Evidence mapPaperPMID 42328449Full record

ReviewInternational journal of biological sciences2026

Copper-Iron Cell Death Axis: Mechanistic Crosstalk, Disease Implications and an Integrated Metallo-Redox-Metabolic Framework.

HaoQi Huang, YuLu Chen, Yi Lu, ZiLong Yuan, Ahmed Zahoor, LiPing Ren, YuanYuan Luo, BaoCai Zhong, Jian Huang, Hui Chen and 1 more

Abstract readReview
In one paragraph

Review in International journal of biological sciences, 2026. 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

11 authors.

HaoQi HuangSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
YuLu ChenSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Yi LuSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
ZiLong YuanSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Ahmed ZahoorSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
LiPing RenSchool of Healthcare and Technology, Chengdu Neusoft University, Chengdu, Sichuan, China.
YuanYuan LuoSchool of Healthcare and Technology, Chengdu Neusoft University, Chengdu, Sichuan, China.
BaoCai ZhongSchool of Healthcare and Technology, Chengdu Neusoft University, Chengdu, Sichuan, China.
Jian HuangSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Hui ChenSchool of Healthcare and Technology, Chengdu Neusoft University, Chengdu, Sichuan, China.
Lin NingSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cuproptosis and ferroptosis are two major forms of metal-dependent cell death, characterized by mitochondrial proteotoxicity and lipid peroxidation, respectively, and are broadly implicated in diverse disease contexts. Here, by integrating mechanistic, biological, and disease-associated evidence, we propose the metal-metabolism-redox vulnerability axis, which describes cellular states under metal stress as a continuous space defined by metal homeostasis, mitochondrial metabolism, and redox balance. Within this space, cuproptosis and ferroptosis correspond to distinct execution regions rather than independent processes. Building on this concept, we further establish a metallo-redox-metabolic framework to explain how key state variables and their coupling relationships determine execution bias and drive dynamic transitions between death modalities. This framework reframes metal-dependent cell death as a state-driven system rather than a collection of discrete pathways and provides a unified perspective for understanding its roles in complex diseases. In addition, we outline predictive and testable hypotheses and highlight the importance of multi-omics integration and artificial intelligence based modeling in capturing cellular state and enabling dynamic prediction. Collectively, this work provides a conceptual foundation for understanding metal-driven cell fate decisions and for developing state-oriented therapeutic strategies.

Indexed as

CopperIronAnimalsCell DeathCuproptosisFerroptosisHumansMitochondriaOxidation-ReductionCopperIronbioinformaticscuproptosisferroptosismetal-dependent programmed cell deathmetallo-redox-metabolic framework

Identifiers

PMID42328449
PMCPMC13282742

What Socratic 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 Socratic graph.