The Drosophila neuromuscular junction (NMJ) ranks as one of the preeminent model systems for studying synaptic development, function, and plasticity. In this article, we review the experimental genetic methods that include the use of mutated or reengineered ion channels to manipulate the synaptic connections made by motor neurons onto larval body-wall muscles. We also provide a consideration of environmental and rearing conditions that phenocopy some of the genetic manipulations.
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http://dx.doi.org/10.1101/pdb.top067785 | DOI Listing |
J Electromyogr Kinesiol
December 2024
School of Information Science and Technology, Dalian Maritime University, Linghai Road 1, Dalian, Liaoning Province 116026, China. Electronic address:
This study proposed a U-Net based partial convolutional time-domain model for a real-time high-density surface electromyography (HD-sEMG) decomposition. The model combines U-Net and a separation block containing partial convolution, aiming to efficiently identify motor units (MUs) without preprocessing. The proposed U-Net based network was trained by the HD-sEMG signals with innervation pulse trains (IPTs) labels, and the results are compared between different step sizes, noises, and model structures under the sliding time window with 120 sampling points.
View Article and Find Full Text PDFMed Phys
December 2024
Department of Physics, Lakehead University, Thunder Bay, Ontario, Canada.
Background: This study investigates a multi-angle acquisition method aimed at improving image quality in organ-targeted PET detectors with planar detector heads. Organ-targeted PET technologies have emerged to address limitations of conventional whole-body PET/CT systems, such as restricted axial field-of-view (AFOV), limited spatial resolution, and high radiation exposure associated with PET procedures. The AFOV in organ-targeted PET can be adjusted to the organ of interest, minimizing unwanted signals from other parts of the body, thus improving signal collection efficiency and reducing the dose of administered radiotracer.
View Article and Find Full Text PDFIn unsupervised transfer learning for medical image segmentation, where existing algorithms face the challenge of error propagation due to inaccessible source domain data. In response to this scenario, source-free domain transfer algorithm with reduced style sensitivity (SFDT-RSS) is designed. SFDT-RSS initially pre-trains the source domain model by using the generalization strategy and subsequently adapts the pre-trained model to target domain without accessing source data.
View Article and Find Full Text PDFPLoS One
December 2024
College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning Province, China.
The iterative shrinkage-thresholding algorithm (ISTA) is a classic optimization algorithm for solving ill-posed linear inverse problems. Recently, this algorithm has continued to improve, and the iterative weighted shrinkage-thresholding algorithm (IWSTA) is one of the improved versions with a more evident advantage over the ISTA. It processes features with different weights, making different features have different contributions.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Materials and Production, Aalborg University, Aalborg, Denmark.
Background: In magnetic resonance imaging (MRI) segmentation research, the choice of sequence influences the segmentation accuracy. This study introduces a method to compare sequences. By aligning sequences with specific segmentation objectives, we provide an example of a comparative analysis of various sequences for knee images.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!