Construction of Sonosensitizer‐Drug Co‐Assembly Based on Deep Learning Method DOI
Kanqi Wang, Liuyin Yang, Xiaowei Lu

et al.

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

Published: May 16, 2025

Abstract Drug co‐assemblies have attracted extensive attention due to their advantages of easy preparation, adjustable performance and drug component co‐delivery. However, the lack a clear reasonable co‐assembly strategy has hindered wide application promotion drug‐co assembly. This paper introduces deep learning‐based sonosensitizer‐drug interaction (SDI) model predict particle size mixture. To analyze factors influencing after mixing, graph neural network is employed capture atomic, bond, structural features molecules. A multi‐scale cross‐attention mechanism designed integrate feature representations different scale substructures two drugs, which not only improves prediction accuracy but also allows for analysis impact molecular structures on predictions. Ablation experiments evaluate properties, comparisons with other machine learning methods show superiority, achieving 90.00% precision, 96.00% recall, 91.67% F1‐score. Furthermore, SDI predicts chemotherapy methotrexate (MET) sonosensitizer emodin (EMO) form nanomedicine NanoME. further validated through experiments, demonstrating that NanoME can be used fluorescence imaging liver cancer sonodynamic/chemotherapy anticancer therapy.

Language: Английский

Polymeric Polylactic Acid–Glycolic Acid-Based Nanoparticles Deliver Nintedanib Across the Blood–Brain Barrier to Inhibit Glioblastoma Growth DOI Open Access

Ying Dang,

Zhi‐Wen Zhao, Bo Wang

et al.

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(2), P. 443 - 443

Published: Jan. 7, 2025

The aim of this study was to investigate the inhibitory effect nintedanib (BIBF) on glioblastoma (GBM) cells and its mechanism action optimize a drug delivery strategy overcome limitations posed by blood-brain barrier (BBB). We analyzed inhibition GBM cell lines following BIBF treatment explored autophagy pathway. cytotoxicity assessed using CCK-8 assay, further techniques such as transmission electron microscopy, Western blotting (WB), flow cytometry were employed demonstrate that could block autophagic pathway inhibiting fusion autophagosomes lysosomes, ultimately limiting proliferation cells. Molecular docking surface plasmon resonance (SPR) experiments indicated specifically binds autophagy-associated protein VPS18, interfering with function normal progression autophagy. However, application in therapy is limited due restricted penetration across BBB. Therefore, utilized poly-lactic-co-glycolic acid (PLGA) nanocarriers system significantly enhance efficiency vivo. In vitro cellular vivo animal model validation demonstrated PLGA-BIBF NPs effectively overcame BBB, enhanced antitumor activity BIBF, improved therapeutic efficacy BALB/c-Nude model. This exerted significant effects binding VPS18 Combined PLGA nanocarrier system, permeability anti-tumor enhanced. Targeting BIBF-VPS18 optimizing through nanotechnology may represent new for treatment, providing innovative clinical ideas theoretical basis patients GBM.

Language: Английский

Citations

1
Design Considerations for Organ-Selective Nanoparticles DOI
Min‐Jun Baek, Won Hur, Satoshi Kashiwagi

et al.

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: April 7, 2025

Nanoparticles (NPs) have been extensively researched for targeted diagnostic imaging and drug delivery, yet their clinical translation remains limited, with only a few achieving Food Drug Administration approval. This limited success is primarily due to challenges in precise organ- or tissue-specific targeting, which arise from off-target tissue accumulation suboptimal clearance profiles. Herein we examine the critical role of physicochemical properties, including size, surface charge, shape, elasticity, hardness, density, governing biodistribution, targetability, NPs. We highlight recent advancements engineering NPs showcasing both significant progress remaining field nanomedicine. Additionally, discuss emerging tools technologies that are being developed address these challenges. Based on insights materials science, biomedical engineering, computational biology, research, propose key design considerations next-generation nanomedicines enhanced organ selectivity.

Language: Английский

Citations

1
Computer‐Aided Design of Self‐Assembled Nanoparticles to Enhance Cancer Chemoimmunotherapy via Dual‐Modulation Strategy DOI Open Access
Xiaoting Shan, Ying Cai,

Binyu Zhu

et al.

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

Published: Jan. 19, 2025

Abstract The rational design of self‐assembled compounds is crucial for the highly efficient development carrier‐free nanomedicines. Herein, based on computer‐aided strategies, important physicochemical properties are identified to guide compounds. Then, pharmacophore hybridization strategy used self‐assemble nanoparticles by preparing new chemical structures combining groups different bioactive Hydroxychloroquine grafted with lipophilic vitamin E succinate and then co‐assembled bortezomib fabricate nanoparticle. nanoparticle can reduce M2‐type tumor‐associated macrophages (TAMs) through lysosomal alkalization induce immunogenic cell death (ICD) nuclear factor‐κB (NF‐κB) inhibition in tumor cells. In mouse models, decreased levels TAMs, regulatory T cells, transforming growth factor‐β (TGF‐β), increase proportion cytotoxicity lymphocytes. Additionally, secretion Interleukin‐6 (IL‐6) inhibiting NF‐κB enhance programmed ligand‐1 (PD‐L1) checkpoint blockade therapy. hybridization‐derived provides a dual‐modulation reprogram microenvironment, which will efficiently chemoimmunotherapy against triple‐negative breast cancer.

