Evidence map›Paper›PMID 40904334›Full record

ArticleRSC advances2025

A highly sensitive label-free aptamer sensor for timely detection of human serum albumin.

Hanghang Cheng, Wentao Chen, Zejun Deng, Minghui Yin, Chengyu Zhuang, Zhi-Mei Qi, Ning Xue, Chunxiu Liu

Abstract read
In one paragraph

Article in RSC advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

8 authors.

Hanghang ChengState Key Laboratory of Transducer Technology, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences Beijing China zhimei-qi@mail.ie.ac.cn cxliu@mail.ie.ac.cn.ORCID https://orcid.org/0000-0003-3718-9364
Wentao ChenState Key Laboratory of Transducer Technology, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences Beijing China zhimei-qi@mail.ie.ac.cn cxliu@mail.ie.ac.cn.
Zejun DengCentral South University Changsha China.
Minghui YinState Key Laboratory of Transducer Technology, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences Beijing China zhimei-qi@mail.ie.ac.cn cxliu@mail.ie.ac.cn.
Chengyu ZhuangRuijin Hospital, Shanghai Jiao Tong University School of Medicine Shanghai China zhuangchengyu@msn.com.
Zhi-Mei QiState Key Laboratory of Transducer Technology, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences Beijing China zhimei-qi@mail.ie.ac.cn cxliu@mail.ie.ac.cn.
Ning XueLingang Laboratory Shanghai China xuening@mail.ie.ac.cn.
Chunxiu LiuState Key Laboratory of Transducer Technology, Aerospace Information Research Institute (AIR), Chinese Academy of Sciences Beijing China zhimei-qi@mail.ie.ac.cn cxliu@mail.ie.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The trace-level detection of proteins in the human body holds significant importance for health monitoring and disease prevention. To conduct real-time monitoring of the human body's health status, both wearable and implantable devices require label-free sensing. However, the signals of a considerable number of label-free electrochemical sensors originate from the signal capture medium. These signals are weak and are prone to being lost or masked by other signals. We report a Prussian blue (PB)-based self-redox aptamer sensor was developed, enabling real-time human serum albumin (HSA) detection without external redox mediators. The designed sensing interface successfully achieved the quantitative detection of HSA in PBS with a sensitivity of 124 fg mL

Identifiers

PMID40904334
PMCPMC12403663

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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.