Traumatic brain injury presents a significant challenge, characterized by complex pathologies including neuroinflammation and axonal degeneration with limited treatment options. One of the promising areas of traumatic brain injury treatment is cell therapy. However, a critical aspect of this therapy is the method of stem/progenitor cell administration. This study aimed to evaluate the therapeutic potential of glial progenitor cells derived from induced pluripotent stem cells after intra-arterial administration in an experimental model of traumatic brain injury of male Wistar rats. Neurological status was assessed using the limb-placing, cylinder, and beam walking tests. Lesion volume was quantified by magnetic resonance imaging. Markers of inflammation and neurogenesis were analyzed using immunofluorescence staining and quantitative reverse transcription polymerase chain reaction. Cell migration was tracked via magnetic resonance imaging and histology. Intra-arterial administration provided targeted delivery of cells into the cerebral vasculature. The cells successfully crossed the blood-brain barrier, migrated into the brain parenchyma, and were detectable for up to 48 hours. Transplantation led to significant improvement in sensorimotor function, reduced neuroinflammation in the injured area, and promoted neurogenesis. The observed therapeutic effects are likely mediated by the factors secreted by glial progenitor cells, which possess anti-inflammatory and regenerative properties (paracrine signaling effect) and/or by their transient interactions with the target cells (juxtacrine signaling effect). Glial progenitor cells derived from induced pluripotent stem cells and delivered via the intra-arterial route show promise for the treatment of traumatic brain injury by reducing inflammation and enhancing neurogenesis.
Brain aging is accompanied by progressive disturbances in calcium signaling, mitochondrial function, redox balance, neuroimmune regulation, and barrier-fluid homeostasis, collectively increasing susceptibility to neurodegenerative diseases. Therefore, identifying physiological regulators that stabilize these interconnected processes is central to understanding brain aging. Klotho, an antiaging protein initially characterized by its systemic roles in mineral metabolism and lifespan regulation, has emerged as a key modulator of cellular and tissue homeostasis across multiple organs, including the central nervous system. In the brain, Klotho is predominantly expressed in the choroid plexus and selectively in neuronal and oligodendroglial populations, positioning it at the interface of barrier physiology and neural function. Experimental studies have indicated that Klotho contributes to cerebrospinal fluid homeostasis, synaptic plasticity, neurogenesis, myelination, and resistance to metabolic and oxidative stress. Rather than acting through disease-specific pathways, Klotho stabilizes the core physiological axes that govern neuronal resilience, including Ca2+ signaling, mitochondrial-redox homeostasis, neuroimmune balance, growth factor signaling, and barrier integrity. Consistent with these physiological roles, reduced Klotho availability is associated with cognitive decline and multiple neurodegenerative disorders. This review positions Klotho as a central determinant of cognitive reserve and neuro-resilience, providing a unifying physiological framework that links systemic homeostasis to brain aging and explains how disruption of Klotho signaling amplifies vulnerability to neurodegenerative disease, whereas its preservation supports lifelong brain integrity.
The exponential growth in plastic production since the mid-twentieth century has led to the pervasive presence of micro- and nanoplastics (MNPs) across ecosystems and human exposure pathways, coinciding with a rising global burden of neurological disorders. Increasing evidence demonstrates that MNPs are not confined to peripheral tissues but can accumulate even in the human brain, raising concerns about their potential contribution to neurological disease. This structured review synthesizes global trends in plastic production, environmental MNP burden, and human exposure, together with emerging data on brain accumulation, entry pathways, neurotoxic mechanisms, and key translational challenges. We present evidence showing that MNPs may cross brain barriers via multiple routes, including the blood-brain barrier, blood-cerebrospinal fluid barrier, olfactory, and circumventricular pathways, particularly under conditions of barrier vulnerability. Experimental studies reveal that once in neural tissue, MNPs may disrupt synaptic function, mitochondrial homeostasis, autophagy, and redox balance, while activating neuroinflammatory and gut-brain axis-mediated pathways. These mechanisms intersect with disease-relevant processes implicated in multiple neurological disorders whose global prevalence and societal burden have sharply increased over recent decades, including stroke, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, mood disorders, and neurodevelopmental conditions. Despite growing mechanistic plausibility, translational and human epidemiological evidence remains limited by methodological heterogeneity, a lack of standardized detection methods, and the absence of longitudinal clinical data/studies. We highlight critical analytical and translational gaps, public health implications, and priorities for longitudinal, biomarker‑driven studies needed to rigorously test whether MNPs may contribute to population‑level risk of neurological disease.