Language: Английский

Citations

0
Sustainable biosynthesis of silver nanoparticles from Gmelina arborea: Photocatalytic, in vitro biological implications, and in silico analysis for microbial metalloproteins DOI

Milan Thakar,

Pooja Trivedi,

Gaurang Sindhav

et al.

Journal of Molecular Liquids, Journal Year: 2025, Volume and Issue: 422, P. 126966 - 126966

Published: Jan. 21, 2025

Language: Английский

Citations

0
Breaking the barriers in effective and safe toll-like receptor stimulation via nano-immunomodulators for potent cancer immunotherapy DOI
Yaoqi Li, Yitian Chen, Yongan Tang

et al.

Journal of Controlled Release, Journal Year: 2025, Volume and Issue: unknown, P. 113667 - 113667

Published: March 1, 2025

Language: Английский

Citations

0
Biocompatible lipid nanovehicles for preventive and therapeutic vaccine development DOI

Yaru Jia,

Ziran Zhou,

Luksika Jiramonai

et al.

Coordination Chemistry Reviews, Journal Year: 2025, Volume and Issue: 538, P. 216718 - 216718

Published: April 22, 2025

Language: Английский

Citations

0
Engineered Cell Membrane Coating Technologies for Biomedical Applications: From Nanoscale to Macroscale DOI
Yongqi An, Cheng Ji, Hao Zhang

et al.

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: March 24, 2025

Cell membrane coating has emerged as a promising strategy for the surface modification of biomaterials with biological membranes, serving cloak that can carry more functions. The cloaked inherit diverse intrinsic biofunctions derived from different cell sources, including enhanced biocompatibility, immunity evasion, specific targeting capacity, and immune regulation regenerative microenvironment. characteristics biomimicry biointerfacing have demonstrated versatility technology on variety biomaterials, thus, furthering research into wide range biomedical applications clinical translation. Here, preparation coatings is emphasized, sizes coated nanoscale to macroscale well engineering strategies introduce additional are summarized. Subsequently, utilization biomimetic membrane-cloaked in discussed, drug delivery, imaging phototherapy, cancer immunotherapy, anti-infection detoxification, implant modification. In conclusion, latest advancements preclinical studies, along multiple benefits membrane-coated nanoparticles (NPs) systems, elucidated.

Language: Английский

Citations

0
The Transformative Role of Nanotechnology in the Management of Diabetes Mellitus: Insights from Current Research DOI Creative Commons
Natalia G. Vallianou, Μaria Dalamaga,

Argyro Pavlou

et al.

Biomolecules, Journal Year: 2025, Volume and Issue: 15(5), P. 653 - 653

Published: May 1, 2025

Nanotechnology refers to the science that modulates molecules nanoscale dimension. Nanomedicine, i.e., utilization of nanotechnology for diagnosing and treating several disorders, is a subject ongoing research. The concept behind nanomedicine in diabetes mellitus (DM) treatment stems from need ameliorate absorption distribution antidiabetic therapies order overcome barriers, namely pH throughout gastrointestinal tract, gut microbiota, temperature/heat difficulties incorporation drugs into cells. Thus, scope particularly challenging demanding, considering fact human body perpetually changing entity achieve homeostasis. In this review, we will delve various nanoparticles are being studied terms treatment, their pros cons expanding knowledge field. Despite seems be very promising, there still many gaps our understanding how addresses its utilization. Moreover, high costs, along with an as-yet unclear safety profile, remain significant barrier widespread adoption. describe both phytochemicals chemical compounds seeks exploit pave way more efficacious comprehensive management mellitus.

Language: Английский

Citations

0
Construction of Sonosensitizer‐Drug Co‐Assembly Based on Deep Learning Method DOI
Kanqi Wang, Liuyin Yang, Xiaowei Lu

et al.

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

Published: May 16, 2025

Abstract Drug co‐assemblies have attracted extensive attention due to their advantages of easy preparation, adjustable performance and drug component co‐delivery. However, the lack a clear reasonable co‐assembly strategy has hindered wide application promotion drug‐co assembly. This paper introduces deep learning‐based sonosensitizer‐drug interaction (SDI) model predict particle size mixture. To analyze factors influencing after mixing, graph neural network is employed capture atomic, bond, structural features molecules. A multi‐scale cross‐attention mechanism designed integrate feature representations different scale substructures two drugs, which not only improves prediction accuracy but also allows for analysis impact molecular structures on predictions. Ablation experiments evaluate properties, comparisons with other machine learning methods show superiority, achieving 90.00% precision, 96.00% recall, 91.67% F1‐score. Furthermore, SDI predicts chemotherapy methotrexate (MET) sonosensitizer emodin (EMO) form nanomedicine NanoME. further validated through experiments, demonstrating that NanoME can be used fluorescence imaging liver cancer sonodynamic/chemotherapy anticancer therapy.

Language: Английский

Citations

0