Evidence map›Paper›PMID 40659497›Full record

ArticleGenome research2025

A novel multislice framework for precision 3D spatial domain reconstruction and disease pathology analysis.

Daijun Zhang, Ren Qi, Xun Lan, Bin Liu

Abstract read
In one paragraph

Article in Genome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  9. [Management and consideration of positive surgical margins in locally advanced oropharyngeal squamous cell carcinoma treated with oral robotic surgery].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2025
    Article
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

4 authors.

Daijun ZhangSchool of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.
Ren QiSchool of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China.
Xun LanSchool of Medicine, Tsinghua University, Beijing 100084, China.
Bin LiuSchool of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China; bliu@bliulab.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of spatial transcriptomics (ST) technologies has revolutionized the way we map the complex organization and functions of tissues. These technologies offer valuable insights into the organization and function of complex biological systems. However, existing methods often focus too narrowly on single modalities or resolutions, thereby hindering the comprehensive capture of multilayered biological heterogeneity. Here, STMSC is proposed as a multislice joint analysis framework featuring a precorrection mechanism that enables the precise identification of complex spatial domains, advancing disease pathology insights. STMSC assumes that precise three-dimensional (3D) reconstruction is essential for an in-depth investigation of tissue components and mechanisms. Incorporating hematoxylin and eosin (H&E) imaging data, STMSC enhances slice alignment accuracy in 3D reconstruction. By deconstructing microenvironments, it reconstructs fine-grained cellular landscapes and emphasizes collective cellular behavior in defining spatial domains. Its graph attention autoencoder with precorrection balances biological information at different levels, improving the accuracy of ST analyses. By analyzing consecutive tissue slices and pathological data sets, STMSC accurately reconstructs 3D structures and provides deeper insights into complex cancer environments. Specifically, STMSC captures intra- and interstage heterogeneity in cancer development, offering novel insights into the complexity of pathological tissue structures.

Indexed as

Imaging, Three-DimensionalNeoplasmsHumansTumor Microenvironment

Identifiers

PMID40659497
PMCPMC12315711

What OpenQuestion holds

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Registered trials

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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.