Evidence map›Paper›PMID 37963245›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Rapid and signal crowdedness-robust in situ sequencing through hybrid block coding.

Tianyi Chang, Wuji Han, Mengcheng Jiang, Jizhou Li, Zhizhao Liao, Mingchuan Tang, Jianyun Zhang, Jie Shen, Zitian Chen, Peng Fei and 5 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. A Guide for Spatial Omics Technologies: Innovation, Evaluation, and Application.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  2. Applications and development of in situ nucleic acid visualization techniques.Frontiers in bioengineering and biotechnology · 2026
    Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Review
4 · The record

Corrections and comments

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

15 authors.

Tianyi Chang *Biomedical Pioneering Innovation Center, Peking University, Beijing 100871, China.ORCID 0009-0000-3943-6192
Wuji Han *Biomedical Pioneering Innovation Center, Peking University, Beijing 100871, China.ORCID 0009-0002-3949-3343
Mengcheng Jiang *Biomedical Pioneering Innovation Center, Peking University, Beijing 100871, China.
Jizhou Li *School of Life Sciences, Tsinghua University, Beijing 100084, China.ORCID 0000-0003-1226-1067
Zhizhao LiaoAcademy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
Mingchuan TangBiomedical Pioneering Innovation Center, Peking University, Beijing 100871, China.ORCID 0009-0000-2245-6947
Jianyun ZhangDepartment of Oral Pathology, Peking University School and Hospital of Stomatology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing 100081, China.
Jie ShenSchool of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Capital Medical University, Beijing 100069, China.
Zitian ChenBiomedical Pioneering Innovation Center, Peking University, Beijing 100871, China.
Peng FeiSchool of Optical and Electronic Information - Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China.
Xianwen RenChangping Laboratory, Changping District, Beijing 102206, China.ORCID 0000-0002-8558-5401
Yuhong PangBiomedical Pioneering Innovation Center, Peking University, Beijing 100871, China.
Guanbo WangBiomedical Pioneering Innovation Center, Peking University, Beijing 100871, China.ORCID 0000-0002-5468-8993
Jianbin WangSchool of Life Sciences, Tsinghua University, Beijing 100084, China.ORCID 0000-0001-6725-7925
Yanyi HuangBiomedical Pioneering Innovation Center, Peking University, Beijing 100871, China.

Funding

Beijing Advanced Innovation Center for Genomics NaNBeijing Municipal Science and Technology Commission Grant Z211100003321006National Natural Science Foundation of China Grant 21927802National Natural Science Foundation of China Grant 22050002National Natural Science Foundation of China Grant T2188102
6 · The paper itself

Abstract

Spatial transcriptomics technology has revolutionized our understanding of cell types and tissue organization, opening possibilities for researchers to explore transcript distributions at subcellular levels. However, existing methods have limitations in resolution, sensitivity, or speed. To overcome these challenges, we introduce SPRINTseq (Spatially Resolved and signal-diluted Next-generation Targeted sequencing), an innovative in situ sequencing strategy that combines hybrid block coding and molecular dilution strategies. Our method enables fast and sensitive high-resolution data acquisition, as demonstrated by recovering over 142 million transcripts using a 108-gene panel from 453,843 cells from four mouse brain coronal slices in less than 2 d. Using this advanced technology, we uncover the cellular and subcellular molecular architecture of Alzheimer's disease, providing additional information into abnormal cellular behaviors and their subcellular mRNA distribution. This improved spatial transcriptomics technology holds great promise for exploring complex biological processes and disease mechanisms.

Indexed as

Gene Expression ProfilingHigh-Throughput Nucleotide SequencingAnimalsMiceRNA, MessengerTranscriptomeRNA, Messengerblock codegene expressionin situ sequencingmicrofluidics

Identifiers

PMID37963245
PMCPMC10666108

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.