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Diffusion tensor-magnetic resonance electrical impedance tomography (DT-MREIT) is an imaging modality to obtain low-frequency anisotropic conductivity distribution employing diffusion tensor imaging and MREIT techniques. DT-MREIT is based on the linear relationship between the conductivity and water self-diffusion tensors in a porous medium, like the brain white matter. Several DT-MREIT studies in the literature provide cross-sectional anisotropic conductivity images of tissue phantoms, canine brain, and the human brain. In these studies, the conductivity tensor images are reconstructed using the diffusion tensor and current density data acquired by injecting two linearly independent current patterns. In this study, a novel reconstruction algorithm is devised for DT-MREIT to reconstruct the conductivity tensor images using a single current injection. Therefore, the clinical applicability of DT-MREIT can be improved by reducing the total acquisition time, the number of current injection cables, and contact electrodes to half by decreasing the number of current injection patterns to one. The proposed method is evaluated utilizing simulated measurements and physical experiments. The results obtained show the successful reconstruction of the anisotropic conductivity distribution using the proposed single current DT-MREIT.
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http://dx.doi.org/10.1088/1361-6560/abddcf | DOI Listing |
Adv Sci (Weinh)
September 2025
Department of Chemistry and Chemical Biology, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA.
Traumatic Brain Injury (TBI) is a common and debilitating injury, causing long-lasting neurological deficits. Current therapeies for recovery remain inadequate, undersing the urgent need for innovative interventions. In this study, a novel therapeutic approach is introduced that delivers extracellular vesicles (EVs) derived from human-induced pluripotent stem cell-derived neural progenitor cells (hiPSC-NPCs) with a gelatin-based injectable bioorthogonal hydrogel (BIOGEL).
View Article and Find Full Text PDFAdv Sci (Weinh)
September 2025
School of Stomatology, Xuzhou Medical University, Affiliated Stomatological Hospital of Xuzhou Medical University, Xuzhou, 221004, China.
Musculoskeletal disorders, including bone fractures, osteoarthritis, and muscle injuries, represent a leading cause of global disability, revealing the urgency for advanced therapeutic solutions. However, current therapies face limitations including donor-site morbidity, immune rejection, and inadequate mimicry of dynamic tissue repair processes. DNA-based hydrogels emerge as transformative platforms for musculoskeletal reconstruction, with their sequence programmability, dynamic adaptability, and biocompatibility to balance structural support and biological functions.
View Article and Find Full Text PDFAm J Lifestyle Med
September 2025
Center for Behavioral Emergency & Addiction Research, McWilliams School of Biomedical Informatics, the University of Texas Health Science Center at Houston, Houston, TX, USA (ASC, MCT, AL, TCL).
Background: Substance use disorders (SUD) are associated with metabolic dysregulation and nutritional deficiencies. Studies show that incorporating nutrition interventions into treatment may improve physical and psychological health. This study sought to explore dietary and consumer behavior in individuals currently using substances.
View Article and Find Full Text PDFNat Photonics
June 2025
University of Vienna, Faculty of Physics, Vienna Center for Quantum Science and Technology (VCQ), Vienna, Austria.
Recently, machine learning has had remarkable impact in scientific to everyday-life applications. However, complex tasks often require the consumption of unfeasible amounts of energy and computational power. Quantum computation may lower such requirements, although it is unclear whether enhancements are reachable with current technologies.
View Article and Find Full Text PDFInt J Mass Spectrom
December 2025
Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, IN 47907-2084, USA.
An electrostatic linear ion trap (ELIT) is used to trap ions between two ion mirrors with image current detection by central detection electrode. Transformation of the time-domain signal to the frequency-domain via Fourier transform (FT) yields an ion frequency spectrum that can be converted to a mass-to-charge scale. Injection of ions into an ELIT from an external ion source leads to a time-of-flight ion separation that ultimately determines the range of over which ions can be collected from a given ion injection step.
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