Brain-X最新文献

{"title":"Bidirectional interaction between ferroptosis and chronic fatigue syndrome: Insights into neuroinflammation and oxidative stress","authors":"Guiping Wang,&nbsp;Peipei Guo,&nbsp;Cong Liu,&nbsp;Heng Tang,&nbsp;Yuanyuan Fan,&nbsp;Can Mei,&nbsp;Yujia Xu,&nbsp;Zijun Shi,&nbsp;Linwanyue Chen,&nbsp;Weiji Zhou,&nbsp;Qing Xu,&nbsp;Yuchen Huang,&nbsp;Tao Huang,&nbsp;Bin Deng,&nbsp;Jianbo Zhan,&nbsp;Jing Cheng","doi":"10.1002/brx2.70058","DOIUrl":"https://doi.org/10.1002/brx2.70058","url":null,"abstract":"<p>Chronic fatigue syndrome (CFS) is a multisystem disease of unknown aetiology. It disrupts multiple physiological systems, and its pathogenesis, reliable diagnostic markers and targeted therapies remain poorly understood. Ferroptosis is a newly characterised form of programmed cell death. This cell death is associated with the pathogenesis of a variety of neurodegenerative diseases, making it a potential therapeutic target for such diseases. In this review, we focus on the interplay between CFS and ferroptosis. Relevant domestic and international literature is reviewed to summarise available findings, elucidate molecular regulatory mechanisms, and identify promising directions for future research. Our analysis reveals a bidirectional interaction between CFS and ferroptosis. Ferroptosis may contribute to CFS through oxidative stress and neuroinflammation, whereas pathological changes associated with CFS could further exacerbate ferroptosis. This review first describes the function of ferroptosis in CFS pathogenesis. Targeting ferroptosis-related pathways may offer a potential therapeutic strategy for CFS. Nevertheless, further clinical evidence is still needed to support relevant research, and the specific regulatory network and interactions with other pathological mechanisms remain to be clarified.</p>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 3","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149146227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal trends, pathogen distribution, and forecasted burden of neonatal meningitis in China (1990–2023): A descriptive analysis based on Global Burden of Disease 2023","authors":"Mengya Sun,&nbsp;Mengmeng Ge,&nbsp;Lukun Tang,&nbsp;Xianghong Li,&nbsp;Guoqiang Cheng,&nbsp;Shujuan Li,&nbsp;Weiyin Yu,&nbsp;Shoo K. Lee,&nbsp;Joseph Y. Ting,&nbsp;Peng Zhang,&nbsp;Hong Jiang,&nbsp;Siyuan Jiang,&nbsp;Wenhao Zhou","doi":"10.1002/brx2.70057","DOIUrl":"https://doi.org/10.1002/brx2.70057","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Neonatal meningitis remains an important cause of mortality and health loss. We characterized temporal trends, pathogen distributions, and risk-attributable burden in China using Global Burden of Disease (GBD) 2023 estimates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We analyzed GBD-modeled incidence, mortality, disability-adjusted life years, years of life lost, and years lived with disability among early (0–6 days) and late (7–27 days) neonates. Trends were assessed using estimated annual percentage change (EAPC) and segmented log-linear regression. Log-exponential smoothing (ETS) projected mortality through 2035, with log-ARIMA as a sensitivity analysis. Pathogen shares and GBD-estimated risk-attributable burden were also assessed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>From 1990 to 2023, modeled incidence and mortality decreased from 715.7 and 98.0 to 79.0 and 4.5 per 100,000, respectively (EAPC = −7.6% [95% confidence interval {CI} −8.2 to −6.9] and −9.6% [95% CI −9.9 to −9.2]). Early-neonatal mortality remained higher than late-neonatal mortality (2023 rate ratio 1.8). Segmented regression identified 1997–2002 as the steepest decline. The 2035 log-ETS forecasts were 4.3 (95% prediction interval [PI] 0.5–10.4), 5.5 (95% PI 0.6–12.5), and 3.9 (95% PI 0.5–9.7) per 100,000 for overall, early, and late neonates. The cumulative share of pathogen-attributable mortality for the top five pathogens increased from 58.9% to 62.9%. Low birth weight and short gestation had the largest attributable fraction (47.7% [95% uncertainty interval 44.0%–51.1%]).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Despite substantial reductions in burden, persistent early-neonatal vulnerability and divergent exploratory forecasts underscore the need for clinical surveillance to validate these modeled findings and inform prevention.