Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
12 authors.
Lei Tang *State Key Laboratory of Membrane Biology, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0009-0000-8617-9889
Kang Tian *State Key Laboratory of Membrane Biology, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China. tiankang@mail.tsinghua.edu.cn.ORCID http://orcid.org/0009-0008-7493-2640
Xiaolei Fu *State Key Laboratory of Membrane Biology, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0009-0001-4303-3967
Yingjia Xu *State Key Laboratory of Membrane Biology, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0009-0004-6002-2225
Jincheng WuState Key Laboratory of Molecular Oncology, MOE Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, China.
Jinsong ZhangState Key Laboratory of Membrane Biology, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China.ORCID http://orcid.org/0000-0002-1949-2979
Xi-Wen WangState Key Laboratory of Membrane Biology, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China.
Chunxiang YeDepartment of General Surgery, Beijing Chao-Yang Hospital, Capital Medical University, No. 8 Gongtinan Road, Chaoyang District, Beijing, China.
Qiong WuState Key Laboratory of Molecular Oncology, MOE Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, China.
Wei WuState Key Laboratory of Molecular Oncology, MOE Key Laboratory of Protein Science, Beijing Advanced Innovation Center for Structural Biology, School of Life Sciences, Tsinghua University, Beijing, China. wwu@mail.tsinghua.edu.cn.ORCID http://orcid.org/0009-0004-9304-3671
Changjiang FengDepartment of Thoracic Surgery, the First Medical Center, Beijing 301 Hospital, Beijing, China. fengcj301@163.com.ORCID http://orcid.org/0009-0006-5407-842X
Qiangfeng Cliff ZhangState Key Laboratory of Membrane Biology, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing, China. qczhang@tsinghua.edu.cn.ORCID http://orcid.org/0000-0002-4913-0338
Funding
National Natural Science Foundation of China (National Science Foundation of China) 32125007National Natural Science Foundation of China (National Science Foundation of China) 32230018
6 · The paper itself
Abstract
Cells in complex organisms function through extensive interactions, yet mapping these interaction networks at scale remains challenging. Here we present CCI-seq, a high-throughput method to unbiasedly capture cell-cell interactions across a proximity continuum by combining cell clump combinatorial indexing with single-cell sequencing. CCI-seq identified known interactions and fine-grained cellular organization in mouse kidney and intestine, and uncovered aberrant interactions and disrupted spatial organization in adenomatous polyposis coli knockout (Apc-KO) intestines. Applied to human colorectal cancer, it revealed subtype-specific interactions linked to clinical classifications. By leveraging a single-cell RNA sequencing backbone, CCI-seq achieves deep transcriptome coverage, enabling analysis of molecular states arising from interactions. This functional resolution revealed that interacting cells associate with distinct transcriptional programs-driving ion transport in kidney, antigen presentation in Apc-KO villi and NF-κB inflammatory activation in colorectal cancer. Thus, CCI-seq provides a scalable platform to unveil large-scale cell-cell interaction networks and dissect their molecular and functional impacts, enhancing our understanding of complex multicellular systems.
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.
Resolving cell-cell interaction networks and their molecular logic in complex tissues. · full record | Socratic