Evidence map›Paper›PMID 41326343›Full record

ArticleNature communications2025

A nanoMIP sensor for real-time in vivo monitoring of levodopa pharmacokinetics in precision Parkinson's therapy.

Yue Zhou, Junhao Li, Zhongyi Xu, Yixin Zhao, Shanshan Zhang, Tong Liu, Yelan Yao, Lu Fang, Yu Cai, Xuesong Ye and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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.

Yue ZhouBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China.
Junhao LiBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China.
Zhongyi XuBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China.
Yixin ZhaoBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China.
Shanshan ZhangBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China.
Tong LiuBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China.ORCID http://orcid.org/0009-0002-3791-6605
Yelan YaoBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China.
Lu FangCollege of Automation, Hangzhou Dianzi University, Hangzhou, Zhejiang, PR China.
Yu CaiBinjiang Institute of Zhejiang University, Hangzhou, PR China.
Xuesong YeBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China. yexuesong@zju.edu.cn.
Bo LiangBiosensor National Special Laboratory, Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, PR China. boliang1986@zju.edu.cn.ORCID http://orcid.org/0000-0002-3670-2296

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82272120
6 · The paper itself

Abstract

Real-time in vivo monitoring of levodopa pharmacokinetics is essential to address its narrow therapeutic window in Parkinson's disease (PD) therapy. However, current methods require excessive sample volumes, suffer low sampling frequencies, and fail to capture complete pharmacokinetic profiles. Here, we present an in vivo monitoring system for real-time tracking of levodopa levels in interstitial fluid (ISF) using a spindle-shaped carbon nanotube (CNT) fiber electrochemical sensor functionalized with a nanoscale molecularly imprinted polymer (nanoMIP) on single electroactive CNTs. The core-shell (CNT-nanoMIP) nanostructures provide sensitive, selective detection of levodopa, along with resistance to both biofouling and chemical fouling in continuous ISF detection. The system was validated for monitoring complete pharmacokinetic profiles and assessing temporal correlations between ISF/plasma levodopa pharmacokinetics in both PD rat models and healthy rats. We also demonstrated optimized and adjustable pharmacokinetic profiles through in vivo experiments with rationally designed levodopa dosing regimens, highlighting the system's potential for personalized PD pharmacotherapy.

Indexed as

Antiparkinson AgentsBiosensing TechniquesDrug MonitoringLevodopaParkinson DiseaseAnimalsExtracellular FluidMaleNanotubes, CarbonPrecision MedicineRatsRats, Sprague-DawleyAntiparkinson AgentsLevodopaNanotubes, Carbon

Identifiers

PMID41326343
PMCPMC12669667

What OpenQuestion holds

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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.