Mass analysis of proteolytic fragment peptides following hydrogen/deuterium exchange offers a general measure of solvent accessibility/hydrogen bonding (and thus conformation) of solution-phase proteins and their complexes. The primary problem in such mass analyses is reliable and rapid assignment of mass spectral peaks to the correct charge state and degree of deuteration of each fragment peptide, in the presence of substantial overlap between isotopic distributions of target peptides, autolysis products, and other interferant species. Here, we show that at sufficiently high mass resolving power (m/Delta m(50%) > or = 100,000), it becomes possible to resolve enough of those overlaps so that automated data reduction becomes possible, based on the actual elemental composition of each peptide without the need to deconvolve isotopic distributions. We demonstrate automated, rapid, reliable assignment of peptide masses from H/D exchange experiments, based on electrospray ionization FT-ICR mass spectra from H/D exchange of solution-phase myoglobin. Combined with previously demonstrated automated data acquisition for such experiments, the present data reduction algorithm enhances automation (and thus expands generality and applicability) for high-resolution mass spectrometry-based analysis of H/D exchange of solution-phase proteins.
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http://dx.doi.org/10.1016/j.jasms.2009.12.016 | DOI Listing |
NPJ Digit Med
January 2025
Neurofibromatosis Type 1 Center and Laboratory for Neurofibromatosis Type 1 Research, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200011, China.
Deep-learning models have shown promise in differentiating between benign and malignant lesions. Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background.
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January 2025
School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, India.
Mechanical ventilation is the process through which breathing support is provided to patients who face inconvenience during respiration. During the pandemic, many people were suffering from lung disorders, which elevated the demand for mechanical ventilators. The handling of mechanical ventilators is to be done under the assistance of trained professionals and demands the selection of ideal parameters.
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January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
View Article and Find Full Text PDFAm J Orthod Dentofacial Orthop
February 2025
Department of Orthodontics, Faculty of Dentistry, Çanakkale Onsekiz Mart University, Çanakkale, Turkey.
Introduction: This study aimed to assess the precision of an open-source, clinician-trained, and user-friendly convolutional neural network-based model for automatically segmenting the mandible.
Methods: A total of 55 cone-beam computed tomography scans that met the inclusion criteria were collected and divided into test and training groups. The MONAI (Medical Open Network for Artificial Intelligence) Label active learning tool extension was used to train the automatic model.
Waste Manag
January 2025
Chair of Waste Processing Technology and Waste Management, Montanuniversitaet Leoben, Leoben, Austria. Electronic address:
Global waste generation is projected to reach 3.40 billion tons by 2050, necessitating improved waste sorting for effective recycling and progress toward a circular economy. Achieving this transformation requires higher sorting intensity through intensified processes, increased efficiency, and enhanced yield.
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