Evidence map›Paper›PMID 32556889›Full record

ArticlePathology oncology research : POR2020

Mid-Infrared Imaging Is Able to Characterize and Separate Cancer Cell Lines.

E Kontsek, A Pesti, M Björnstedt, T Üveges, E Szabó, T Garay, P Gordon, S Gergely, A Kiss

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Pathology oncology research : POR, 2020. 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
2.7field-weighted citation impact, top 9% 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, 20 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

9 authors at 3 institutions in 2 countries.

E Kontsek2nd Department of Pathology, Semmelweis University, Budapest, Hungary. kontsek.endre@med.semmelweis-univ.hu.ORCID https://orcid.org/0000-0002-8098-1392
A Pesti2nd Department of Pathology, Semmelweis University, Budapest, Hungary.
M BjörnstedtLaboratory for Clinical Pathology and Cytology, Department of Laboratory Medicine, Division of Pathology, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
T ÜvegesDepartment of Applied Biotechnology and Food Science, Budapest University of Technology and Economics, Budapest, Hungary.
E SzabóDepartment of Applied Biotechnology and Food Science, Budapest University of Technology and Economics, Budapest, Hungary.
T Garay2nd Department of Pathology, Semmelweis University, Budapest, Hungary.
P GordonDepartment of Electronics Technology, Budapest University of Technology and Economics, Budapest, Hungary.
S GergelyDepartment of Applied Biotechnology and Food Science, Budapest University of Technology and Economics, Budapest, Hungary.
A Kiss2nd Department of Pathology, Semmelweis University, Budapest, Hungary.
Budapest University of Technology and Economics · HUSemmelweis University · HUKarolinska University Hospital · SE

Funding

Emberi Eroforrások Minisztériuma BME FIKP-BIOEmberi Eroforrások Minisztériuma EFOP-3.6.3-VEKOP-16-2017-00009.
6 · The paper itself

Abstract

Malignancies are still responsible for a large share of lethalities. Macroscopical evaluation of the surgical resection margins is uncertain. Big data based imaging approaches have emerged in the recent decade (mass spectrometry, two-photon microscopy, infrared and Raman spectroscopy). Indocianine green labelled MS is the most common approach, however, label free mid-infrared imaging is more promising for future practical application. We aimed to identify and separate different transformed (A-375, HT-29) and non-transformed (CCD986SK) cell lines by a label-free infrared spectroscopy method. Our approach applied a novel set-up for label-free mid-infrared range classification method. Transflection spectroscopy was used on aluminium coated glass slides. Both whole range spectra (4000-648 cm

Indexed as

NeoplasmsCell Line, TumorCell SeparationHumansOptical ImagingSpectrophotometry, InfraredCancerFingerprint regionFT-IRTransflectance

Identifiers

PMID32556889
PMCPMC7471106
OpenAlexW3036211102

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.