Yang H, Liu Y, Zhang F
… +6 more, Jiang Y, Shuai N, Li X, Xiao L, Liu Z, Xu S
Int J Neurosci
· 2026 Jun · PMID 42260977
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BACKGROUND: Perioperative neurocognitive disorders (PNDs) encompass delayed neurocognitive recovery (dNCR; ≤30 days) and postoperative neurocognitive disorder (NCD; >30 days). While the HMGB1-TLR4/NF-κB axis drives acute...BACKGROUND: Perioperative neurocognitive disorders (PNDs) encompass delayed neurocognitive recovery (dNCR; ≤30 days) and postoperative neurocognitive disorder (NCD; >30 days). While the HMGB1-TLR4/NF-κB axis drives acute neuroinflammation, temporal dynamics beyond the acute phase and distinct contributions of HMGB1 versus TLR4 to dNCR-to-NCD transition remain elusive. This study investigated whether glycyrrhizin attenuates sevoflurane-surgery-induced recognition memory deficit HMGB1-TLR4 modulation. METHODS: Eight-month-old male C57BL/6J mice underwent right common carotid artery dissection under prolonged sevoflurane anesthesia (3%, 2 h) with or without glycyrrhizin pretreatment (30 mg/kg, i.p.; = 15/group for batch 1, = 7/group for batch 2). Cognitive function was assessed open field, novel object recognition, Y-maze, and Morris water maze. Hippocampal neuroinflammation , HMGB1-TLR4-NF-κB signaling, synaptic proteins , and Nissl staining were evaluated at postoperative days 7 and 20. RESULTS: Prolonged sevoflurane exposure combined with surgery induced recognition memory impairment and reduced platform crossings, both attenuated by glycyrrhizin. While peripheral IL-6 normalized by day 7, hippocampal cytokines (IL-6, IL-1β, TNF-α) and glial activation persisted through day 20. HMGB1 was elevated at day 7 but normalized by day 20, whereas TLR4/NF-κB remained elevated at both time points; glycyrrhizin suppressed this cascade. Synaptic proteins were reduced and CA3/dentate gyrus exhibited Nissl staining reductions at days 7 and 20, protected by glycyrrhizin, whereas CA1 showed no significant alterations. CONCLUSIONS: These findings demonstrate temporal dissociation between HMGB1 normalization and sustained TLR4/NF-κB activation following sevoflurane-surgery in middle-aged mice. Prophylactic glycyrrhizin attenuates recognition memory deficits and suppresses hippocampal neuroinflammation, though mechanistic inferences remain speculative and require rigorous validation.
In mammals, slow-wave sleep is characterized by synchronized neuronal activity that alternates between on and off periods. Slow-wave activity (SWA) and synchrony reflect sleep need, are correlated with synaptic strength...In mammals, slow-wave sleep is characterized by synchronized neuronal activity that alternates between on and off periods. Slow-wave activity (SWA) and synchrony reflect sleep need, are correlated with synaptic strength in cortical circuits and promote synaptic downselection and memory consolidation. Here we assessed whether these core benefits of sleep can be obtained during waking. We locally induced alternating on/off periods during wakefulness using optogenetics in mice. This led to a local ipsilateral reduction in SWA and synchrony during subsequent sleep, and to reduced markers of synaptic strength. Moreover, bilateral induction of off periods over sensorimotor cortex during sleep deprivation restored memory consolidation. Thus, inducing on/off activity during wakefulness is sufficient to reduce local sleep need and fulfill core functions of sleep.
