Evidence map›Paper›PMID 39310140›Full record

ArticleACS omega2024

Comparison and Optimization of Simple DNA Extraction Methods for LAMP-Based Point-of-Care Applications Employing Submillimeter Skin Biopsies.

Juan M Boza, Jason Cade Manning, David C Erickson

Abstract read
In one paragraph

Article in ACS omega, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

3 authors.

Juan M BozaMeinig School of Biomedical Engineering, Cornell University, Ithaca, New York 14850, United States.ORCID https://orcid.org/0000-0001-8153-9371
Jason Cade ManningMeinig School of Biomedical Engineering, Cornell University, Ithaca, New York 14850, United States.
David C EricksonSibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York 14850, United States.ORCID https://orcid.org/0000-0002-1624-9711

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Loop-mediated isothermal amplification (LAMP) has gained particular attention for point-of-care (POC) applications due to its advantages over traditional nucleic acid testing approaches. However, a prevailing limitation of LAMP in POC applications is nucleic acid extraction from the sample prior to analysis. This is particularly true for complex samples such as submillimeter skin biopsies where lysis and digestion involve intricate and lengthy procedures. The objective of this study was to compare alternative methodologies against the spin-column laboratory standard and evaluate them based on the World Health Organization ASSURED criteria for POC testing. Four methods-magnetic bead extraction, alkaline extraction, proteinase K-heat inactivation extraction, and boiling method extraction-were optimized utilizing porcine skin submillimeter punch biopsies and subsequently validated on human skin. Results show that both alkaline extraction and proteinase K-heat inactivation produce DNA yields equivalent to or higher than the spin-column method in porcine and human skin. When evaluated against the ASSURED criteria, both methods demonstrated low complexity while being highly scalable and readily accessible. Overall, this comparative study established a robust framework for selecting DNA extraction methods for submillimeter skin biopsies in POC applications. It also underscored the performance of the alkaline extraction method based on the ASSURED criteria, providing equivalent DNA yields to laboratory standards with reduced complexity and potential for cost-effective scalability.

Identifiers

PMID39310140
PMCPMC11411550

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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.