Li Min Li

Climate change, driven predominantly by anthropogenic actions, represents a defining challenge of the 21st century. While its general health implications are well documented, the specific impact of global warming on neurological diseases has remained underemphasized for decades. To evaluate the association between rising global temperatures and the exacerbation or incidence of various neurological conditions through a systematic review. A systematic search was conducted in the PubMed/MEDLINE and SciELO databases for studies published between 2011 and 2026. Following strict eligibility criteria, 13 peer-reviewed articles were selected for qualitative synthesis. The evidence reveals that rising temperatures are increasingly linked to the worsening of conditions such as epilepsy, stroke, multiple sclerosis (MS), and neurodegenerative disorders like Alzheimer's and Parkinson's diseases. Specifically, heat exposure is associated with higher hospitalization rates and acute symptom exacerbation, such as Uhthoff's phenomenon in MS and autonomic thermoregulatory failure in Parkinson's. Although some geographic and methodological discrepancies exist, particularly regarding stroke and seizure frequency, the overall trend indicates increased neurological vulnerability to thermal stress. While research is expanding, neurological diseases remain an understudied frontier of the climate crisis. Targeted scientific investigation and robust public health strategies are imperative to mitigate the emerging neurological risks of a warming planet.

The climate crisis has emerged as a defining challenge of the 21st century, with profound implications for human health. While its environmental and economic consequences are widely recognized, its impact on neurological disorders remains underexplored. Epilepsy, affecting approximately 1% of the global population, represents a uniquely sensitive model to understand the complex interplay between environmental, biological, and social determinants of brain health. This perspective examines how climate change may influence epilepsy through multiple pathways. Rising temperatures, air pollution, and the expansion of climate-sensitive infectious diseases contribute both directly and indirectly to seizure risk and disease burden. Mechanisms include sleep disruption, metabolic and electrolyte imbalance, neuroinflammation, and increased cerebrovascular risk. In addition, climate-related disruptions to healthcare systems, medication stability, and access to treatment further compromise disease control, particularly in vulnerable populations. The climate crisis also amplifies existing social inequalities, disproportionately affecting individuals in low- and middle-income regions where epilepsy burden is already higher. These overlapping vulnerabilities and epilepsy stigma highlight the need for a broader framework that integrates environmental determinants into neurological care and research. More than an emerging area of study, this is a call for action. Neurology must expand its scope to address the health impacts of a rapidly changing planet. Recognizing epilepsy as a sentinel condition in this context may help guide more resilient, equitable, and forward-looking approaches to brain health in the decades ahead.

O Compromisso de Campinas pela IA Ética e Soberana constitui um manifesto elaborado a partir das reflexões, debates e diálogos promovidos pelo InPacto, iniciativa do CPDI Ibrachina Ibrawork voltada à discussão dos impactos da Inteligência Artificial no desenvolvimento do Brasil. O documento reúne princípios e recomendações para orientar a construção de uma estratégia brasileira de Inteligência Artificial comprometida com a soberania tecnológica, a democracia, o desenvolvimento humano, a sustentabilidade e a cooperação entre os diferentes setores da sociedade. O manifesto aborda temas como a IA como questão estratégica nacional, a necessidade de uma regulação ética e democrática, o fortalecimento da infraestrutura tecnológica nacional, a formação humana, a utilização da IA na gestão pública e nas cidades, bem como sua contribuição para a sustentabilidade, a adaptação às mudanças climáticas e o desenvolvimento local. Também apresenta recomendações dirigidas aos formuladores de políticas públicas e um convite para que lideranças políticas, acadêmicas, empresariais e da sociedade civil assumam um compromisso com uma Inteligência Artificial orientada pelo interesse público. O documento conclui reafirmando que o desenvolvimento da IA deve fortalecer a inovação, reduzir desigualdades e colocar a tecnologia a serviço das pessoas, das comunidades e do futuro do Brasil.

A Inteligência Artificial tornou-se um dos principais fatores de transformação econômica, política e geopolítica do século XXI, exigindo que os países desenvolvam estratégias capazes de conciliar inovação tecnológica, democracia e soberania. Este capítulo analisa o papel da IA como infraestrutura crítica para o desenvolvimento nacional, discutindo seus impactos sobre a organização do Estado, a economia, a sociedade e as relações internacionais. A partir de uma perspectiva que integra neurociência, inovação e políticas públicas, são examinados os desafios decorrentes da concentração tecnológica, da desinformação, da influência das grandes plataformas digitais e da crescente disputa global por infraestrutura computacional, dados e capacidade científica. O texto propõe que a construção de uma Inteligência Artificial soberana depende do fortalecimento de quatro pilares estratégicos: infraestrutura computacional, dados, formação de recursos humanos qualificados e investimento contínuo em pesquisa e desenvolvimento. Defende ainda que a governança da IA deve estar orientada pelo desenvolvimento humano, pela proteção da democracia, pela diversidade cultural e pela preservação da autonomia nacional. Conclui que o desafio brasileiro não consiste apenas em adotar novas tecnologias, mas em construir uma estratégia própria de desenvolvimento que coloque a Inteligência Artificial a serviço das pessoas, fortalecendo a soberania tecnológica, a inclusão social e o bem comum.