</p>\u0000 </section>\u0000 </div>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 3","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149084141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The neuro-immune interface in multiple sclerosis: From pathogenesis to therapeutic opportunities","authors":"Ruohan Wang,&nbsp;Mengqi Li,&nbsp;Xinyao Chen,&nbsp;Manling Lang,&nbsp;Qifei Cong","doi":"10.1002/brx2.70055","DOIUrl":"https://doi.org/10.1002/brx2.70055","url":null,"abstract":"<p>Multiple sclerosis (MS) is a chronic inflammatory and autoimmune disorder of the central nervous system, characterized by demyelination and axonal damage. The epidemiology of MS reflects a complex interplay between genetic susceptibility, including specific HLA alleles, and environmental factors such as geographic location, vitamin D status, and Epstein-Barr virus infection. MS is more common in women, who more frequently develop relapsing-remitting disease, whereas primary progressive MS is relatively more common in men. Disruption of the blood-brain barrier facilitates immune-cell infiltration and promotes neuroinflammation. The innate immune response involves macrophages, microglia, and other cell types that contribute to inflammation and neuronal damage. In contrast, the adaptive immune response is driven by autoreactive T and B cells, which damage myelin and neurons through cytokine production and antigen presentation. Glial cells play context-dependent roles in both promoting neuroinflammation and supporting tissue repair. Key molecular mechanisms include MHC-mediated antigen presentation, complex networks of pro-inflammatory and anti-inflammatory cytokines and chemokines that regulate cell migration, colony-stimulating factors, and complement system activation. Current therapeutic approaches primarily emphasize immunomodulation and immunosuppression using agents such as interferon-β, glatiramer acetate, monoclonal antibodies, and inhibitors of cell migration. Recent therapeutic developments, including cellular therapies and strategies that modulate the gut microbiota, offer new avenues for improving disease control and promoting repair in MS. Despite these advances, the interactions among immune, glial, and molecular mechanisms remain incompletely understood. Defining these interactions more precisely will be essential for developing more targeted and effective therapies.</p>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 2","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70055","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Divergent trajectories of major depressive disorder burden: A comparative analysis of trends in China and worldwide from 1990 to 2021, with projections to 2035","authors":"Ruiqi Wang,&nbsp;Xue Zhou,&nbsp;Xiongjun Xu,&nbsp;Ruoqi Shen,&nbsp;Yiju Huang,&nbsp;Xuyun Peng,&nbsp;Yang Yang,&nbsp;Weicheng Liang,&nbsp;Panlong Li","doi":"10.1002/brx2.70054","DOIUrl":"https://doi.org/10.1002/brx2.70054","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Backgroud</h3>\u0000 \u0000 <p>Major depressive disorder (MDD) remains a leading contributor to the global health burden. However, its burden exhibits substantial variation across populations and over time.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using data from the global burden of disease study 2021, we analyzed MDD metrics across 204 countries and territories in this study. Joinpoint regression was used to calculate annual percentage changes in MDD trends, and age–period–cohort analysis examined age, period, and cohort effects and local drift in disability-adjusted life years (DALYs). Bayesian age–period–cohort models projected age-standardized prevalence, incidence, and DALY rates through 2035 for China and worldwide.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>From 1990 to 2021, the number of MDD cases in China increased by 38.3%, whereas age-standardized rates declined, reaching levels approximately 49% lower than global averages in 2021. The global burden peaked at ages 20–39 years, whereas in China it peaked at 50–59 years, with widening sex disparities. Joinpoint analyses indicated a decline in the MDD burden in China, with a rebound during 2010–2015. Global trends showed a stable decline until 2010, followed by sustained growth and a sharp rise during 2019–2021. Age–period–cohort analysis showed an age-related increase and a period effect in China after 2010. The global pattern displayed a plateau in midlife, a decline at older ages, and stronger period effects after 2015. Projections indicated that the MDD burden would continue to decline in China but remain stable or increase worldwide through 2035.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Intensified efforts are needed to address the growing caregiving burden associated with aging populations and strengthen mental health service systems.</p>\u0000 </section>\u0000 </div>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 2","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From three-dimensional culture to translational modeling: Human spinal cord organoids as an emerging precision platform for neurotrauma research","authors":"Shi Lv,&nbsp;Xinggui Tian,&nbsp;Jingyi Sun,&nbsp;Sen Guo,&nbsp;Liang Liu,&nbsp;Wenzhao Wang,&nbsp;Zhijian Wei","doi":"10.1002/brx2.70056","DOIUrl":"https://doi.org/10.1002/brx2.70056","url":null,"abstract":"<p>Spinal cord injury (SCI) remains a debilitating neurological disorder for which no curative therapy currently exists, largely because conventional animal models and two‑dimensional cultures incompletely replicate the cellular complexity and pathophysiological dynamics of the human spinal cord. Human pluripotent stem cell (hPSC)‑derived spinal cord organoids (SCOs) provide a three‑dimensional platform that recapitulates essential features of regional patterning, cell‑type diversity, and nascent neural circuitry. This