Evidence map›Paper›PMID 36090543›Full record

ArticleEmergency medicine international2022

Application of Melatonin with N-Acetylcysteine Exceeds Traditional Treatment for Acetaminophen-Induced Hepatotoxicity.

Mengfei Chen, Jinfang Ke, Shilan Ma, Hua Chai, Liang Zhang, Ling Zhang

RetractedOpen access · goldAbstract readRetracted Publication
In one paragraph

Article in Emergency medicine international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Mengfei ChenDepartment of Emergency, People's Hospital of Ningxia Hui Autonomous Region, Ningxia, China.
Jinfang KeDepartment of Emergency, People's Hospital of Ningxia Hui Autonomous Region, Ningxia, China.
Shilan MaDepartment of Emergency, People's Hospital of Ningxia Hui Autonomous Region, Ningxia, China.
Hua ChaiDepartment of Emergency, People's Hospital of Ningxia Hui Autonomous Region, Ningxia, China.
Liang ZhangDepartment of Emergency, People's Hospital of Ningxia Hui Autonomous Region, Ningxia, China.
Ling ZhangDepartment of Emergency, People's Hospital of Ningxia Hui Autonomous Region, Ningxia, China.ORCID https://orcid.org/0000-0001-7576-680X
The Fourth People's Hospital of Ningxia Hui Autonomous Region · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acetaminophen (APAP) overdose is one of the leading causes of acute liver damage. Given N-acetylcysteine (NAC) and melatonin (MLT) both have an attenuated value for APAP-induced liver toxification, where an optimized integrated treatment has not been well deciphered. Here, by giving a single dose of APAP (500 mg/kg) to wild-type male mice, combined with a single dose of 500 mg/kg NAC or 100 mg/kg MLT separately as the therapeutic method, this study aimed to investigate the effects of NAC and melatonin (MLT) alone or combined on acetaminophen (APAP)-induced liver injury. In this study, NAC and MLT both partially have an alleviated function in APAP-challenged liver injury. However, MLT's add-on role strengthens the hepatoprotective effect of NAC on APAP-induced liver damage and resolute the inflammatory infiltration. Meanwhile, the combination of two reagents attenuates the decreased glutathione (GSH) and activation of the p38/JNK pathway. The combination of MLT and NAC can further ameliorate APAP-induced liver injury, which provides a novel strategy for drug-induced liver injury (DILI).

Identifiers

PMID36090543
PMCPMC9463034
OpenAlexW4295437235

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.