A novel antibacterial and fluorescent coating composed of polydopamine and carbon dots on the surface of orthodontic brackets.

Many kinds of antibacterial coatings have been designed to prevent the adherence of bacteria onto the surface of a fixed orthodontic device of brackets. However, the problems such as weak binding force, undetectable, drug resistance, cytotoxicity and short duration needed to be solved. Thus, it has great value in developing novel coating methods with long-term antibacterial and fluorescence properties according to the clinical application of brackets. In this study, we synthesized blue fluorescent carbon dots (HCDs) using the traditional Chinese medicinal honokiol, which could cause irreversible killing effects on both gram-positive and gram-negative bacteria through positive charges on the surface and inducing reactive oxygen species (ROS) production. Based on this, the surface of brackets was serially modified with polydopamine and HCDs, taking advantage of the strong adhesive properties as well as the negative surface charge of polydopamine particles. It is found that this coating exhibits stable antibacterial properties in 14 days with good biocompatibility, which can provide a new solution and strategy to solve the series of hazards caused by bacterial adhesion on the surface of orthodontic brackets.

High-efficiency reinforcement learning with hybrid architecture photonic integrated circuit.

Reinforcement learning (RL) stands as one of the three fundamental paradigms within machine learning and has made a substantial leap to build general-purpose learning systems. However, using traditional electrical computers to simulate agent-environment interactions in RL models consumes tremendous computing resources, posing a significant challenge to the efficiency of RL. Here, we propose a universal framework that utilizes a photonic integrated circuit (PIC) to simulate the interactions in RL for improving the algorithm efficiency. High parallelism and precision on-chip optical interaction calculations are implemented with the assistance of link calibration in the hybrid architecture PIC. By introducing similarity information into the reward function of the RL model, PIC-RL successfully accomplishes perovskite materials synthesis task within a 3472-dimensional state space, resulting in a notable 56% improvement in efficiency. Our results validate the effectiveness of simulating RL algorithm interactions on the PIC platform, highlighting its potential to boost computing power in large-scale and sophisticated RL tasks.

Carbon dots and composite materials with excellent performances in cancer-targeted bioimaging and killing: a review.

Carbon dots (CDs) are nanomaterials with excellent properties, including good biocompatibility, small size, ideal photoluminescence and surface modification, and are becoming one of the most attractive nanomaterials for the imaging, detection and treatment of tumors. Based on these advantages, CDs can be combined other materials to obtain composite particles with improved, even new, performance, mainly in photothermal and photodynamic therapies. This paper reviews the research progress of CDs and their composites in targeted tumor imaging, detection, diagnosis, drug delivery and tumor killing. It also discusses and proposes the challenges and perspectives of their future applications in these fields. This review provides ideas for future applications of novel CD-based materials in the diagnosis and treatment of cancer.