Deep learning approaches have become central to brain MRI analysis; however, their reliability under dataset shift remains a critical barrier to safe and scalable deployment in neuroscience and clinical research. While convolutional neural networks (CNNs) provide strong locality-driven inductive biases for robust feature extraction, they lack global contextual awareness. Conversely, transformer-based architectures capture long-range dependencies but often exhibit reduced robustness and miscalibrated confidence when applied to heterogeneous medical imaging data, particularly in Cross-Dataset settings. In this work, we propose a calibration-aware hierarchical CNN-Transformer fusion framework designed for robust brain MRI analysis under dataset shift. The architecture integrates a pretrained multi-scale CNN backbone with a hierarchical transformer branch and performs scale-aligned fusion through cross-attention mechanisms. By allowing local convolutional features to selectively query global contextual representations, the proposed design maintains stable feature contributions during fusion and mitigates overconfident reliance on transformer features when generalization degrades across datasets. The framework is evaluated using a strict Cross-Dataset protocol, where models are trained on one dataset and tested on a distinct dataset. Experimental results demonstrate that the proposed fusion model achieves competitive classification performance while substantially improving probabilistic calibration relative to both CNN-only and transformer-only baselines. Specifically, the model attains an average accuracy of 99.20% and achieves lower Expected Calibration Error (ECE = 0.0041), Brier score (0.0028), and Negative Log-Likelihood (NLL = 0.0277) compared to a standalone Swin Transformer and a strong ResNet50 baseline. These findings demonstrate that calibration-aware hierarchical CNN-Transformer fusion enhances both predictive reliability and robustness under Cross-Dataset evaluation. By improving the alignment between predictive confidence and empirical correctness, the proposed method supports safer large-scale analysis of heterogeneous brain MRI data, with important implications for multi-center neuroscience studies and trustworthy clinical decision support.
Synthetic data generation (SDG) structured health data is increasingly promoted as a solution to longstanding barriers in health data access. It is offering the promise of privacy-preserving data reuse for research, innovation, and policy. Despite rapid technical advances, the adoption of synthetic health data in real-world settings remains limited. Shaped by challenges around data quality, representativeness, infrastructure readiness, trust, and legal uncertainty, this viewpoint draws on experiences from 7 European research initiatives within the HealthData4EU cluster to reflect on how SDG is being operationalized in practice. It synthesizes cross-project insights to highlight recurring methodological and governance tensions and to examine their implications for trust and responsible use. The analysis argues that trustworthy SDG cannot be achieved through technical optimization alone but requires alignment between evaluation practices, upstream data stewardship, regulatory clarity, and sustained stakeholder engagement. Addressing these conditions is essential for moving synthetic data from experimental pilots toward a credible and sustainable component of European health research ecosystems.
Major advances have been made in understanding the biological mechanisms underlying the Dark Triad - Machiavellianism, narcissism, and psychopathy - yet existing research remains fragmented and rarely examines these traits as an integrated construct. Previous studies have identified structural and functional brain correlates of individual components, but findings are often inconsistent and isolated. This systematic review addresses this gap by synthesizing evidence from 16 empirical studies with a total sample of N = 4246 participants. Integrating results from neuroimaging, lesion, and genetic research, the review provides the first comprehensive overview of the neural architecture of the Dark Triad. The findings indicate a shared core of heightened striatal reward sensitivity, alongside distinct neural profiles: Machiavellianism is associated with enhanced prefrontal and insular activity, psychopathy with deficits in amygdala-orbitofrontal circuits, and narcissism with altered default mode network functioning related to self-referential processing. Overall, the Dark Triad is best understood as emerging from distributed, interacting neural systems rather than isolated brain regions.
