聊聊Sci
淼淼Elva聊聊Science和Nature！
| Publishes | Daily | Episodes | 161 | Founded | 4 months ago |
|---|---|---|---|---|---|
| Language |  Vietnamese | Category | Science | ||
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这篇来自诺奖得主David Baker组最新的Science研究论文介绍了预测人类蛋白质-蛋白质相互作用（PPI）的系统性方法，旨在克服现有实验和计算方法的局限性。研究人员通过两个关键创新显著提高了预测精度和效率：首先，他们利用7倍更深的多序列比对（MSAs），直接从大量未组装的真核基因组数据中获取更强的共进化信号，创建了omicMSA。其次，他们开发了一种名为RoseTTAFold2-PPI (RF2-PPI)的快速深度学习网络，该网络利用从AlphaFold数据库中提取的结构域-结构域相互作... more
这篇文章报告了一项多组学研究，旨在找出导致非小细胞肺癌患者对免疫检查点抑制剂联合化疗产生抵抗的因素。通过分析大量的单细胞转录组和空间转录组数据，研究人员在肿瘤微环境中发现了胶原蛋白XI α 1链阳性（COL11A1+）癌症相关成纤维细胞和分泌型磷蛋白1阳性（SPP1+）巨噬细胞之间的相互作用。这种相互作用会导致肿瘤边界胶原纤维沉积，从而阻碍T细胞浸润，预示着较差的预后。此外，研究还揭示了三级淋巴结构（TLSs）的不同成熟阶段，其中激活的TLSs与改善预后相关，而缺氧环境则可能抑制TLSs的发展并... more
这篇文章详细介绍了一种名为 TORCH 的深度学习模型，该模型旨在使用细胞学图像来 预测原发灶不明癌症 (CUP) 的肿瘤来源，特别是在胸腔积液和腹水病例中。研究人员使用来自四个医院的 57,220 例数据集开发并测试了TORCH，结果显示其在 癌症诊断和肿瘤定位 方面表现出 高准确性 和强大的泛化能力。值得注意的是，TORCH 的预测效果 优于病理学家，并且在辅助初级病理学家诊断时能 显著提高他们的准确率。此外，该研究还发现，根据 TORCH 预测结果进行治疗的 CUP 患者的 总体生存期更长... more
这篇文章介绍了名为 TOOLUNIVERSE 的创新生态系统，旨在通过提供一个统一的工具和数据分析共享环境来实现人工智能科学家的自主化。这个开源平台将大型语言模型（LLMs）、代理和推理模型与 600 多种科学工具、数据集和 API 相结合，以便构建定制的 AI 科学家。TOOLUNIVERSE 通过其 AI-工具交互协议标准化了工具的识别和调用，并提供了工具发现、创建、优化和组合等核心组件，从而支持端到端的研究工作流。一个针对高胆固醇血症的案例研究表明，TOOLUNIVERSE 能够筛选和优化... more
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聊聊Sci launched 4 months ago and published 161 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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