Results 81 to 90 of about 1,725,169 (334)

Large‐scale bidirectional arrayed genetic screens identify OXR1 and EMC4 as modifiers of αSynuclein aggregation

FEBS Open Bio, EarlyView.
Activation of the mitochondrial protein OXR1 increases pSyn129 αSynuclein aggregation by lowering ATP levels and altering mitochondrial membrane potential, particularly in response to MSA‐derived fibrils. In contrast, ablation of the ER protein EMC4 enhances autophagic flux and lysosomal clearance, broadly reducing α‐synuclein aggregates.
Sandesh Neupane, Lea Nikolić, Lorenzo Maraio, Thomas Goiran, Nathan Karpilovsky, Stefano Sellitto, Vangelis Bouris, Jiang‐An Yin, Ronald Melki, Edward A Fon, Adriano Aguzzi, Elena De Cecco   +11 more
wiley   +1 more source

Mutant NPM1 in Acute Myeloid Leukemia Initiation and Maintenance

Aging and Cancer, EarlyView.
NPM1 mutations drive acute myeloid leukemia by acting as neomorphic transcriptional regulators that cooperate with Menin–MLL and XPO1 to sustain HOX/MEIS1 expression and block differentiation. Targeting these mutant‐specific transcriptional dependencies provides a rational therapeutic strategy for NPM1‐mutated AML.
Yanan Jiang, Zhong Fan, Runmeng Liu, Xiaotian Zhang   +3 more
wiley   +1 more source

An Algorithmic Theory of Dependent Regularizers, Part 1: Submodular Structure [PDF]

, 2013
We present an exploration of the rich theoretical connections between several classes of regularized models, network flows, and recent results in submodular function theory.
Koepke, Hoyt, Meila, Marina
core  

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Estimation of Neuromuscular Primitives from EEG Slow Cortical Potentials in Incomplete Spinal Cord Injury Individuals for a New Class of Brain-Machine Interfaces

Frontiers in Computational Neuroscience, 2018
One of the current challenges in human motor rehabilitation is the robust application of Brain-Machine Interfaces to assistive technologies such as powered lower limb exoskeletons.
Andrés Úbeda, Andrés Úbeda, José M. Azorín, Dario Farina, Massimo Sartori   +4 more
doaj   +1 more source

Remote Monitoring in Myasthenia Gravis: Exploring Symptom Variability

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare, autoimmune disorder characterized by fluctuating muscle weakness and potential life‐threatening crises. While continuous specialized care is essential, access barriers often delay timely interventions. To address this, we developed MyaLink, a telemedical platform for MG patients.
Maike Stein, Maximilian Mönch, Meret Herdick, Frauke Stascheit, Sarah Hoffmann, Hannah Preßler, Philipp Mergenthaler, Carla Dusemund, Paolo Doksani, Haoqi Sun, Pushpa Narayanaswami, Andreas Meisel, Lea Gerischer, Sophie Lehnerer   +13 more
wiley   +1 more source

Machine Theory of Mind

, 2018
Theory of mind (ToM; Premack & Woodruff, 1978) broadly refers to humans' ability to represent the mental states of others, including their desires, beliefs, and intentions. We propose to train a machine to build such models too. We design a Theory of Mind neural network -- a ToMnet -- which uses meta-learning to build models of the agents it ...
Rabinowitz, Neil C., Perbet, Frank, Song, H. Francis, Zhang, Chiyuan, Eslami, S. M. Ali, Botvinick, Matthew   +5 more
openaire   +2 more sources

Machine learning and social theory: Collective machine behaviour in algorithmic trading

European Journal of Social Theory, 2021
This article examines what the rise in machine learning (ML) systems might mean for social theory. Focusing on financial markets, in which algorithmic securities trading founded on ML-based decision-making is gaining traction, I discuss the extent to which established sociological notions remain relevant or demand a reconsideration when applied to an ...
openaire   +2 more sources

Feasibility and Tolerability of Performing Portable MRI for Neurological Disorders in an Outpatient Neurology Clinic: A Prospective Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Accessing brain magnetic resonance imaging (MRI) can be challenging, especially for underserved patients, which may lead to disparities in neurological diagnosis. Method This mixed‐methods study enrolled adults with one of four neurological disorders: mild cognitive impairment or dementia of the Alzheimer type, multiple sclerosis ...
Maya L. Mastick, Nomin Enkhtsetseg, Joseph Sadok, Matheus Mochetti, Annabel Sorby Adams, Jennifer Guo, Cristina Trapaga Hacker, Isabella Gomez Hjerthen, Seungwon Lee, Siddharth Satish, Andrew S. Ham, Justin Hill, Denis Balaban, Kevin Kyle, Rebecca L. Gillani, Marcelo Matiello, Aleksandar Videnovic, Eric C. Klawiter, W. Taylor Kimberly, Farrah J. Mateen   +19 more
wiley   +1 more source

Functional and Structural Evidence of Neurofluid Circuit Aberrations in Huntington Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Disrupted neurofluid regulation may contribute to neurodegeneration in Huntington disease (HD). Because neurofluid pathways influence waste clearance, inflammation, and the distribution of central nervous system (CNS)–delivered therapeutics, understanding their dysfunction is increasingly important as targeted treatments emerge.
Kilian Hett, Abigail Dubois, Melanie Leguizamon, Alexander Song, Paula Trujillo, Colin D. McKnight, Ciaran M. Considine, Manus J. Donahue, Daniel O. Claassen   +8 more
wiley   +1 more source