Diffusion-weighted magnetic resonance imaging provides a non-invasive way to probe brain tissue microstructure and is widely used in neuroscience and clinical research. Reliable microstructural maps usually require long scan times because many measurements are needed to sample the underlying parameter space. This limits clinical feasibility and accessibility. The aim of this study is to determine whether simulation-based inference can reduce the amount of diffusion data required while preserving estimation fidelity across commonly used diffusion models. We apply simulation-based inference using neural posterior estimation to infer diffusion parameters directly from measured signals. The approach is tested on diffusion tensor imaging, diffusion kurtosis imaging, and biophysical models of axonal density and size. Models are trained entirely on simulated data and evaluated using both simulated datasets and experimental brain data from healthy and pathological individuals. Performance is compared with standard non-linear least squares fitting under noisy and sparsely sampled conditions. Here we show that simulation-based inference achieves reliable parameter estimates using up to 90% fewer measurements than conventional approaches. The method consistently outperforms standard fitting when data are noisy or limited and remains robust across models, sampling schemes, and both healthy and pathological brain data. This study demonstrates that simulation-based inference enables fast and robust microstructural imaging with substantially reduced scan times. The approach supports privacy-preserving workflows, could expand dMRI access, e.g., for pediatric and other time-sensitive patients, enable advanced microstructure-sensitive protocols, and rescue legacy data with suboptimal quality. Magnetic resonance imaging (MRI) is widely used to study the brain, but advanced MRI methods that reveal fine details of brain tissue usually require long scan times. This makes them difficult to use in everyday clinical practice. The aim of this study was to find a way to obtain detailed brain information using much shorter MRI scans. To do this, we used computer simulations and artificial intelligence to learn how to estimate brain tissue properties from limited and noisy MRI data. Instead of training on patient data, the method was trained only on signals designed to imitate those seen in real patient data. We show that reliable brain measurements can be obtained with far fewer MRI scans than usual. This could make advanced MRI faster, more accessible, and easier to use in hospitals. In the future, this approach may help improve diagnosis of disease while reducing scan time and patient burden.
The structure of biology spans length scales from meters to Ångstroms - from whole organisms to the atomic positions of macromolecules. Cryo-electron microscopy is well-established for determining the structures of individual macromolecules in isolation, including pathological aggregates from post-mortem donor Alzheimer's disease brain. Recent advances integrating cryo-fluorescence microscopy, sample preparation and cryo-electron tomography are revealing macromolecular structures in the context of cells and anatomically intact tissues. In this chapter, we describe experimental workflows for targeting the in-tissue structure of Alzheimer's disease pathology. We discuss associated practical considerations and limitations of fluorescence labelling, vitrification, sample thinning by cryo-ultramicrotomy and cryo-focused ion-beam scanning electron microscopy (cryoFIB-SEM), cryogenic correlated light and electron microscopy (cryoCLEM), cryo-electron tomography (cryoET) and in-tissue subtomogram averaging (STA). These experimental considerations may be useful and applicable to amyloids, diseases and fundamental structural biology research questions more broadly.
The 30th Annual Society on Neuroimmune Pharmacology (SNIP) conference will be held on May 3-6th at the Graduate Hotel by Hilton in Annapolis, Maryland. This 4-day conference will present preclinical, translational, and clinical research in the intersecting fields of neuro-HIV and substance use disorders, as well as related neurodegenerative conditions. The speakers and poster presenters will share cutting-edge research funded by the National Institutes of Health. On the first day, we will have two concurrent preconference symposia. The first is "Single Cell HIV and SUD Effects on the Brain: SCORCH Consortium Progress", with an overview and 7 presentations by investigators, highlighting the outstanding work in the Single Cell Opioid Response in the Context of HIV (SCORCH). The second concurrent symposium is "Catalyzing Interdisciplinary Research on HIV-Associated Co-occurring Conditions." In the evening, we will have our first Poster Session with 52 abstracts by early-stage-career investigators (ECIs), including those that received the ECI travel awards. On days 2-4, in addition to a plenary talk and two memorial lectures, we will have 11 symposia, with 62 speakers (including 12 who are early-stage career investigator travel awardees), and 65 additional poster presentations. In total, the 30th SNIP conference received 185 abstracts for the 70 oral presentations and 115 posters. Topics covered by these symposia and poster presentations include mechanistic and observational studies that evaluate neuronal injury and neuroinflammation associated with HIV brain infection, and how drugs of abuse, including stimulants, opioids, and cannabis, may exacerbate or mitigate neuropathogenesis. In addition, with the aging population of people with HIV and many with substance use disorders, recent work also evaluated how aging and various neurodegenerative disorders could further impact brain health. At the plenary lecture, Dr. Nora Volkow will highlight the priorities of HIV research at the National Institute on Drug Abuse (NIDA), while our banquet speaker, Dr. Avindra Nath will elucidate how viruses, particularly retroviruses, may invade the brain, infect brain cells, and adapt to the local environment for decades or mutate and possibly lead to neurodegenerative disorders. This will be an exciting conference that will continue SNIP's emphasis on the career development of early-stage investigators.
