Efficiently capturing multi-scale local information and building long-range dependencies among pixels are essential for medical image segmentation because of the various sizes and shapes of the lesion regions or organs. In this paper, researchers propose the multi-scale cross-axis attention (MCA) mechanism to address these challenges through enhanced axial attention. To address the issues of insufficient learning of positional bias and limited long-distance interaction in axial attention caused by the small dataset, researchers propose using a dual cross-attention mechanism instead of axial attention to enhance global information capture. Meanwhile, to compensate for the lack of explicit attention to local information in axial attention, researchers use multiple convolutions of strip-shaped kernels with different kernel sizes in each axial attention path, which improves the efficiency of MCA in local information encoding. By integrating MCA into the multi-scale cross-axis attention network (MSCAN) backbone, researchers develop their network architecture, termed MCANet. With merely 4 M+ parameters, MCANet outperforms previous heavyweight approaches (e.g., swin transformer-based methods) across four challenging tasks: skin lesion segmentation, nuclei segmentation, abdominal multi-organ segmentation, and polyp segmentation. The code is available at https://github.com/haoshao-nku/medical_seg. 

Researchers at Kumamoto University have uncovered a previously unknown molecular mechanism by which human T-cell leukemia virus type I (HTLV-1) drives the development of adult T-cell leukemia-lymphoma (ATL), one of the most aggressive and difficult-to-treat blood cancers. The findings provide critical insight into why only a small fraction of HTLV-1 carriers develop leukemia—and point toward new strategies for targeted therapy.

Geothermal energy is clean and renewable, derived from the heat stored within accessible depths of the Earth’s crust. The adoption of a single-well system for medium-deep and deep geothermal energy extraction has attracted significant interest from the scientific and industrial communities because it effectively circumvents issues such as downhole inter-well connections and induced seismicity. However, the low heat transfer capacity in geothermal formations limits the heat extraction performance of single-well systems and hinders their commercial deployment. This review covers various enhancement concepts for optimizing the heat transfer within single-well systems, emphasizing critical parameters such as heat transfer area, heat transfer coefficient, and temperature difference. Additionally, it presents the thermo-economic evaluation of different configurations of single-well borehole heat exchangers and superlong gravity heat pipes (SLGHPs). The SLHGP, utilizing phase-change heat transfer, is recognized as a highly effective and continuously productive technology, capable of extracting over 1 MW of heat. Its pumpless operation and ease of installation in abandoned wells make it cost-effective, offering a promising economic advantage over traditional geothermal systems. It also highlights the challenges and potential research opportunities that can help identify gaps in research to enhance the performance of single-well geothermal systems.