Blocking estrogen synthesis via aromatase inhibition helps prevent the recurrence of estrogen-receptor positive breast cancer but also results in cognitive, sleep and thermoregulatory disturbances. These side-effects dim...Blocking estrogen synthesis via aromatase inhibition helps prevent the recurrence of estrogen-receptor positive breast cancer but also results in cognitive, sleep and thermoregulatory disturbances. These side-effects diminish quality of life and contribute to treatment nonadherence in a large proportion of patients. DHED is a brain-selective prodrug that, in rodent models, converts to 17β-estradiol (E) selectively in the brain without affecting the periphery. We investigated whether DHED could prevent side effects associated with the aromatase inhibitor letrozole in a primate model of aging. Chronic oral treatment with DHED in letrozole-treated male and female marmosets led to a robust increase in E levels across brain regions without affecting estrogen levels at the periphery. In addition, DHED treatment (1) improved memory at short delays and prevented letrozole-induced cognitive slowing in a hippocampal-dependent memory task; (2) normalized hippocampal neuronal membrane potential and excitability and (3) reduced sleep fragmentation. However, DHED treatment had opposite effects on thermoregulation in males and females, necessitating additional research in this area. Overall, the results suggest that DHED, which lacks estrogenic effects in peripheral tissues, could be a safe and effective novel hormonal therapy for improving quality of life in breast cancer patients treated with aromatase inhibitors. Women with estrogen receptor positive (ER+) breast cancers take aromatase inhibitors to lower estrogens and reduce cancer recurrence. As a result, they often experience symptoms of estrogen deficiency that compromise treatment adherence. Here, we show that a brain-selective estrogen therapy administered orally via the prodrug DHED substantially increases estrogen levels in the marmoset brain without affecting the periphery and normalizes impairments in working memory, hippocampal neuronal excitability and sleep induced by aromatase inhibition. These findings in a translational primate model represent a significant advance for women's health by positioning DHED as a non-invasive, safe and efficient novel hormone therapy to improve quality of life of women with ER+ breast cancers.
Dimopoulos D, Dafou D, Sklaviadis T
… +1 more, Xanthopoulos K
Neuroscience
· 2026 Jun · PMID 42259419
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Prion diseases are fatal neurodegenerative disorders caused by the misfolding of the host-encoded prion protein (PrP) into a pathogenic conformer (PrP). Despite decades of investigation, no therapy has proven effective,...Prion diseases are fatal neurodegenerative disorders caused by the misfolding of the host-encoded prion protein (PrP) into a pathogenic conformer (PrP). Despite decades of investigation, no therapy has proven effective, largely due to rapid disease progression and the absence of druggable intermediates. Recent molecular advances, however, have established PrP itself as a viable therapeutic substrate. Experimental ablation or suppression of Prnp in mice -the gene encoding PrP- confers complete resistance to prion infection in animal models, providing a strong genetic rationale for PrP- lowering interventions. This review focuses on current genetic approaches aiming at reducing PrP expression. Antisense oligonucleotides (ASOs) and RNA-interference (RNAi) vectors have demonstrated potent, durable suppression of Prnp transcripts and extended survival in prion diseases murine models, while genome- and epigenome-editing platforms, including CRISPR-Cas and dCas9-based repressors, now permit permanent or reversible transcriptional control of Prnp with increasing precision. While these technologies are conceptually transformative, translational application faces major challenges, including early diagnosis, brain-wide delivery, biomarker validation and ethical implementation of presymptomatic therapy in Prnp mutation carriers. Integration of validated cerebrospinal biomarkers such as PrP and neurofilament light chain, adaptive trial designs and international registries will be essential for clinical development. Together, these advances position genetic approaches focusing on PrP-lowering as a promising paradigm for preventive treatment of prion diseases and as a model for rational gene-targeted therapies in other rapidly progressive neurodegenerative disorders.
