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| http://dx.doi.org/10.1186/s12888-022-03776-8 | DOI Listing |
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Background: Urine neutrophil gelatinase-associated lipocalin (uNGAL) is a biomarker for the early diagnosis of AKI.
Objectives: To evaluate uNGAL in dogs with non-associative immune mediated hemolytic anemia (IMHA) and to evaluate whether uNGAL correlates with disease severity markers, negative prognostic indicators and outcome.
Animals: Twenty-two dogs with non-associative IMHA and 14 healthy dogs.
Introduction: The most frequent form of diabetes in pediatric patients is polygenic autoimmune diabetes (T1D), but single-gene variants responsible for autoimmune diabetes have also been described. Both disorders share clinical features, which can lead to monogenic forms being misdiagnosed as T1D. However, correct diagnosis is crucial for therapeutic choice, prognosis and genetic counseling.
View Article and Find Full Text PDFAdditively Manufactured Subperiosteal Implants for the Rehabilitations of Lateral Incisors Agenesis - a case series.
J Stomatol Oral Maxillofac Surg
January 2025
Department of Prosthodontics and Gerostomatology, Poznan University of Medical Sciences, 60-792 Poznan, Poland.
Background: Tooth agenesis, particularly the absence of upper lateral incisors, presents substantial challenges for clinicians due to the associated bone atrophy, which limits the use of traditional implant solutions. Current options, such as endosseous implants combined with guided bone regeneration (GBR), often fail due to insufficient osseointegration in atrophic bone. This study aims to evaluate the effectiveness of custom-made, additively manufactured subperiosteal implants in addressing these challenges METHODS: This retrospective study assessed 16 custom-made subperiosteal implants used in 12 patients (10 females, 2 males; mean age 25 ± 2.
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.
Spatio-temporal transformers for decoding neural movement control.
J Neural Eng
January 2025
Department of Information Engineering, Electronics and Telecommunications, University of Rome La Sapienza, Piazzale Aldo Moro 5, Rome, 00185, ITALY.
Deep learning tools applied to high-resolution neurophysiological data have significantly progressed, offering enhanced decoding, real-time processing, and readability for practical applications. However, the design of artificial neural networks to analyze neural activity in vivo remains a challenge, requiring a delicate balance between efficiency in low-data regimes and the interpretability of the results. Approach: To address this challenge, we introduce a novel specialized transformer architecture to analyze single-neuron spiking activity.
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