Epilepsy, described for millennia, has historically been interpreted through supernatural perspectives, leading to the search for religious intercession. Among the saints associated with the disease, Saint Valentine stood out in medieval Europe, especially in German-speaking regions, where his image was depicted curing people with seizures. Pilgrimages to sites with relics and popular names such as “Saint Valentine's Disease” highlight this devotion. In the 21^st century, this symbolic heritage was reinterpreted in the context of advocacy, influencing the creation of International Epilepsy Day, celebrated on the second Monday of February, close to the saint's liturgical date on February 14^th. This article revisits the historical trajectory of this association and discusses how cultural elements can be used to reduce stigma and promote scientific awareness about epilepsy. Conceptualization: PVT, LML, JWS; Supervision: JWS; Writing - original draft: PVT, LML; Writing - review & editing: PVT, LML, JWS. Data will be available upon request to the corresponding author. Editor-in-Chief: Hélio A. G. Teive.https://orcid.org/0000-0003-2305-1073 Associate Editor: Eliaz Engelhardt.https://orcid.org/0000-0003-4168-1992 Received: 14 August 2025 Accepted: 18 December 2025 Article published online: 07 April 2026 © 2026. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit (https://creativecommons.org/licenses/by/4.0/) Thieme Revinter Publicações Ltda. Rua Rego Freitas, 175, loja 1, República, São Paulo, SP, CEP 01220-010, Brazil

Deep vision foundation models such as DINOv3 offer strong visual representation capacity, but their direct deployment in medical image segmentation remains difficult due to the limited availability of annotated clinical data and the computational cost of full fine-tuning. This study proposes an adaptation framework called StrDiSeg that integrates lightweight bottleneck adapters between selected transformer layers of DINOv3, enabling task-specific learning while preserving pretrained knowledge. An attention-enhanced U-Net decoder with multi-scale feature fusion further refines the representations. Experiments were performed on two publicly available ischemic stroke lesion segmentation datasets—AISD (Non Contrast CT) and ISLES22 (DWI). The proposed method achieved Dice scores of 0.516 on AISD and 0.824 on ISLES22, outperforming baseline models and demonstrating strong robustness across different clinical imaging modalities. These results indicate that adapter-based fine-tuning provides a practical and computationally efficient strategy for leveraging large pretrained vision models in medical image segmentation.

Carotid artery stenosis (CAS) is a common vascular disease with long-term consequences for the brain. Although CAS is strongly associated with impaired cerebral hemodynamics and neurodegeneration, the mechanisms underlying hemodynamic impairment in the microvasculature remain unknown. In this work, we employed functional near-infrared spectroscopy (fNIRS) to introduce a methodological approach for quantifying the temporal delay of the evoked hemodynamic response. The method was validated during a vasodilatory task (breath-holding) in 50 CAS patients and 20 controls. Our results suggest that the hemodynamic response to breath-holding can be delayed by up to 6 s in the most severe patients, a significant increase from the median 4 s measured for the control group (p = 0.01). In addition, the fraction of brain regions that responded to the task decreased as the CAS severity increased, from a median of 90% in controls to 73% in the most severe CAS group (p = 0.04). The presence of collateral circulation increases the response to breath-holding and decreases the average time delays across the brain, although the number of communicating arteries alone cannot predict these fNIRS-based hemodynamic variables (p > 0.09). Overall, this work proposes a method to quantitatively assess impaired cerebral hemodynamics in CAS patients.

The study of functional reorganization following stroke has been steadily growing supported by advances in neuroimaging techniques, such as functional magnetic resonance imaging (fMRI). Concomitantly, graph theory has been increasingly employed in neuroscience to model the brain's functional connectivity (FC) and to investigate it in a variety of contexts. The aims of this study were: 1) to investigate the reorganization of network topology in the ipsilesional (IL) and contralesional (CL) hemispheres of stroke patients with (motor stroke group) and without (control stroke group) motor impairment, and 2) to predict motor recovery through the relationship between local topological variations of the functional network and increased motor function. We modeled the brain's FC as a graph using fMRI data, and we characterized its interactions with the following graph metrics: degree, clustering coefficient, characteristic path length, and betweenness centrality (BC). For both patient groups, BC yielded the largest variations between the two analyzed time points, especially in the motor stroke group. This group presented significant correlations (P<0.05) between average BC changes and the improvements in upper-extremity Fugl-Meyer (UE-FM) scores at the primary sensorimotor cortex and the supplementary motor area for the CL hemisphere. These regions participate in processes related to the selection, planning, and execution of movement. Generally, higher increases in average BC over these areas were related to larger improvements in UE-FM assessment. Although the sample was small, these results suggest the possibility of using BC as an indication of brain plasticity mechanisms following stroke.

Following a stroke, the brain undergoes a process of neuronal reorganization to compensate for structural damage and cope with functionality loss. Increases in stroke-induced neurogenesis rates in the dentate gyrus and neural migration from the hippocampus towards the affected site have been observed, suggesting that the hippocampus is involved in functionality gains and neural reorganization. Despite the observed hippocampal contributions to structural changes, the hippocampal physiology for stroke recovery has been poorly characterized. To this end, we measured resting-state whole-brain activity from non-hippocampal stroke survivors (n=13) during functional MRI scanning. Analysis of multiple hippocampal subregions revealed that the voxel activity of hippocampal readout sites (CA1 and subiculum) forecast the patient’s chronicity stage stronger than early regions of the hippocampal circuit. Furthermore, we observed hemispheric-specific contributions to chronicity forecasting, raising the hypothesis that left and right hippocampus are functionally dissociable during recovery. In addition, we suggest that in contrast with whole-brain analysis, the monitoring of segregated and specialized sub-networks after stroke potentially reveals detailed aspects of stroke recovery. Altogether, our results shed light on the contribution of the subcortical-cortical interplay for neural reorganization and highlight new avenues for stroke rehabilitation.