Evidence map›Paper›PMID 42501412›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

De Novo-Designed Peptide-Engineered Multimodal Platform for Post-Ischemic Stroke Tissue Repair.

Yue Wang, Wen Guo, Zeqi Chen, Jianwen Ma, Fa Tian, Erkang Tian, Qiuhao Luo, Long Bai, Yu Wu, Dongdong Wu and 3 more

Abstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 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

13 authors.

Yue WangNational Engineering Research Center for Biomaterials and College of Biomedical Engineering, Sichuan University, Chengdu, China.
Wen GuoDepartment of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Zeqi ChenNational Engineering Research Center for Biomaterials and College of Biomedical Engineering, Sichuan University, Chengdu, China.
Jianwen MaCollege of Chemistry, Sichuan University, Chengdu, China.
Fa TianCollege of Information Engineering, Sichuan Agricultural University, Ya'an, China.
Erkang TianState Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Qiuhao LuoNational Engineering Research Center for Biomaterials and College of Biomedical Engineering, Sichuan University, Chengdu, China.
Long BaiTianfu Jincheng Laboratory (Frontier Medical Center), Chengdu, China.ORCID https://orcid.org/0009-0005-3674-4022
Yu WuNational Engineering Research Center for Biomaterials and College of Biomedical Engineering, Sichuan University, Chengdu, China.
Dongdong WuNational Engineering Research Center for Biomaterials and College of Biomedical Engineering, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0003-2368-2035
Li YangNational Engineering Research Center for Biomaterials and College of Biomedical Engineering, Sichuan University, Chengdu, China.
Cheng HuNational Engineering Research Center for Biomaterials and College of Biomedical Engineering, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0003-4316-231X
Yunbing WangNational Engineering Research Center for Biomaterials and College of Biomedical Engineering, Sichuan University, Chengdu, China.ORCID https://orcid.org/0000-0002-2412-6762

Funding

CAMS Innovation Fund for Medical Sciences 2021-12M-5-013Fundamental Research Funds for the Central Universities 2023SCUH0011Fundamental Research Funds for the Central Universities YJ2021115National Key Research and Development Program of China 2022YFC2402800National Key Research and Development Program of China 2023YFC2412802National Natural Science Foundation of China 22405182National Natural Science Foundation of China 32301115Natural Science Foundation of Sichuan Province 2025ZNSFSC0245Natural Science Foundation of Sichuan Province 2025ZNSFSC0889
6 · The paper itself

Abstract

Orchestrating tissue regeneration in complex pathologies like post-ischemic stroke requires materials that can precisely regulate multiple signaling pathways. A central challenge is engineering a single platform integrating mechanical, electrical, and biochemical cues to redirect these pathological networks. Here, we present a computation-driven, multimodal hydrogel engineered to function as a programmable regulatory node. The system integrates a computationally screened de novo vasculogenic peptide scaffold and surface-engineered, inflammation-responsive conductive MXene nanosheets. This rational surface engineering solves the critical bottleneck of MXene instability, preserving colloidal stability for over 2 months and maintaining high conductivity (1.2 mS/cm) within the injectable system. In a mouse model of ischemic stroke, this targeted modulation reconstructed the neurovascular unit integrity, suppressed glial scarring, and promoted remyelination and synaptic repair. Crucially, the platform re-established neural electrical signal transmission, leading to the recovery of neural function. Mechanistically, machine learning-driven transcriptomics highlighted Akt2 as a candidate regulatory hub, while untargeted metabolomics, prompted by a striking hair yellowing phenotype, suggested metabolic remodeling involving the phospholipase D signaling pathway. Our findings demonstrate a promising data-driven, bottom-up rational design paradigm for advanced bioelectronic tissue repair materials.

Indexed as

Ischemic StrokePeptidesAnimalsHydrogelsMiceTissue ScaffoldsHydrogelsPeptidesbioactive peptidesinjectable hydrogelsneurovascular regenerationpost‐ischemic stroke repair

Identifiers

PMID42501412
PMCPMC13579172

What Socratic 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 Socratic graph.