Evidence map›Paper›PMID 38746456›Full record

ArticlebioRxiv : the preprint server for biology2024

Adaptive optical third-harmonic generation microscopy for in vivo imaging of tissues.

Cristina Rodríguez, Daisong Pan, Ryan G Natan, Manuel A Mohr, Max Miao, Xiaoke Chen, Trent R Northen, John P Vogel, Na Ji

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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
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.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Cristina RodríguezDepartment of Physics, University of California, Berkeley, CA, USA.ORCID 0000-0002-5525-3174
Daisong PanDepartment of Physics, University of California, Berkeley, CA, USA.ORCID 0000-0002-2367-437X
Ryan G NatanDepartment of Physics, University of California, Berkeley, CA, USA.
Manuel A MohrDepartment of Biology, Stanford University, Stanford, CA, USA.ORCID 0000-0002-5189-541X
Max MiaoEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Xiaoke ChenDepartment of Biology, Stanford University, Stanford, CA, USA.
Trent R NorthenEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
John P VogelEnvironmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Na JiDepartment of Physics, University of California, Berkeley, CA, USA.

Funding

Adaptive optical microscopy for high-accuracy recording of neural activity in vivoU01NS118300 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI JI, NA · 2021 to 2023
$1.7M
NINDS NIH HHS U01 NS118300
6 · The paper itself

Abstract

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plant

Identifiers

PMID38746456
PMCPMC11092640

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.