Subarachnoid hemorrhage (SAH) is a severe cerebrovascular condition associated with high morbidity and mortality. Inflammation and oxidative stress play critical roles in its pathophysiology, especially in the development of secondary vascular damage. This study aimed to evaluate the protective effects of colchicine on vascular integrity and biochemical markers following SAH in an experimental rat model. Eighteen female Sprague Dawley rats were randomly divided into 3 groups: Control (no SAH), SAH (induced without treatment), and SAH + colchicine (received intraperitoneal colchicine at a dose of 1 mg/kg). SAH was induced by injecting autologous blood into the cisterna magna. Rats were sacrificed 48 h post induction. Biochemical parameters were assessed in serum and brain tissue, and histopathological evaluations were conducted to assess vascular damage. Compared to the untreated SAH group, colchicine significantly reduced serum levels of interleukin-1β, interleukin-6, and tumor necrosis factor-α (p < 0.05). Oxidative stress markers, including total oxidant status and oxidative stress index, decreased, while total antioxidant status showed partial recovery. Thiol-disulfide homeostasis was improved, evidenced by elevated native thiol levels and reduced disulfide/native thiol ratios. Histopathological analyses showed attenuation of endothelial injury and inflammation; however, basilar artery diameter and wall thickness remained statistically unchanged. Colchicine reduced inflammation and oxidative stress markers in an experimental rat model of SAH, offering partial protection against vascular injury. Further studies are needed to evaluate long-term effects and dosing strategies for colchicine as a neuroprotective agent in cerebrovascular injury.
Mental health difficulties are common following moderate-to-severe traumatic brain injury (TBI) and impact health-related quality of life. This systematic review and meta-analysis evaluated the effectiveness of psychosocial interventions for adults with moderate-to-severe TBI experiencing mental health difficulties (anxiety, depression, psychological distress, suicidality, alcohol/substance misuse, insomnia and sexual dysfunction). Psychological and behavioural interventions across settings were compared with control/baseline conditions in clinical trials or single-case experimental-designs, with self-reported mental health symptoms as the primary outcome. Five databases were searched in May 2024 for studies published worldwide. Screening and risk-of-bias ratings were performed by two independent reviewers. Thirty-three studies were identified; 22 were included in the meta-analysis. Cognitive behaviour therapy (CBT) showed moderate effects for anxiety, depression, distress and suicidality (Hedges' g = 0.48); acceptance and commitment therapy showed small-moderate effects (g = 0.43). Psychological interventions (e.g., motivational interviewing) showed small-moderate effects for alcohol/substance misuse (g = 0.39), and CBT showed small-moderate effects for insomnia (g = 0.30). GRADE certainty of evidence was low for anxiety, depression, distress and suicidality, and very low for alcohol/substance misuse, sleep difficulties/insomnia and sexual dysfunction. Psychosocial interventions appear beneficial for mental health difficulties post-TBI, with most consistent evidence for CBT. Findings will inform Clinical Practice Guidelines.
Neuroangiostrongyliasis is a neuroinvasive helminth infection caused primarily by the rat lungworm Angiostrongylus cantonensis, which is the main causative agent of eosinophilic meningitis in humans. The closely related species Angiostrongylus malaysiensis coexists in many endemic regions particularly in Asia and Oceania and shares substantial morphological and genetic similarity with A. cantonensis, yet its pathogenic potential remain poorly understood. Here, we performed a direct comparative investigation of neuropathogenesis and host immune responses following experimental infection with A. cantonensis or A. malaysiensis in a murine model. Both species established central nervous system infection and induced neurological manifestations and inflammatory responses. However, infection with A. malaysiensis resulted in more severe clinical disease, characterized by greater weight loss, higher clinical scores, and extensive cerebral hemorrhage, accompanied by increased parasite invasion into the brain parenchyma. In contrast, A. cantonensis infection elicited stronger neuroimmune activation, including increased leukocyte recruitment and elevated expression of type 2 cytokines and chemokines within the brain and meninges. Despite the more severe neurological complications observed in A. malaysiensis infection, immune cell accumulation in the central nervous system was comparatively reduced, suggesting differences in parasite containment at the neuroimmune interface. Together, these findings demonstrate that closely related Angiostrongylus species can induce distinct patterns of neuropathogenesis and immune regulation. Our results highlight the importance of species-specific host-parasite interactions in shaping disease severity and provide new insight into mechanisms underlying the pathogenesis of neuroangiostrongyliasis.
