Evidence map›Paper›PMID 35540214›Full record

ArticleRSC advances2019

Selection and preliminary application of a single stranded DNA aptamer targeting colorectal cancer serum.

Kun Li, Liqing Qi, LiMing Gao, Ming Shi, Jian Li, ZhiWei Liu, Lu Zhao

Abstract read
In one paragraph

Article in RSC advances, 2019. 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. Article
  3. Article
  4. Aptamer-based approaches forResearch in pharmaceutical sciences · 2020
    Review
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.

Kun LiCollege of Environmental & Chemical Engineering, Yanshan University Qinhuangdao Hebei Province 066004 China likun@ysu.edu.cn.ORCID https://orcid.org/0000-0002-6064-1163
Liqing QiCollege of Environmental & Chemical Engineering, Yanshan University Qinhuangdao Hebei Province 066004 China likun@ysu.edu.cn.
LiMing GaoThe First Hospital of Qinhuangdao City Qinhuangdao 066000 China.
Ming ShiCollege of Environmental & Chemical Engineering, Yanshan University Qinhuangdao Hebei Province 066004 China likun@ysu.edu.cn.
Jian LiCollege of Environmental & Chemical Engineering, Yanshan University Qinhuangdao Hebei Province 066004 China likun@ysu.edu.cn.ORCID https://orcid.org/0000-0003-1539-1166
ZhiWei LiuCollege of Environmental & Chemical Engineering, Yanshan University Qinhuangdao Hebei Province 066004 China likun@ysu.edu.cn.
Lu ZhaoCollege of Environmental & Chemical Engineering, Yanshan University Qinhuangdao Hebei Province 066004 China likun@ysu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer is one of the common causes of malignant tumors in recent years, thus the discovery of potential compounds that detect the occurrence of colorectal cancer by efficient approaches is necessary. In this study, the method of systematic evolution of ligands by exponential enrichment (SELEX) was used for recognizing serum from colorectal cancer patients by a single-stranded DNA library of aptamers assisted by single-walled carbon nanotubes (SWCNTs) to remove single-stranded DNA with low affinity. Ten rounds of selection were applied using colorectal cancer serum as a target with the serum of healthy individuals as a control. As the result, we have successfully identified four candidate aptamers after high-throughput genome sequencing analysis, comparison analysis and secondary structure prediction. Among them, aptamer Seq-2 exhibited the highest affinity and the strongest selectivity with an equilibrium dissociation constant (

Identifiers

PMID35540214
PMCPMC9075956

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Registered trials

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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.