Evidence map›Paper›PMID 40598854›Full record

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

An MOF-Enhanced Anti-Fouling Immunoprobe Platform for Efficient Direct Screening of Pancreatic Cancer.

Wenjuan Yang, Shujuan Mao, Hao Zhu, Handong Yao, Wei Jin, Lingyan Feng, Xinghua Gao, Xuefeng Wang, Wei Chen, Min Tu and 1 more

Abstract read
PubMed Full text at PMC Publisher
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

11 authors.

Wenjuan YangMaterials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai, 200444, China.
Shujuan MaoMaterials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai, 200444, China.
Hao ZhuMaterials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai, 200444, China.
Handong YaoMaterials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai, 200444, China.
Wei JinMaterials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai, 200444, China.
Lingyan FengMaterials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai, 200444, China.
Xinghua GaoMaterials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai, 200444, China.
Xuefeng WangState Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.
Wei ChenDepartment of Emergency, Tongji Hospital, Tongji University School of Medicine, Shanghai, 200065, China.
Min TuState Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China.ORCID https://orcid.org/0000-0003-4751-3877
Yuan ZhangMaterials Genome Institute, Shanghai Engineering Research Center for Integrated Circuits and Advanced Display Materials, Shanghai University, Shanghai, 200444, China.

Funding

Key Technologies Research and Development Program 2024YFF1502704National Natural Science Foundation of China 22201289
6 · The paper itself

Abstract

Monitoring biomarkers offers insights for early disease (e.g., cancer, chronic diseases) screening, treatment guidance and response evaluation. To tackle challenges in precise biomarker detection in complex blood samples, we propose a metal-organic framework (MOF)-enhanced anti-fouling immunoprobe (MAIP). This sensing platform integrates several key features, including an anti-fouling surface, fully oriented antibody immobilization, and an enhanced electron transfer layer. This platform demonstrates remarkable sensitivity and specificity, capable of detecting trace concentrations of cancer markers, ranging from pg/mL to ng/mL. Comprehensive analysis of clinical serum samples, combined with machine learning (ML) evaluations, underscores the platform's reliability and effectiveness in cancer biomarker detection. Using a combination of three biomarkers, the algorithm demonstrated satisfactory classification performance with an accuracy of 100% on the test set across 64 serum samples. Moreover, when evaluated using 10-fold cross-validation, the optimized model maintained a robust accuracy of 0.955 ± 0.09, reinforcing its strong stability and good generalization ability across different data partitions. The MAIP-based platform developed here offers swift analysis, high accuracy, and a simplified testing process. This makes it a promising approach for directly profiling cancer markers from blood, thereby facilitating timely and effective patient care.

Indexed as

Biomarkers, TumorEarly Detection of CancerMetal-Organic FrameworksPancreatic NeoplasmsHumansReproducibility of ResultsBiomarkers, TumorMetal-Organic Frameworksanti‐fouling immunoprobecancer biomarker detectionearly diagnosismachine learningmetal‐organic framework

Identifiers

PMID40598854
PMCPMC12463068

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.