review systematically synthesises current strategies for generating these organoids through morphogen‑guided differentiation, their composition encompassing motor neurons, interneurons, astrocytes, and oligodendrocyte lineages, and the progressive incorporation of microglial and vascular elements to model neuroinflammation and barrier integrity. We critically appraise functional assessment techniques, including calcium imaging and multielectrode array recordings, alongside bioengineering advances such as microfluidic devices and bioprinting that improve structural organisation and experimental reproducibility. Despite notable progress, major constraints persist, including cellular immaturity, inadequate representation of chronic injury and ageing phenotypes, incomplete glial and vascular integration, and the absence of systemic immune and pharmacokinetic interactions. We argue that SCOs are presently best suited for mechanistic dissection, pharmacological screening, and patient‑stratified modelling, whereas therapeutic implantation remains at a preclinical stage. Translational impact will ultimately depend on rigorous standardisation, benchmarking against human reference atlases, regulatory qualification, and complementary validation using animal models and clinical endpoints.</p>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 2","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148942782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Liquid neural networks for adaptive latent brain-state modeling: A perspective","authors":"Yifan Zhang,&nbsp;Jingde Yin,&nbsp;Xiaoyue Ji,&nbsp;Jiansong Ji,&nbsp;Chun Sing Lai,&nbsp;Zhekang Dong","doi":"10.1002/brx2.70053","DOIUrl":"https://doi.org/10.1002/brx2.70053","url":null,"abstract":"<p>Understanding brain function requires models that characterize neural activity as evolving latent brain states rather than as isolated signal segments. Existing artificial intelligence methods have advanced neural decoding, disease classification, functional connectivity analysis, and brain–computer interfaces. However, brain-state prediction, temporal organization, state transitions, dynamical stability, and intervention responses are often studied as separate problems, limiting a unified understanding of how brain states are represented, organized, transformed, disrupted, and regulated. In this perspective, we examine liquid neural networks (LNNs) as a computational framework for adaptive latent brain-state modeling. We do not argue that LNNs are the only approach to continuous-time modeling. Instead, we focus on how their continuous dynamics and input- and state-dependent temporal adaptation can help link latent trajectories, temporal-scale regulation, state stability, and perturbation responses. We position LNNs in relation to spiking neural networks, recurrent neural networks, transformers, neural ordinary differential equations, and state-space models, and discuss their relevance to multimodal neural signal fusion, cortical hierarchical dynamics, brain-state transitions, dynamic disease prediction, and closed-loop neuromodulation. Overall, LNNs show promise for adaptive latent brain-state modeling, but their scientific and translational value depends on rigorous benchmarking, biological validation, computational feasibility, generalization, and real-world safety.</p>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 2","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Text-to-image generation method based on cognitive-inspired bidirectional attention mechanisms","authors":"Yunzhi Tian,&nbsp;Hongbo Wei,&nbsp;Wenhao Sun,&nbsp;Gengchen Liu,&nbsp;Weiqi Xue,&nbsp;Hao Zhang,&nbsp;Qingqi Zhou,&nbsp;Peng Wang,&nbsp;Jiaqing Yan","doi":"10.1002/brx2.70050","DOIUrl":"https://doi.org/10.1002/brx2.70050","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Backgroud</h3>\u0000 \u0000 <p>The human visual system can effectively perceive and understand complex visual scenes through the synergistic effect of bottom-up primary visual cortex feature extraction and top-down prefrontal cortex semantic guidance. This biological mechanism achieves an optimal balance between capturing fine-grained detail and comprehending global semantics, providing valuable inspiration for multimodal generation research.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Inspired by this neural mechanism, this study proposes a method for text-to-image multimodal tasks and presents a new diffusion model framework that integrates bottom-up and top-down attention mechanisms. The bottom-up mechanism employs global-shape convolution, local key aggregation, and hyperbolic space mapping to hierarchically extract multi-scale visual features, preserving both global structural integrity and local fine-grained details by adaptively highlighting salient image regions. The top-down mechanism dynamically modulates cross-attention weights using mutual information, which quantifies text–image semantic correlation to enhance task-relevant features, and information entropy, which measures feature uncertainty to suppress irrelevant noise.