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http://dx.doi.org/10.3390/brainsci12081107 | DOI Listing |
Neurosci Bull
January 2025
Liaoning Provincial Key Laboratory of Cerebral Diseases, Department of Physiology, College of Basic Medical Sciences, Dalian Medical University, Dalian, 116044, China.
Anal Chem
January 2025
State Key Laboratory of Cellular Stress Biology, Institute of Artificial Intelligence, School of Life Sciences, Faculty of Medicine and Life Sciences, National Institute for Data Science in Health and Medicine, XMU-HBN skin biomedical research center, Xiamen University, Xiamen, Fujian 361102, China.
In metabolomic analysis based on liquid chromatography coupled with mass spectrometry, detecting and quantifying intricate objects is a massive job. Current peak picking methods still cause high rates of incorrectly picked peaks to influence the reliability and reproducibility of results. To address these challenges, we developed QuanFormer, a deep learning method based on object detection designed to accurately quantify peak signals.
View Article and Find Full Text PDFFront Oncol
January 2025
Department of Obstetrics and Gynecology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
[This corrects the article DOI: 10.3389/fonc.2022.
View Article and Find Full Text PDFFront Med (Lausanne)
January 2025
National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China.
Aims: To compare the efficiency of scleral buckling (SB) and pars plana vitrectomy (PPV) with or without SB in patients with primary simple phakic fovea-splitting rhegmatogenous retinal detachment (RRD).
Methods: A retrospective case-control study included 101 patients aged <55 years diagnosed with phakic fovea-splitting RRD. The primary outcome was functional success, defined as achieving a postoperative logarithm of the minimum angle of resolution best-corrected visual acuity of 0.
J Pain Res
January 2025
Jiangxi Provincial Key Laboratory for Precision Pathology and Intelligent Diagnosis, Department of Radiology, the First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, People's Republic of China.
Purpose: To investigate whether functional radiomic features in bilateral hippocampi can identify the cognitively impaired patients from low-back-related leg pain (LBLP).
Patients And Methods: For this retrospective study, a total of 95 clinically definite LBLP patients (40 cognitively impaired patients and 45 cognitively preserved patients) were included, and all patients underwent functional MRI and clinical assessments. After calculating the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC) and degree centrality (DC) imaging, the radiomic features (n = 819) of bilateral hippocampi were extracted from these images, respectively.
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