ArticleTechnology in cancer research & treatment
Nanopore Detection of Cancer Biomarkers: A Challenge to Science.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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.
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Who cites it
2 citing papers in PubMed.
- Nanopore-based sensing for biomarker detection: from fundamental principles to translational diagnostics.Journal of nanobiotechnology · 2025Review
- Detection of Biological Molecules Using Nanopore Sensing Techniques.Biomedicines · 2023Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer is the most complex and leading cause of fatality worldwide. Despite meritorious research in the field of cancer, it is still a substantial threat to human life. In this article, we address a question on the present strategies and manifest the importance of critical biomarkers for cancer screening and early diagnosis before the symptoms appear. However, this goal can only be achieved if scientists will focus on ultra-sensitive detection techniques such as "Nanopore." Nanopore sensing is a simple and rapid single-molecule detection technique that can detect multiple cancer biomarkers in femto-Molar concentrations in real time. Last but not least, we propose a systematic policy to win the war against cancer that is a big challenge to science.
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Registered trials
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.