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Extensive experiments conducted on the Common Objects in Context (COCO), Fill50K, and Large Scale Scene Understanding (LSUN) datasets show that our model compared favorably with the Stable Diffusion model in generation quality and diversity, achieving an inception score of 21.64 and a Fréchet inception distance (FID) of 23.65 on the COCO dataset. The model also achieved FID scores of 3.06 on LSUN Bedrooms and 4.98 on LSUN Churches. Ablation studies further validated the synergistic effect of the bidirectional framework and the independent contribution of each component, with notable improvements observed in text-image alignment and fine-grained detail handling.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study demonstrates that cognitive-inspired bidirectional attention mechanisms can effectively enhance text-to-image generation by balancing structural fidelity and semantic consistency. The integration of mutual information and information entropy provides a novel theoretical approach for multimodal fusion tasks and offers new directions for advancing the quality and applicability of generative models.</p>\u0000 </section>\u0000 </div>","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 2","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148943703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"User vulnerability in artificial intelligence-based mental health interventions: Personality and developmental perspectives","authors":"Yuan Cao,&nbsp;Paulo Lizano","doi":"10.1002/brx2.70052","DOIUrl":"https://doi.org/10.1002/brx2.70052","url":null,"abstract":"&lt;p&gt;The rapid development of large language models is transforming psychiatric care, in part through the rise of chatbot-based digital mental health interventions. These artificial intelligence (AI)-driven interfaces function as a “digital first-aid kit” for individuals experiencing mental health challenges. Offering anonymity, immediate 24/7 access, personalized interaction, and low cost, they are often used before any contact with a human clinician. By lowering barriers to care, these tools have unprecedented potential to help close the global mental health gap. At the same time, they carry inherent risks. As Opel and Breakspear noted,&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; generative AI is susceptible to hallucinations and may align excessively with user intent, generating misguided or unsafe guidance that, in extreme cases, could contribute to suicide risk. While hallucinations and other model-level failures remain important concerns and may be partially mitigated through domain-specific fine-tuning and reinforcement learning,&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt; they represent only one side of AI-related risk. The safety of AI-mediated mental health support may also be shaped by user vulnerability, including how individuals interpret, trust, and respond to AI-generated outputs. Drawing on the biopsychosocial model, we propose that personality characteristics, developmental processes, clinical vulnerabilities, and social contexts may shape these responses (Figure 1).&lt;/p&gt;&lt;p&gt;In general, generative AI produces responses that are linguistically plausible rather than clinically grounded. Individuals frequently engage with chatbots as trusted peers, relying on emotional subtext and culturally grounded shorthand that current AI interfaces cannot reliably interpret. Particularly in those seeking emotional reassurance, this interaction may foster a perception of empathy and understanding that exceeds the actual capabilities of AI systems. Such perceptions may increase the likelihood of anthropomorphizing chatbots and relying on their guidance in emotionally salient situations. It is possible for individuals with attachment insecurity, interpersonal sensitivity, loneliness, reassurance-seeking tendencies, or dependency-related personality traits to be more likely to perceive AI as trusted social partners. This tendency may be particularly relevant in individuals with mental disorders; conditions frequently associated with interpersonal sensitivity and personality-related vulnerabilities. Across these disorders, altered functional networks involved in self-referential processing, salience detection, and cognitive control may increase susceptibility to external guidance, although direct evidence linking these neural alterations to AI overreliance remains limited. Within this context, reliance on AI advice may be shaped less by model accuracy alone but by user characteristics that influence trust, interpretation, and dependence on AI-generated guidance. Individuals with high sugges","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 2","pages":""},"PeriodicalIF":6.4,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/brx2.70052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148533482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148078987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":94303,"journal":{"name":"Brain-X","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148076545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}