Evidence map›Paper›PMID 42239494›Full record

ReviewQRB discovery2026

Recent advances of in situ and in vivo electrochemical analysis of brain chemistry at micro- and nanoscale.

Jinger Chen, Lijiao Cao, Yuying Liu, Junlan Zhou, Xiaoke Nan, Chuqi Li, Meiping Xiong, Chao Yuan, Xianchan Li

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in QRB discovery, 2026. 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

9 authors.

Jinger ChenState Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Science, Beijing Key Laboratory of Carbohydrate Intelligent Manufacture and Functional Applications, Peking University, Beijing 100191, China.
Lijiao CaoState Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Science, Beijing Key Laboratory of Carbohydrate Intelligent Manufacture and Functional Applications, Peking University, Beijing 100191, China.
Yuying LiuState Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Science, Beijing Key Laboratory of Carbohydrate Intelligent Manufacture and Functional Applications, Peking University, Beijing 100191, China.
Junlan ZhouState Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Science, Beijing Key Laboratory of Carbohydrate Intelligent Manufacture and Functional Applications, Peking University, Beijing 100191, China.
Xiaoke NanState Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Science, Beijing Key Laboratory of Carbohydrate Intelligent Manufacture and Functional Applications, Peking University, Beijing 100191, China.
Chuqi LiState Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Science, Beijing Key Laboratory of Carbohydrate Intelligent Manufacture and Functional Applications, Peking University, Beijing 100191, China.
Meiping XiongState Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Science, Beijing Key Laboratory of Carbohydrate Intelligent Manufacture and Functional Applications, Peking University, Beijing 100191, China.
Chao YuanDepartment of Preventive Dentistry, Peking University School and Hospital of Stomatology, National Center for Stomatology, National Clinical Research Center for Oral Diseases, National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, Beijing Key Laboratory of Digital Stomatology, NHC Key Laboratory of Digital Stomatology, NMPA Key Laboratory for Dental Materials, Beijing 100081, China.
Xianchan LiState Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Science, Beijing Key Laboratory of Carbohydrate Intelligent Manufacture and Functional Applications, Peking University, Beijing 100191, China.ORCID https://orcid.org/0000-0002-3256-6610

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Real-time, in situ monitoring of neurochemical dynamics in intact neural circuits is critical for elucidating brain function. Recent innovations in micro- and nanoelectrode engineering have markedly advanced our ability to detect neurotransmitter and neuromodulator release with high spatiotemporal resolution, while the application of machine learning (ML) has facilitated the development of next-generation electrodes and enhanced signal processing capabilities. Here, we outline a vision for the potential directions for electrode interface design and the deepening integration of ML in in situ neurochemical sensing, illustrating how breakthroughs over the past decade have illuminated these opportunities.

Indexed as

brain chemistryelectrochemistryin vivo analysismachine learningneurotransmitter

Identifiers

PMID42239494
PMCPMC13227304

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.