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Genetic protection against Alzheimer disease 预防阿尔茨海默病的基因保护
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-05-14 DOI: 10.1038/s41582-024-00968-6
Lisa Kiani
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引用次数: 0
Infant microbiome predicts neurodevelopmental disorders 婴儿微生物组可预测神经发育障碍
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-05-14 DOI: 10.1038/s41582-024-00969-5
Lisa Kiani
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引用次数: 0
Blood test for early Parkinson disease diagnosis 用于早期诊断帕金森病的血液检测
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-05-14 DOI: 10.1038/s41582-024-00970-y
Lisa Kiani
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引用次数: 0
Nanoprobe for blood–brain barrier changes 检测血脑屏障变化的纳米探针
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-05-14 DOI: 10.1038/s41582-024-00971-x
Lisa Kiani
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引用次数: 0
CAR T cells offer hope in glioblastoma CAR T 细胞为胶质母细胞瘤带来希望
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-05-14 DOI: 10.1038/s41582-024-00972-w
Ian Fyfe
Novel CAR T cells delivered directly to the CNS could have therapeutic effects in recurrent glioblastoma, according to two early-stage trials.
根据两项早期试验的结果,直接向中枢神经系统输送的新型 CAR T 细胞可对复发性胶质母细胞瘤产生治疗效果。
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引用次数: 0
The clinical importance of suspected non-Alzheimer disease pathophysiology 疑似非阿尔茨海默病病理生理学的临床重要性
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-05-09 DOI: 10.1038/s41582-024-00962-y
Stephanie J. B. Vos, Aurore Delvenne, Clifford R. Jack Jr, Dietmar R. Thal, Pieter Jelle Visser
The development of biomarkers for Alzheimer disease (AD) has led to the origin of suspected non-AD pathophysiology (SNAP) — a heterogeneous biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. In this Review, we describe the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology. As we discuss, SNAP can be operationalized using different biomarker modalities, which could affect prevalence estimates and reported characteristics of SNAP in ways that are not yet fully understood. Moreover, the underlying aetiologies that lead to a SNAP biomarker profile, and whether SNAP is the same in people with and without cognitive impairment, remains unclear. Improved insight into the clinical characteristics and pathophysiology of SNAP is of major importance for research and clinical practice, as well as for trial design to optimize care and treatment of individuals with SNAP. Suspected non-AD pathophysiology (SNAP) is a biomarker-based concept that describes individuals with normal amyloid and abnormal tau and/or neurodegeneration biomarker status. This Review discusses the origins of the SNAP construct, along with its prevalence, diagnostic and prognostic implications, and underlying neuropathology.
阿尔茨海默病(AD)生物标志物的开发导致了疑似非 AD 病理生理学(SNAP)的起源--这是一种基于生物标志物的异质性概念,描述了淀粉样蛋白正常而 tau 和/或神经变性生物标志物异常的个体。在本综述中,我们将介绍 SNAP 概念的起源、流行程度、诊断和预后意义以及潜在的神经病理学。正如我们所讨论的那样,SNAP 可通过不同的生物标志物模式进行操作,这可能会以尚未完全理解的方式影响 SNAP 的患病率估计和报告特征。此外,导致 SNAP 生物标志物特征的潜在病因,以及 SNAP 在有认知障碍和无认知障碍的人群中是否相同,目前仍不清楚。更好地了解 SNAP 的临床特征和病理生理学对研究和临床实践以及试验设计至关重要,有助于优化对 SNAP 患者的护理和治疗。
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引用次数: 0
Artificial intelligence in epilepsy — applications and pathways to the clinic 人工智能在癫痫中的应用及临床路径
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-05-08 DOI: 10.1038/s41582-024-00965-9
Alfredo Lucas, Andrew Revell, Kathryn A. Davis
Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy have increased exponentially over the past decade. Integration of AI into epilepsy management promises to revolutionize the diagnosis and treatment of this complex disorder. However, translation of AI into neurology clinical practice has not yet been successful, emphasizing the need to consider progress to date and assess challenges and limitations of AI. In this Review, we provide an overview of AI applications that have been developed in epilepsy using a variety of data modalities: neuroimaging, electroencephalography, electronic health records, medical devices and multimodal data integration. For each, we consider potential applications, including seizure detection and prediction, seizure lateralization, localization of the seizure-onset zone and assessment for surgical or neurostimulation interventions, and review the performance of AI tools developed to date. We also discuss methodological considerations and challenges that must be addressed to successfully integrate AI into clinical practice. Our goal is to provide an overview of the current state of the field and provide guidance for leveraging AI in future to improve management of epilepsy. Integration of artificial intelligence into epilepsy management could revolutionize diagnosis and treatment. In this Review, the authors provide an overview of artificial intelligence applications that have been developed in epilepsy and discuss challenges that must be addressed to successfully integrate artificial intelligence into clinical practice.
