Evidence map›Paper›PMID 35907928›Full record

ArticleScientific reports2022

Intravital 3D visualization and segmentation of murine neural networks at micron resolution.

Ziv Lautman, Yonatan Winetraub, Eran Blacher, Caroline Yu, Itamar Terem, Adelaida Chibukhchyan, James H Marshel, Adam de la Zerda

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 53% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

8 authors at 2 institutions in 2 countries.

Ziv Lautman *Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Yonatan Winetraub *Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Eran Blacher *Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA, 94305, USA.
Caroline YuDepartment of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Itamar TeremDepartment of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Adelaida ChibukhchyanDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
James H MarshelCNC Department, Stanford University, Stanford, CA, 94305, USA.
Adam de la ZerdaDepartment of Structural Biology, Stanford University School of Medicine, Stanford, CA, 94305, USA. adlz@stanford.edu.
Stanford Medicine · USStanford University · US

Funding

Pilot ProjectsU54CA151459 · NCI · STANFORD UNIVERSITY · PI GAMBHIR, SANJIV S · 2010 to 2014
$12.6M
Molecular Imaging of Protein Glycosylation in Living SubjectsDP5OD012179 · OD · STANFORD UNIVERSITY · PI DE LA ZERDA, ADAM · 2012 to 2016
$2.0M
OCT as a Platform for Non-Invasive Virtual H&E BiopsyDP5OD031858 · OD · STANFORD UNIVERSITY · PI WINETRAUB, YONATAN · 2021 to 2025
$1.9M
Repurposing systemic therapies to improve clinical outcomes in advanced basal cell cancerK23CA211793 · NCI · STANFORD UNIVERSITY · PI SARIN, KAVITA YANG · 2018 to 2022
$868k
NCI NIH HHS K23 CA211793NCI NIH HHS U54 CA151459NIH HHS DP5 OD012179NIH HHS DP5 OD031858
6 · The paper itself

Abstract

Optical coherence tomography (OCT) allows label-free, micron-scale 3D imaging of biological tissues' fine structures with significant depth and large field-of-view. Here we introduce a novel OCT-based neuroimaging setting, accompanied by a feature segmentation algorithm, which enables rapid, accurate, and high-resolution in vivo imaging of 700 μm depth across the mouse cortex. Using a commercial OCT device, we demonstrate 3D reconstruction of microarchitectural elements through a cortical column. Our system is sensitive to structural and cellular changes at micron-scale resolution in vivo, such as those from injury or disease. Therefore, it can serve as a tool to visualize and quantify spatiotemporal brain elasticity patterns. This highly transformative and versatile platform allows accurate investigation of brain cellular architectural changes by quantifying features such as brain cell bodies' density, volume, and average distance to the nearest cell. Hence, it may assist in longitudinal studies of microstructural tissue alteration in aging, injury, or disease in a living rodent brain.

Indexed as

Imaging, Three-DimensionalTomography, Optical CoherenceAlgorithmsAnimalsMiceNeural Networks, ComputerNeuroimaging

Identifiers

PMID35907928
PMCPMC9338956
OpenAlexW4288758259

What OpenQuestion 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 OpenQuestion graph.