Evidence map›Paper›PMID 36768680›Full record

ArticleInternational journal of molecular sciences2023

In Vivo Optical Imaging of Bladder Cancer Tissues in an MB49 Bladder Cancer Orthotopic Mouse Model Using the Intravesical or Intravenous Administration of Near-Infrared Fluorescence Probe.

Katsunori Teranishi

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. In vivo near-infrared fluorescence imaging of gastric cancer in an MKN-45 gastric cancer xenograft mouse model using intraoperative ureteral identification agent ASP5354.Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology · 2023
    Article
  3. Article
  4. 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

1 author.

Katsunori TeranishiGraduate School of Bioresources, Mie University, 1577 Kurimamachiya, Tsu 514-8507, Japan.ORCID 0000-0002-2607-7976

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bladder cancer was the twelfth most common cancer worldwide in 2020. Although bladder cancer has been diagnosed using macroscopic techniques, such as white-light cystoscopy and fluorescence blue-light cystoscopy, there is a need to explore more effective noninvasive optical imaging techniques for accurate bladder cancer diagnosis. This study demonstrates the high effectiveness of the near-infrared fluorescence (NIRF) probe ASP5354, which has been developed for ureteral identification during in vivo diagnosis of bladder cancer in an MB49 bladder cancer orthotopic mouse model. After the intravesical injection of 2.4 μM ASP5354 followed by bladder rinsing with saline at 5 min post injection or intravenous administration of ASP5354 at 240 nmol/kg mouse body weight, followed by a waiting period of 5-24 h in mice, ASP5354 was absorbed specifically by cancerous tissue and not by normal tissues in the bladder. NIRF of ASP5354 in cancer tissues was detected using the NIRF imaging camera system. The NIRF clearly showed a boundary between cancerous and normal tissues. Therefore, ASP5354 provides noninvasive and specific optical in vivo imaging of MB49 bladder cancer using intravesical or intravenous injection of ASP5354. ASP5354 may allow for new diagnostic applications for bladder cancer in humans.

Indexed as

Urinary Bladder NeoplasmsAnimalsCell Line, TumorDisease Models, AnimalHumansInjections, IntravenousMiceOptical ImagingUrinary BladderASP5354bladder cancerdiagnosisfluorescence imagingnear-infrared fluorescence

Identifiers

PMID36768680
PMCPMC9916938

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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.