人工智能(AI)正在迅速改变医疗保健,其在癫痫领域的应用在过去十年中呈指数级增长。将人工智能融入癫痫管理有望彻底改变这一复杂疾病的诊断和治疗。然而,将人工智能转化为神经病学临床实践尚未取得成功,这就强调了有必要考虑迄今为止所取得的进展,并评估人工智能所面临的挑战和局限性。在本综述中,我们将概述利用各种数据模式在癫痫领域开发的人工智能应用:神经影像学、脑电图、电子健康记录、医疗设备和多模态数据集成。对于每种模式,我们都考虑了潜在的应用,包括癫痫发作检测和预测、癫痫发作侧位化、癫痫发作起始区定位以及手术或神经刺激干预评估,并回顾了迄今为止开发的人工智能工具的性能。我们还讨论了将人工智能成功融入临床实践必须解决的方法学考虑因素和挑战。我们的目标是概述该领域的现状,并为未来利用人工智能改善癫痫管理提供指导。
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引用次数: 0
Author Correction: The complex aetiology of cerebral palsy 作者更正:脑瘫的复杂病因。
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-04-25 DOI: 10.1038/s41582-024-00964-w
Steven J. Korzeniewski, Jaime Slaughter, Madeleine Lenski, Peterson Haak, Nigel Paneth
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引用次数: 0
Neuronal activity drives glymphatic waste clearance 神经元活动驱动甘液废物清除
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-04-15 DOI: 10.1038/s41582-024-00963-x
Lisa Kiani
Two new studies show that clearance of waste, including pathogenic amyloid, through the glymphatic system is driven by synchronized neuronal activity.
两项新研究表明,通过淋巴系统清除废物(包括致病性淀粉样蛋白)是由同步神经元活动驱动的。
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引用次数: 0
Neurofilaments as biomarkers in neurological disorders — towards clinical application 作为神经系统疾病生物标记物的神经丝--走向临床应用
IF 38.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2024-04-12 DOI: 10.1038/s41582-024-00955-x
Michael Khalil, Charlotte E. Teunissen, Sylvain Lehmann, Markus Otto, Fredrik Piehl, Tjalf Ziemssen, Stefan Bittner, Maria Pia Sormani, Thomas Gattringer, Samir Abu-Rumeileh, Simon Thebault, Ahmed Abdelhak, Ari Green, Pascal Benkert, Ludwig Kappos, Manuel Comabella, Hayrettin Tumani, Mark S. Freedman, Axel Petzold, Kaj Blennow, Henrik Zetterberg, David Leppert, Jens Kuhle
Neurofilament proteins have been validated as specific body fluid biomarkers of neuro-axonal injury. The advent of highly sensitive analytical platforms that enable reliable quantification of neurofilaments in blood samples and simplify longitudinal follow-up has paved the way for the development of neurofilaments as a biomarker in clinical practice. Potential applications include assessment of disease activity, monitoring of treatment responses, and determining prognosis in many acute and chronic neurological disorders as well as their use as an outcome measure in trials of novel therapies. Progress has now moved the measurement of neurofilaments to the doorstep of routine clinical practice for the evaluation of individuals. In this Review, we first outline current knowledge on the structure and function of neurofilaments. We then discuss analytical and statistical approaches and challenges in determining neurofilament levels in different clinical contexts and assess the implications of neurofilament light chain (NfL) levels in normal ageing and the confounding factors that need to be considered when interpreting NfL measures. In addition, we summarize the current value and potential clinical applications of neurofilaments as a biomarker of neuro-axonal damage in a range of neurological disorders, including multiple sclerosis, Alzheimer disease, frontotemporal dementia, amyotrophic lateral sclerosis, stroke and cerebrovascular disease, traumatic brain injury, and Parkinson disease. We also consider the steps needed to complete the translation of neurofilaments from the laboratory to the management of neurological diseases in clinical practice. Neurofilaments have been validated as specific body fluid biomarkers of neuro-axonal injury. In this Review, Khalil and colleagues provide an update on the structure and function of neurofilaments, analytical approaches and challenges in different clinical contexts, and progress towards clinical application of neurofilaments as a biomarker in various neurological disorders.
神经丝蛋白已被证实是神经轴突损伤的特异性体液生物标记物。高灵敏度分析平台的出现实现了对血液样本中神经丝蛋白的可靠定量,并简化了纵向跟踪,这为神经丝蛋白在临床实践中作为生物标记物的发展铺平了道路。其潜在应用包括评估疾病活动、监测治疗反应、确定许多急性和慢性神经系统疾病的预后,以及将其作为新型疗法试验的结果测量指标。目前,神经丝蛋白的测量已经进入了常规临床实践的阶段,可用于对个体进行评估。在本综述中,我们首先概述了目前有关神经丝结构和功能的知识。然后,我们讨论了在不同临床环境中确定神经丝水平的分析和统计方法及挑战,并评估了神经丝轻链(NfL)水平对正常老龄化的影响以及在解释 NfL 测量时需要考虑的混杂因素。此外,我们还总结了神经丝作为神经轴突损伤生物标记物在一系列神经系统疾病中的当前价值和潜在临床应用,这些疾病包括多发性硬化症、阿尔茨海默病、额颞叶痴呆症、肌萎缩性脊髓侧索硬化症、中风和脑血管疾病、脑外伤和帕金森病。我们还考虑了将神经丝从实验室转化为临床神经疾病治疗所需的步骤。
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