-catenin deficiency models. Therefore, it is important to examine the effects of δ-catenin haploinsufficiency on animals' behaviors and excitatory synapses. Here, we use heterozygous δ-catenin KO and G34S mice as a δ-catenin haploinsufficiency model to examine this idea. Multiple behavioral assays, a social behavior test, contextual fear conditioning, and an open field test, reveal that both δ-catenin KO and G34S haploinsufficiency significantly disrupt animals' social behavior and fear learning and memory. Interestingly, only KO haploinsufficiency mice show anxiety-like behavior. A biochemical assay using brain extracts demonstrates that δ-catenin haploinsufficiency significantly affects the levels of synaptic δ-catenin and AMPARs. Our findings thus suggest that δ-catenin haploinsufficiency affects animals' behaviors via altering glutamatergic synaptic activity.

Recent advances in high-throughput technologies have led to an increased generation of biological data across genomics, transcriptomics, proteomics, epigenomics, and metabolomics. However, a major challenge remains: effectively integrating these multi-omics datasets to allow a more holistic understanding of the complex, interconnected mechanisms underlying human diseases. Neurodevelopmental, neurodegenerative, and psychiatric disorders are particularly multifactorial and heterogeneous, making them candidates for multi-omics approaches. In this context, this systematic review assesses the current state of multi-omics integration in neurological research. Records retrieved from five major databases were processed, and 156 studies were included for further analysis. The most frequently studied conditions were Alzheimer's Disease, Depressive Disorder and Parkinson's Disease, with epigenomics-transcriptomics and metagenomics-metabolomics emerging as the most common omics pairings. The field remains dominated by studies integrating pairs of omics layers. Only a limited number of computational tools are currently being applied to the integration of more than two omics layers, highlighting a gap in comprehensive multi-omics modeling. Despite progress, key challenges persist, including data accessibility and the need for standardized frameworks to allow cross-study comparisons. Moreover, most computational findings lack experimental validation in wet-laboratory settings. Future research should address these challenges, develop scalable algorithms for integrating multi-omics data, and leverage large, open-access datasets. Integrating computational predictions with experimental validation could help researchers prioritize high-confidence biomarkers relevant to clinical applications. Collaborative efforts among bioinformaticians, clinicians, and experimentalists will be essential to translating these advances into clinically actionable solutions.

Mitochondrial dysfunction is a critical early driver of retinal ganglion cell (RGC) loss in optic nerve injury. We evaluated whether HDAP2, a mitochondria-targeted aromatic peptide designed to support mitochondrial membrane integrity, could preserve neuronal structure after optic nerve crush (ONC) in C57BL/6 mice (both sexes, n = 31). Systemically administered HDAP2 penetrated the blood-retinal barrier and localized to RGCs and mitochondrial-rich retinal layers. Daily treatment significantly improved RGC survival compared to saline-treated ONC animals. RGC densities increased across central, midperipheral, and peripheral regions. Transmission electron microscopy revealed that HDAP2 substantially reduced mitochondrial loss within crushed optic nerve axons. Mitochondrial density in HDAP2-treated nerves approached levels observed in uninjured controls and was nearly 3-fold higher than untreated ONC nerves. Mitochondrial morphology was similar across groups, indicating that HDAP2 prevents mitochondrial loss rather than rescuing damaged organelles. HDAP2-treated nerves also exhibited a numerically higher density of structurally intact axons, consistent with reduced ultrastructural degeneration. These findings demonstrate that HDAP2 limits mitochondrial loss and attenuates neuronal degeneration after ONC. Together, the results support HDAP2 as a promising therapeutic candidate for protecting CNS projection neurons by maintaining mitochondrial stability after axonal injury.