Evidence map›Paper›PMID 38932669›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Systematic Selection of High-Affinity ssDNA Sequences to Carbon Nanotubes.

Dakyeon Lee, Jaekang Lee, Woojin Kim, Yeongjoo Suh, Jiwoo Park, Sungjee Kim, YongJoo Kim, Sunyoung Kwon, Sanghwa Jeong

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  5. Article
  6. Review
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  8. Review
  9. Article
  10. High-Throughput Approaches to Engineer Fluorescent Nanosensors.Advanced materials (Deerfield Beach, Fla.) · 2025
    Article
  11. Review
  12. Article
  13. Review
  14. Systematic Selection of High-Affinity ssDNA Sequences to Carbon Nanotubes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    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.

Dakyeon LeeSchool of Biomedical Convergence Engineering, Pusan National University, Yangsan, 50612, Republic of Korea.ORCID 0009-0000-0993-3964
Jaekang LeeSchool of Biomedical Convergence Engineering, Pusan National University, Yangsan, 50612, Republic of Korea.
Woojin KimDepartment of Materials Science and Engineering, Kookmin University, Seoul, 02707, Republic of Korea.
Yeongjoo SuhSchool of Biomedical Convergence Engineering, Pusan National University, Yangsan, 50612, Republic of Korea.
Jiwoo ParkSchool of Biomedical Convergence Engineering, Pusan National University, Yangsan, 50612, Republic of Korea.
Sungjee KimDepartment of Chemistry, Pohang University of Science and Technology, Pohang, 37673, Republic of Korea.
YongJoo KimDepartment of Materials Science and Engineering, Korea University, Seoul, 02841, Republic of Korea.
Sunyoung KwonSchool of Biomedical Convergence Engineering, Pusan National University, Yangsan, 50612, Republic of Korea.
Sanghwa JeongSchool of Biomedical Convergence Engineering, Pusan National University, Yangsan, 50612, Republic of Korea.ORCID 0000-0003-3529-0346

Funding

Korea Institute for Advancement of TechnologyMinistry of Education-Ministry of Trade, Industry and EnergyNational Research Foundation of Korea 2021R1F1A1062224National Research Foundation of Korea 2022R1A5A2027161National Research Foundation of Korea RS-2023-00210462Next Generation bio-health industry Innovation Talent Training Program P0022108Pusan National UniversitySeegene Medical Foundation SMF-AI-EJ003-2023
6 · The paper itself

Abstract

Single-walled carbon nanotubes (SWCNTs) have gained significant interest for their potential in biomedicine and nanoelectronics. The functionalization of SWCNTs with single-stranded DNA (ssDNA) enables the precise control of SWCNT alignment and the development of optical and electronic biosensors. This study addresses the current gaps in the field by employing high-throughput systematic selection, enriching high-affinity ssDNA sequences from a vast random library. Specific base compositions and patterns are identified that govern the binding affinity between ssDNA and SWCNTs. Molecular dynamics simulations validate the stability of ssDNA conformations on SWCNTs and reveal the pivotal role of hydrogen bonds in this interaction. Additionally, it is demonstrated that machine learning could accurately distinguish high-affinity ssDNA sequences, providing an accessible model on a dedicated webpage (http://service.k-medai.com/ssdna4cnt). These findings open new avenues for high-affinity ssDNA-SWCNT constructs for stable and sensitive molecular detection across diverse scientific disciplines.

Indexed as

DNA, Single-StrandedMolecular Dynamics SimulationNanotubes, CarbonBiosensing TechniquesMachine LearningDNA, Single-StrandedNanotubes, Carbonbinding affinitymachine learningmolecular dynamicsselectionsingle‐walled carbon nanotubessDNA

Identifiers

PMID38932669
PMCPMC11348070

What OpenQuestion holds

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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.