Evidence map›Paper›PMID 37340584›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2023

Hollow Crystallization COF Capsuled MOF Hybrids Depict Serum Metabolic Profiling for Precise Early Diagnosis and Risk Stratification of Acute Coronary Syndrome.

Chenjie Yang, Yilong Pan, Hailong Yu, Xufang Hu, Xiaodong Li, Chunhui Deng

Open access · goldAbstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
6.6field-weighted citation impact, top 3% 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

11 citing papers in PubMed, 43 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Automated Diagnosis and Phenotyping of Tuberculosis Using Serum Metabolic Fingerprints.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  7. In Situ Construction of Hollow Coral-Like Porous S-Doped g-CAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  8. Serum Metabolic Fingerprints Characterize Systemic Lupus Erythematosus.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  9. Article
  10. Review
  11. 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

6 authors at 3 institutions in 1 country.

Chenjie YangDepartment of Chemistry, Fudan University, Shanghai, 200433, China.
Yilong PanDepartment of Cardiology, Shengjing Hospital of China Medical University, NO.36 Sanhao Street, Heping District, Shenyang, 110004, China.
Hailong YuDepartment of Chemistry, Fudan University, Shanghai, 200433, China.
Xufang HuSchool of Chemical Science and Technology, Yunnan University, No. 2 North Cuihu Road, Kunming, 650091, P. R. China.
Xiaodong LiDepartment of Cardiology, Shengjing Hospital of China Medical University, NO.36 Sanhao Street, Heping District, Shenyang, 110004, China.
Chunhui DengDepartment of Chemistry, Fudan University, Shanghai, 200433, China.ORCID 0000-0002-8704-7543
Fudan University · CNChina Medical University · CNYunnan University · CN

Funding

345 Talent Project of Shengjing HospitalNational Key R&D Program of China 2018YFA0507501National Natural Science Foundation of China 21425518National Natural Science Foundation of China 22004017National Natural Science Foundation of China 22074019Shanghai Sailing Program 20YF1405300
6 · The paper itself

Abstract

Acute coronary syndrome (ACS), comprising unstable angina (UA) and acute myocardial infarction (AMI), is the leading cause of death worldwide. Currently, lacking effective strategies for classifying ACS hinders the prognosis improvement of ACS patients. Disclosing the nature of metabolic disorders holds the potential to reflect disease progress and high-throughput mass spectrometry-based metabolic analysis is a promising tool for large-scale screening. Herein, a hollow crystallization COF capsuled MOF hybrids (UiO-66@HCOF) assisted serum metabolic analysis is developed for the early diagnosis and risk stratification of ACS. UiO-66@HCOF exhibits unrivaled chemical and structural stability as well as endowing satisfying desorption/ionization efficiency in the detection of metabolites. Paired with machine learning algorithms, early diagnosis of ACS is achieved with the area under the curve (AUC) value of 0.945 for validation sets. Besides, a comprehensive ACS risk stratification method is established, and the AUC value for the discrimination of ACS from healthy controls, and AMI from UA are 0.890, and 0.928. Moreover, the AUC value of the subtyping of AMI is 0.964. Finally, the potential biomarkers exhibit high sensitivity and specificity. This study makes metabolic molecular diagnosis a reality and provided new insight into the progress of ACS.

Indexed as

Acute Coronary SyndromeMyocardial InfarctionAngina, UnstableCrystallizationEarly DiagnosisHumansMetal-Organic FrameworksPhthalic AcidsRisk AssessmentMetal-Organic FrameworksPhthalic AcidsUiO-66acute coronary syndromeacute myocardial infarctioncovalent organic frameworks (COFs)metabolic profilingmetal-organic frameworks (MOFs)

Identifiers

PMID37340584
PMCPMC10460873
OpenAlexW4381470588

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.