Evidence map›Paper›PMID 42801702›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Engineered Allosteric Biosensor for In Situ DNA Glycosylase Detection in Neuroblastoma Risk Stratification and Drug Resistance Monitoring.

Yaqing Lu, Yingyu Zhang, Xianwei Zhang, Mengxin Zhang, Fei Zhang, Jushan Sun, Yahui Yang, Kangbo Liu, Peng Wang, Shuying Luo and 1 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Yaqing Lu *Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Yingyu Zhang *Henan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, China.
Xianwei Zhang *Health Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Mengxin ZhangHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Fei ZhangHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Jushan SunHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Yahui YangHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Kangbo LiuNMPA Key Laboratory for Quality Evaluation of Medical Protective and Implant Devices, Henan Institute for Drug and Medical Device Inspection (Henan Vaccine Issuance Center), Zhengzhou, China.
Peng WangDepartment of Biomedical Engineering, School of Engineering, China Pharmaceutical University, Nanjing, China.ORCID https://orcid.org/0000-0003-2359-908X
Shuying LuoHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.
Wancun ZhangHealth Commission of Henan Province Key Laboratory for Precision Diagnosis and Treatment of Pediatric Tumor, Children's Hospital Affiliated to Zhengzhou University, Zhengzhou, China.ORCID https://orcid.org/0000-0002-3231-2602

Funding

Henan Medical Science and Technology Program LHGJ20230583Henan Medical Science and Technology Program LHGJ20250596Henan Medical Science and Technology Program LHGJ20250605Henan Medical Science and Technology Program SBGJ202403052Henan Medical Science and Technology Program SBGJ202502095National Natural Science Foundation of China 32201237Scientific and Technological Projects of Henan Province 242102310383Scientific and Technological Projects of Henan Province 262102310053Scientific and Technological Projects of Henan Province 262102311041Scientific and Technological Projects of Henan Province 262102311123Zhengzhou Outstanding Young Scientific and Technological Talents (Doctor) Training Project 2024046Zhengzhou Zhongrui Foreign Expert Workstation for Precision Diagnosis and Treatment of Neuroblastoma ZZGZS2024006
6 · The paper itself

Abstract

Accurate and in situ detection of uracil-DNA glycosylase (UDG) is crucial for clinical diagnosis and prognosis assessment. However, conventional methods show low accuracy, limited sensitivity, and off-target signal leakage due to flawed signal input/output and amplification mechanisms. Therefore, an engineered allosteric biosensor (UUU-DZ-tFNA) was developed, in which UDG specifically recognizes and activates a DNAzyme to achieve signal cycle amplification in a sequentially activatable mode. Experimental results demonstrated that UUU-DZ-tFNA enables rapid, highly sensitive (LOD = 0.025 mU/mL), and specific detection of UDG. In addition, UUU-DZ-tFNA enables in situ molecular imaging of UDG at both the neuroblastoma (NB) cellular and animal levels, as well as precise in situ detection of UDG in plasma exosomes from NB patients. In particular, the non-invasive risk stratification model for NB developed using machine learning based on exosomal UDG and clinical multidimensional indicators, including MYCN amplification status, International NB Risk Factors (IDRFs), neuron-specific enolase (NSE), and lactate dehydrogenase (LDH), showed excellent discriminatory ability, with 85.7% sensitivity, 100.0% specificity, and 92.8% accuracy. UUU-DZ-tFNA also enables image-guided surgical excision in vivo and effective monitoring of drug resistance in NB. In summary, UUU-DZ-tFNA enables in situ detection of UDG, facilitating risk stratification and drug resistance monitoring of NB.

Indexed as

biosensorcancer researchdna glycosylasedrug resistancein vivolactate dehydrogenasemachine learningneuroblastomarisk stratification

Identifiers

PMID42801702
PMCPMC13616298

What OpenQuestion holds

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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.