Pub Date : 2024-05-16DOI: 10.1038/s41582-024-00966-8
Chelsea M. Kaplan, Eoin Kelleher, Anushka Irani, Andrew Schrepf, Daniel J. Clauw, Steven E. Harte
Nociplastic pain is a mechanistic term used to describe pain that arises or is sustained by altered nociception, despite the absence of tissue damage. Although nociplastic pain has distinct pathophysiology from nociceptive and neuropathic pain, these pain mechanisms often coincide within individuals, which contributes to the intractability of chronic pain. Key symptoms of nociplastic pain include pain in multiple body regions, fatigue, sleep disturbances, cognitive dysfunction, depression and anxiety. Individuals with nociplastic pain are often diffusely tender — indicative of hyperalgesia and/or allodynia — and are often more sensitive than others to non-painful sensory stimuli such as lights, odours and noises. This Review summarizes the risk factors, clinical presentation and treatment of nociplastic pain, and describes how alterations in brain function and structure, immune processing and peripheral factors might contribute to the nociplastic pain phenotype. This article concludes with a discussion of two proposed subtypes of nociplastic pain that reflect distinct neurobiological features and treatment responsivity. Nociplastic pain arises from altered nociception despite the absence of tissue damage. In this Review, the authors summarize the risk factors and clinical presentation of nociplastic pain, and discuss its potential underlying mechanisms, including evidence of CNS, immune and peripheral contributions.
{"title":"Deciphering nociplastic pain: clinical features, risk factors and potential mechanisms","authors":"Chelsea M. Kaplan, Eoin Kelleher, Anushka Irani, Andrew Schrepf, Daniel J. Clauw, Steven E. Harte","doi":"10.1038/s41582-024-00966-8","DOIUrl":"10.1038/s41582-024-00966-8","url":null,"abstract":"Nociplastic pain is a mechanistic term used to describe pain that arises or is sustained by altered nociception, despite the absence of tissue damage. Although nociplastic pain has distinct pathophysiology from nociceptive and neuropathic pain, these pain mechanisms often coincide within individuals, which contributes to the intractability of chronic pain. Key symptoms of nociplastic pain include pain in multiple body regions, fatigue, sleep disturbances, cognitive dysfunction, depression and anxiety. Individuals with nociplastic pain are often diffusely tender — indicative of hyperalgesia and/or allodynia — and are often more sensitive than others to non-painful sensory stimuli such as lights, odours and noises. This Review summarizes the risk factors, clinical presentation and treatment of nociplastic pain, and describes how alterations in brain function and structure, immune processing and peripheral factors might contribute to the nociplastic pain phenotype. This article concludes with a discussion of two proposed subtypes of nociplastic pain that reflect distinct neurobiological features and treatment responsivity. Nociplastic pain arises from altered nociception despite the absence of tissue damage. In this Review, the authors summarize the risk factors and clinical presentation of nociplastic pain, and discuss its potential underlying mechanisms, including evidence of CNS, immune and peripheral contributions.","PeriodicalId":19085,"journal":{"name":"Nature Reviews Neurology","volume":"20 6","pages":"347-363"},"PeriodicalIF":38.1,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140949382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.1038/s41582-024-00970-y
Lisa Kiani
{"title":"Blood test for early Parkinson disease diagnosis","authors":"Lisa Kiani","doi":"10.1038/s41582-024-00970-y","DOIUrl":"10.1038/s41582-024-00970-y","url":null,"abstract":"","PeriodicalId":19085,"journal":{"name":"Nature Reviews Neurology","volume":"20 6","pages":"316-316"},"PeriodicalIF":38.1,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140919634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 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。
{"title":"CAR T cells offer hope in glioblastoma","authors":"Ian Fyfe","doi":"10.1038/s41582-024-00972-w","DOIUrl":"10.1038/s41582-024-00972-w","url":null,"abstract":"Novel CAR T cells delivered directly to the CNS could have therapeutic effects in recurrent glioblastoma, according to two early-stage trials.","PeriodicalId":19085,"journal":{"name":"Nature Reviews Neurology","volume":"20 6","pages":"315-315"},"PeriodicalIF":38.1,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140919735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-09DOI: 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。
{"title":"The clinical importance of suspected non-Alzheimer disease pathophysiology","authors":"Stephanie J. B. Vos, Aurore Delvenne, Clifford R. Jack Jr, Dietmar R. Thal, Pieter Jelle Visser","doi":"10.1038/s41582-024-00962-y","DOIUrl":"10.1038/s41582-024-00962-y","url":null,"abstract":"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.","PeriodicalId":19085,"journal":{"name":"Nature Reviews Neurology","volume":"20 6","pages":"337-346"},"PeriodicalIF":38.1,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140895564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-08DOI: 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.
{"title":"Artificial intelligence in epilepsy — applications and pathways to the clinic","authors":"Alfredo Lucas, Andrew Revell, Kathryn A. Davis","doi":"10.1038/s41582-024-00965-9","DOIUrl":"10.1038/s41582-024-00965-9","url":null,"abstract":"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.","PeriodicalId":19085,"journal":{"name":"Nature Reviews Neurology","volume":"20 6","pages":"319-336"},"PeriodicalIF":38.1,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140881290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-15DOI: 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。
{"title":"Neuronal activity drives glymphatic waste clearance","authors":"Lisa Kiani","doi":"10.1038/s41582-024-00963-x","DOIUrl":"10.1038/s41582-024-00963-x","url":null,"abstract":"Two new studies show that clearance of waste, including pathogenic amyloid, through the glymphatic system is driven by synchronized neuronal activity.","PeriodicalId":19085,"journal":{"name":"Nature Reviews Neurology","volume":"20 5","pages":"255-255"},"PeriodicalIF":38.1,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140556817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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