Evidence map›Paper›PMID 39731324›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

SAM-dPCR: Accurate and Generalist Nuclei Acid Quantification Leveraging the Zero-Shot Segment Anything Model.

Yuanyuan Wei, Shanhang Luo, Changran Xu, Yingqi Fu, Yi Zhang, Fuyang Qu, Guoxun Zhang, Yi-Ping Ho, Ho-Pui Ho, Wu Yuan

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Yuanyuan WeiDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.ORCID https://orcid.org/0000-0003-1886-0407
Shanhang LuoDepartment of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Changran XuDepartment of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Yingqi FuDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Yi ZhangDepartment of Electronic Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Fuyang QuDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Guoxun ZhangDepartment of Automation, Tsinghua University, Beijing, 100084, China.
Yi-Ping HoDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Ho-Pui HoDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Wu YuanDepartment of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.

Funding

Hong Kong Research Grants Council GRF14203821Hong Kong Research Grants Council GRF14203919Hong Kong Research Grants Council GRF14204621Hong Kong Research Grants Council GRF14207121Hong Kong Research Grants Council GRF14207419Hong Kong Research Grants Council GRF14207920Hong Kong Research Grants Council GRF14216222Marine Conservation Enhancement Fund MCEF20108_L02The Science, Technology, and Innovation Commission of Shenzhen Municipality SGDX20220530111005039
6 · The paper itself

Abstract

Digital PCR (dPCR) has transformed nucleic acid diagnostics by enabling the absolute quantification of rare mutations and target sequences. However, traditional dPCR detection methods, such as those involving flow cytometry and fluorescence imaging, may face challenges due to high costs, complexity, limited accuracy, and slow processing speeds. In this study, SAM-dPCR is introduced, a training-free open-source bioanalysis paradigm that offers swift and precise absolute quantification of biological samples. SAM-dPCR leverages the robustness of the zero-shot Segment Anything Model (SAM) to achieve rapid processing times (<4 seconds) with an accuracy exceeding 97.10%. This method has been extensively validated across diverse samples and reactor morphologies, demonstrating its broad applicability. Utilizing standard laboratory fluorescence microscopes, SAM-dPCR can measure nucleic acid template concentrations ranging from 0.154 copies µL

Indexed as

Nucleic AcidsPolymerase Chain ReactionHumansNucleic Acidsdeep‐learningdigital PCRdroplet microfluidicsnucleic acid quantificationsegment anything model

Identifiers

PMID39731324
PMCPMC11831435

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.