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Efficacy and safety of teriparatide in kidney transplant recipients with osteoporosis and low bone turnover: a real-world experience.
Int Urol Nephrol
January 2025
Nephrology, Dialysis and Kidney Transplant Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
Introduction: Kidney transplantation is the preferred treatment for end-stage kidney disease (ESKD), enhancing survival and quality of life. However, kidney transplant recipients (KTRs) are at high risk for bone disorders, particularly low bone turnover disease, which increases fracture risk. Teriparatide, an anabolic agent, may provide a beneficial treatment option for these patients.
View Article and Find Full Text PDFA deep learning pipeline for three-dimensional brain-wide mapping of local neuronal ensembles in teravoxel light-sheet microscopy.
Nat Methods
January 2025
Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
Teravoxel-scale, cellular-resolution images of cleared rodent brains acquired with light-sheet fluorescence microscopy have transformed the way we study the brain. Realizing the potential of this technology requires computational pipelines that generalize across experimental protocols and map neuronal activity at the laminar and subpopulation-specific levels, beyond atlas-defined regions. Here, we present artficial intelligence-based cartography of ensembles (ACE), an end-to-end pipeline that employs three-dimensional deep learning segmentation models and advanced cluster-wise statistical algorithms, to enable unbiased mapping of local neuronal activity and connectivity.
View Article and Find Full Text PDFReducing IgG accumulation via neonatal Fc receptor (FcRn) blockade relieves neuropathic pain.
Brain Behav Immun
January 2025
Laboratories of Neuroimmunology, Department of Symptom Research, University of Texas MD Anderson Cancer Center, Houston, USA. Electronic address:
Preclinical and clinical studies have established that autoreactive immunoglobulin G (IgG) can drive neuropathic pain. We recently demonstrated that sciatic nerve chronic constriction injury (CCI) in male and female mice results in the production of pronociceptive IgG, which accumulates around the lumbar region, including within the dorsal root ganglia (DRG) and spinal cord, facilitating the development of neuropathic pain. These data raise the intriguing possibility that neuropathic pain may be alleviated by reducing the accumulation of IgG.
View Article and Find Full Text PDFAutomated Diagnosis and Classification of Temporomandibular Joint Degenerative Joint Disease via Artificial Intelligence Using CBCT Imaging.
J Dent
January 2025
Department of Oral & Maxillofacial Radiology, Peking University School & Hospital of Stomatology, Beijing 100081, China; National Center for Stomatology & National Clinical Research Center for Oral Diseases, Beijing 100081, China; National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing 100081, China; Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China. Electronic address:
Objectives: In this study, artificial intelligence techniques were used to achieve automated diagnosis and classification of temporomandibular joint (TMJ) degenerative joint disease (DJD) on cone beam computed tomography (CBCT) images.
Methods: An AI model utilizing the YOLOv10 algorithm was trained, validated and tested on 7357 annotated and corrected oblique sagittal TMJ images (3010 images of normal condyles and 4347 images of condyles with DJD) from 1018 patients who visited Peking University School and Hospital of Stomatology for temporomandibular disorders and underwent TMJ CBCT examinations. This model could identify DJD as well as the radiographic signs of DJD, namely, erosion, osteophytes, sclerosis and subchondral cysts.
A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario.
Comput Biol Med
January 2025
Department of Mathematics and Computer Science, University of Cagliari, Via Ospedale 72, 09124, Cagliari, Italy.
Background: Malaria is a critical and potentially fatal disease caused by the Plasmodium parasite and is responsible for more than 600,000 deaths globally. Early and accurate detection of malaria parasites is crucial for effective treatment, yet conventional microscopy faces limitations in variability and efficiency.
Methods: We propose a novel computer-aided detection framework based on deep learning and attention mechanisms, extending the YOLO-SPAM and YOLO-PAM models.
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