Artificial intelligence‐assisted design, synthesis and analysis of smart biomaterials DOI Creative Commons
Pengfei Jiang, Yan Dai, Yujun Hou

et al.

BMEMat, Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

Abstract Smart biomaterials that can self‐adapt or respond to microenvironmental factors external signals hold excellent potential for a variety of biomedical applications, from biosensing, drug delivery, and cell therapy tissue engineering. The complexity smart biomaterials, including the rational design their structure composition, accurate analysis prediction properties, automatic scale‐up synthesis remains critical challenge but be addressed by recent rise artificial intelligence (AI). To bridge literature gap, current mini‐review will introduce background why marrying AI with is essential how biomaterial scientists integrate machine learning (ML) discovery, design, analysis, biomaterials. For this purpose, basic principles ML first introduced so use as tool research. Next, representative examples using high throughput screen establish big data structure‐function relationship responding both chemical, biological, physical signals. Most importantly, applications AI‐designed AI‐discovered overviewed, focus on field Lastly, new directions, such robot‐chemists‐assisted fabrication highlighted. Taken together, engaging most updates in material science, we expect observe continuous growth science benefit clinical translation treating diseases.

Language: Английский

DNA‐Capturing Manganese‐Coordinated Chitosan Microparticles Potentiate Radiotherapy via Activating the cGAS‐STING Pathway and Maintaining Tumor‐Infiltrating CD8+ T‐Cell Stemness DOI Open Access
Shuai Zhang, Chunjie Wang, Yujie Zhu

et al.

Advanced Materials, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 16, 2025

The radiotherapy-induced release of DNA fragments can stimulate the cyclic guanosine monophosphate-adenosine monophosphate synthase-stimulator interferon genes (cGAS-STING) pathway to prime antitumor immunity, but this is expected be less potent because inefficient cytosolic delivery negatively charged fragments. In study, manganese-coordinated chitosan (CS-Mn) microparticles with selective DNA-capturing capacity are concisely prepared via a coordination-directed one-pot synthesis process potentiate immunogenicity radiotherapy. obtained CS-Mn that undergo rapid disassembly under physiological conditions selectively bind form positively DNA-CS assemblies strong electrostatic interaction between linear and molecules. They thus enable efficient in presence serum cooperate Mn2+ activate cGAS-STING dendritic cells. Upon intratumoral injection, markedly enhance efficacy radiotherapy against both irradiated distal tumors different tumor models collectively promoting tumor-infiltrating CD8+ T-cell stemness activation innate immunity. radiosensitization effect further augmented by concurrently applying anti-programmed cell death protein 1 (anti-PD-1) immunotherapy. This work highlights an ingenious strategy prepare Trojan horse-like as cGAS-STING-activating radiosensitizers for effective radioimmunotherapy.

Language: Английский

Citations

1
Artificial intelligence‐assisted design, synthesis and analysis of smart biomaterials DOI Creative Commons
Pengfei Jiang, Yan Dai, Yujun Hou

et al.

BMEMat, Journal Year: 2025, Volume and Issue: unknown

Published: March 25, 2025

Abstract Smart biomaterials that can self‐adapt or respond to microenvironmental factors external signals hold excellent potential for a variety of biomedical applications, from biosensing, drug delivery, and cell therapy tissue engineering. The complexity smart biomaterials, including the rational design their structure composition, accurate analysis prediction properties, automatic scale‐up synthesis remains critical challenge but be addressed by recent rise artificial intelligence (AI). To bridge literature gap, current mini‐review will introduce background why marrying AI with is essential how biomaterial scientists integrate machine learning (ML) discovery, design, analysis, biomaterials. For this purpose, basic principles ML first introduced so use as tool research. Next, representative examples using high throughput screen establish big data structure‐function relationship responding both chemical, biological, physical signals. Most importantly, applications AI‐designed AI‐discovered overviewed, focus on field Lastly, new directions, such robot‐chemists‐assisted fabrication highlighted. Taken together, engaging most updates in material science, we expect observe continuous growth science benefit clinical translation treating diseases.

Language: Английский

Citations

0