Results 91 to 100 of about 15,697,207 (237)

Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang, Dongxu Zhang, Dongyuan Liu, Da Lin, Hao Wang   +4 more
wiley   +1 more source

A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi, Giorgio Ricciardiello Mejia, Andre Metzger, Kang Hyun Ryu, Salonee Marwaha, Eva Grzegorczyk, Li Zhou, Eliana Jacobs, Boris Gilyadov, Claudia Kunney, Liqhwa Ncube, Ankit Parekh, Emmanuel Mignot, Fanny M. Elahi, Joseph Winer, Kathleen Poston, Andreas Brink‐Kjaer, Emmanuel H. During   +17 more
wiley   +1 more source

Advanced lifetime data modeling: Extension, structural properties and an application

Scientific African
This study provides a comprehensive investigation of the Toppe Leone Lomax Logarithmic Distribution (TLLomLD), a newly developed probabilistic model designed to capture various data patterns.
Denylson Takunda Dondo, Regent Retrospect Musekwa, Precious Mdlongwa   +2 more
doaj   +1 more source

Subclinical Optic Nerve Involvement in Radiologically Isolated Syndrome: Multimodal Detection and Diagnostic Impact

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We aimed to determine the frequency of subclinical optic nerve (ON) lesions using MRI, optical coherence tomography (OCT), and visual evoked potentials (VEP) in radiologically isolated syndrome (RIS), and to assess their diagnostic and prognostic significance.
Christine Lebrun‐Frenay, Cassandre Landes‐Château, Lydiane Mondot, Mikael Cohen, Margherita Popolo, Jérôme de Seze, Bertrand Bourre, Françoise Durand‐Dubief, Olivier Casez, Orhun H. Kantarci, Aksel Siva, Stephanie Baillif, Darin T. Okuda, Letizia Leocani   +13 more
wiley   +1 more source

Probabilistic assessment of Vasyugan and Tyumen Formations permeability within Surgut oil and gas region

Известия Томского политехнического университета: Инжиниринг георесурсов
Relevance. The need to combine deterministic methods with stochastic ones to increase the reliability of three-dimensional models. Aim. To determine the filtration indicators of reservoir rocks using a stochastic method in order to increase the ...
Nikita R. Mardanov, Pavel N. Strakhov
doaj   +1 more source

Neurochemical Endpoints to Inform Early‐Stage Trials of Spinocerebellar Ataxia 2 and 3 in a Multisite Setting

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Neurochemical levels measured by brain MR spectroscopy (MRS) have been proposed as endpoints for clinical trials in early‐stage spinocerebellar ataxia (SCA) trials. We tested their trial‐readiness by quantifying neurochemicals in three affected brain regions in early‐stage cohorts of SCA2 and SCA3, examining their reproducibility in ...
James M. Joers, Yaqiao Wei, Dinesh K. Deelchand, Adam Berrington, Young Woo Park, Guita Banan, Michal Povazan, Jens T. Rosenberg, André J. W. van der Kouwe, Tetsuo Ashizawa, Khalaf O. Bushara, Chiadi U. Onyike, Sub H. Subramony, Jeremy D. Schmahmann, Brian J. Soher, Peter B. Barker, Thomas H. Mareci, Eva‐Maria Ratai, Lynn E. Eberly, Gülin Öz   +19 more
wiley   +1 more source

A new unified Probabilistic model

, 2004
This paper proposes a new unified probabilistic model. Two previous models, Robertson et al.'s "Model 0" and "Model 3," each have strengths and weaknesses. The strength of Model 0 not found in Model 3, is that it does not require relevance data about the
Robertson, S., Bodoff, D.
core   +1 more source

Electroencephalographic Normalization as a Biomarker of Clinical Recovery in Down Syndrome Regression Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Down syndrome regression disorder is a syndrome characterized by subacute loss of cognitive, behavioral, and functional abilities in individuals with Down syndrome. Electroencephalography abnormalities are frequently observed during evaluation, but it remains unclear whether these findings represent a dynamic marker of disease ...
Jonathan D. Santoro, Mackenzie Silverman, Maeve C. Lucas, Mariam M. Yousuf, Samuel T. Otey, Stella V. Gray, Brittany Jordan, Madeline D. Kahan, Latanya D. Agurs, Michelle Van Hirtum Das, Deborah Holder, Devin King, Eileen A. Quinn, Ryan Kammeyer, Michael S. Rafii   +14 more
wiley   +1 more source

Integrating Time‐Adjusted Imaging Instability Into Functional Outcome Prediction After Intracerebral Hemorrhage: Development and Validation of the HAGIV Score

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Early risk stratification may support clinical decision‐making in spontaneous intracerebral hemorrhage (ICH). We aimed to develop and internally validate HAGIV, a score integrating frequency of imaging markers (FIM), a time‐adjusted non‐contrast computed tomography (CT) metric of hematoma expansion, with established predictors for 90‐
Lei Song, Ren Ke, Anqi Chen, Yufei Fu, Hang Zhou, Rujia Wang, Liwei Zou, Yongqiang Yu, Ming Yuan, Xiaoming Qiu, Mengzhou Xue   +10 more
wiley   +1 more source

Algorithm-Sensitive Feature Weighting using Mutual Information and ReliefF for Heart Disease Classification

Edumatic
Heart disease remains a critical global health issue requiring reliable early prediction for clinical decision-making. This study evaluates the effect of feature selection and feature weighting on the performance of machine learning models with different
Dwi Prihantono, Umar Faqih, Indra Indra
doaj   +1 more source