Ultra-Photostable Bacterial-Seeking Near-Infrared CPDs for Simultaneous NIR-II Bioimaging and Antibacterial Therapy.
Jingyi DuanBaosheng LiYanqun LiuTianyang HanFengming YeHuan XiaKaifeng LiuJie HeXueke WangQing CaiWeiyan MengShoujun ZhuPublished in: Advanced healthcare materials (2024)
Bacterial infections can pose significant health risks as they have the potential to cause a range of illnesses. These infections can spread rapidly and lead to complications if not promptly diagnosed and treated. Therefore, it is of great significance to develop a probe to selectively target and image pathogenic bacteria while simultaneously killing them, as there are currently no effective clinical solutions available. This study presents a novel approach using near-infrared carbonized polymer dots (NIR-CPDs) for simultaneous in vivo imaging and treatment of bacterial infections. The core-shell structure of the NIR-CPDs facilitates their incorporation into bacterial cell membranes, leading to an increase in fluorescence brightness and photostability. Significantly, the NIR-CPDs exhibit selective bacterial-targeting properties, specifically identifying Staphylococcus aureus (S. aureus) while sparing Escherichia coli (E. coli). Moreover, under 808 nm laser irradiation, the NIR-CPDs exhibit potent photodynamic effects by generating reactive oxygen species that target and damage bacterial membranes. In vivo experiments on infected mouse models demonstrate not only precise imaging capabilities but also significant therapeutic efficacy, with marked improvements in wound healing. The study provides the dual-functional potential of NIR-CPDs as a highly effective tool for the advancement of medical diagnostics and therapeutics in the fight against bacterial infections.
Keyphrases
- photodynamic therapy
- fluorescent probe
- escherichia coli
- fluorescence imaging
- staphylococcus aureus
- drug release
- living cells
- high resolution
- stem cells
- quantum dots
- mental health
- radiation therapy
- oxidative stress
- risk factors
- single cell
- cancer therapy
- pseudomonas aeruginosa
- biofilm formation
- deep learning
- robot assisted
- multidrug resistant
- mesenchymal stem cells
- anti inflammatory
- combination therapy