Int J Neurosci
· 2026 Jun · PMID 42252862
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AIM: Stroke is considered as one of the most prevalent causes of death and disability for the humans, although it is preventable and treatable. Earlier stroke detection and treatment management helps in enhancing the cli...AIM: Stroke is considered as one of the most prevalent causes of death and disability for the humans, although it is preventable and treatable. Earlier stroke detection and treatment management helps in enhancing the clinical outcomes, thereby significantly minimizing the risk of disease. Thus, this work presents a sophisticated deep learning-based stroke prediction framework using the Magnetic Resonance Imaging (MRI) and provides specialized and flexible diagnostic guidance. METHODS: The developed stroke detection system begins by collecting the required MR images in the benchmark sources. Further, the gathered MR images are fed to the stroke lesion segmentation using the developed Region Masked Attention-based Multi-Dilated Inception Unet++ (RMA-MIUnet++), which is accurately focus on stroke-affected regions. The segmented images are acquired as the outcomes from the proposed RMA-MIUnet++ model. These segmented images are further classified in the developed Efficient InceptionV3 with Novel Activation Function (EIV3-NAF)-based stroke classification model. RESULTS: The experimental validation is performed on the developed system by comparing it with other conventional methods. When considering the batch size at 48, the accuracy of the proposed model for dataset 1 is 97% and dataset 2 is 93.26%. CONCLUSION: The results achieved by the developed EIV3-NAF model clearly show enriched performance in classifying the strokes.
Wang Y, Wang K, Wang Z
… +5 more, Li Y, Jiang S, Xu T, Yang M, Gu Y
Neuroscience
· 2026 Jun · PMID 42250855
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Oxidative stress represents a fundamental pathological driver of the secondary injury cascade following traumatic spinal cord injury (SCI). Although the pan-histone deacetylase inhibitor Trichostatin A (TSA) exhibits neu...Oxidative stress represents a fundamental pathological driver of the secondary injury cascade following traumatic spinal cord injury (SCI). Although the pan-histone deacetylase inhibitor Trichostatin A (TSA) exhibits neuroprotective properties in various contexts, its capacity to modulate the endogenous NRF2/HO-1 antioxidant defense system within the human spinal cord microenvironment remains to be elucidated. In this study, we utilized human induced pluripotent stem cell-derived spinal cord organoids (hSCOs) as a sophisticated, human-relevant platform to investigate these mechanisms. In vitro analyses revealed that TSA preconditioning significantly bolsters the resilience of hSCOs against oxidative damage, manifesting as enhanced cellular viability, diminished accumulation of reactive oxygen species and malondialdehyde, and elevated superoxide dismutase activity. Mechanistic evaluations suggested that this protection is mediated by NRF2 nuclear translocation and subsequent HO-1 upregulation, an effect completely reversed following the pharmacological inhibition of NRF2. Furthermore, the transplantation of TSA-preconditioned hSCOs, encapsulated within a GelMA hydrogel, into a rat contusion model led to marked structural and functional restoration. Compared to untreated organoid grafts, the TSA-primed hSCOs significantly promoted motor function recovery, diminished lesion cavitation, and enhanced neuronal survival, while simultaneously attenuating glial scarring, neuroinflammation, and axonal degeneration. These findings indicate that pharmacological priming with TSA optimizes the therapeutic efficacy of organoid transplantation in a manner involving NRF2/HO-1 activation, establishing a highly promising combinatorial strategy for clinical neural regeneration.
Uddin KN, Ghose P, Njie E
… +6 more, Mahmood N, Kumar N, Haque MN, Gaur L, Li A, Mallik S
Neuroscience
· 2026 Jun · PMID 42250854
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Artificial Intelligence (AI) has become integral to the research of neurological diseases due to the rapid expansion of neuroimaging, clinical, physiological, and wearable data. However, the concise synthesis of recent m...Artificial Intelligence (AI) has become integral to the research of neurological diseases due to the rapid expansion of neuroimaging, clinical, physiological, and wearable data. However, the concise synthesis of recent machine learning (ML) and deep learning (DL) remains limited. This systematic review analyzes studies published between January 2021 and March 2026 on five major conditions- Alzheimer's disease, stroke, Parkinson's disease, brain tumors, and traumatic brain injury (TBI)-following the PRISMA 2020 guidelines and a structured search of PubMed, Scopus, and Web of Science, yielding 206 eligible articles. The results show that convolutional and encoder-decoder architectures dominate imaging tasks, whereas hybrid and multimodal approaches increasingly combine imaging with clinical and sensor data. Emerging paradigms, including federated learning, self-supervised learning, and foundation models, address data scarcity, privacy, and cross-institutional variability. Key advances include high-performing transformer-based models for Alzheimer's diagnosis, real-time stroke detection by CT/MRI, improved Parkinson's detection by multimodal fusion, hybrid models for brain tumor classification, and outcome prediction in TBI. Despite these gains, challenges in generalizability, interpretability, and clinical translation persist, underscoring the need for more robust and clinically reliable AI systems to address these issues.
