Výsledky vyhledávání

Akademický článek

A subunit vaccine based on Brucella rBP26 induces Th1 immune responses and M1 macrophage activation

Autor: Wen Jia, Li Zihua, Lv Yongxue, Ding Shuqin, Zhu Yazhou, Yang Jihui, Tang Jing, Zhu Mingxing, Zhao Yinqi, Zhao Wei

Publikováno v: Acta Biochimica et Biophysica Sinica, Vol 56, Pp 879-891 (2024)

Brucellosis is a global zoonotic infection caused by Brucella bacteria, which poses a significant burden on society. While transmission prevention is currently the most effective method, the absence of a licenced vaccine for humans necessitates the u

Externí odkaz: https://doaj.org/article/fab1ecc0528d4d11957c513f5d9cab5c

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Akademický článek

Immunoprotective effect and mechanism of rEg.P29 against CD4+ T cell-deficient mice with Echinococcus multilocularis infection

Autor: Li Ming, Zhu Yazhou, Li Zihua, Song Jiahui, Zhao Wei

Publikováno v: Acta Biochimica et Biophysica Sinica, Vol 56, Pp 482-489 (2023)

Alveolar echinococcosis (AE) is a zoonotic parasitic disease caused by infection with the larval stage of Echinococcus multilocularis and a major challenge to human public health. Vaccines are the most effective way to prevent and control infectious

Externí odkaz: https://doaj.org/article/fa382514fd3a4780a019e5626be20695

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Akademický článek

Identification of a dominant murine T-cell epitope in recombinant protein P29 from Echinococcus granulosus

Autor: Lv Yongxue, Zhu Yazhou, Chang Liangliang, Yang Jihui, Zhao Yinqi, Zhao Jiaqing, Wang Yana, Zhu Mingxing, Wu Changyou, Zhao Wei

Publikováno v: Acta Biochimica et Biophysica Sinica, Vol 54, Pp 482-493 (2022)

Echinococcus granulosus causes echinococcosis, an important zoonotic disease worldwide and a major public health issue. Vaccination is an economical and practical approach for controlling E. granulosus. We have previously revealed that a recombinant

Externí odkaz: https://doaj.org/article/86814030b0424f30904b613ebd16ad30

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RobustEMD: Domain Robust Matching for Cross-domain Few-shot Medical Image Segmentation

Autor: Zhu, Yazhou, Li, Minxian, Ye, Qiaolin, Wang, Shidong, Xin, Tong, Zhang, Haofeng

Few-shot medical image segmentation (FSMIS) aims to perform the limited annotated data learning in the medical image analysis scope. Despite the progress has been achieved, current FSMIS models are all trained and deployed on the same data domain, as

Externí odkaz: http://arxiv.org/abs/2410.01110

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Partition-A-Medical-Image: Extracting Multiple Representative Sub-regions for Few-shot Medical Image Segmentation

Autor: Zhu, Yazhou, Wang, Shidong, Xin, Tong, Zhang, Zheng, Zhang, Haofeng

Few-shot Medical Image Segmentation (FSMIS) is a more promising solution for medical image segmentation tasks where high-quality annotations are naturally scarce. However, current mainstream methods primarily focus on extracting holistic representati

Externí odkaz: http://arxiv.org/abs/2309.11172

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Few-Shot Medical Image Segmentation via a Region-enhanced Prototypical Transformer

Autor: Zhu, Yazhou, Wang, Shidong, Xin, Tong, Zhang, Haofeng

Automated segmentation of large volumes of medical images is often plagued by the limited availability of fully annotated data and the diversity of organ surface properties resulting from the use of different acquisition protocols for different patie

Externí odkaz: http://arxiv.org/abs/2309.04825

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