Results 111 to 120 of about 449,466 (261)

Epilepsy‐Associated Variants of a Single SCN1A Codon Exhibit Divergent Functional Properties

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Pathogenic variants in SCN1A, which encodes the voltage‐gated sodium channel NaV1.1, are associated with multiple epilepsy syndromes exhibiting a range of clinical severity. SCN1A variants are reported in different syndromes, including Dravet syndrome, which is associated with loss‐of‐function, whereas neonatal/infantile‐onset ...
Lanie N. Liebovitz, Christopher H. Thompson, Linda C. Laux, Alfred L. George Jr.   +3 more
wiley   +1 more source

A Systematic Review and Meta‐Analysis of the Recurrence of Autoimmune Encephalitis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Autoimmune encephalitis (AE) is a disease with a potential for recurrence, and patients receive immunotherapy to prevent it. However, there is no consensus on the duration of immunotherapy. This study aimed to determine the recurrence rate and identify the risk factors for AE to provide guidance on the duration of immunotherapy ...
Shangkai Bai, Sen Zhang, Haipei Zhang, Yating Zhang, Junhong Guo, Xiaoyan Yang   +5 more
wiley   +1 more source

Paramagnetic Rim Lesions Are Associated With Trans‐Synaptic Degeneration of the Visual Pathway in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Retrograde trans‐synaptic degeneration (rTSD) from posterior visual pathway lesions in multiple sclerosis (MS) is characterized by hemi‐macular ganglion cell‐inner plexiform layer (GCIPL) thinning and contralateral visual field loss.
Abdul Jaber Tayem, Angel Liu, Sargis Manukyan, Mustafa Subhi, Elaina Luskin, Bryan Quah, Sreekanth Madhusoodhanan Nair, Arzu C. Has Silemek, Gabriela Zabala, Yujie Cui, Laura Locke, Paula Barreras, Marwa Kaisey, Vinicius Calsavara, Daniel S. Reich, Nancy L. Sicotte, Pascal Sati, Omar Al‐Louzi   +17 more
wiley   +1 more source

Multivariate L1 Statistical Methods: The Package MNM

Journal of Statistical Software, 2011
In the paper we present an R package MNM dedicated to multivariate data analysis based on the L1 norm. The analysis proceeds very much as does a traditional multivariate analysis.
Klaus Nordhausen, Hannu Oja
doaj  

Reperfusion‐Dependent Outcomes After Endovascular Thrombectomy Stratified by NIHSS‐ASPECTS Clinical‐Core Mismatch

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective This analysis evaluates the effect of successful reperfusion on functional outcomes after MT, stratified by admission National Institutes of Health Stroke Scale (NIHSS) and Alberta Stroke Program Early CT Score (ASPECTS) as surrogates for clinical‐core mismatch, using multicenter registry data.
Felix Schlicht, Lukas Meyer, Gabriel Broocks, Matthias Bechstein, Christian Thaler, Christian Heitkamp, Laurens Winkelmeier, Vincent Geest, Alexander Heitkamp, Maximilian Jungnitz, Gregor Peter, Luca Meucci, Tobias Faizy, Jawed Nawabi, Caspar Brekenfeld, Fabian Flottmann, Maximilian Schell, Alexandros Hadjilaou, Uta Hanning, Götz Thomalla, Jens Fiehler, Susanne Gellißen, Helge C. Kniep, for the German Stroke Registry Endovascular Treatment, (GSR‐ET) Alexander Nave, Anna Alegiani, Annerose Mengel, Arno Reich, Bernd Eckert, Charlotte Pietrock, Christian Nolte, Eberhard Siebert, Fabian Flottmann, Fee Keil, Franziska Dorn, Gabor Petzold, Götz Thomalla, Hanna Zimmermann, Jan Borggrefe, Jan Hendrik Schäfer, Jens Fiehler, Joachim Röther, Klaus Gröschel, Lars Kellert, Mario Abruscato, Maximilian Schell, Omid Nikoubashman, Peter Schellinger, Silke Wunderlich, Steffen Tiedt, Sven Thonke, Timo Uphaus, Tobias Boeckh‐Behrens, Ulrike Ernemann   +53 more
wiley   +1 more source

Minimally Clinically Important Difference of the Clinical Assessment Scale in Autoimmune Encephalitis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT The Clinical Assessment Scale in Autoimmune Encephalitis (CASE) tracks disease severity in autoimmune encephalitis (AE), but no threshold for significant change exists. We aimed to determine the minimally clinically important difference (MCID) for CASE.
Yihui Goh, Yoon Hee Shin, Soo Hyun Ahn, Su Yee Mon, Soo Jean Shin, Woo‐Jin Lee, Yoonhyuk Jang, Myoung‐Jin Jang, Soon‐Tae Lee   +8 more
wiley   +1 more source

Von Economo Neuron Loss in Frontotemporal Dementia: A Meta‐Analysis of Neuropathological Studies

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Von Economo neurons (VENs) have been reported to be vulnerable to neurodegeneration in frontotemporal dementia (FTD), particularly the behavioral variant (bvFTD), but these findings have not been systematically assessed across independent brain banks.
Daniel Talmasov, Alexander F. Santillo, Patrick R. Hof   +2 more
wiley   +1 more source

Comparison of machine learning models for hemoglobin prediction in patients undergoing maintenance hemodialysis. [PDF]

Front Mol Biosci
Xie T, Su X, Yun C, Tang X, Zheng X, Dong J, Guo Q, Zhu S, Tang D, Dai Y, Yin L.   +10 more
europepmc   +1 more source

A Depolarizing Leak in Sodium Bicarbonate Cotransporter NBCe1 Causes Brain Edema

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives SLC4A4 encodes electrogenic sodium bicarbonate cotransporter NBCe1, prominently expressed in kidney and brain. Recessive loss‐of‐function variants in SLC4A4 cause proximal renal tubular acidosis, no brain edema. In the brain, NBCe1 is expressed by astrocytes, where it regulates pH and mediates astrocyte volume changes.
Quinty Bisseling, Mark D. Parker, Sven Kerst, Richard A. Pasternack, Jacob Tondreau, Marjolein Breur, Gemma M. van Rooijen‐van Leeuwen, Davide Tonduti, Ettore Salsano, Alejandra Darling, Joanna A. E. van Wijk, Susanna Törnroth‐Horsefield, Marianna Bugiani, Petra J. W. Pouwels, Quinten Waisfisz, Marjo S. van der Knaap, Rogier Min   +16 more
wiley   +1 more source

Semi-supervised feature selection using mean absolute deviation

, 2020
Yüksek boyutlu veri kümeleri öğrenme aşamasında (Örneğin: Sınıflandırma veya Kümeleme) sorunlara neden olabilir. Özellik azaltma, veri kümelerindeki bir özelliğin sayısının azaltılmasına yardımcı olur ve bunun sonucunda öğrenme adımlarının algoritmalarını daha hızlı gerçekleştirir ve bir veri kümesindeki tüm özellikleri kullanmaktan daha iyi sonuç ...
openaire   +1 more source