Neurosensory development of the visual system has its origins long before birth. The genetic processes of basic structure formation are followed by endogenous retinal ganglion cell activation in the form of spontaneous synchronous waves of stimulation. These waves of stimulation are required to establish the topographic relationship among retina, lateral geniculate nucleus, and visual cortex. This process prepares the visual system for visual experience. Visual experience ultimately stimulates creation of columns of neurons in the visual cortex, which are needed to see and interpret patterns, lines, movement, and color. Spontaneous synchronous retinal waves occur in preterm infants in the neonatal intensive care unit and must be protected, as they are critical for visual development.
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http://dx.doi.org/10.1016/j.clp.2004.04.010 | DOI Listing |
Front Biosci (Landmark Ed)
December 2024
Research Centre for Medical Genetics, 115522 Moscow, Russia.
Background: There is a growing interest in exploring the biological characteristics of nanoparticles and exploring their potential applications. However, there is still a lack of research into the potential genotoxicity of fullerene derivatives and their impact on gene expression in human cells. In this study, we investigated the effects of a water-soluble fullerene derivative, C60[C6H4SCH2COOK]5H (F1), on human embryonic lung fibroblasts (HELF).
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December 2024
Department of Biological Sciences, Hunter College, City University of New York, New York, NY 10065, USA.
Background: Spatial-temporal control of mRNA translation in dendrites is important for synaptic plasticity. In response to pre-synaptic stimuli, local mRNA translation can be rapidly triggered near stimulated synapses to supply the necessary proteins for synapse maturation or elimination, and 3' untranslated regions (UTRs) are responsible for proper localization of mRNAs in dendrites. Although is a robust technique for analyzing RNA localization in fixed neurons, live-cell imaging of RNA dynamics remains challenging.
View Article and Find Full Text PDFJ Integr Neurosci
December 2024
Department of Computer Science and Engineering, Shaoxing University, 312000 Shaoxing, Zhejiang, China.
Background: Motor imagery (MI) plays an important role in brain-computer interfaces, especially in evoking event-related desynchronization and synchronization (ERD/S) rhythms in electroencephalogram (EEG) signals. However, the procedure for performing a MI task for a single subject is subjective, making it difficult to determine the actual situation of an individual's MI task and resulting in significant individual EEG response variations during motion cognitive decoding.
Methods: To explore this issue, we designed three visual stimuli (arrow, human, and robot), each of which was used to present three MI tasks (left arm, right arm, and feet), and evaluated differences in brain response in terms of ERD/S rhythms.
JACS Au
December 2024
Department of Chemistry and HKU-CAS Joint Laboratory of Metallomics for Health and Environment, The University of Hong Kong, Pokfulam Road, Hong Kong, SAR, P.R. China.
Metal ions, either essential or therapeutic, play critical roles in life processes or in the treatment of diseases. Proteins and enzymes are involved in metal homeostasis and the action of metallodrugs. Imaging and identifying these metal-binding proteins will facilitate the elucidation of metal-mediated life processes.
View Article and Find Full Text PDFIndian J Orthop
January 2025
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001 China.
Introduction: The Steinberg classification system is commonly used by orthopedic surgeons to stage the severity of patients with osteonecrosis of the femoral head (ONFH), and it includes mild, moderate, and severe grading of each stage based on the area of the femoral head affected. However, clinicians mostly grade approximately by visual assessment or not at all. To accurately distinguish the mild, moderate, or severe grade of early stage ONFH, we propose a convolutional neural network (CNN) based on magnetic resonance imaging (MRI) of the hip joint of patients to accurately grade and aid diagnosis of ONFH.
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