Evidence map›Paper›PMID 33692351›Full record

ArticleNature communications2021

Whole-brain tissue mapping toolkit using large-scale highly multiplexed immunofluorescence imaging and deep neural networks.

Dragan Maric, Jahandar Jahanipour, Xiaoyang Rebecca Li, Aditi Singh, Aryan Mobiny, Hien Van Nguyen, Andrea Sedlock, Kedar Grama, Badrinath Roysam

Abstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing 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

56 citing papers in PubMed.

  1. Article
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  7. Chemoarchitectural studies of the rat hypothalamus and zona incerta.bioRxiv : the preprint server for biology · 2025
    Article
  8. Review
  9. Article
  10. Mass Spectrometry Imaging.Analytical chemistry · 2025
    Review
  11. Article
  12. Article
  13. Article
  14. Characterization of theFASEB bioAdvances · 2025
    Article
  15. Article
  16. Article
  17. Laser capture microdissection.Nature reviews. Methods primers · 2025
    Article
  18. Article
  19. Article
  20. 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

9 authors.

Dragan Maric *National Institute of Neurological Disorders and Stroke, Bethesda, MD, 20892, USA. maricd@ninds.nih.gov.ORCID 0000-0003-2912-7921
Jahandar Jahanipour *National Institute of Neurological Disorders and Stroke, Bethesda, MD, 20892, USA.ORCID 0000-0001-5178-1124
Xiaoyang Rebecca LiCullen College of Engineering, University of Houston, Houston, TX, 77204, USA.
Aditi SinghCullen College of Engineering, University of Houston, Houston, TX, 77204, USA.ORCID 0000-0002-0782-3371
Aryan MobinyCullen College of Engineering, University of Houston, Houston, TX, 77204, USA.
Hien Van NguyenCullen College of Engineering, University of Houston, Houston, TX, 77204, USA.
Andrea SedlockNational Institute of Neurological Disorders and Stroke, Bethesda, MD, 20892, USA.
Kedar GramaCullen College of Engineering, University of Houston, Houston, TX, 77204, USA.ORCID 0000-0003-1518-276X
Badrinath RoysamCullen College of Engineering, University of Houston, Houston, TX, 77204, USA. broysam@uh.edu.ORCID 0000-0002-8310-1389

Funding

Comprehensive Quantitative Profiling of Cellular Alterations Caused by InjuryR01NS109118 · NINDS · UNIVERSITY OF HOUSTON · PI DASH, PRAMOD K, REDELL, JOHN B · 2019 to 2023
$3.2M
NINDS NIH HHS R01 NS109118
6 · The paper itself

Abstract

Mapping biological processes in brain tissues requires piecing together numerous histological observations of multiple tissue samples. We present a direct method that generates readouts for a comprehensive panel of biomarkers from serial whole-brain slices, characterizing all major brain cell types, at scales ranging from subcellular compartments, individual cells, local multi-cellular niches, to whole-brain regions from each slice. We use iterative cycles of optimized 10-plex immunostaining with 10-color epifluorescence imaging to accumulate highly enriched image datasets from individual whole-brain slices, from which seamless signal-corrected mosaics are reconstructed. Specific fluorescent signals of interest are isolated computationally, rejecting autofluorescence, imaging noise, cross-channel bleed-through, and cross-labeling. Reliable large-scale cell detection and segmentation are achieved using deep neural networks. Cell phenotyping is performed by analyzing unique biomarker combinations over appropriate subcellular compartments. This approach can accelerate pre-clinical drug evaluation and system-level brain histology studies by simultaneously profiling multiple biological processes in their native anatomical context.

Indexed as

BrainBrain MappingHumansImage Processing, Computer-AssistedNeural Networks, Computer

Identifiers

PMID33692351
PMCPMC7946933

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.