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Showing 1–7 of 7 results
Advanced filters: Author: Kehan Song Clear advanced filters

  • To overcome various challenges in forensic pathology, the authors present SongCi, a visual-language AI trained on multi-modal autopsy cases of various cohorts. SongCi detects diverse post-mortem diseases and injuries and gives clear image-text explanations for forensic analysis, rivaling senior pathologists.

    • Chen Shen
    • Chunfeng Lian
    • Zhenyuan Wang
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-20

  • Generative AI holds promise for creating novel compounds. Here, authors introduce TamGen, a GPT-like model designed to generate molecules tailored to specific target proteins. TamGen identified 14 potent compounds against the Tuberculosis ClpP protease, showing its potential for drug discovery.

    • Kehan Wu
    • Yingce Xia
    • Tie-Yan Liu
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-12

  • Emulsion gels have several attributes desirable for biomedical applications including large-amount encapsulation and storage, but the preparation method is usually specific and complicated. Here, the authors report a simple method for fabricating bridged emulsion gels by employing a polymer to regulate the assembly of commercial silica nanoparticles at the water/oil interfaces.

    • Chuchu Wan
    • Si He
    • Jintao Zhu
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-12

  • Question Answering (QA) models have emerged as crucial tools for acquiring knowledge and evaluating domain-specific abilities, however, the domain of chemical QA remains underexplored. Here, the authors report ScholarChemQA as a large-scale QA dataset and introduce a ChemMatch model for effectively answering chemical questions and acquiring chemical-related knowledge.

    • Xiuying Chen
    • Tairan Wang
    • Xiangliang Zhang
    ResearchOpen Access
    Communications Chemistry
    Volume: 8, P: 1-11

  • In an inter-laboratory study, the authors compare the accuracy and performance of three optical density calibration protocols (colloidal silica, serial dilution of silica microspheres, and colony-forming unit (CFU) assay). They demonstrate that serial dilution of silica microspheres is the best of these tested protocols, allowing precise and robust calibration that is easily assessed for quality control and can also evaluate the effective linear range of an instrument.

    • Jacob Beal
    • Natalie G. Farny
    • Jiajie Zhou
    ResearchOpen Access
    Communications Biology
    Volume: 3, P: 1-29