Results 141 to 150 of about 518,429 (303)

A Prospective Study of Individuals at Risk of Multiple Sclerosis Informs the Design of Primary Prevention Studies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective In multiple sclerosis, the optimal time for deploying a therapeutic intervention is before the central nervous system is damaged; given the success of trials treating the earliest stage of MS, the radiologically isolated syndrome, developing primary prevention strategies is an important next challenge.
Amy W. Laitinen, Ceren Tozlu, Tina Roostaei, Fatoumata Diallo, Kaho Onomichi, Jiyeon Son, Zongqi Xia, Philip L. De Jager   +7 more
wiley   +1 more source

Bone resorption in mouse models of mitochondrial neurological diseases

Bone Reports, 2020
Vasiliki-Iris Perivolidi, Foteini Violitzi, George Panayotou, Eleni Douni   +3 more
doaj   +1 more source

Neurological Model [PDF]

, 2020
openaire   +1 more source

Multilevel Computational Modelling in Epilepsy: Classical Studies and Recent Advances

, 2015
Springer Series in Computational NeuroscienceIn this chapter we present a review of computational models for study- ing the dynamic mechanisms that describe the function of the human brain, with a specific focus on epilepsy.
Terry, John R., Woldman, Wessel, John R. Terry, Wessel Woldman   +3 more
core   +1 more source

Developmental and Epileptic Encephalopathy due to Biallelic Pathogenic Variants in PIGM

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective PIGM encodes a critical enzyme in the glycosylphosphatidylinositol (GPI)‐anchor biosynthesis pathway. While promoter‐region mutations in PIGM have been associated with a relatively mild phenotype characterized by portal vein thrombosis and absence seizures, recent evidence suggests that coding‐region mutations result in a more severe
Júlia Sala‐Coromina, Anna Marcé‐Grau, Barbara Masotto, Marta Codina, Lamia BenJemaa, Yasmina Elaribi, Mónica Martinez‐Gallo, Roger Colobran, Angel Sanchez‐Montañez, Irene Valenzuela, Yoshiko Murakami, Alfons Macaya   +11 more
wiley   +1 more source

Efficacy of Intermittent Theta‐Burst Stimulation for Prolonged Disorders of Consciousness: A Prospective, Randomized, Controlled Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Emerging evidence suggests that low‐frequency neural oscillations are dynamically regulated by consciousness levels, with the recovery of low cortical activity potentially serving as a neurophysiological substrate for conscious emergence. Targeted enhancement of these low‐frequency rhythms in patients with disorders of consciousness
Chuan Xu, Jun Hu, Qianqian Wu, Min Wu, Yamei Yu, Hangcheng Li, Jian Gao, Jingqi Li, Nai Ding, Jie Yu, Benyan Luo   +10 more
wiley   +1 more source

A Systematic Review of Genetics- and Molecular-Pathway-Based Machine Learning Models for Neurological Disorder Diagnosis

The process of identification and management of neurological disorder conditions faces challenges, prompting the investigation of novel methods in order to improve diagnostic accuracy.
Nasser Ali Aljarallah, Ashit Kumar Dutta, Abdul Rahaman Wahab Sait   +2 more
core   +1 more source

Mouse models of neurological disorders—A comparison of heritable and acquired traits

, 2010
Human neurological disorders include a wide range of illnesses which have a disproportionately high prevalence in the increasingly populous geriatric community.
Harper, Alex
core   +1 more source

FDG‐PET Associations With Disease Severity and Outcomes in NMDA‐Receptor IgG Autoimmune Encephalitis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Patients with N‐methyl‐D‐aspartate (NMDA) receptor‐immunoglobulin G (IgG) autoimmune encephalitis (NMDAR‐IgG AE) demonstrate occipital lobe hypometabolism on baseline brain fluorodeoxyglucose‐positron emission tomography (bFDG‐PET).
Jonathan K. Lee, Jeffrey Lambe, Scott Johnson, Akua Abrah, Jennifer Bullen, Jeffrey A. Cohen, Tatchaporn Ongphichetmetha, Amy Kunchok   +7 more
wiley   +1 more source

Automated Fazekas classification from brain MRI reports: an artificial intelligence approach with GPT-4

The Egyptian Journal of Radiology and Nuclear Medicine
Background This study focuses on evaluating the effectiveness and reliability of GPT-4 in classifying radiological reports based on the Fazekas scale, a critical tool for assessing white matter signal abnormalities in brain MRI. We applied synthetic data
Carlo Augusto Mallio, Andrea Carlomaria Sertorio, Caterina Bernetti, Federico Greco, Gianfranco Di Gennaro, Bruno Beomonte Zobel   +5 more
doaj   +1 more source