Evidence map›Paper›PMID 26353981›Full record

ArticleScientific reports2015

Direct label-free measurement of the distribution of small molecular weight compound inside thick biological tissue using coherent Raman microspectroscopy.

Masahiko Kawagishi, Yuki Obara, Takayuki Suzuki, Masumi Hayashi, Kazuhiko Misawa, Sumio Terada

Abstract read
In one paragraph

Article in Scientific reports, 2015. 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

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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

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

6 authors.

Masahiko KawagishiDepartment of Neuroanatomy and Cellular Neurobiology, &Center for Brain Integration Research, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.
Yuki ObaraDepartment of Applied Physics, Tokyo University of Agriculture and Technology (TUAT), Koganei, Japan.
Takayuki SuzukiDepartment of Applied Physics, Tokyo University of Agriculture and Technology (TUAT), Koganei, Japan.
Masumi HayashiWired Co., Ltd., Komae, Japan.
Kazuhiko MisawaDepartment of Applied Physics, Tokyo University of Agriculture and Technology (TUAT), Koganei, Japan.
Sumio TeradaDepartment of Neuroanatomy and Cellular Neurobiology, &Center for Brain Integration Research, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Distributions of small molecular weight (less than 300 Da) compounds inside biological tissue have been obscure because of the lack of appropriate methods to measure them. Although fluorescence techniques are widely used to characterise the localisation of large biomolecules, they cannot be easily applied to the cases with small molecule compounds. We used CARS spectroscopy to detect and identify a label-free small molecule compound. To facilitate detection in aqueous environment, we utilised time-resolved and phase-sensitive techniques to reduce non-resonant background generated from water. We applied this technique to detect small molecular weight compound, taurine, inside mouse cornea tissue immersed in taurine solution as an initial model experiment. We detected a Raman peak of taurine near wavenumber 1033 cm(-1) inside cornea and successfully characterised its depth profile in the tissue. Our CARS spectra measurement can be a promising method to measure and visualise the distribution of small bio-related compounds in biological background without using any labeling, paving the way for new cell biological analysis in various disciplines.

Indexed as

Spectrum Analysis, RamanTissue DistributionAnimalsAqueous HumorCorneaMiceMolecular WeightSpectroscopy, Fourier Transform InfraredTaurineTime FactorsTaurine

Identifiers

PMID26353981
PMCPMC4564726

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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.