From passive bionics to active adaptation: a new strategy for tissue regeneration based on cell-autonomous construction of microenvironments DOI Creative Commons

Ji-ji Zhou,

Zhenyu Wen, Zhikai Wang

et al.

Published: April 1, 2025

Language: Английский

Nanofibrous Scaffolds’ Ability to Induce Mesenchymal Stem Cell Differentiation for Soft Tissue Regenerative Applications DOI Creative Commons
Silvia Pisani,

A EVANGELISTA,

Luca Chesi

et al.

Pharmaceuticals, Journal Year: 2025, Volume and Issue: 18(2), P. 239 - 239

Published: Feb. 11, 2025

Mesenchymal stem cells (MSCs) have gained recognition as a highly versatile and promising cell source for repopulating bioengineered scaffolds due to their inherent capacity differentiate into multiple types. However, MSC implantation techniques often yielded inconsistent clinical results, underscoring the need advanced approaches enhance therapeutic efficacy. Recent developments in three-dimensional (3D) provided significant breakthrough by closely mimicking vivo environment, addressing limitations of traditional two-dimensional (2D) cultures. Among these, nanofibrous proven particularly effective, offering an optimal 3D framework, growth-permissive substrates, delivery trophic factors crucial survival regeneration. Furthermore, selection appropriate biomaterials can amplify paracrine effects MSCs, promoting both proliferation targeted differentiation. The synergistic combination MSCs with has demonstrated remarkable potential achieving repair, regeneration, tissue-specific differentiation enhanced safety efficacy, paving way routine applications. In this review, we examine most recent studies (2013–2023) that explore combined use cardiogenic, epithelial, myogenic, tendon, vascular lineages. Using PubMed, identified analyzed 275 relevant articles based on search terms “Nanofibers”, “Electrospinning”, “Mesenchymal cells”, “Differentiation”. This review highlights critical advancements platform tissue By summarizing key findings from last decade, it provides valuable insights researchers clinicians aiming optimize scaffold design, integration, translational These could significantly influence future research directions development more effective regenerative therapies.

Language: Английский

Citations

0

AI‐Guided Design of Antimicrobial Peptide Hydrogels for Precise Treatment of Drug‐resistant Bacterial Infections DOI
Zhihui Jiang,

Jianwen Feng,

Fan Wang

et al.

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

Published: March 30, 2025

Abstract Traditional biomaterial development lacks systematicity and predictability, posing significant challenges in addressing the intricate engineering issues related to infections with drug‐resistant bacteria. The unprecedented ability of artificial intelligence (AI) manage complex systems offers a novel paradigm for materials development. However, no AI model currently guides antibacterial biomaterials based on an in‐depth understanding interplay between In this study, AI‐guided design platform (AMP‐hydrogel‐Designer) is developed generate biomaterials. This utilizes generative multi‐objective constrained optimization thiol‐containing high‐efficiency antimicrobial peptide (AMP), that functionally coupled hydrogel form network structure. Additionally, Cu‐modified barium titanate (Cu‐BTO) incorporated facilitate further cross–linking via Cu 2+ /SH coordination produce AI‐AMP‐hydrogel. vitro, AI‐AMP‐hydrogel exhibits > 99.99% bactericidal efficacy against Methicillin‐resistant Staphylococcus aureus (MRSA) Escherichia coli ( E. coli) . Furthermore, Cu‐BTO converts mechanical stimulation into electrical signals, thereby promoting expression growth factors angiogenesis. rat dynamic wounds, AI‐AMP significantly reduces MRSA load markedly accelerates wound healing. Therefore, strategy innovative solution precisely treat bacterial infections.

Language: Английский

Citations

0

From passive bionics to active adaptation: a new strategy for tissue regeneration based on cell-autonomous construction of microenvironments DOI Creative Commons

Ji-ji Zhou,

Zhenyu Wen, Zhikai Wang

et al.

Published: April 1, 2025

Language: Английский

Citations

0