Results 61 to 70 of about 344,220 (168)

Enhancement of neuronal regeneration by optogenetic cellular activation in C. elegans [PDF]

open access: yes, 2015
Large numbers of people suffer from nervous system injuries and neurodegenerative diseases each year, with little success in regaining lost neural functions.
Shay, James
core   +1 more source

Terminal differentiation precedes functional circuit integration in the peduncle neurons in regenerating Hydra vulgaris [PDF]

open access: yes
Understanding how neural circuits are regenerated following injury is a fundamental question in neuroscience. Hydra is a powerful model for studying this process because it has a simple neural circuit structure, significant and reproducible regenerative ...
Duret, Guillaume   +5 more
core   +1 more source

Harnessing the power of cell transplantation to target respiratory dysfunction following spinal cord injury. [PDF]

open access: yes, 2017
The therapeutic benefit of cell transplantation has been assessed in a host of central nervous system (CNS) diseases, including disorders of the spinal cord such as traumatic spinal cord injury (SCI).
Charsar, Brittany A.   +2 more
core   +2 more sources

The App NL-G-F mouse retina is a site for preclinical Alzheimer’s disease diagnosis and research

open access: yesActa Neuropathologica Communications, 2021
In this study, we report the results of a comprehensive phenotyping of the retina of the App NL-G-F mouse. We demonstrate that soluble Aβ accumulation is present in the retina of these mice early in life and progresses to Aβ plaque formation by midlife ...
Marjan Vandenabeele   +16 more
doaj   +1 more source

Potential use of human periapical cyst-mesenchymal stem cells (hPCy-MSCs) as a novel stem cell source for regenerative medicine applications [PDF]

open access: yes, 2017
Mesenchymal stem cells (MSCs) are attracting growing interest by the scientific community due to their huge regenerative potential. Thus, the plasticity of MSCs strongly suggests the utilization of these cells for regenerative medicine applications.
Codispoti, Bruna   +6 more
core   +2 more sources

The role of mtDAMPs in the trauma-induced systemic inflammatory response syndrome

open access: yesFrontiers in Immunology, 2023
Systemic inflammatory response syndrome (SIRS) is a non-specific exaggerated defense response caused by infectious or non-infectious stressors such as trauma, burn, surgery, ischemia and reperfusion, and malignancy, which can eventually lead to an ...
Jingjing Ye   +7 more
doaj   +1 more source

Multipotent vascular stem cells contribute to neurovascular regeneration of peripheral nerve. [PDF]

open access: yes, 2019
BackgroundNeurovascular unit restoration is crucial for nerve regeneration, especially in critical gaps of injured peripheral nerve. Multipotent vascular stem cells (MVSCs) harvested from an adult blood vessel are involved in vascular remodeling; however,
Hsueh, Yuan-Yu   +4 more
core  

PORCN Negatively Regulates AMPAR Function Independently of Subunit Composition and the Amino-Terminal and Carboxy-Terminal Domains of AMPARs

open access: yesFrontiers in Cell and Developmental Biology, 2020
Most fast excitatory synaptic transmissions in the mammalian brain are mediated by α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid receptors (AMPARs), which are ligand-gated cation channels.
Mengping Wei   +19 more
doaj   +1 more source

Logarithmic Continual Learning [PDF]

open access: yesarXiv, 2022
We introduce a neural network architecture that logarithmically reduces the number of self-rehearsal steps in the generative rehearsal of continually learned models. In continual learning (CL), training samples come in subsequent tasks, and the trained model can access only a single task at a time.
arxiv  

Repaint: Improving the Generalization of Down-Stream Visual Tasks by Generating Multiple Instances of Training Examples [PDF]

open access: yesarXiv, 2021
Convolutional Neural Networks (CNNs) for visual tasks are believed to learn both the low-level textures and high-level object attributes, throughout the network depth. This paper further investigates the `texture bias' in CNNs. To this end, we regenerate multiple instances of training examples from each original image, through a process we call ...
arxiv  

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