Fecal microbiota transplantation (FMT) has emerged as a novel approach for understanding anorexia nervosa (AN), a complex eating disorder characterized by severe underweight, fear of weight gain and distorted body image. Patients with AN show alterations in the gut microbiome, brain structure, and inflammatory processes, indicating the importance of the microbiome‒gut‒brain axis in AN pathology. This study aimed to investigate whether FMT from patients with AN into antibiotic-treated rats could transfer a phenotype associated with the disease inducing AN-like symptoms and hippocampal alterations. Female Wistar rats received antibiotics followed by FMT from healthy controls, patients with AN, or water. Gut microbiota effects were assessed through 16S rRNA gene sequencing, alongside post-mortem analyses of glial cells, neurogenesis markers, and inflammatory markers. The results revealed dysregulated microbial diversity after antibiotic treatment, which was partially restored after FMT. Successful transfer of human bacterial species was observed, but AN-like symptoms and changes in glial/neuronal counts were not detected. Notably, a decrease in hippocampal Bdnf expression was detected in the antibiotic control group, which was reversed by healthy control stool transplantation but not in the AN-transplanted group. Similar patterns were observed for neuroinflammation and Mki67, a marker of cell neogenesis. These findings suggest potential links between microbial changes, neuroinflammation and neuroplasticity in the hippocampus with the potential to correct deficits with FMT. Future studies should extend these findings by exploring the combination of FMT and starvation phases to better understand the roles of specific microbial populations in neuroinflammatory processes and, ultimately, clinical outcomes in AN.
Following the publication of the above paper, it was drawn to the Editor's attention by a concerned reader that various of the western blot data featured in Fig. 2B appeared to have also been included in Figs. 4B and 8A; moreover, western blot data also appeared to have been duplicated comparing Figs. 3A and 8A, Figs. 4B and 5A, Figs. 3A and 5A, and Figs. 6A and 7A. In addition, western blot data featured in various of these figures also reappeared in two papers written by different authors at different research institutes that were submitted for publication at later dates to the journals Experimental and Therapeutic Medicine and Molecular Medicine Reports. In view of the fact that so many instances of the duplication of data within several of the figures in the above paper were identified, the Editor has decided that this paper should be retracted from the Journal on account of a lack of confidence in the data. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Molecular Medicine Reports 12: 6591‑6597, 2015; DOI: 10.3892/mmr.2015.4292].
Both basic and clinical consciousness research aims to find objective measures that reliably distinguish conscious from unconscious brain states. Electroencephalogram (EEG) measures are widely used, although they may be affected by interference from electrical signals such as those generated by muscles. To assess this source of error, we investigated the impact of neuromuscular blockade (NMB) on proposed measures of awareness (spectral slope, Lempel-Ziv complexity (LZc), connectivity, alpha peak frequency, power in canonical EEG frequency bands) computed from spontaneous high-density EEG recorded from six healthy volunteers in three different conditions: (1) awake-unparalysed (normal wakefulness), (2) awake-paralysed (complete paralysis caused by neuromuscular blocking agent (NMBA)), and (3) sedated-paralysed (deep sedation with propofol, with paralysis by NMBA). The measures we investigated distinguished awake-unparalysed states from sedated-paralysed with close to perfect accuracy in accordance with past findings. However, our analysis revealed a serious failure of most measures to recognise the awake-paralysed condition as an aware state. Errors ranged from 7% of awake-paralysed time segments predicted as unaware (using alpha power) to 100% (using LZc). Using a unique high-density EEG data set, this study clearly demonstrates that many EEG-based measures fail to recognise awareness in awake subjects under the influence of muscle relaxants. These results highlight critical limitations of current EEG-based measures at detecting awareness.
