Evidence map›Paper›PMID 39738239›Full record

ArticleScientific reports2024

Serum and plasma as a good candidates of body fluids for detection lung cancer by FTIR liquid biopsy.

Jolanta Smok-Kalwat, Stanisław Góźdź, Paweł Macek, Zuzanna Kalwat, Maryna Khalavka, Wioletta Rzad, Andrzej Stepulak, Joanna Depciuch

Abstract read
In one paragraph

Article in Scientific reports, 2024. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Review
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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

8 authors.

Jolanta Smok-KalwatDepartment of Clinical Oncology, Holy Cross Cancer Centre, 3 Artwinskiego Street, 25-734, Kielce, Poland. jolantasm@onkol.kielce.pl.
Stanisław GóźdźDepartment of Clinical Oncology, Holy Cross Cancer Centre, 3 Artwinskiego Street, 25-734, Kielce, Poland.
Paweł MacekCollegium Medicum, Jan Kochanowski University, 25-317, Kielce, Poland.
Zuzanna KalwatDepartment of Epidemiology and Cancer Control, Holy Cross Cancer Centre, S. Artwińskiego St. 3, 25-734, Kielce, Poland.
Maryna KhalavkaIndependent Unit of Spectroscopy and Chemical Imaging, Faculty of Biomedicine, Medical University of Lublin, Chodźki 4a, 20-093, Lublin, Poland.
Wioletta RzadDepartment of Pharmaceutical Microbiology, Medical University of Lublin, Chodźki 1, 20-093, Lublin, Poland.
Andrzej StepulakDepartment of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093, Lublin, Poland.
Joanna DepciuchDepartment of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093, Lublin, Poland. joanna.depciuch@ifj.edu.pl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using Fourier Transform Infrared spectroscopy (FTIR), it is possible to show chemical composition of materials and / or profile chemical changes occurring in tissues, cells, and body fluids during onset and progression of diseases. For diagnostic application, the use of blood would be the most appropriate in biospectroscopy studies since, (i) it is easily accessible and, (ii) enables frequent analyses of biochemical changes occurring in pathological states. At present, different studies have investigated potential of serum, plasma and sputum being alternative biofluids for lung cancer detection using FTIR. However, until now, it has not been shown which biofluid; among serum and plasma, that can serve as the best material medium for detecting lung cancer with highest levels of accuracy. In this study, plasma and serum isolated from blood consenting participants without lung cancer symptoms (controls) and lung cancer patients. The samples were measured using FTIR and subsequently analyzed by machine learning (ML) algorithms in order to show which fluids (serum or plasma) would better enhance detection of lung cancer. Higher absorbances values of PO

Indexed as

Lung NeoplasmsAdultAgedBiomarkers, TumorBody FluidsFemaleHumansLiquid BiopsyMachine LearningMaleMiddle AgedPlasmaPrincipal Component AnalysisSerumSpectroscopy, Fourier Transform InfraredBiomarkers, TumorFTIR-ATRLung cancerMachine learningPlasmaSerum

Identifiers

PMID39738239
PMCPMC11686151

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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.