Results 111 to 120 of about 1,207,913 (297)

A Depolarizing Leak in Sodium Bicarbonate Cotransporter NBCe1 Causes Brain Edema

open access: yesAnnals 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   +16 more
wiley   +1 more source

Test-retest reliability and validity of vagally-mediated heart rate variability to monitor internal training load in older adults: a within-subjects (repeated-measures) randomized study

open access: yesBMC Sports Science, Medicine and Rehabilitation
Background Vagally-mediated heart rate variability (vm-HRV) shows promise as a biomarker of internal training load (ITL) during exergame-based training or motor-cognitive training in general.
Patrick Manser, Eling D. de Bruin
doaj   +1 more source

CSF Monoamine Metabolites and Cognitive Trajectory in Early Parkinson's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Imaging and postmortem studies indicate that abnormalities in monoaminergic neurotransmission contribute to cognitive impairment in Parkinson's disease (PD). However, it remains uncertain if cerebrospinal fluid (CSF) monoamine metabolites can serve as biomarkers of cognitive decline in early PD.
Jing‐Yu Shao   +7 more
wiley   +1 more source

A Comparative Study of Machine Learning Models for Tabular Data Through Challenge of Monitoring Parkinson's Disease Progression Using Voice Recordings

open access: yes, 2020
People with Parkinson's disease must be regularly monitored by their physician to observe how the disease is progressing and potentially adjust treatment plans to mitigate the symptoms.
Arabnia, Hamid Reza   +3 more
core  

Route training in mobile robots through system identification [PDF]

open access: yes, 2006
Fundamental sensor-motor couplings form the backbone of most mobile robot control tasks, and often need to be implemented fast, efficiently and nevertheless reliably.
Billings, S.A.   +3 more
core   +1 more source

Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi   +8 more
wiley   +1 more source

Word Up! Directed motor action improves word learning [Abstract] [PDF]

open access: yes, 2011
Can simple motor actions help people expand their vocabulary? Here we show that word learning depends on where students place their flash cards after studying them.
Casasanto, D., De Bruin, A.
core   +1 more source

A Systematic Comparison of Alpha‐Synuclein Seed Amplification Assays for Increasing Reproducibility

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Seed amplification assays (SAAs) enable ultrasensitive detection of misfolded α‐synuclein across biofluids and tissues. Yet, heterogeneity in protocols limits cross‐study comparability and clinical translation. Here, we review α‐synuclein SAA methods and their performance across various biological matrices.
Manuela Amaral‐do‐Nascimento   +3 more
wiley   +1 more source

Humanoid Motion Description Language [PDF]

open access: yes, 2002
In this paper we propose a description language for specifying motions for humanoid robots and for allowing humanoid robots to acquire motor skills. Locomotion greatly increases our ability to interact with our environments, which in turn increases our ...
Chen, Yanbing, Choi, Ben
core  

Learning Robot Activities from First-Person Human Videos Using Convolutional Future Regression

open access: yes, 2017
We design a new approach that allows robot learning of new activities from unlabeled human example videos. Given videos of humans executing the same activity from a human's viewpoint (i.e., first-person videos), our objective is to make the robot learn ...
Lee, Jangwon, Ryoo, Michael S.
core   +1 more source

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