Evidence map›Paper›PMID 41811539›Full record

ArticleMikrochimica acta2026

A rime-like Au-Pt nanostructured film and polyaniline-MIP based electrochemical sensor for olanzapine detection.

Xiang Gao, Yujiao Hou, Fang Lin, Limei Wen, Yali Guo, Weijun Kong, Junping Hu, Jianhua Yang

Abstract read
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Article in Mikrochimica acta, 2026. 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

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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

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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.

Xiang GaoCollege of Pharmacy, Xinjiang Medical University, Urumqi, 830054, P.R. China.
Yujiao HouCollege of Pharmacy, Xinjiang Medical University, Urumqi, 830054, P.R. China.
Fang LinCollege of Pharmacy, Xinjiang Medical University, Urumqi, 830054, P.R. China.
Limei WenDepartment of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, P.R. China.
Yali GuoCollege of Pharmacy, Xinjiang Medical University, Urumqi, 830054, P.R. China.
Weijun KongSchool of Traditional Chinese Medicine, Capital Medical University, Beijing, 100069, China.
Junping HuCollege of Pharmacy, Xinjiang Medical University, Urumqi, 830054, P.R. China. hjp_yft@163.com.
Jianhua YangDepartment of Pharmacy, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, P.R. China. yjh_yfy@163.com.

Funding

The Natural Science Foundation of Xinjiang Uygur Autonomous Region 2024D01C140The second group of Tianshan Talent Training Program: Youth Support Talent Project 2023TSYCQNTJ0025Youth Science and Technology Elite Talent Program, Xinjiang Medical University XYD2024Q02
6 · The paper itself

Abstract

An electrochemical (EC) molecularly imprinted polymer (MIP) sensor for therapeutic drug monitoring of olanzapine (OLZ) has been developed. A “rime-like” gold-platinum nanostructured film (Au-Pt NF) was fabricated on a screen-printed carbon electrode (SPCE) via an one-step hydrogen bubble dynamic template (HBDT) method, followed by electropolymerization of a polyaniline-based MIP. The Au-Pt NF/SPCE served as an ideal three-dimensional conductive substrate with a large active area and enhanced electron-transfer capability, endowing the specific MIP sensor with high sensitivity. Using [Fe(CN)6]3−/4− as a redox probe, the sensor quantified OLZ by the decrease in differential pulse voltammetry current caused by target binding. It exhibited two linear ranges (0.005–0.4 µM and 0.4–10 µM) with a detection limit of 0.94 nM, and demonstrated high selectivity, reproducibility, and stability. The sensor achieved recoveries of 96.7–102.7% for OLZ in tablets, urine, and whole blood. This work provides a reliable, all-EC sensing platform with strong potential for rapid OLZ monitoring in clinical settings.

Indexed as

Biological samplesDifferential pulse voltammetryEC sensorMolecularly imprinted polymerOlanzapineRime-like Au-Pt nanostructured filmScreen-printed carbon electrode

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Registered trials

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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.