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http://dx.doi.org/10.1111/apt.17603 | DOI Listing |
Korean J Anesthesiol
September 2025
Department of Anesthesiology and Pain Medicine, Chonnam National University Hwasun Hospital, Chonnam National University Medical School, Gwangju, Korea.
Theor Appl Genet
September 2025
Institute for Breeding Research on Agricultural Crops, Julius Kühn Institute (JKI) - Federal Research Centre for Cultivated Plants, Sanitz, 18190, Germany.
Low-cost and high-throughput RNA sequencing data for barley RILs achieved GP performance comparable to or better than traditional SNP array datasets when combined with parental whole-genome sequencing SNP data. The field of genomic selection (GS) is advancing rapidly on many fronts including the utilization of multi-omics datasets with the goal of increasing prediction ability and becoming an integral part of an increasing number of breeding programs ensuring future food security. In this study, we used RNA sequencing (RNA-Seq) data to perform genomic prediction (GP) on three related barley RIL populations.
View Article and Find Full Text PDFJ Stomatol Oral Maxillofac Surg
September 2025
Department of Oral Medicine and Radiology, Sree Sai Dental College, Srikakulam 532401, INDIA. Electronic address:
Objective: Oral potentially malignant disorders (OPMDs) are a diverse group of oral mucosal lesions that carry an increased risk of malignant transformation. Although biopsy is the gold standard for the diagnosis of these lesions, early detection is crucial, emphasizing the need to introduce more reliable non-invasive screening modalities. The aim of the study was to compare the efficacy of VELscope and vital tissue staining techniques as screening tools in the detection of early dysplastic changes in OPMDS, such as oral leukoplakia (OL), oral lichen planus (OLP) & oral submucous fibrosis (OSMF) with histopathological confirmation.
View Article and Find Full Text PDFJ Magn Reson Imaging
September 2025
Department of Osteopathic Manipulative Medicine, College of Osteopathic Medicine, New York Institute of Technology, Old Westbury, New York, USA.
Front Rehabil Sci
August 2025
Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA, United States.
Introduction: Spinal cord injury (SCI) presents a significant burden to patients, families, and the healthcare system. The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.
Methods: We conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes.