Evidence map›Paper›PMID 34027089›Full record

ArticleBioengineering & translational medicine2021

Screening of important metabolites and KRAS genotypes in colon cancer using secondary ion mass spectrometry.

Kookrae Cho, Eun-Sook Choi, Sung Young Lee, Jung-Hee Kim, Dae Won Moon, Jong-Wuk Son, Eunjoo Kim

Open access · goldAbstract read
In one paragraph

Article in Bioengineering & translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 29% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Colorectal neoplasia-specific amino acid profiles and their diagnostic potential: a systematic review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Pooled it
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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

7 authors at 2 institutions in 2 countries.

Kookrae ChoDivision of Electronic Information System Research Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea.
Eun-Sook ChoiDivision of Bio-Fusion Research Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea.
Sung Young LeeDivision of Technology Business, National Institute for Nanomaterials Technology (NINT) Pohang University of Science and Technology (POSTECH) Pohang Republic of Korea.
Jung-Hee KimDivision of Electronic Information System Research Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea.
Dae Won MoonDepartment of New Biology Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea.
Jong-Wuk SonDivision of Electronic Information System Research Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea.
Eunjoo KimDivision of Electronic Information System Research Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea.ORCID https://orcid.org/0000-0001-5328-1182
Daegu Gyeongbuk Institute of Science and Technology · KRPohang University of Science and Technology · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is an imaging-based analytical technique that can characterize the surfaces of biomaterials. We used TOF-SIMS to identify important metabolites and oncogenic KRAS mutation expressed in human colorectal cancer (CRC). We obtained 540 TOF-SIMS spectra from 180 tissue samples by scanning cryo-sections and selected discriminatory molecules using the support vector machine (SVM) algorithm. Each TOF-SIMS spectrum contained nearly 860,000 ion profiles and hundreds of spectra were analyzed; therefore, reducing the dimensionality of the original data was necessary. We performed principal component analysis after preprocessing the spectral data, and the principal components (20) of each spectrum were used as the inputs of the SVM algorithm using the R package. The performance of the algorithm was evaluated using the receiver operating characteristic (ROC) area under the curve (AUC) (0.9297). Spectral peaks (

Indexed as

biomarker screeningcolorectal cancerKRAS somatic mutationsupport vector machine learning algorithmtime‐of‐flight secondary ion mass spectrometry (TOF‐SIMS)

Identifiers

PMID34027089
PMCPMC8126813
OpenAlexW3105899752

What Socratic 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 Socratic graph.