Evidence map›Paper›PMID 38569219›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Artificial Intelligence-Guided Gut-Microenvironment-Triggered Imaging Sensor Reveals Potential Indicators of Parkinson's Disease.

Yiwei Li, Hong-Xia Ren, Chong-Yung Chi, Yang-Bao Miao

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Shadow-Calibrated Stereo Vision for Colorimetric Sweat Analysis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  3. Review
  4. A systemic immunogenic reactor leveraging modifiedActa pharmaceutica Sinica. B · 2026
    Article
  5. Review
  6. Review
  7. Review
  8. Review
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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

4 authors.

Yiwei LiDepartment of Haematology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, School of Medicine of University of Electronic Science and Technology of China, No. 32, West Section 2, First Ring Road, Qingyang District, Chengdu, 610000, China.
Hong-Xia RenSichuan Technology & Business College, Chengdu, 611800, China.
Chong-Yung ChiInstitute of Communications Engineering & Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 30013, Taiwan.
Yang-Bao MiaoDepartment of Haematology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, School of Medicine of University of Electronic Science and Technology of China, No. 32, West Section 2, First Ring Road, Qingyang District, Chengdu, 610000, China.ORCID 0000-0001-7705-8567

Funding

Central Government Guides Local Science and Technology Development Fund Project 23ZYZYTS0260Central Government Guides Local Science and Technology Development Fund Project 24GJHZ0072Ministry of Science and Technology, Taiwan 110-2221-E-007-031Ministry of Science and Technology, Taiwan 111-2221-E-007-035-MY2Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital 30420220004Sichuan Province Science and Technology Activities Funding for Returned Overseas ScholarsSichuan Science and Technology Program 24GJH0072
6 · The paper itself

Abstract

The gut-brain axis has recently emerged as a crucial link in the development and progression of Parkinson's disease (PD). Dysregulation of the gut microbiota has been implicated in the pathogenesis of this disease, sparking growing interest in the quest for non-invasive biomarkers derived from the gut for early PD diagnosis. Herein, an artificial intelligence-guided gut-microenvironment-triggered imaging sensor (Eu-MOF@Au-Aptmer) to achieve non-invasive, accurate screening for various stages of PD is presented. The sensor works by analyzing α-Syn in the gut using deep learning algorithms. By monitoring changes in α-Syn, the sensor can predict the onset of PD with high accuracy. This work has the potential to revolutionize the diagnosis and treatment of PD by allowing for early intervention and personalized treatment plans. Moreover, it exemplifies the promising prospects of integrating artificial intelligence (AI) and advanced sensors in the monitoring and prediction of a broad spectrum of diseases and health conditions.

Indexed as

Artificial IntelligenceGastrointestinal MicrobiomeParkinson DiseaseAnimalsBiomarkersBiosensing TechniquesBrain-Gut AxisDeep LearningHumansBiomarkersartificial intelligencedeep learninggut microbiotaoral deliverysensor

Identifiers

PMID38569219
PMCPMC11187919

What OpenQuestion holds

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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.