Results 101 to 110 of about 1,654,724 (346)

"Role of the neuronal protein Cap23 in the maturation and maintenance of dendritic arbors in-vivo" [PDF]

open access: yes, 2006
Dendrites in the central nervous system are the postsynaptic counterparts in the neural circuitry, and the principal sites of excitatory synaptic inputs.
Sadhu, Anirban
core   +1 more source

Bone Marrow Contributes Simultaneously to Different Neural Types in the Central Nervous System through Different Mechanisms of Plasticity

open access: yesCell Transplantation, 2011
Many studies have reported the contribution of bone marrow-derived cells (BMDC) to the CNS, raising the possibility of using them as a new source to repair damaged brain tissue or restore neuronal function.
Javier S. Recio   +6 more
doaj   +1 more source

ADP‐ribosylation: An emerging regulator of the epigenome

open access: yesMolecular Oncology, EarlyView.
ADP‐ribosylation has emerged as a dynamic epigenetic signaling mechanism that modifies histones and chromatin‐associated proteins. Through coordinated PARylation and MARylation, it integrates with other histone modifications to regulate chromatin structure, transcription factor activity, and gene expression, influencing genome function and disease ...
Cristel V. Camacho   +2 more
wiley   +1 more source

Imprinting and cortical plasticity: A comparative review: a comparative review [PDF]

open access: yes, 1983
Bischof H-J. Imprinting and cortical plasticity: A comparative review: a comparative review. Neuroscience and Biobehavioral Reviews. 1983;7(2):213-225.Results of research on imprinting and developmental neurobiology of the visual cortex are compared to ...
Bischof, Hans-Joachim
core   +1 more source

Arginine methylation as a regulatory ratchet in cancer: From substrate selection to malignant‐state stabilization

open access: yesMolecular Oncology, EarlyView.
Arginine methylation can be viewed as a persistence‐prone post‐translational modification regulated by a network of PRMTs. Competitive and compensatory interactions among PRMTs can redistribute methylation across substrate pools shaped by sequence, structural, spatial, and environmental layers, reinforcing RNA‐processing, chromatin, and signaling ...
So Hyun Kwon, Ji Min Lee
wiley   +1 more source

Mild Cerebellar Neurodegeneration of Aged Heterozygous PCD Mice Increases Cell Fusion of Purkinje and Bone Marrow-Derived Cells

open access: yesCell Transplantation, 2012
Bone marrow-derived cells have different plastic properties, especially regarding cell fusion, which increases with time and is prompted by tissue injury.
David Díaz   +3 more
doaj   +1 more source

Impaired synaptic incorporation of AMPA receptors in a mouse model of fragile X syndrome

open access: yesFrontiers in Molecular Neuroscience, 2023
Fragile X syndrome (FXS) is the most common monogenetic cause of inherited intellectual disability and autism in humans. One of the well-characterized molecular phenotypes of Fmr1 KO mice, a model of FXS, is increased translation of synaptic proteins ...
Magdalena Chojnacka   +7 more
doaj   +1 more source

Guiding AlphaFold to predict how Munc13‐1 opens Syntaxin‐1

open access: yesFEBS Open Bio, EarlyView.
The syntaxin‐1 Habc‐domain (orange), linker (pink) and SNARE motif (yellow) form a closed conformation that binds to Munc18‐1 (violet) and is opened by the Munc13‐1 MUN domain (cyan) to form the SNARE complex that triggers neurotransmitter release.
Madhurima Chattopadhyay   +2 more
wiley   +1 more source

Homeostatic plasticity improves signal propagation in continuous time recurrent neural networks

open access: yes, 2005
Continuous-time recurrent neural networks (CTRNNs) are potentially an excellent substrate for the generation of adaptive behaviour in artificial autonomous agents. However, node saturation effects in these networks can leave them insensitive to input and
Williams, Hywel, Noble, Jason
core   +1 more source

Reinforcement learning in populations of spiking neurons [PDF]

open access: yes, 2008
Population coding is widely regarded as a key mechanism for achieving reliable behavioral responses in the face of neuronal variability. But in standard reinforcement learning a flip-side becomes apparent.
Urbanczik, R   +3 more
core   +1 more source

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