Sensory information processing is a fundamental operation in the brain that is based on dynamic interactions between different neuronal populations. Astrocytes, a type of glial cells, have been proposed to represent active elements of brain microcircuits that, through dynamic interactions with neurons, provide a modulatory control of neuronal network activity. Specifically, astrocytes in different brain regions have been described to respond to neuronal signals with intracellular Ca elevations that represent a key step in the functional recruitment of astrocytes to specific brain circuits. Accumulating evidence shows that Ca elevations regulate the release of gliotransmitters that, in turn, modulate synaptic transmission and neuronal excitability. Recent studies also provided new insights into the spatial and temporal features of astrocytic Ca elevations revealing a surprising complexity of Ca signal dynamics in astrocytes. Here we discuss how recently developed experimental tools such as the genetically encoded Ca indicators (GECI), optogenetics and chemogenetics can be applied to the study of astrocytic Ca signals in the living brain.
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http://dx.doi.org/10.3389/fncel.2017.00134 | DOI Listing |
Adv Sci (Weinh)
January 2025
Department of Bone and Joint Surgery, the First Affiliated Hospital of Jinan University, Key Laboratory of Regenerative Medicine of Ministry of Education, Jinan University, Guangzhou, Guangdong, 510630, China.
Osteoarthritis (OA) is increasingly recognized as a whole-organ disease predominantly affecting the elderly, characterized by typical alterations in subchondral bone and cartilage, along with recurrent synovial inflammation. Despite the availability of various therapeutics and medications, a complete resolution of OA remains elusive. In this study, novel functional hydrogels are developed by integrating natural bioactive molecules for OA treatment.
View Article and Find Full Text PDFNanophotonics
January 2025
Key Laboratory for Information Science of Electromagnetic Waves, School of Information Science and Technology, Fudan University, Shanghai 200433, China.
Gesture recognition plays a significant role in human-machine interaction (HMI) system. This paper proposes a gesture-controlled reconfigurable metasurface system based on surface electromyography (sEMG) for real-time beam deflection and polarization conversion. By recognizing the sEMG signals of user gestures through a pre-trained convolutional neural network (CNN) model, the system dynamically modulates the metasurface, enabling precise control of the deflection direction and polarization state of electromagnetic waves.
View Article and Find Full Text PDFChem Sci
January 2025
Key Laboratory for Advanced Materials, Institute of Fine Chemicals, Feringa Nobel Prize Scientist Joint Research Center, Frontiers Science Center for Materiobiology and Dynamic Chemistry, School of Chemistry and Molecular Engineering, Center of Photosensitive Chemicals Engineering, East China University of Science and Technology Shanghai 200237 China
Given that proteins with minor variations in amino acid sequences cause distinct functional outcomes, identifying and quantifying similar proteins is crucial, but remains a long-standing challenge. Herein, we present a two-dimensional orthogonal fluorescence and chemiluminescence design strategy for the probe DCM-SA, which is sequentially activated by albumin-mediated hydrolysis, exhibiting light-up fluorescence and photo-induced cycloaddition generating chemiluminescence, enabling orthogonal signal amplification for discrimination of subtle differences between similar proteins. By orthogonalizing these dual-mode signals, a two-dimensional work curve of fluorescence and chemiluminescence is established to distinguish and quantify similar proteins HSA and BSA.
View Article and Find Full Text PDFFront Neurorobot
January 2025
Software Engineering College, Zhengzhou University of Light Industry, Zhengzhou, China.
Introduction: Tracking the hidden states of dynamic systems is a fundamental task in signal processing. Recursive Kalman Filters (KF) are widely regarded as an efficient solution for linear and Gaussian systems, offering low computational complexity. However, real-world applications often involve non-linear dynamics, making it challenging for traditional Kalman Filters to achieve accurate state estimation.
View Article and Find Full Text PDFF1000Res
January 2025
Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Introduction: Magnetic resonance imaging (MRI) is essential for brain imaging, but conventional methods rely on qualitative contrast, are time-intensive, and prone to variability. Magnetic resonance finger printing (MRF) addresses these limitations by enabling fast, simultaneous mapping of multiple tissue properties like T1, T2. Using dynamic acquisition parameters and a precomputed signal dictionary, MRF provides robust, qualitative maps, improving diagnostic precision and expanding clinical and research applications in brain imaging.
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