Evidence map›Paper›PMID 37592342›Full record

ReviewMilitary Medical Research2023

Spatial transcriptomics: recent developments and insights in respiratory research.

Wen-Jia Wang, Liu-Xi Chu, Li-Yong He, Ming-Jing Zhang, Kai-Tong Dang, Chen Gao, Qin-Yu Ge, Zhou-Guang Wang, Xiang-Wei Zhao

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Military Medical Research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
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  7. Gene Editing for Enhanced Swine Production: Current Advances and Prospects.Animals : an open access journal from MDPI · 2025
    Review
  8. Review
  9. Review
  10. Review
  11. Review
  12. Article
  13. Review
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  15. Article
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  18. Single-Nucleus RNA-Seq: Open the Era of Great Navigation for FFPE Tissue.International journal of molecular sciences · 2023
    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

9 authors.

Wen-Jia Wang *State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Liu-Xi Chu *State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Li-Yong HeState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Ming-Jing ZhangOrthopaedic Bioengineering Research Group, Division of Surgery and Interventional Science, University College London, London, HA7 4LP, UK.
Kai-Tong DangState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Chen GaoState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Qin-Yu GeState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China.
Zhou-Guang WangOujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China. wangzhouguang@wmu.edu.cn.
Xiang-Wei ZhaoState Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China. xwzhao@seu.edu.cn.ORCID http://orcid.org/0000-0003-0678-5219

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The respiratory system's complex cellular heterogeneity presents unique challenges to researchers in this field. Although bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) have provided insights into cell types and heterogeneity in the respiratory system, the relevant specific spatial localization and cellular interactions have not been clearly elucidated. Spatial transcriptomics (ST) has filled this gap and has been widely used in respiratory studies. This review focuses on the latest iterative technology of ST in recent years, summarizing how ST can be applied to the physiological and pathological processes of the respiratory system, with emphasis on the lungs. Finally, the current challenges and potential development directions are proposed, including high-throughput full-length transcriptome, integration of multi-omics, temporal and spatial omics, bioinformatics analysis, etc. These viewpoints are expected to advance the study of systematic mechanisms, including respiratory studies.

Indexed as

Gene Expression ProfilingTranscriptomeComputational BiologyHumansMultiomicsLungSpatial multi-omicsSpatial transcriptomicsTumor

Identifiers

PMID37592342
PMCPMC10433685

What OpenQuestion holds

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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.