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Integrated bioinformatics analysis identified cuproptosis-related hub gene Mpeg1 as potential biomarker in spinal cord injury.
Sci Rep
January 2025
Department of Neurosurgery, The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou, China.
Spinal cord injury (SCI) is a profound ailment lacking a well-defined molecular mechanism and effective treatments. Cuproptosis, identified as a recently discovered cell death pathway, exhibits diverse roles in various cancers. Nevertheless, its involvement in SCI is yet to be elucidated.
View Article and Find Full Text PDFFast and accurate deep learning scans for signatures of natural selection in genomes using FASTER-NN.
Commun Biol
January 2025
University of Twente, Enschede, The Netherlands.
Deep learning classification models based on Convolutional Neural Networks (CNNs) are increasingly used in population genetic inference for detecting signatures of natural selection. Prevailing detection methods treat the design of the classifier as a discrete phase, assuming that high classification accuracy is the sole prerequisite for precise detection. This frequently steers method development toward classification-driven optimizations that can inadvertently impede detection.
View Article and Find Full Text PDFAbnormality detection in nailfold capillary images using deep learning with EfficientNet and cascade transfer learning.
Sci Rep
January 2025
Hive AI Innovation Studio, Department of Computer Science and Engineering, University of Louisville, Louisville, KY, 40292, USA.
Nailfold Capillaroscopy (NFC) is a simple, non-invasive diagnostic tool used to detect microvascular changes in nailfold. Chronic pathological changes associated with a wide range of systemic diseases, such as diabetes, cardiovascular disorders, and rheumatological conditions like systemic sclerosis, can manifest as observable microvascular changes in the terminal capillaries of nailfolds. The current gold standard relies on experts performing manual evaluations, which is an exhaustive time-intensive, and subjective process.
View Article and Find Full Text PDFExtracting organs of interest from medical images based on convolutional neural network with auxiliary and refined constraints.
Sci Rep
January 2025
Department of Rehabilitation Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200336, China.
Accurately extracting organs from medical images provides radiologist with more comprehensive evidences to clinical diagnose, which offers up a higher accuracy and efficiency. However, the key to achieving accurate segmentation lies in abundant clues for contour distinction, which has a high demand for the network architecture design and its practical training status. To this end, we design auxiliary and refined constraints to optimize the energy function by supplying additional guidance in training procedure, thus promoting model's ability to capture information.
View Article and Find Full Text PDFResting state BOLD-perfusion coupling patterns using multiband multi-echo pseudo-continuous arterial spin label imaging.
Sci Rep
January 2025
Department of Radiology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
The alteration of neurovascular coupling (NVC), where acute localized blood flow increases following neural activity, plays a key role in several neurovascular processes including aging and neurodegeneration. While not equivalent to NVC, the coupling between simultaneously measured cerebral blood flow (CBF) with arterial spin labeling (ASL) and blood oxygenation dependent (BOLD) signals, can also be affected. Moreover, the acquisition of BOLD data allows the assessment of resting state (RS) fMRI metrics.
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