Evidence map›Paper›PMID 36557288›Full record

ArticleMetabolites2022

Identification of Biomarkers for Methamphetamine Exposure Time Prediction in Mice Using Metabolomics and Machine Learning Approaches.

Wei Sheng, Runbin Sun, Ran Zhang, Peng Xu, Youmei Wang, Hui Xu, Jiye Aa, Guangji Wang, Yuan Xie

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Metabolites, 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
0.6field-weighted citation impact, top 35% 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, 7 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. 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 2 institutions in 1 country.

Wei ShengChina Pharmaceutical University Nanjing Drum Tower Hospital, Nanjing 210000, China.
Runbin SunChina Pharmaceutical University Nanjing Drum Tower Hospital, Nanjing 210000, China.
Ran ZhangKey Laboratory of Drug Metabolism and Pharmacokinetics, State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.
Peng XuChina National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, China Pharmaceutical University, Nanjing 210009, China.
Youmei WangChina National Narcotics Control Commission-China Pharmaceutical University Joint Laboratory on Key Technologies of Narcotics Control, China Pharmaceutical University, Nanjing 210009, China.
Hui XuKey Laboratory of Drug Metabolism and Pharmacokinetics, State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.
Jiye AaKey Laboratory of Drug Metabolism and Pharmacokinetics, State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.
Guangji WangKey Laboratory of Drug Metabolism and Pharmacokinetics, State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.
Yuan XieKey Laboratory of Drug Metabolism and Pharmacokinetics, State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.
China Pharmaceutical University · CNState Key Laboratory of Natural Medicine

Funding

the National Key Research and Development Program of China 2018YFC0807403the National Natural Science Foundation of China No. 81872932, 81673679the Sanming Project of Medicine in Shenzhen SZSM201801060the Six Talent Peaks Project in Jiangsu Province SWYY-061
6 · The paper itself

Abstract

Methamphetamine (METH) abuse has become a global public health and safety problem. More information is needed to identify the time of drug abuse. In this study, methamphetamine was administered to male C57BL/6J mice with increasing doses from 5 to 30 mg kg

Indexed as

biomarkerdrug abusemachine learningmetabolomicsmethamphetamine

Identifiers

PMID36557288
PMCPMC9780981
OpenAlexW4311134602

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.