Bioelectronic medicine is a rapidly growing field where targeted electrical signals can act as an adjunct or alternative to drugs to treat neurological disorders and diseases via stimulating the peripheral nervous system on demand. However, current existing strategies are limited by external battery requirements, and the injury and inflammation caused by the mechanical mismatch between rigid electrodes and soft nerves. Here we report a wireless, leadless, and battery-free ferroelectret implant, termed NeuroRing, that wraps around the target peripheral nerve and demonstrates high mechanical conformability to dynamic motion nerve tissue. As-fabricated NeuroRing can act as an ultrasound receiver that converts ultrasound vibrations into electrostimulation pulses, thus stimulating the targeted peripheral nerve on demand. This capability is demonstrated by the precise modulation of the sacral splanchnic nerve to treat colitis, providing a framework for future bioelectronic medicines that offer an alternative to non-specific pharmacological approaches.
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http://dx.doi.org/10.1038/s41467-023-44065-6 | DOI Listing |
Sci Rep
January 2025
Department of Orthopedic Surgery, Chang Gung Memorial Hospital, No. 5, Fuxing St., Guishan Dist, Linkou, Taoyuan, 33305, Taiwan.
Objective: To investigate the predictive ability of the MRI-based vertebral bone quality (VBQ) score for pedicle screw loosening following instrumented transforaminal lumbar interbody fusion (TLIF).
Methods: Data from patients who have received one or two-level instrumented TLIF from February 2014 to March 2015 were retrospectively collected. Pedicle screw loosening was diagnosed when the radiolucent zone around the screw exceeded 1 mm in plain radiographs.
Am J Obstet Gynecol
January 2025
University of California, San Francisco, San Francisco, CA.
Background: With increasingly restricted access to facility-based abortion in the United States, pregnant people are increasingly relying on models of care that utilize history-based or no-test approaches to eligibility assessment. Minimal research has examined the accuracy of abortion patients' self-assessment of eligibility for medication abortion using their health history, a necessary step towards ensuring optimal access to history-based or no-test models, as well as potential over-the-counter access.
Objective: To examine the accuracy of pregnant people's eligibility for medication abortion determined using their self-reported health history as compared to clinician assessment with ultrasound and other tests.
J Clin Med
January 2025
Department of Radiology, Bursa Yuksek Ihtisas Training and Research Hospital, 16310 Bursa, Turkey.
: This study aimed to evaluate the diagnostic performance of the Kaiser score (KS) on the modified abbreviated breast magnetic resonance imaging (AB-MRI) protocol for characterizing breast lesions by comparing it with full-protocol MRI (FP-MRI), using the histological data as the reference standard. : Breast MRIs detecting histologically verified contrast-enhancing breast lesions were evaluated retrospectively. A modified AB-MRI protocol was created from the standard FP-MRI, which comprised axial fat-suppressed T2-weighted imaging (T2WI), pre-contrast T1-weighted imaging (T1WI), and first, second, and fourth post-contrast phases.
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December 2024
Artificial Intelligence Center, Chung Shan Medical University Hospital, Taichung 40201, Taiwan.
The duration of the response to radiotherapy-related treatment is a critical prognostic indicator for patients with nasopharyngeal carcinoma (NPC). Persistent tumor status, including residual tumor presence and early recurrence, is associated with poorer survival outcomes. To address this, we developed a prediction model to identify patients at a high risk of persistent tumor status prior to initiating treatment.
View Article and Find Full Text PDFCancers (Basel)
December 2024
65+ Outpatient Clinic, Amalia Fleming General Hospital, 14, 25th Martiou Str., 15127 Melissia, Greece.
: Melanoma, an aggressive form of skin cancer, accounts for a significant proportion of skin-cancer-related deaths worldwide. Early and accurate differentiation between melanoma and benign melanocytic nevi is critical for improving survival rates but remains challenging because of diagnostic variability. Convolutional neural networks (CNNs) have shown promise in automating melanoma detection with accuracy comparable to expert dermatologists.
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