Oral biofilms, formed by multiple microorganisms and their extracellular polymeric substances, seriously affect people’s life. The emergence of the resistance of biofilms to conventional antibiotics and their side effects on the oral cavity have posed a great challenge in the treatment of dental diseases. Recently, antimicrobial peptides have been recognized as promising alternatives to conventional antibiotics due to their broad antibacterial spectrum, high antibacterial activity, and specific mechanism. However, the research of their anti-biofilm behaviors is still in its infancy, and the underlying mechanism remains unclear. In this study, we investigated the anti-biofilm activities of a designed helical peptide (G3) against Streptococcus mutans (S. mutans), one of the primary causative pathogens of caries. The results indicated that G3 inhibited S. mutans biofilm formation by interfering with different stages of biofilm development. At the initial stage, G3 inhibited the bacterial adhesion by decreasing the bacterial surface charges, hydrophobicity, membrane integrity, and adhesion-related gene transcription. At the later stage, G3 interacted with extracellular DNA to destabilize the 3D architecture of mature biofilms and thus dispersed them. The high activity of G3 against S. mutans biofilms, along with its specific modes of action, endows it great application potential in preventing and treating dental plaque diseases.

The current study aims to clarify the longitudinal relations among parent emotion regulation (ER), child ER, and children’s oppositional defiant disorder (ODD) symptoms. In the current study, parents of 275 children (195 boys, 70.1%) with ODD symptoms ( Mage = 9.32 years, SD = 1.64) reported their ER using the Difficulties in Emotion Regulation Scale, child ERs using the Emotion Regulation Checklist, and children’s ODD symptoms using the eight symptoms indicated in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR) at three time points (T1, T2, and T3) within 2 years. Results indicated the longitudinal relationships between parent ER and children’s ODD symptoms were directly influenced by each other. Children’s ODD symptoms had important effects on both child ER and parent ER. Findings suggested that to reduce children’s ODD symptoms, it is necessary not only to improve child ER but also to improve parent ER.

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Because of their distinctive mode of action in targeting bacterial cell membranes, antimicrobial peptides (AMPs) are increasingly regarded as a potential candidate for the development of novel antibiotics to combat the wide spread of bacterial resistance. To date, understanding of the exact molecular process by which AMPs act on the real bacterial envelope remains challenging. Simultaneously, the aggregated state of AMPs upon interaction with bacterial envelopes is still elusive. Previously, we have demonstrated that the potent antibacterial activity of a designed surfactant-like peptide Ac−A 9 K−NH 2 benefited greatly from its high self-assembling ability and appropriate self-assembled morphologies and sizes. By using high-resolution atomic force microscopy, we here not only follow the variations of the Escherichia coli cell envelope in the presence of Ac−A 9 K−NH 2 but also characterize the peptide aggregates on the bacterial surface as well as on the substrate surface. The results, together with those from fluorescence, zeta potential, circular dichroism, and scanning electron microscopy measurements, indicate that both the positively charged peptide monomers and self-assembled nanostructures can directly act on the negatively charged bacterial surface, followed by their insertion into the bacterial membrane, the formation of surface nanopores, and membrane lysis. The mechanism of Ac−A 9 K−NH 2 against E. coli is thus consistent with the detergent-like mode of action. This work enhances our mechanistic understanding of the antibacterial behaviors of self-assembling peptides that will be valuable in exploring their biomedical applications.

In recent years, large-scale structure-based virtual screening has attracted increasing levels of interest for identification of novel compounds corresponding to potential drug targets. It is critical to understand the strengths and weaknesses of docking algorithms to increase the success rate in practical applications. Here, we systematically investigated the docking successes and failures of two representative docking programs: UCSF DOCK 3.7 and AutoDock Vina. DOCK 3.7 performed better in early enrichment on the Directory of Useful Decoys: Enhanced (DUD-E) data set, although both docking methods were roughly comparable in overall enrichment performance. DOCK 3.7 also showed superior computational efficiency. Intriguingly, the Vina scoring function showed a bias toward compounds with higher molecular weights. Both the tested docking approaches yielded incorrectly predicted ligand binding poses caused by the limitations of torsion sampling. Based on a careful analysis of docking results from six representative cases, we propose the reasons underlying docking failures; furthermore, we provide a few solutions, representing practical guidance for large-scale virtual screening campaigns and future docking algorithm development.