Adaptive behavior requires control over automatic tendencies to approach reward and avoid threat. Dysregulation of this control characterizes disorders such as anxiety or addiction, yet the underlying neural mechanisms r...Adaptive behavior requires control over automatic tendencies to approach reward and avoid threat. Dysregulation of this control characterizes disorders such as anxiety or addiction, yet the underlying neural mechanisms remain unclear. Here, we investigated circuits engaged during approach-avoidance control using fMRI with eye-tracking, and behavioral measures. Forty participants (22 females) completed an approach-avoidance conflict task with free- and forced-choice trials. Each trial comprised anticipation, response (using a joystick to approach/obtain or avoid/forgo outcomes), and outcome phases. Before scanning, participants were instructed and experienced that conditioned stimuli (CS) predicted an aversive painful stimulation (avCS+), an appetitive monetary reward (appCS+), both outcomes (confCS+), or no outcome (neuCS-). Discordant responses (e.g., approaching avCS+) were slower than concordant responses (e.g., avoiding avCS+), confirming heightened control demands. Overcoming threat-driven avoidance specifically recruited the left inferior frontal gyrus (IFG), while suppressing reward-driven approach lacked distinct neural signatures. During anticipation, confCS+ and avCS+ showed overlapping activation in salience-control networks, including middle/anterior cingulate cortex (MCC/ACC), anterior insula, IFG, and ventral striatum (VS). Interestingly, confCS+ evoked threat-like anticipatory neurophysiological responses (pupil dilation; ACC/insula activation) but subsequently triggered reward-like approach behavior. Multivariate pattern and psychophysiological interaction analyses revealed that this dissociation was driven by differential encoding of upcoming responses in the VS during the anticipation phase and by altered functional coupling between the VS and the right temporoparietal junction (rTPJ). These findings indicate that motivational control prioritizes salience over valence and suggest a VS-rTPJ network for resolving approach-avoidance conflicts, offering novel insights into neural dynamics of flexible goal-directed behavior. This study advances our understanding of how the brain dynamically resolves conflicts between avoiding pain and obtaining monetary rewards. By measuring neural activity during approach-avoidance conflicts, our study identified overlapping neural circuits for threat and conflict processing (e.g., middle/anterior cingulate, ventral striatum). It revealed that threat-like neural responses to conflicting stimuli triggered approach behaviors resembling reward-motivated actions. Critically, connectivity between the ventral striatum and the temporoparietal junction predicted individual differences in conflict resolution, linking network-level interactions to adaptive behavioral control. These findings suggest that salience overrides valence in motivational control and motivate hypothesis-driven tests of network disruptions in psychiatric populations.
