Evidence map›Paper›PMID 34323397›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2021

Ultra-Fast Label-Free Serum Metabolic Diagnosis of Coronary Heart Disease via a Deep Stabilizer.

Mengji Zhang, Lin Huang, Jing Yang, Wei Xu, Haiyang Su, Jing Cao, Qian Wang, Jun Pu, Kun Qian

Open access · goldAbstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
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

13 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
  2. Article
  3. Automated Diagnosis and Phenotyping of Tuberculosis Using Serum Metabolic Fingerprints.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  4. Article
  5. Fast Label-Free Metabolic Profile Recognition Identifies Phenylketonuria and Subtypes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Diagnosis and prognosis of breast cancer by high-performance serum metabolic fingerprints.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  12. Article
  13. Article
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 at 1 institution in 1 country.

Mengji ZhangState Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Lin HuangState Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Jing YangState Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Wei XuState Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Haiyang SuState Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Jing CaoState Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Qian WangState Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Jun PuState Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Cancer Institute, 160 Pujian Road, Shanghai, 200127, P. R. China.
Kun QianState Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering, Institute of Medical Robotics and Med-X Research Institute, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.ORCID 0000-0003-1666-1965
Shanghai Jiao Tong University · CN

Funding

Innovation Group Project of Shanghai Municipal Health Commission 2019CXJQ03Ministry of Science and Technology of China 2017YFE0124400National Key R&D Program of China 2018YFC1312802National Natural Science Foundation of China 81771983National Natural Science Foundation of China 81971771Shanghai Institutions of Higher Learning 2021-01-07-00-02-E00083Shanghai Municipal Education Commission ZXWF082101Shanghai Rising-Star Program 19QA1404800
6 · The paper itself

Abstract

Although mass spectrometry (MS) of metabolites has the potential to provide real-time monitoring of patient status for diagnostic purposes, the diagnostic application of MS is limited due to sample treatment and data quality/reproducibility. Here, the generation of a deep stabilizer for ultra-fast, label-free MS detection and the application of this method for serum metabolic diagnosis of coronary heart disease (CHD) are reported. Nanoparticle-assisted laser desorption/ionization-MS is used to achieve direct metabolic analysis of trace unprocessed serum in seconds. Furthermore, a deep stabilizer is constructed to map native MS results to high-quality results obtained by established methods. Finally, using the newly developed protocol and diagnosis variation characteristic surface to characterize sensitivity/specificity and variation, CHD is diagnosed with advanced accuracy in a high-throughput/speed manner. This work advances design of metabolic analysis tools for disease detection as it provides a direct label-free, ultra-fast, and stabilized platform for future protocol development in clinics.

Indexed as

Coronary DiseaseHumansNanoparticlesReproducibility of ResultsSensitivity and SpecificitySpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationTimecoronary heart diseasesdeep learningdiagnosticsmass spectrometrymetabolites

Identifiers

PMID34323397
PMCPMC8456274
OpenAlexW3183854831

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.