Evidence map›Paper›PMID 35661092›Full record

ArticleJournal of visualized experiments : JoVE2022

Label-free Super-resolution Imaging Enabled by Vibrational Imaging of Swelled Tissue and Analysis.

Kun Miao, Li-En Lin, Chenxi Qian, Lu Wei

Open access · greenAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Coherent Raman Microscopy: from instrumentation to applications.Journal of visualized experiments : JoVE · 2023
    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

4 authors at 2 institutions in 1 country.

Kun MiaoDivision of Chemistry and Chemical Engineering, California Institute of Technology.
Li-En LinDivision of Chemistry and Chemical Engineering, California Institute of Technology.
Chenxi QianDivision of Chemistry and Chemical Engineering, California Institute of Technology.
Lu WeiDivision of Chemistry and Chemical Engineering, California Institute of Technology; lwei@caltech.edu.
California Institute of Technology · USDivision of Chemistry · US

Funding

Super-resolution Chemical Imaging for BiomedicineDP2GM140919 · NIGMS · CALIFORNIA INSTITUTE OF TECHNOLOGY · PI WEI, LU · 2020 to 2020
$2.3M
NIGMS NIH HHS DP2 GM140919
6 · The paper itself

Abstract

The universal utilization of fluorescence microscopy, especially super-resolution microscopy, has greatly advanced knowledge about modern biology. Conversely, the requirement of fluorophore labeling in fluorescent techniques poses significant challenges, such as photobleaching and non-uniform labeling of fluorescent probes and prolonged sample processing. In this protocol, the detailed working procedures of vibrational imaging of swelled tissue and analysis (VISTA) are presented. VISTA circumvents obstacles associated with fluorophores and achieves label-free super-resolution volumetric imaging in biological samples with spatial resolution down to 78 nm. The procedure is established by embedding cells and tissues in hydrogel, isotropically expanding the hydrogel sample hybrid, and visualizing endogenous protein distributions by vibrational imaging with stimulated Raman scattering microscopy. The method is demonstrated on both cells and mouse brain tissues. Highly correlative VISTA and immunofluorescence images were observed, validating the protein origin of imaging specificities. Exploiting such correlation, a machine learning-based image-segmentation algorithm was trained to achieve multi-component prediction of nuclei, blood vessels, neuronal cells, and dendrites from label-free mouse brain images. The procedure was further adapted to investigate pathological poly-glutamine (polyQ) aggregates in cells and amyloid-beta (Aβ) plaques in brain tissues with high throughput, justifying its potential for large-scale clinical samples.

Indexed as

Amyloid beta-PeptidesPlaque, AmyloidAnimalsFluorescent DyesHydrogelsImage Processing, Computer-AssistedMiceMicroscopy, FluorescenceAmyloid beta-PeptidesFluorescent DyesHydrogels

Identifiers

PMID35661092
PMCPMC9549918
OpenAlexW4280540591

What OpenQuestion holds

Textmetadata
LicenceTDM
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.