SenNet Supplement - Consortium Benchmarking

项目摘要 本补充文件的目的是进一步推进CODCC行政核心（C小节： 行政核心：包括财团协调和推广）在两个领域：1。比较 空间转录组学和蛋白质组学技术在同一组织上的表现，以及 2.比较相同模态在不同组织上的性能。关于SenNet 该联盟正在共同开发和应用多种空间成像技术， 研究衰老组织中细胞衰老的分子和细胞异质性。 然而，该财团面临的一个主要障碍是围绕能力的不确定性， 各种技术被用来鲁棒地表征衰老细胞在不同 组织中为了应对这一挑战，SenNet联盟将开展合作努力， 为了测试各种空间组学技术在同一人体组织上的有效性， 不同的部位，以及测试它们在不同组织中的有效性。这一奋进旨在 实现几个目标：首先，确定衰老相关的鲁棒性， 基于平台的标记检测，其次，提取关于 同一组织的衰老。该联盟范围内的基准项目将侧重于 提供单细胞分辨率的空间组学技术。这种方法是基于目前 理解衰老细胞在衰老组织中以相对低的丰度存在， 需要使用能够准确检测单个衰老细胞的技术， 将它们与周围的细胞区分开来。通过严格测试high-plex的健壮性， SenNet联盟已经在多个站点和组织中使用的技术，我们 将确定哪种技术在检测衰老细胞方面最准确和信息量最大 在不同的组织中。

Project Abstract The purpose of the Supplement is to further the CODCC Administrative Core (Sub-Section C: Administrative Core: Including Consortium Coordination & Outreach) in two areas: 1. comparing the performance of spatial transcriptomics and proteomics techniques on the same tissue, and 2. comparing the performance of the same modality on different tissues. The SenNet consortium is working together to develop and apply multiple spatial imaging technologies to investigate the molecular and cellular heterogeneity of cellular senescence in aged tissues. However, one major obstacle faced by the consortium is the uncertainty surrounding the ability of the various technologies being employed to robustly characterize senescent cells in different tissues. To address this challenge, the SenNet consortium will undertake a collaborative effort to test the effectiveness of various spatial omics technologies on the same human tissue across different sites, as well as to test their effectiveness across different tissues. This endeavor aims to accomplish several goals: firstly, to determine the robustness of senescence-associated marker detection based on the platform, secondly, to extract diverse information about senescence from the same tissue. This consortium-wide benchmarking project will focus on spatial omics techniques that offer single-cell resolution. This approach is based on the current understanding that senescent cells are present in relatively low abundance in aged tissues and the need to use technologies that can accurately detect individual senescent cells and differentiate them from surrounding cells. By rigorously testing the robustness of high-plex technologies already in use within the SenNet Consortium across multiple sites and tissues, we will determine which techniques are most accurate and informative in detecting senescent cells in different tissues.