▲ Vol 05 Issue 02 |  June, 2024

肿瘤相关三级淋巴结构在免疫治疗研究中的前沿进展

胡楚鹏, 陈云

三级淋巴结构 （TLS） 是近年来在慢性炎症刺激的非淋巴组织中发现的异位淋巴结构，与淋巴结具有相似的结构和功能，主要由B淋巴细胞、T淋巴细胞和树突状细胞组成，也是抗肿瘤免疫应答启动的直接部位。肿瘤中TLS促进免疫细胞，特别是T细胞和B细胞等效应免疫细胞，向肿瘤微环境聚集，为抗肿瘤的细胞和体液免疫应答提供一个重要的局部场所，预示患者可能有良好的生存预后和积极的免疫治疗反应。本文概述了肿瘤相关TLS的评估鉴定、结构与组成、以及形成的驱动因素，并阐述了 TLS 作为潜在生物标志物在肿瘤免疫治疗中的作用及潜在临床运用价值。此外，本文还讨论了 TLS在肿瘤免疫治疗中的挑战和未来研究方向。

http://swyxzh.ijournals.cn/swyxzh/article/abstract/20240203?st=article_issue

▲ Vol 01 Issue 02 |  June, 2024

Fueling the future: Innovating the path to carbon-neutral skies with CO2-to-aviation fuel

Guo Tian, Chenxi Zhang, Fei Wei

Considering the increasing concerns regarding climate change, a fundamental transformation in global energy policies is imperative, particularly within the aviation sector, which is historically anchored in the consumption of fossil fuels. This perspective presents a scholarly evaluation of the progression from deep-rooted fossil-fuel-dependent technologies to innovative strategies aimed at carbon neutrality, specifically focusing on the formulation of sustainable aviation fuel from CO2. An analytical review of the cutting-edge methodologies for CO2-to-jet fuel conversion is provided, and the practicality of current industrial models are assessed. This perspective explores the intricate consequences of adopting such groundbreaking technologies and evaluates their technical practicability, economic feasibility, and environmental advantages. The insights obtained from this study will substantially contribute to the discussion on energy sustainability, emphasizing the synergy between sophisticated CO2 conversion processes and the overarching goal of realizing global carbon neutrality.

https://www.sciopen.com/article/10.26599/CF.2024.9200010

▲ Vol 38 Issue 03 |  June, 2024

花岗岩红壤坡面沟头高度对沟床跌穴发育过程的影响

王建羽, 林哲, 廖达兰, 段晓倩, 邓羽松

[目的] 为明确花岗岩红壤坡面沟头溯源侵蚀的关键过程及形成机制。[方法] 通过设定5个沟头高度(25,50,75,100,125 cm)研究花岗岩红壤坡面沟床跌穴发育过程。[结果] (1)随沟头高度增加,沟床径流雷诺数、径流剪切力、径流功率和射流参数(触底流速、射流剪切应力、瞬时动能、跌穴径流能耗)均表现为增加趋势。(2)红土层沟床形成“V”形跌穴,随流量增加跌穴形态变化增大,但只形成面积较小的跌穴。而砂土层在冲刷过程中,沟床跌穴发育较为明显,当流量增大到120 L/min后,沟床破碎化程度增加,跌穴轮廓逐渐清晰,横截面积增大。(3)通过随机森林算法和沙普利值构建并表征模型各参数的关系,红土层沟床径流的弗罗德数、径流功率、水平出射动能、雷诺数与横截面积呈负相关;砂土层沟床径流的弗罗德数和跌穴径流能耗与横截面积呈负相关。沟床跌穴侵蚀程度可用随机森林算法构建模型预测(LCCC=1.02,R2adjusted=0.876和0.868)。[结论] 研究结果可为揭示沟头溯源侵蚀机理和沟蚀防治提供理论依据。

http://stbcxb.alljournal.com.cn/stbcxb/article/issue/2024_38_3

▲ Vol 15 Issue 21 | 07 June, 2024

DiffBindFR: an SE(3) equivariant network for flexible protein–ligand docking

Jintao Zhu, Zhonghui Gu, Jianfeng Pei and  Luhua Lai

[Molecular docking, a key technique in structure-based drug design, plays pivotal roles in protein–ligand interaction modeling, hit identification and optimization, in which accurate prediction of protein–ligand binding mode is essential. Conventional docking approaches perform well in redocking tasks with known protein binding pocket conformation in the complex state. However, in real-world docking scenario without knowing the protein binding conformation for a new ligand, accurately modeling the binding complex structure remains challenging as flexible docking is computationally expensive and inaccurate. Typical deep learning-based docking methods do not explicitly consider protein side chain conformations and fail to ensure the physical plausibility and detailed atomic interactions. In this study, we present DiffBindFR, a full-atom diffusion-based flexible docking model that operates over the product space of ligand overall movements and flexibility and pocket side chain torsion changes. We show that DiffBindFR has higher accuracy in producing native-like binding structures with physically plausible and detailed interactions than available docking methods. Furthermore, in the Apo and AlphaFold2 modeled structures, DiffBindFR demonstrates superior advantages in accurate ligand binding pose and protein binding conformation prediction, making it suitable for Apo and AlphaFold2 structure-based drug design. DiffBindFR provides a powerful flexible docking tool for modeling accurate protein–ligand binding structures.

https://pubs.rsc.org/en/content/articlelanding/2024/sc/d3sc06803j

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