Efficacy of peptide-based enamel coatings in the prevention of demineralization using fixed orthodontic brackets in a rat model.

INTRODUCTION: White spot lesions (WSLs) represent a prominent pathology encountered during orthodontic treatment, originating from enamel demineralization induced by the accumulation of bacterial biofilms. The previously developed bioinspired enamel coating form of self-assembling antimicrobial peptide D-GL13K exhibited antimicrobial activity and enhanced acid impermeability, offering a potential solution to prevent demineralization. The primary aim of this investigation is to assess the in vivo anti-demineralization properties and biocompatibility of the D-GL13K coating. METHODS: A rat model was developed to assess the antimicrobial enamel coating during fixed orthodontic treatment. The anti-demineralization efficacy attributed to the D-GL13K coating was evaluated by employing optical coherence tomography, Vickers microhardness testing, and scanning electron microscopy. The biocompatibility of the D-GL13K coating was investigated through histologic observations of vital organs and tissues using hematoxylin and eosin. RESULTS: The D-GL13K coating demonstrated significant anti-demineralization effects, evidenced by reduced demineralization depth analyzed through optical coherence tomography and enhanced Vickers hardness than in the noncoated control group, showcasing the coating's potential to protect teeth from WSLs. Scanning electron microscopy analysis further elucidated the diminished enamel damage observed in the group treated with D-GL13K. Importantly, histologic examination of vital organs and tissues using hematoxylin and eosin staining revealed no overt disparities between the D-GL13K coated group and the noncoated control group. CONCLUSIONS: The D-GL13K enamel coating demonstrated promising anti-demineralization and biocompatibility properties in a rat model, thereby suggesting its potential for averting WSLs after orthodontic interventions. Further research in human clinical settings is needed to evaluate the coating's long-term efficacy.

Multifunctional nanocoating for enhanced titanium implant osseointegration.

Preventing bacterial infection and promoting osseointegration are essential for the long-term success of titanium (Ti) implants. In this study, we developed a multifunctional nanocoating on Ti mini-implants to simultaneously address these challenges. The nanocoating consists of self-assembled antimicrobial peptides GL13K and silver nanoparticles, referred to as Ag-GL. Our results showed that the Ag-GL coating did not alter the surface morphology of the mini-implants. Ag-GL coated mini-implants demonstrated a two orders of magnitude reduction in colony-forming unit (CFU) values compared to the noncoated eTi group, resulting in minimal inflammation and no apparent bone destruction in a bacterial infection in vivo model. When evaluating osseointegration properties, micro-CT analysis, histomorphometric analysis, and pull-out tests revealed that the Ag-GL coating significantly enhanced osseointegration and promoted new bone formation in vivo.

Modeling Driver Behavior near Intersections in Hidden Markov Model.

Intersections are one of the major locations where safety is a big concern to drivers. Inappropriate driver behaviors in response to frequent changes when approaching intersections often lead to intersection-related crashes or collisions. Thus to better understand driver behaviors at intersections, especially in the dilemma zone, a Hidden Markov Model (HMM) is utilized in this study. With the discrete data processing, the observed dynamic data of vehicles are used for the inference of the Hidden Markov Model. The Baum-Welch (B-W) estimation algorithm is applied to calculate the vehicle state transition probability matrix and the observation probability matrix. When combined with the Forward algorithm, the most likely state of the driver can be obtained. Thus the model can be used to measure the stability and risk of driver behavior. It is found that drivers' behaviors in the dilemma zone are of lower stability and higher risk compared with those in other regions around intersections. In addition to the B-W estimation algorithm, the Viterbi Algorithm is utilized to predict the potential dangers of vehicles. The results can be applied to driving assistance systems to warn drivers to avoid possible accidents.