Evidence map›Paper›PMID 41839994›Full record

ArticleScientific reports2026

Establishment of a rapid Brucella detection method based on MCDA-CRISPR dual signal amplification system for reducing transfusion-transmitted diseases.

Xinjing Fu, Fan Zhao, Jiejie Ge, Hongya Guan, Pengju Lv, Feifei Guo, Hongye Ma, Muyesaier Ainiwaer, Shoukui Hu

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Xinjing Fu *The Second Affiliated Hospital of Xinjiang Medical University, Ürümqi, 830011, China.
Fan Zhao *Aerospace Center Hospital, Beijing, 100049, China.
Jiejie Ge *Department of Clinical Laboratory, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, 450007, China.
Hongya GuanDepartment of Clinical Laboratory, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, 450007, China.
Pengju LvDepartment of Clinical Laboratory, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, 450007, China.
Feifei GuoDepartment of Clinical Laboratory, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, 450007, China.
Hongye MaDepartment of Clinical Laboratory, Beijing Hospital of Traditional Chinese Medicine, Beijing, 100010, China.
Muyesaier AiniwaerUrumqi Blood Center, Ürümqi, 830011, China.
Shoukui HuDepartment of Clinical Laboratory, Beijing Hospital of Traditional Chinese Medicine, Beijing, 100010, China. shoukuihu@163.com.

Funding

the Capital's Funds for Health Improvement and Research 2022-2-6042the Doctoral Scientific Research Startup Fund of Zhengzhou Central Hospital KYQDJJ2024006The Guidance Plan Project for Scientific and Technological Innovation in the Medical and Health Field of Zhengzhou City 2025YLZDJH193the Xinjiang Medical University Graduate Innovation and Entrepreneurship Project CXCY2025024
6 · The paper itself

Abstract

Brucellosis is a common zoonotic disease caused by Brucella and remains a globally concerning public health issue. Timely and effective detection methods are crucial for clinical diagnosis. We developed a novel Brucella detection platform (MCDA-CRISPR) by integrating multiple cross displacement amplification (MCDA) with a CRISPR-Cas12a-based biosensing system, and preliminarily applied it for the first time to screen for Brucella in voluntary blood donors from Xinjiang, China. This technology enables amplification under isothermal conditions at 64 °C using only a water bath, requires no specialized equipment, and completes detection within 60 min. Amplification products can be directly visualized under UV light without complex interpretation. Performance results demonstrated a minimum detection limit of 1 fg/μL for Brucella DNA, making the method 100 times more sensitive than conventional PCR. The assay showed 100% specificity for Brucella detection with no cross-reactivity to non-Brucella pathogens. The assay could also detect Brucella in blood donors samples and showed the same sensitivity and specificity as the culture method. The assay is a visual, sensitive, and highly specific detection technique. When applied to routine blood transfusion screening in areas with high prevalence of brucellosis, such as Xinjiang, can effectively reduce the risk of transfusion-transmitted brucellosis, and hold broad application prospects in resource-limited primary or field testing scenarios.

Indexed as

BrucellaBrucellosisCRISPR-Cas SystemsNucleic Acid Amplification TechniquesTransfusion ReactionBlood DonorsDNA, BacterialHumansRapid Diagnostic TestsSensitivity and SpecificityDNA, BacterialBrucellaCRISPRMolecular diagnosisMultiple cross displacement amplification

Identifiers

PMID41839994
PMCPMC13125532

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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.