A CE-MS method was developed and validated for the quantitative analysis of negatively charged metabolites by making use of the high mass accuracy and the quantitation capabilities of a TOF mass analyzer in combination with automated feature extraction and database search. Metabolites of the central carbon metabolism were quantified with an LOD and lower LOQ (LLOQ) of 0.2-2 and 1-4 microM, respectively. The method was used to elucidate metabolic changes in the Escherichia coli deletion mutant PntAB-UdhA that lacks nicotinamide nucleotide transhydrogenase function, under both stationary and exponential growth conditions. The reproducibility of metabolite extraction and CE-TOF-MS analysis ranged from 3.7 to 22.7 and 7.9 to 22.6%, respectively, while the biological variance was 3.4-31.3%. We observed significant differences in metabolite abundance, particularly in the citrate cycle, between wild-type and mutant E. coli. Overall, more than 600 features were found by automated feature detection, which resulted in approximately 150 high-confidence metabolite identifications. Concomitant analyses with two different GC-MS methods allowed not only crossvalidation of the quantitative results obtained by the various methods, but also led to a more comprehensive coverage of the E. coli metabolome.
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http://dx.doi.org/10.1002/elps.200700517 | DOI Listing |
JMIR Cancer
January 2025
Division of Radiology and Biomedical Engineering, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Background: The application of natural language processing in medicine has increased significantly, including tasks such as information extraction and classification. Natural language processing plays a crucial role in structuring free-form radiology reports, facilitating the interpretation of textual content, and enhancing data utility through clustering techniques. Clustering allows for the identification of similar lesions and disease patterns across a broad dataset, making it useful for aggregating information and discovering new insights in medical imaging.
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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
School of Food and Pharmacy, Zhejiang Ocean University, Zhoushan, 316022, People's Republic of China.
Accurate and rapid segmentation of key parts of frozen tuna, along with precise pose estimation, is crucial for automated processing. However, challenges such as size differences and indistinct features of tuna parts, as well as the complexity of determining fish poses in multi-fish scenarios, hinder this process. To address these issues, this paper introduces TunaVision, a vision model based on YOLOv8 designed for automated tuna processing.
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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 PDFJ Shoulder Elbow Surg
January 2025
Department of Orthopedics and Trauma, Peking University People's Hospital, Beijing 100044, China; Key Laboratory of Trauma and Neural Regeneration (Peking University), Ministry of Education, Beijing 100044, China; National Center for Trauma Medicine, Peking University People's Hospital, Beijing 100044, China. Electronic address:
Objective: The bare area is defined as a transverse region within the trochlear notch, serving as an optimal entry point for olecranon osteotomy due to the absence of articular cartilage coverage. However, there is limited research on the morphology and location of the bare area, and there is a lack of intuitive visual description. Thus, the purpose of this study is to delineate anatomical features of the bare area and visualize its morphology and refine the olecranon osteotomy approach.
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