Electrical stimulation (ES) of cellular systems can be utilized for biotechnological applications and electroceuticals (bioelectric medicine). Neural cell stimulation especially has a long history in neuroscience research and is increasingly applied for clinical therapies. Application of ES via conventional electrodes requires external connectors and power sources, hindering scientific and therapeutic applications. Here engineering novel 3D scaffold-free human neural stem cell constructs with integrated piezoelectric nanoparticles for enhanced neural tissue induction and function is described. Tetragonal barium titanate (BaTi03) nanoparticles are employed as piezoelectric stimulators prepared as cytocompatible dispersions, incorporated into 3D self-organizing neural spheroids, and activated wirelessly by ultrasound. Ultrasound delivery (low frequency; 40 kHz) is optimized for cell survival, and nanoparticle activation enabled ES throughout the spheroids during differentiation, tissue formation, and maturation. The resultant human neural tissues represent the first example of direct tissue loading with piezoelectric particles for ensuing 3D ultrasound-mediated piezoelectric enhancement of human neuronal induction from stem cells, including augmented neuritogenesis and synaptogenesis. It is anticipated that the platform described will facilitate advanced tissue engineering and in vitro modeling of human neural (and potentially non-neural) tissues, with modeling including tissue development and pathology, and applicable to preclinical testing and prototyping of both electroceuticals and pharmaceuticals.
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http://dx.doi.org/10.1002/advs.202310010 | DOI Listing |
Vestn Otorinolaringol
December 2024
St. Petersburg Research Institute of Ear, Throat, Nose and Speech, St. Petersburg, Russia.
Unlabelled: The article is devoted to the problem of the rehabilitation stage of cochlear implantation in patients with inner ear abnormalities. It provides a detailed analysis of the audiological characteristics of such patients and draws conclusions about approaches to interpreting diagnostic data and speech processors fitting.
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Environ Sci Pollut Res Int
December 2024
Department of Earth Sciences, Indian Institute of Technology Roorkee, Roorkee-247667, Roorkee, Uttarakhand, India.
Groundwater is an essential freshwater source worldwide, but increasing pollution poses risks to its sustainability. This study applied a comprehensive approach to assess hydrogeochemical facies and groundwater quality in Odisha's large low-lying coastal regions. Analysis of 136 samples revealed that sodium (9.
View Article and Find Full Text PDFCell Mol Neurobiol
December 2024
Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
It is difficult to distinguish Parkinson's disease (PD) in the early stage from those of various disorders including atypical Parkinson's syndrome (APS), vascular parkinsonism (VP), and even essential tremor (ET), because of the overlap of symptoms. Other, more challenging problems will arise when Parkinson's disease develops into Parkinson's disease dementia (PDD) in the middle and late stages. At this time, the differential diagnosis of PDD and DLB becomes thorny.
View Article and Find Full Text PDFTomography
December 2024
Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.
This research introduces BAE-ViT, a specialized vision transformer model developed for bone age estimation (BAE). This model is designed to efficiently merge image and sex data, a capability not present in traditional convolutional neural networks (CNNs). BAE-ViT employs a novel data fusion method to facilitate detailed interactions between visual and non-visual data by tokenizing non-visual information and concatenating all tokens (visual or non-visual) as the input to the model.
View Article and Find Full Text PDFTomography
December 2024
Department of Medical Imaging and Radiological Science, I-Shou University, Kaohsiung City 824005, Taiwan.
Breast cancer is a leading cause of mortality among women in Taiwan and globally. Non-invasive imaging methods, such as mammography and ultrasound, are critical for early detection, yet standalone modalities have limitations in regard to their diagnostic accuracy. This study aims to enhance breast cancer detection through a cross-modality fusion approach combining mammography and ultrasound imaging, using advanced convolutional neural network (CNN) architectures.
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