Methicillin-resistant Staphylococcus aureus (MRSA) is among the common drug resistant bacteria, which has gained worldwide attention due to its high drug resistance and infection rates. Biofilms produced by S. aureus are known to increase antibiotic resistance, making the treatment of S. aureus infections even more challenging. Hence, inhibition of biofilm formation has become an alternative strategy for controlling persistent infections. In this study, we evaluated the efficacy of geraniol as a treatment for MRSA biofilm infection. The results of crystal violet staining indicated that 256 μg/mL concentration of geraniol inhibited USA300 biofilm formation by 86.13% and removed mature biofilms by 49.87%. Geraniol exerted its anti-biofilm effect by influencing the major components of the MRSA biofilm structure. We found that geraniol inhibited the synthesis of major virulence factors, including staphyloxanthin and autolysins. The colony count revealed that geraniol inhibited staphyloxanthin and sensitized USA300 cells to hydrogen peroxide. Interestingly, geraniol not only reduced the release of extracellular nucleic acids (eDNA) but also inhibited cell autolysis. Real-time polymerase chain reaction data revealed the downregulation of genes involved in biofilm formation, which verified the results of the phenotypic analysis. Geraniol increased the effect of vancomycin in eliminating USA300 biofilms in a mouse infection model. Our findings revealed that geraniol effectively inhibits biofilm formation in vitro. Furthermore, in combination with vancomycin, geraniol can reduce the biofilm adhesion to the implant in mice. This suggests the potential of geraniol as an anti-MRSA biofilm drug and can provide a solution for the clinical treatment of biofilm infection.

The COVID-19 pandemic has had an enormous impact on traditional tourism. Influenced by the uncertainties of the current epidemic, to revive the development of tourism and local economics, local governments have used short video accounts to release tourist promotion short videos for publicizing and marketing. This study takes official promotion short videos as the research object, establishes a structural equation model based on the SOR theory, and explores the influencing factors of official short videos on tourists’ destination decisions through empirical analysis. It finds that the official promotion short videos can positively stimulate users’ perception and sentiments significantly due to the three unique features of authority, interactivity and interest, thus influencing tourists’ destination decision-making behavior. On this basis, this study proposes to improve the operation of an official short video from three aspects: enhancing the authority of official short video accounts, attaching importance to the interactive mechanism, and strengthening the creativity of short videos. It is hoped that the study may help enhance the influence of official promotion short videos and promote the high-quality development of local tourism.

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Recently, AutoRegressive (AR) models for the whole image generation empowered by transformers have achieved comparable or even better performance to Generative Adversarial Networks (GANs). Unfortunately, directly applying such AR models to edit/change local image regions, may suffer from the problems of missing global information, slow inference speed, and information leakage of local guidance. To address these limitations, we propose a novel model -image Local Autoregressive Transformer (iLAT), to better facilitate the locally guided image synthesis. Our iLAT learns the novel local discrete representations, by the newly proposed local autoregressive (LA) transformer of the attention mask and convolution mechanism. Thus iLAT can efficiently synthesize the local image regions by key guidance information. Our iLAT is evaluated on various locally guided image syntheses, such as pose-guided person image synthesis and face editing. Both the quantitative and qualitative results show the efficacy of our model.