A Ferrous-Supply-Regenerating Lipid Nanoparticle Integrating RNAi Induces Ferroptosis for Cancer Therapy.

Dun Hu, Yun-Hua Xu, Dan Peng, Qi Tan, Jun-Lin Jiang, Sheng-Dan Nie, Shan Wang

Abstract read

In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 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

7 authors.

Dun HuCollege of Chemistry and Chemical Engineering, Central South University, Hunan, People's Republic of China.ORCID https://orcid.org/0000-0002-5529-9455

Yun-Hua XuCollege of Chemistry and Chemical Engineering, Central South University, Hunan, People's Republic of China.

Dan PengDepartment of Pharmacology Xiangya School of Pharmacy, Central South University, Hunan, People's Republic of China.

Qi TanR&D, Rayzon Medical Technology Co., Ltd., Hunan, People's Republic of China.

Jun-Lin JiangDepartment of Pharmacology Xiangya School of Pharmacy, Central South University, Hunan, People's Republic of China.ORCID https://orcid.org/0000-0002-9897-2523

Sheng-Dan NieInstitute of Clinical Medicine, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Hunan, China.

Shan WangCollege of Chemistry and Chemical Engineering, Central South University, Hunan, People's Republic of China.ORCID https://orcid.org/0000-0002-1402-1051

Funding

National Natural Science Foundation of China 82170850

6 · The paper itself

Abstract

Targeting iron-dependent ferroptosis with siRNA has emerged as a promising strategy for cancer treatment. The concept of ferrous-supply regeneration, inspired by electro-Fenton technology, has also gained interest as a non-apoptotic approach to induce ferroptosis. However, integrating both strategies into a single lipid nanoparticle (LNP) remains challenging. To address this, we developed ALSF, a novel LNP in which DSPC is replaced with arachidonic acid (AA) to enable co-delivery of Glutathione Peroxidase 4-siRNA (GPX4-siRNA) and Fe

Indexed as

FerroptosisLipidsNanoparticlesNeoplasmsRNA InterferenceAnimalsCell Line, TumorHumansHydrogen PeroxideIronLipid PeroxidationLiposomesMiceMice, NudePhospholipid Hydroperoxide Glutathione PeroxidaseReactive Oxygen SpeciesHydrogen PeroxideIronLipid NanoparticlesLipidsLiposomesPhospholipid Hydroperoxide Glutathione PeroxidaseReactive Oxygen SpeciesRNA, Small Interferingarachidonic acidferroptosisGPX4iron cyclinglipid nanoparticlessmall interfering RNA

Identifiers

PMID42528415

DOI10.1002/smll.74925

PMCPMC13630411

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

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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.