Väyrynen T, Helakari H, Korhonen V
… +13 more, Tuunanen J, Huotari N, Kananen J, Ebrahimi SM, Elabasy A, Järvelä M, Hautamäki K, Laurén K, Raitamaa L, Salmi U, Piispala J, Kallio M, Kiviniemi V
Human brain exhibits three propagating pulsations, namely cardiovascular, respiratory, and infra-slow fluctuations (ISF <0.1 Hz), which are thought to contribute to the flow of intracranial fluids. While their pulsation...Human brain exhibits three propagating pulsations, namely cardiovascular, respiratory, and infra-slow fluctuations (ISF <0.1 Hz), which are thought to contribute to the flow of intracranial fluids. While their pulsation characteristics have been extensively studied, their mutual dependencies have not been systematically investigated. Using ultrafast whole brain magnetic resonance encephalography (MREG) fMRI sequence, we analysed the frequency domain up to 5 Hz for cross-frequency oscillatory interactions in awake and NREM-sleep states of 23 (13 F, 10 M) healthy volunteers. Using phase transfer entropy (TE) analysis, we found that in the awake state the resting state network (RSN) activity largely predicted the neurofluid (NF) signal changes. NREM-sleep was associated with increased power of ISF and with altered directed coupling patterns between RSN and NF components. Importantly, within these independent signal sources, we found three distinct cross-frequency coupling frequency ranges occurring at ISF (<0.1 Hz), respiratory (∼0.25 Hz), and cardiovascular (∼1 Hz) frequencies, where the slower pulsations generally predicted the faster ones, except for a finding of inverted cardiorespiratory coupling in NREM-2 sleep. These results suggest the presence of directional ISF mediated mechanisms underlying brain pulsations that contribute to driving the intracranial fluid transfer processes. Cerebrospinal fluid (CSF) flow is essential for brain fluid homeostasis and interstitial metabolite clearance. Human brain exhibits three types of intracranial pulsations linked to CSF flow, which are particularly distinct during sleep, when fluid clearance processes are most active. We hypothesized that these pulsations, despite their independent sources, interact with each other to facilitate CSF flow. Using functional magnetic resonance imaging (fMRI) during wakefulness and non-rapid eye movement sleep (NREM), we investigated cross-frequency coupling patterns up to 5 Hz within the brain. The results revealed novel cross-frequency coupling bands in the human brain, in which infra-slow fluctuation (ISF) dynamics predicted faster brain pulsations, potentially contributing to increased perivascular clearance during sleep.
Modern high-density neural recordings demand spike sorting algorithms that can handle diverse probe geometries and complex, neuron-specific drift, yet existing methods often rely on rigid geometric assumptions and one-di...Modern high-density neural recordings demand spike sorting algorithms that can handle diverse probe geometries and complex, neuron-specific drift, yet existing methods often rely on rigid geometric assumptions and one-dimensional drift models. Here, we introduce KIASORT (Knowledge-Integrated Automated Spike Sorting), a geometry-free approach for per-neuron drift tracking. KIASORT builds channel-specific sorting models from a hybrid linear-nonlinear sample-sorting stage, using representative template banks or supervised classifiers. These channel-specific models then sort spikes by independently tracking each neuron, unconstrained by probe layout. Biophysical simulations showed that even sub-micron probe displacements induce neuron-specific waveform distortions that standard drift models cannot correct. In ground-truth benchmarks with heterogeneous, neuron-specific drift, KIASORT outperformed Kilosort4 in recovering high-quality units, while maintaining real-time performance on standard CPUs. Its robustness was further illustrated on both primate and mouse data. KIASORT combines automated sorting with manual curation in a unified graphical interface, offering a complete and user-friendly spike sorting platform. The software is freely available at https://kiasort.com. Accurate spike sorting remains a fundamental challenge in systems neuroscience, particularly as recording technologies advance toward simultaneous monitoring of thousands of neurons and the next generations of recording probes. Current methods often rely on rigid assumptions about probe geometry and uniform drift patterns for different neurons which often fail in real-world recordings. We introduce KIASORT with capability to track neurons in a geometry-free framework, as a fundamentally new approach that addresses these critical limitations with many use cases which are not supported by other existing methods.
