Evidence map›Paper›PMID 34871866›Full record

ArticleTalanta2022

Carboxylic submetabolome-driven signature characterization of COVID-19 asymptomatic infection.

Jing Xu, Yu Yuan, Yao-Yu Chen, Cai-Feng Xiong, Zheng Zhang, Yu-Qi Feng

Open access · greenAbstract read
In one paragraph

Article in Talanta, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Bile acids and coronavirus disease 2019.Acta pharmaceutica Sinica. B · 2024
    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

6 authors at 3 institutions in 1 country.

Jing XuDepartment of Chemistry, Wuhan University, Wuhan, 430072, PR China.
Yu YuanHubei Key Lab of Environment and Health Incubating, Department of Occupation and Environmental Health, Huazhong University of Science & Technology, Wuhan, 430030, PR China.
Yao-Yu ChenDepartment of Chemistry, Wuhan University, Wuhan, 430072, PR China.
Cai-Feng XiongDepartment of Chemistry, Wuhan University, Wuhan, 430072, PR China.
Zheng ZhangSchool of Life Sciences, Central China Normal University, 152 Luoyu Rd, Wuhan, 430079, PR China. Electronic address: zhangzheng_whu@126.com.
Yu-Qi FengDepartment of Chemistry, Wuhan University, Wuhan, 430072, PR China; School of Health Sciences, Wuhan University, Wuhan, 430071, PR China. Electronic address: yqfeng@whu.edu.cn.
Wuhan University · CNCentral China Normal University · CNHuazhong University of Science and Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Asymptomatic infection of COVID-19 is a global threat for public health. Unfortunately, the study about metabolic dysregulation of asymptomatic infection is barely investigated. Here, we performed carboxylic submetabolome profiling of serum from 62 asymptomatic and 122 control individuals, by a highly sensitive chemical isotope labelling method. Twenty-one discriminative carboxylic features, including 12-hydroxyeicosatetraenoic acid, cholic acid, glycoursodeoxycholic acid and 15,16-dihydroxyoctadeca-9,12-dienoic acid were discovered to be dysregulated in asymptomatic patients. This panel containing 21 carboxylic features could accurately identify asymptomatic patients based on a random forest model, providing an accuracy of 85.7% with only 3.6% false positive rate and 7.1% false negative rate. The dysregulated metabolites found in asymptomatic patients covered several important pathways, such as arachidonic acid metabolism, synthesis of bile acid, β-oxidation of fatty acids, activation of macrophage and platelet aggregation. This work provided valuable knowledge about serum biomarkers and molecular clues associated with asymptomatic COVID-19 patients.

Indexed as

COVID-19Asymptomatic InfectionsFatty AcidsHumansIsotope LabelingSARS-CoV-2Fatty AcidsCarboxylic metabolic dysregulationChemical isotope labellingCOVID-19 asymptomatic infectionMachine learning

Identifiers

PMID34871866
PMCPMC8632795
OpenAlexW3215662626

What OpenQuestion holds

Textmetadata
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.