Evidence map›Paper›PMID 42903898›Full record

ReviewhLife2024

Single-cell omics in tracing cellular heterogeneity of drug-induced liver injury: Technological landscape and prospective application.

Xia Mao, Mingzhu Xu, Xiangying Yan, Lin Chen, Na Lin, Yanqiong Zhang

Abstract readReview
In one paragraph

Review in hLife, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xia MaoInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Mingzhu XuInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Xiangying YanInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Lin ChenArtemisinin Research Center, China Academy of Chinese Medical Sciences, Beijing, China.
Na LinInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.
Yanqiong ZhangInstitute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug-induced liver injury (DILI) remains a serious problem in clinics for both diagnoses and treatment decisions. It is a result of accumulated drugs in human bodies metabolized into toxic constituents generating reactive metabolites, and then arise initial consequences of oxidative stress, organelle stress responses, and lethal consequences (liver necrosis or apoptosis). However, the idiosyncratic nature of DILI complexes its mechanistic studies and still little is known of its potential etiopathogenesis for certain. Single-cell omics technology and approaches serve as powerful tools for investigating cellular heterogeneity and relationships from measurements of up to millions of individual cells at an unprecedented resolution, which are achieved by advances in genome, epigenome, transcriptome, proteome, and metabolism technologies. As liver contains heterogeneous cell types of distinct spatial, molecular, and functional properties, they interact with each other to precede cell type-specific omics reprogramming and play an irreplaceable role in liver cells with heterogeneous properties upon encountering toxic insults. Single-cell omics, especially single-cell transcriptomics and single-cell proteomics, have been utilized for exploring the mechanisms of DILI and prediction for risk factors. In this review, we discuss the recent development and future perspectives of single-cell omics-based technologies for DILI-related research.

Indexed as

cellular heterogeneitydrug-induced liver injurymolecular mechanismrisk predictionsingle-cell omics

Identifiers

PMID42903898
PMCPMC13681521

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.