Neuroscience
· 2026 Jun · PMID 42248236
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Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor. Despite combined treatments, including surgical removal followed by radiation and chemotherapy, the prognosis remains poor. E...Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor. Despite combined treatments, including surgical removal followed by radiation and chemotherapy, the prognosis remains poor. Even with temozolomide, the current standard for GBM treatment, the disease is still incurable because of GBM's highly invasive nature and resistance to therapy. This review examines the contributions of key DNA repair pathways, including O6-methylguanine-DNA methyltransferase, base excision repair, and homologous recombination, to the resolution of DNA lesions induced by therapy. It also highlights emerging molecular therapeutic targets that exploit synthetic lethality to enhance treatment efficacy. In addition, the review explores other determinants of GBM resistance, such as oncogenic genetic mutations, the tumorigenic glioma stem cells (GSCs), metabolic reprogramming within the tumor microenvironment that promotes immune evasion, and the restrictive nature of the blood-brain barrier, which limits effective drug intratumoral concentrations. Finally, we discuss patient-specific immunotherapeutic strategies, including chimeric antigen receptor T (CAR-T) cell therapy and personalized cancer vaccines, which hold promise for improving survival outcomes across different GBM subtypes. Advances in multi-omics profiling and machine learning are reshaping opportunities for personalized therapy in GBM. Integrating WES, RNA-seq, and HLA typing enables tailored immunotherapies, while AI-driven antibody design accelerates the development of GSC-targeting candidates. Yet translation remains hindered by GBM's heterogeneity, limited patient availability, and disparities in trial participation. Progress will require combining mechanistic tumor profiling with computational design approaches within more inclusive clinical trials to advance truly personalized and effective GBM treatment.
Yang S, Yong Y, Lin Y
… +6 more, Gao T, Jia S, Li H, Ma H, Li X, Wang N
Neuroscience
· 2026 Jun · PMID 42248235
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High-altitude exposure extensively affects cerebral function. This study investigates attention networks (alertness, orientation, executive control) and prefrontal activation in migrants over 1, 2, and 3 years at high al...High-altitude exposure extensively affects cerebral function. This study investigates attention networks (alertness, orientation, executive control) and prefrontal activation in migrants over 1, 2, and 3 years at high altitude. Using the Attention Network Test and fNIRS, we assessed 137 university students relocated to Tibet, with 65 plain controls. Behaviourally, migrants exhibited significantly lower vigilance, orientation, and executive control than plains, but no differences emerged across exposure time within the migrant group. Critically, fNIRS revealed neuro-behaviour dissociation: during orientation, bilateral ventral frontal pole and left superior temporal cortex activated at two years; during executive control, bilateral dorsal and ventral frontal pole cortex peaked at one year then declined. Brain-behaviour correlation showed negative association between orientation efficiency and prefrontal activation at one year, supporting neural efficiency. These findings suggest the frontal pole cortex exerts compensatory effects on attention networks under high-altitude conditions.
Neuroscience
· 2026 Jun · PMID 42248234
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Neurodegenerative diseases, such as Mild Cognitive Impairment (MCI) and Alzheimer's, pose significant challenges due to their progressive nature and late diagnosis. Early detection remains difficult, particularly when us...Neurodegenerative diseases, such as Mild Cognitive Impairment (MCI) and Alzheimer's, pose significant challenges due to their progressive nature and late diagnosis. Early detection remains difficult, particularly when using conventional machine learning approaches that fail to capture complex spatial and temporal patterns in multimodal clinical data. Motivated by the need for accurate, scalable, and clinically applicable diagnostic tools, this study proposes a hybrid deep learning framework combining Convolutional Neural Networks (CNN) with Optimized Spatial-Temporal Bidirectional Gated LSTM (O‑SBGC‑LSTM). The framework is evaluated on 1,000 multimodal samples, achieving 94.8% accuracy, 93.9% precision, 94.2% recall, and a 94.0% F1-score, outperforming SVM (82.4%), Random Forest (85.7%), and CNN-LSTM (92.5%). Cross-validation confirms robustness (93.8-95.0% accuracy). The approach balances class performance across cognitively normal, MCI, and Alzheimer's cases. Future work will extend this framework to larger, multi-centre datasets and explore real-time clinical deployment, aiming to enhance early diagnosis, reduce misclassification, and support personalized treatment strategies for neurodegenerative disorders.