Evidence map›Paper›PMID 40453474›Full record

ArticleBiosafety and health2025

Detecting and classifying metabolic activity of

Li Liu, Bing Feng, Yang Song, Taijie Zhan, Dongxin Liu, Jia Ding, Xiaohui Song, Jian Xu, Duochun Wang, Qiang Wei

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biosafety and health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. DMikrochimica acta · 2026
    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

10 authors.

Li LiuNational Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Bing FengQingdao Single-Cell Biotechnology Co., Ltd., Qingdao 266100, China.
Yang SongKey Laboratory of Surveillance and Early-Warning on Infectious Disease, National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Taijie ZhanUniversity of Shanghai for Science and Technology, Shanghai 200093, China.
Dongxin LiuNational Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Jia DingQingdao Single-Cell Biotechnology Co., Ltd., Qingdao 266100, China.
Xiaohui SongNational Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Jian XuSingle-Cell Center, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China.
Duochun WangNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
Qiang WeiNational Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The metabolic activity of pathogens poses a substantial risk across diverse domains, including food safety, vaccine development, clinical treatment, and national biosecurity. Conventional subculturing methods typically require several days and fail to detect metabolic activity promptly, limiting their application in many areas. Consequently, there is an urgent need for a method capable of rapidly and accurately detecting this activity. This study builds upon an investigation of the effects of D

Indexed as

D2OHigh-throughputMachine learningMetabolic activityRaman spectroscopyStaphylococcus aureus (S. aureus)

Identifiers

PMID40453474
PMCPMC12125699

What Socratic 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 Socratic graph.