Semantic action sequence knowledge (sASK), the ability to select and correctly order steps in everyday tasks, is a key component of daily functioning. Individuals with Acquired Brain Injury (ABI) often show impairments in sASK, affecting independence. Few standardized tools assess this ability. This study examined the adequacy and preliminary validity of the Daily Action Sequence Task (DAST). Forty-six healthy participants and 27 individuals with ABI completed the DAST, which requires arranging the steps of 15 familiar daily activities in the correct order. Construct validity was assessed by comparing DAST performance between groups and examining associations with executive, attentional, and memory functions. Predictive validity was evaluated by testing whether DAST performance predicted cognitive errors during everyday activities. The DAST provided a benchmark of functional action sequences. Participants with ABI completed fewer correct sequences than controls, and DAST performance strongly predicted everyday cognitive functioning, outperforming a traditional cognitive screening tool. The DAST is a promising, easy-to-use tool for assessing sASK in individuals with ABI and may help identify difficulties in organizing everyday actions. Further studies are needed to confirm these preliminary findings and fully evaluate its validity and reliability. Persistent impairments in semantic Action Sequence Knowledge after acquired brain injury can significantly reduce the ability to perform daily activities independently.A standardized tool like the Daily Action Sequence Task provides a benchmark of functional action sequences and allows clinicians to systematically assess semantic Action Sequence Knowledge, which can help identify specific areas of difficulty.Based on Daily Action Sequence Task performance, clinicians could design targeted rehabilitation interventions, supporting the planning and execution of everyday tasks and promoting independence and functional recovery.
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Caregiver-infant interaction represents the space where development happens through time. According to the mutual regulation model (MRM) by Tronick, meaning-making, emotion regulation, and stress resilience all emerge from the complex fabric of caregiver-infant interaction. Within this model, the dyadic expansion of consciousness (DEC) identifies how adult caregivers and infants co-create an expanded state of consciousness characterized by greater complexity through reciprocal interactions of their individual states of consciousness and alternating phases of matching, mismatching, and reparation. The well-validated Face-to-Face Still-Face paradigm (FFSF), by introducing experimental manipulations of caregiver's interactive availability, represents a reliable procedure to investigate these early forms of socio-emotional and socio-cognitive exchanges. Nonetheless, there is a general lack of studies investigating and providing measures of DEC. Recent advancements in the developmental neuroscience field (i.e., hyperscanning protocols) hold promises to provide renewed interest in studying DEC by exploring the dyadic co-regulation of inter-brain coupling and uncoupling from a caregiver-infant perspective. By employing diverse emerging metrics of neural coupling, researchers can investigate, using unprecedented neuroscientific approaches, how the behavioral and neural activity of each interactive partner may lead to the emergence of a "two-brained system" capable of producing dyadic meanings through dynamically synchronized and resonating individual brain networks. In the present contribution, we highlight how developmental hyperscanning research can be beneficial to our comprehension of the early mutual regulation processes occurring in caregiver-infant dyads.
Following subarachnoid hemorrhage (SAH), long-lasting inflammation triggered by activated glial cells has adverse effects on neurological recovery. As an α2 adrenoceptor agonist commonly utilized for sedative purposes, dexmedetomidine (DEX) has demonstrated the ability to confer neuroprotective effects across diverse physiological or pathological conditions. This study was designed to determine whether DEX protects against SAH by altering astrocytic reactivity. Eight-week-old male C57BL/6 mice were subjected to experimental SAH. They were treated with DEX in the presence or absence of the α2 adrenoceptor antagonist atipamezole (ATI) via intraperitoneal injection. Neurological function was evaluated on the basis of a modified Garcia score and beam balance test. TUNEL staining was conducted to assess neuronal apoptosis. Western blotting was carried out to determine the expression of Bcl-2, Bax, and cleaved caspase-3 in the hippocampus and ZO-1 and occludin in the cortex, and ELISA was conducted to measure TNF-α, IL-6, IL-1β, and HMGB1 expression. The wet‒dry method was employed to measure the water content in the brain tissue. The permeability of the blood‒brain barrier (BBB) was assessed via Evans blue staining. Primary astrocytes were treated with S100A4 and/or DEX. The expression levels of GFAP, C3, GBP2, Serping 1, PTX3, S100A10, S100A4, and the NF-κB pathway were also determined. DEX improved early neurological deficits in SAH mice, mitigated the permeability of the BBB, and reduced the brain water content. DEX attenuated neuronal apoptosis and proinflammatory cytokine (TNF-α, IL-6, IL-1β and HMGB1) expression in the cortex. However, DEX-mediated protective effects were attenuated by ATI administration. Additionally, DEX attenuated GFAP, C3, Serping1, S100A4, and NF-κB pathway activation in the brain and in S100A4-treated primary astrocytes, whereas ATI reversed the effects of DEX. DEX has neuroprotective and anti-inflammatory effects in SAH through the inhibition of S100A4-mediated astrocytic "A1" polarization via the activation of the α2A adrenoceptor.