Evidence map›Paper›PMID 37239183›Full record

ArticleBrain sciences2023

A Convenient All-Cell Optical Imaging Method Compatible with Serial SEM for Brain Mapping.

Tianyi Wang, Peiyao Shi, Dingsan Luo, Jun Guo, Hui Liu, Jinyun Yuan, Haiqun Jin, Xiaolong Wu, Yueyi Zhang, Zhiwei Xiong and 3 more

Open access · goldAbstract read
In one paragraph

Article in Brain sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 94% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

13 authors at 4 institutions in 1 country.

Tianyi WangSchool of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China.
Peiyao ShiJiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
Dingsan LuoJiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
Jun GuoInstitute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
Hui LiuJiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
Jinyun YuanJiangsu Key Laboratory of Medical Optics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China.
Haiqun JinInstitute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
Xiaolong WuInstitute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
Yueyi ZhangInstitute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
Zhiwei XiongInstitute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei 230088, China.
Jinlong ZhuState Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.
Renjie ZhouDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China.
Ruobing ZhangSchool of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China.
Suzhou Institute of Biomedical Engineering and Technology · CNChinese Academy of Sciences · CNChinese University of Hong Kong · CNHuazhong University of Science and Technology · CN

Funding

Chinese Academy of Sciences Project for Young Scientists in Basic Research YSBR-067National Natural Science Foundation of China 32271430
6 · The paper itself

Abstract

The mammalian brain, with its complexity and intricacy, poses significant challenges for researchers aiming to understand its inner workings. Optical multilayer interference tomography (OMLIT) is a novel, promising imaging technique that enables the mapping and reconstruction of mesoscale all-cell brain atlases and is seamlessly compatible with tape-based serial scanning electron microscopy (SEM) for microscale mapping in the same tissue. However, currently, OMLIT suffers from imperfect coatings, leading to background noise and image contamination. In this study, we introduced a new imaging configuration using carbon spraying to eliminate the tape-coating step, resulting in reduced noise and enhanced imaging quality. We demonstrated the improved imaging quality and validated its applicability through a correlative light-electron imaging workflow. Our method successfully reconstructed all cells and vasculature within a large OMLIT dataset, enabling basic morphological classification and analysis. We also show that this approach can perform effectively on thicker sections, extending its applicability to sub-micron scale slices, saving sample preparation and imaging time, and increasing imaging throughput. Consequently, this method emerges as a promising candidate for high-speed, high-throughput brain tissue reconstruction and analysis. Our findings open new avenues for exploring the structure and function of the brain using OMLIT images.

Indexed as

brain mappingcell classificationcorrelative light and electron microscopyoptical multilayer interference tomography

Identifiers

PMID37239183
PMCPMC10216590
OpenAlexW4366829956

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.