In rapidly changing thyroid state Rodbard's Q-Kd interval (reflecting heart contractility) changes more rapidly, than ART (reflecting skeletal muscle contractility). After withdrawal of substitutive therapy in athyreotic patients the Q-Kd intervals prolongs more rapidly than ART and during intensive treatment of hypothyroidism the Q-Kd interval shortens more rapidly that ART. A more rapid metabolic turnover in heart muscle in comparison with skeletal muscle is proposed as suitable explanation. Practical consequences for early diagnosis of hypothyroidism and for instant functional diagnosis of thyroidal disorders are stressed.
Download full-text PDF |
Source |
---|
Nan Fang Yi Ke Da Xue Xue Bao
January 2025
School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
Objectives: To explore the synthesis of high-quality CT (sCT) from cone-beam CT (CBCT) using PE-CycleGAN for adaptive radiotherapy (ART) for nasopharyngeal carcinoma.
Methods: A perception-enhanced CycleGAN model "PE-CycleGAN" was proposed, introducing dual-contrast discriminator loss, multi-perceptual generator loss, and improved U-Net structure. CBCT and CT data from 80 nasopharyngeal carcinoma patients were used as the training set, with 7 cases as the test set.
Anal Chem
January 2025
State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, China.
Small molecule near-infrared (NIR) fluorophores play a critical role in disease diagnosis and early detection of various markers in living organisms. To accelerate their development and design, a deep learning platform, NIRFluor, was established to rapidly screen small molecule NIR fluorophores with the desired optical properties. The core component of NIRFluor is a state-of-the-art deep learning model trained on 5179 experimental big data.
View Article and Find Full Text PDFHeliyon
January 2025
BCN MedTech, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.
Deformable image registration is a cornerstone of many medical image analysis applications, particularly in the context of fetal brain magnetic resonance imaging (MRI), where precise registration is essential for studying the rapidly evolving fetal brain during pregnancy and potentially identifying neurodevelopmental abnormalities. While deep learning has become the leading approach for medical image registration, traditional convolutional neural networks (CNNs) often fall short in capturing fine image details due to their bias toward low spatial frequencies. To address this challenge, we introduce a deep learning registration framework comprising multiple cascaded convolutional networks.
View Article and Find Full Text PDFResearch (Wash D C)
January 2025
Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117583, Singapore.
Acta Neuropathol Commun
January 2025
Sid Faithfull Brain Cancer Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, QLD, 4006, Australia.
Glioblastoma (GBM) is a highly aggressive adult brain cancer, characterised by poor prognosis and a dismal five-year survival rate. Despite significant knowledge gains in tumour biology, meaningful advances in patient survival remain elusive. The field of neuro-oncology faces many disease obstacles, one being the paucity of faithful models to advance preclinical research and guide personalised medicine approaches.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!