Evidence map›Paper›PMID 30168296›Full record

ArticleJournal of biophotonics2019

Optical sensory arrays for the detection of urinary bladder cancer-related volatile organic compounds.

Simian Zhu, Stella Corsetti, Qifan Wang, Chunhui Li, Zhihong Huang, Ghulam Nabi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of biophotonics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

6 authors.

Simian ZhuCancer Research Division, School of Medicine, University of Dundee, Dundee, UK.
Stella CorsettiSchool of Life Sciences, University of Dundee, Dundee, UK.
Qifan WangMechanical and Electronic Engineering, School of Science and Engineering, University of Dundee, Dundee, UK.
Chunhui LiMechanical and Electronic Engineering, School of Science and Engineering, University of Dundee, Dundee, UK.
Zhihong HuangMechanical and Electronic Engineering, School of Science and Engineering, University of Dundee, Dundee, UK.
Ghulam NabiCancer Research Division, School of Medicine, University of Dundee, Dundee, UK.ORCID 0000-0001-9406-5195

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-invasive detection of urinary bladder cancer remains a significant challenge. Urinary volatile organic compounds (VOCs) are a promising alternative to cell-based biomarkers. Herein, we demonstrate a novel diagnosis system based on an optic fluorescence sensor array for detecting urinary bladder cancer VOCs biomarkers. This study describes a fluorescence-based VOCs sensor array detecting system in detail. The choice of VOCs for the initial part was based on an extensive systematic search of the literature and then followed up using urinary samples from patients with urinary bladder transitional cell carcinoma. Canonical discriminant analysis and partial least squares discriminant analysis (PLS-DA) were employed and correctly detected 31/48 urinary bladder cancer VOC biomarkers and achieved an overall 77.75% sensitivity and 93.25% specificity by PLS-DA modelling. All five urine samples from bladder cancer patients, and five healthy controls were successfully identified with the same sensor arrays. Overall, the experiments in this study describe a real-time platform for non-invasive bladder cancer diagnosis using fluorescence-based gas-sensor arrays. Pure VOCs and urine samples from the patients proved such a system to be promising; however, further research is required using a larger population sample.

Indexed as

Optical DevicesBiomarkersHumansPoint-of-Care SystemsSpectrometry, FluorescenceUrinary Bladder NeoplasmsVolatile Organic CompoundsBiomarkersVolatile Organic Compoundsbladder cancerfluorescence gas-sensory arraysurinary volatile organic compounds

Identifiers

PMID30168296
PMCPMC7065633

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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.