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Recessive hereditary methemoglobinemia (RHM) due to NADH-cytochrome b5 reductase deficiency is a rare disease caused by pathogenic variants in . Unlike type I, in RHM type II (RHM2), the enzymatic defect affects erythrocytes and all body tissues, thus resulting in cyanosis and neurological impairment. Although the first description of RHM2 dates back to the mid-1950s, detailed clinical and neuroimaging information are available for only a few patients. Here, we describe a new patient with RHM2 that harbors an unreported homozygous 31 Kb deletion involving part of , and showing a peculiar neuroimaging pattern resembling a ponto-cerebellar hypoplasia-like condition. A careful review of the available literature was performed with the aim of better delineating neurological and neuroimaging as well as the genotypic spectra of this extremely rare disease.
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http://dx.doi.org/10.3390/brainsci12020182 | DOI Listing |
Stroke
September 2025
Department of Neurology, Yale School of Medicine, New Haven, CT (L.H.S.).
Preclinical stroke research faces a critical translational gap, with animal studies failing to reliably predict clinical efficacy. To address this, the field is moving toward rigorous, multicenter preclinical randomized controlled trials (mpRCTs) that mimic phase 3 clinical trials in several key components. This collective statement, derived from experts involved in mpRCTs, outlines considerations for designing and executing such trials.
View Article and Find Full Text PDFAnn Acad Med Singap
August 2025
Dementia Research Centre (Singapore), Lee Kong Chian School of Medicine, Nanyang Technology University, Singapore.
Introduction: Interpretation and analysis of magnetic resonance imaging (MRI) scans in clinical settings comprise time-consuming visual ratings and complex neuroimage processing that require trained professionals. To combat these challenges, artificial intelligence (AI) techniques can aid clinicians in interpreting brain MRI for accurate diagnosis of neurodegenerative diseases but they require extensive validation. Thus, the aim of this study was to validate the use of AI-based AQUA (Neurophet Inc.
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August 2025
Aix-Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106, Marseille 13005, France.
Over three decades, statistical parametric mapping has transformed neuroimaging from descriptive mapping to causal inference, placing generative models at the core of causal explanations for brain function. It inspired to a large degree The Virtual Brain, which builds subject-specific digital twins from multimodal data, enabling brain simulations and exploration. Both frameworks converge at parameter estimation, where model and data meet, providing the mathematical manifestation of cause-effect in pathophysiology.
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August 2025
The Clinical Hospital of Chengdu Brain Sciences Institute, University of Electronic Sciences and Technology of China (UESTC), 2006 Xiyuan Avenue, West Hi Tech Zone, 611731, Chengdu, China.
This commentary reflects three decades of interaction between the Cuban neuroinformatics tradition and the statistical parametric mapping (SPM) framework. From the early development of neurometrics in Cuba to global initiatives like the Global Brain Consortium, our trajectory has paralleled and intersected with that of SPM. We highlight shared commitments to generative modeling, Bayesian inference, and population-level brain mapping, as shaped through collaborations, workshops, and joint theoretical work with Karl Friston and his group.
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August 2025
Department of Psychology, University of Milano-Bicocca, Milan, Italy.
Semantic composition allows us to construct complex meanings (e.g., "dog house", "house dog") from simpler constituents ("dog", "house").
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