Evidence map›Paper›PMID 41757658›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

Machine Learning-Informed Nano Co-Assembly Inhibits Fibroblast Activation Protein and Improves Drug Delivery in Fibrotic Tissue.

Zehua Liu, Qiang Long, Yihao Liu, Xiuqiao Sun, Baoding Zhang, Binxin Liao, Weibin Wu, Wangxi Hai, Pei Zhang, Wenhua Lian and 6 more

Abstract read
PubMed Full text at PMC Publisher
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

16 authors.

Zehua LiuDrug Research Program, Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland.
Qiang LongDepartment of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yihao LiuDepartment of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiuqiao SunDepartment of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Baoding ZhangState Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China.
Binxin LiaoSchool of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian, China.
Weibin WuSchool of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian, China.
Wangxi HaiDepartment of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Pei ZhangDrug Research Program, Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland.
Wenhua LianState Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China.
Yuewen ZhuDepartment of Biomaterials and Biomedical Technology, The Personalized Medicine Research Institute (PRECISION), University Medical Center Groningen (UMCG), University of Groningen, Groningen, The Netherlands.
Zheng WangState Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China.
Caisheng WuSchool of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian, China.
Xianming DengState Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, China.ORCID https://orcid.org/0000-0002-9354-5864
Hélder A SantosDepartment of Biomaterials and Biomedical Technology, The Personalized Medicine Research Institute (PRECISION), University Medical Center Groningen (UMCG), University of Groningen, Groningen, The Netherlands.ORCID https://orcid.org/0000-0001-7850-6309
Xiaofeng YeDepartment of Cardiovascular Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0001-9307-636X

Funding

Academy of Finland 340129Academy of Finland 370362China Postdoctoral Science Foundation 2025M772913Finnish Foundation for Cardiovascular ResearchFundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China JYB2025XDXM506National Key Research and Development Program of China 2022YFA1105100National Natural Science Foundation for Distinguished Young Scholars of China 8212500418National Natural Science Foundation for Distinguished Young Scholars of China 82125019Natural Science Foundation of China 21574019Natural Science Foundation of China 22025702Natural Science Foundation of China 22494692Natural Science Foundation of China 22537003Natural Science Foundation of China 81571826Natural Science Foundation of China 81671832Natural Science Foundation of China 8212500418Natural Science Foundation of China 82502529Natural Science Foundation of China 92253303Shanghai Sailing Program 24YF2726200UMCG Research Funds
6 · The paper itself

Abstract

Nanoparticle-based drug delivery faces persistent challenges, including complex fabrication processes and limited lesional accumulation. Here we introduce SP-13786 (SP), a precise small-molecule inhibitor of fibroblast activation protein (FAP), as a universal and effective excipient enabling facile co-precipitation into stable nanoparticles (SCAN) with diverse hydrophobic drugs. Screening of 861 compounds revealed a broadly enhanced colloidal stability and drug loading by SP. Corresponding simulations and explainable machine learning (XML) showed SCAN assembly hinges on balanced aromaticity, rigidity, and nitrogen-mediated interaction, offering interpretable framework for co-assembly nanomedicine. Biological assessment demonstrate that SCAN enhances drug delivery and therapeutic efficacy in FAP-positive cells, therefore attentuate the fibrosis-induced drug penetration barriers, increasing drug accumulation within the fibrotic tissue. The improved bioavailability correlate with superior therapeutic outcomes in multiple disease models with progressive fibrosis. Overall, we establish SP as a versatile nanotherapeutic platform combining simplicity in preparation, mechanistic insights provided by XML, and broad applicability for diseases characterized by pathological fibrosis and impaired drug delivery.

Indexed as

Drug CarriersDrug Delivery SystemsGelatinasesMachine LearningMembrane ProteinsNanoparticlesAnimalsEndopeptidasesFibroblast Activation Protein AlphaFibrosisHumansMiceSerine EndopeptidasesDrug CarriersEndopeptidasesFibroblast Activation Protein AlphaGelatinasesMembrane ProteinsSerine Endopeptidasesfibroblast activation proteinmyocardial reperfusion injurypancreatic tumorquantitative structure‐property analysisresponsive drug deliveryself‐assembly nanoparticles

Identifiers

PMID41757658
PMCPMC13003906

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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.