Evidence map›Paper›PMID 37010695›Full record

ArticlePhotochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology2023

In vivo near-infrared fluorescence imaging of gastric cancer in an MKN-45 gastric cancer xenograft mouse model using intraoperative ureteral identification agent ASP5354.

Katsunori Teranishi

Abstract read
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In one paragraph

Article in Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.8field-weighted citation impact, top 33% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Katsunori TeranishiGraduate School of Bioresources, Mie University, 1577 Kurimamachiya, Tsu, Mie, 514-8507, Japan. teranisi@bio.mie-u.ac.jp.ORCID http://orcid.org/0000-0002-2607-7976
Mie University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accurate intraoperative identification of gastric cancer lesions and determination of the extent of resection are important for curability and function preservation. This study aimed to investigate the potential of the near-infrared fluorescence (NIRF) imaging agent ASP5354 for in vivo fluorescence imaging of gastric cancer. The capability of ASP5354 was evaluated using an MKN-45 human gastric cancer xenograft mouse model. A single dose of ASP5354 was intravenously administered to the mice at a concentration of 120 nmol (0.37 mg)/kg body weight. In vivo NIRF images of the mouse backs were obtained using an NIRF camera system. Moreover, the cancer tissues were dissected, and the NIRF intensity in the tissue sections was measured using the NIRF camera system. ASP5354 uptake in MKN-45 cells was assessed in vitro using the NIRF microscope. The NIRF signal of ASP5354 was selectively detected in gastric cancer tissues immediately after the intravenous administration of ASP5354. The cancer tissues emitted stronger NIRF signals than adjacent normal tissues. The difference in the NIRF intensity between the normal and cancer tissues was clearly observed at the boundary between them in the macrolevel NIRF images. Cancer tissues can be distinguished from normal tissues based on the measurement of the NIRF of ASP5354, using an NIRF camera system. ASP5354 is a promising agent for NIRF imaging of gastric cancer tissues.

Indexed as

Stomach NeoplasmsAnimalsDisease Models, AnimalHeterograftsHumansMiceOptical ImagingASP5354DiagnosisGastric cancerImagingNear-infrared fluorescence

Identifiers

PMID37010695
OpenAlexW4362506631

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.