AI tool spots blood cell abnormalities missed by doctors
Peer-Reviewed Publication
Updates every hour. Last Updated: 23-Nov-2025 10:11 ET (23-Nov-2025 15:11 GMT/UTC)
An AI tool that can analyse abnormalities in the shape and form of blood cells, and with greater accuracy and reliability than human experts, could change the way conditions such as leukaemia are diagnosed.
Complex digital images of tissue samples that can take an experienced pathologist up to 20 minutes to annotate could be analysed in just one minute using a new AI tool developed by researchers at the University of Cambridge. SMMILe, a machine learning algorithm, is able not only to correctly detect the presence of cancer cells on slides taken from biopsies and surgical sections, but it can predict where the tumour lesions are located and even the proportion of regions with different levels of aggressiveness.
3D printing, as a versatile additive manufacturing technique, offers high design flexibility, rapid prototyping, minimal material waste, and the capability to fabricate complex, customized geometries. These attributes make it particularly well-suited for low-temperature hydrogen electrochemical conversion devices—specifically, proton exchange membrane fuel cells, proton exchange membrane electrolyzer cells, anion exchange membrane electrolyzer cells, and alkaline electrolyzers—which demand finely structured components such as catalyst layers, gas diffusion layers, electrodes, porous transport layers, and bipolar plates. This review provides a focused and critical summary of the current progress in applying 3D printing technologies to these key components. It begins with a concise introduction to the principles and classifications of mainstream 3D printing methods relevant to the hydrogen energy sector and proceeds to analyze their specific applications and performance impacts across different device architectures. Finally, the review identifies existing technical challenges and outlines future research directions to accelerate the integration of 3D printing in next-generation low-temperature hydrogen energy systems.
The integration of systems metabolic engineering with co-culture strategies that couples bacterial cellulose production with natural colorant biosynthesis enabled the one-pot generation of rainbow-colored bacterial cellulose, establishing a sustainable biomanufacturing platform that can replace petroleum-based textiles and eliminate chemical dyeing processes.
A research group at KAIST has successfully developed a modular co-culture platform for the one-pot production of rainbow-colored bacterial cellulose. The team, led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, engineered Komagataeibacter xylinus for bacterial cellulose synthesis and Escherichia coli for natural colorants overproduction. A co-culture of these engineered strains enabled the in situ coloration of bacterial cellulose. This research offers a versatile platform for producing living materials in multiple colors, and provides new opportunities for sustainable textiles, wearable biomaterials, and functional living materials that combine optical and structural properties beyond the reach of conventional textile technologies.