Evidence map›Paper›PMID 36737476›Full record

ArticleCommunications biology2023

Three-dimensional mapping in multi-samples with large-scale imaging and multiplexed post staining.

Siqi Chen, Guangcai Liu, Anan Li, Zhixiang Liu, Ben Long, Xiaoquan Yang, Hui Gong, Xiangning Li

Abstract read
In one paragraph

Article in Communications biology, 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.

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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

8 authors.

Siqi Chen *Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.ORCID 0000-0001-5705-5983
Guangcai Liu *Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.ORCID 0000-0002-1028-2852
Anan LiBritton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.ORCID 0000-0002-5877-4813
Zhixiang LiuBritton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.ORCID 0000-0003-2101-4965
Ben LongKey Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, 570228, China.ORCID 0000-0001-9681-1104
Xiaoquan YangBritton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China. xqyang@mail.hust.edu.cn.
Hui GongBritton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China. huigong@mail.hust.edu.cn.ORCID 0000-0001-5519-6248
Xiangning LiBritton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China. lixiangning@mail.hust.edu.cn.ORCID 0000-0002-3747-2824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dissection of the anatomical information at the single-cell level is crucial for understanding the organization rule and pathological mechanism of biological tissues. Mapping the whole organ in numerous groups with multiple conditions brings the challenges in imaging and analysis. Here, we describe an approach, named array fluorescent micro-optical sectioning tomography (array-fMOST), to identify the three-dimensional information at single-cell resolution from multi-samples. The pipeline contains array embedding, large-scale imaging, post-imaging staining and data analysis, which could image over 24 mouse brains simultaneously and collect the slices for further analysis. With transgenic mice, we acquired the distribution information of neuropeptide somatostatin neurons during natural aging and compared the changes in the microenvironments by multi-component labeling of serial sections with precise co-registration of serial datasets quantitatively. With viral labeling, we also analyzed the input circuits of the medial prefrontal cortex in the whole brain of Alzheimer's disease and autism model mice. This pipeline is highly scalable to be applied to anatomical alterations screening and identification. It provides new opportunities for combining multi-sample whole-organ imaging and molecular phenotypes identification analysis together. Such integrated high-dimensional information acquisition method may accelerate our understanding of pathogenesis and progression of disease in situ at multiple levels.

Indexed as

BrainImaging, Three-DimensionalAnimalsMiceMice, TransgenicNeuronsStaining and Labeling

Identifiers

PMID36737476
PMCPMC9898531

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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.