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Osteoarthritis (OA) is heterogeneous and involves structural changes in the whole joint, such as cartilage, meniscus/labrum, ligaments, and tendons, mainly with short T2 relaxation times. Detecting OA before the onset of irreversible changes is crucial for early proactive management and limit growing disease burden. The more recent advanced quantitative imaging techniques and deep learning (DL) algorithms in musculoskeletal imaging have shown great potential for visualizing "pre-OA.

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deep-AMPpred: A Deep Learning Method for Identifying Antimicrobial Peptides and Their Functional Activities.

J Chem Inf Model

January 2025

School of Information and Artificial Intelligence, Anhui Provincial Engineering Research Center for Beidou Precision Agriculture Information, Key Laboratory of Agricultural Sensors for Ministry of Agriculture and Rural Affairs, Anhui Agricultural University, Hefei, Anhui 230036, China.

Antimicrobial peptides (AMPs) are small peptides that play an important role in disease defense. As the problem of pathogen resistance caused by the misuse of antibiotics intensifies, the identification of AMPs as alternatives to antibiotics has become a hot topic. Accurately identifying AMPs using computational methods has been a key issue in the field of bioinformatics in recent years.

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Research progress on the structural and anti-colorectal malignant tumor properties of Shikonin.

J Cancer Res Ther

December 2024

Department of Oncology, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, China.

Colorectal cancer is the third most prevalent malignant tumor worldwide. Despite the advancements in surgical procedures and treatment options, CRC remains a considerable cause of cancer-related mortality. Shikonin is a naphthoquinone compound that exhibits multiple biological activities, including anti-inflammatory and anti-tumor effects as well as wound healing promotion.

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Advances and applications in single-cell and spatial genomics.

Sci China Life Sci

December 2024

Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China.

The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics.

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Forests have the potential to contribute significantly to global climate policy efforts through enhanced carbon sequestration and storage in terrestrial systems and wood products. Projections models simulate changes future in forest carbon fluxes under different environmental, economic, and policy conditions and can inform landowners and policymakers on how to best utilize global forests for mitigating climate change. However, forest carbon modeling frameworks are often developed and applied in a highly disciplinary manner, e.

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