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Mitochondrial segmentation and function prediction in live-cell images with deep learning.
Nat Commun
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Frontiers Science Center for Flexible Electronics, Xi'an Institute of Flexible Electronics (IFE) and Xi'an Institute of Biomedical Materials & Engineering, Northwestern Polytechnical University, Xi'an, China.
Mitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image segmentation and function prediction. Trained on a dataset of 20,000 manually labeled mitochondria from super-resolution (SR) images, MoDL achieves superior segmentation accuracy, enabling comprehensive morphological analysis.
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Division of Library Services, Charles Sturt University, Albury, NSW, Australia.
Introduction/background: Group work plays a crucial role in healthcare education by fostering collaboration, communication, and teamwork skills. However, students often face challenges such as unequal workload distribution, conflict, and anxiety. Group learning contracts have been introduced to improve group dynamics by setting clear expectations, enhancing accountability, and promoting effective collaboration.
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Plastic waste management is one of the key issues in global environmental protection. Integrating spectroscopy acquisition devices with deep learning algorithms has emerged as an effective method for rapid plastic classification. However, the challenges in collecting plastic samples and spectroscopy data have resulted in a limited number of data samples and an incomplete comparison of relevant classification algorithms.
View Article and Find Full Text PDFLatest Advancements in Transcutaneous Electrical Nerve Stimulation (TENS) and Electronic Muscle Stimulation (EMS): Revisiting an Established Therapy with New Possibilities.
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Transcutaneous Electrical Nerve Stimulation (TENS) and Electronic Muscle Stimulation (EMS) are non-invasive therapies widely used for pain relief and neuromuscular adaptation. However, the clinical research supporting the efficacy of TENS in chronic pain management is limited by significant methodological flaws, including small sample sizes and inconsistent reporting of stimulation parameters. TENS modulates pain perception through various techniques, targeting specific nerve fibers and pain pathways.
View Article and Find Full Text PDFA CNN-based self-supervised learning framework for small-sample near-infrared spectroscopy classification.
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Near-infrared (NIR) spectroscopy, with its advantages of non-destructive analysis, simple operation, and fast detection speed, has been widely applied in various fields. However, the effectiveness of current spectral analysis techniques still relies on complex preprocessing and feature selection of spectral data. While data-driven deep learning can automatically extract features from raw spectral data, it typically requires large amounts of labeled data for training, limiting its application in spectral analysis.
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