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BackgroundCurrent influenza vaccines based on the hemagglutinin protein are strain specific and do not provide good protection against drifted viruses or emergence of new pandemic strains. An influenza vaccine that can confer cross-protection against antigenically different influenza A strains is highly desirable for improving public health.Methodology/Principal FindingsTo develop a cross protective vaccine, we generated influenza virus-like particles containing the highly conserved M2 protein in a membrane-anchored form (M2 VLPs), and investigated their immunogenicity and breadth of cross protection. Immunization of mice with M2 VLPs induced anti-M2 antibodies binding to virions of various strains, M2 specific T cell responses, and conferred long-lasting cross protection against heterologous and heterosubtypic influenza viruses. M2 immune sera were found to play an important role in providing cross protection against heterosubtypic virus and an antigenically distinct 2009 pandemic H1N1 virus, and depletion of dendritic and macrophage cells abolished this cross protection, providing new insight into cross-protective immune mechanisms.Conclusions/SignificanceThese results suggest that presenting M2 on VLPs in a membrane-anchored form is a promising approach for developing broadly cross protective influenza vaccines.

the practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging for clinicians. In accordance with the increasing demands in the healthcare industry, techniques for automatic prediction and detection are being widely researched. Particularly in dentistry, for various reasons, automated mandibular canal detection has become highly desirable. The positioning of the inferior alveolar nerve (IAN), which is one of the major structures in the mandible, is crucial to prevent nerve injury during surgical procedures. However, automatic segmentation using Cone beam computed tomography (CBCT) poses certain difficulties, such as the complex appearance of the human skull, limited number of datasets, unclear edges, and noisy images. Using work-in-progress automation software, experiments were conducted with models based on 2D SegNet, 2D and 3D U-Nets as preliminary research for a dental segmentation automation tool. The 2D U-Net with adjacent images demonstrates higher global accuracy of 0.82 than naïve U-Net variants. The 2D SegNet showed the second highest global accuracy of 0.96, and the 3D U-Net showed the best global accuracy of 0.99. The automated canal detection system through deep learning will contribute significantly to efficient treatment planning and to reducing patients' discomfort by a dentist. This study will be a preliminary report and an opportunity to explore the application of deep learning to other dental fields.

BackgroundPandemic influenza poses a serious threat to global health and the world economy. While vaccines are currently under development, passive immunization could offer an alternative strategy to prevent and treat influenza virus infection. Attempts to develop monoclonal antibodies (mAbs) have been made. However, passive immunization based on mAbs may require a cocktail of mAbs with broader specificity in order to provide full protection since mAbs are generally specific for single epitopes. Chicken immunoglobulins (IgY) found in egg yolk have been used mainly for treatment of infectious diseases of the gastrointestinal tract. Because the recent epidemic of highly pathogenic avian influenza virus (HPAIV) strain H5N1 has resulted in serious economic losses to the poultry industry, many countries including Vietnam have introduced mass vaccination of poultry with H5N1 virus vaccines. We reasoned that IgY from consumable eggs available in supermarkets in Vietnam could provide protection against infections with HPAIV H5N1.Methods and FindingsWe found that H5N1-specific IgY that are prepared from eggs available in supermarkets in Vietnam by a rapid and simple water dilution method cross-protect against infections with HPAIV H5N1 and related H5N2 strains in mice. When administered intranasally before or after lethal infection, the IgY prevent the infection or significantly reduce viral replication resulting in complete recovery from the disease, respectively. We further generated H1N1 virus-specific IgY by immunization of hens with inactivated H1N1 A/PR/8/34 as a model virus for the current pandemic H1N1/09 and found that such H1N1-specific IgY protect mice from lethal influenza virus infection.ConclusionsThe findings suggest that readily available H5N1-specific IgY offer an enormous source of valuable biological material to combat a potential H5N1 pandemic. In addition, our study provides a proof-of-concept for the approach using virus-specific IgY as affordable, safe, and effective alternative for the control of influenza outbreaks, including the current H1N1 pandemic.

Major obstacles to improving the prognosis of patients with oral squamous cell carcinoma (OSCC) are the acquisition of resistance to chemotherapeutic agents and development of metastases. Recently, inflammatory signals are suggested to be one of the most important factors in modulating chemoresistance and establishing metastatic lesions. In addition, epidemiological studies have demonstrated that periodontitis, the most common chronic inflammatory condition of the oral cavity, is closely associated with oral cancer. However, a correlation between chronic periodontitis and chemoresistance/metastasis has not been well established. Herein, we will present our study on whether sustained infection with Porphyromonas gingivalis, a major pathogen of chronic periodontitis, could modify the response of OSCC cells to chemotherapeutic agents and their metastatic capability in vivo. Tumor xenografts composed of P. gingivalis–infected OSCC cells demonstrated a higher resistance to Taxol through Notch1 activation, as compared with uninfected cells. Furthermore, P. gingivalis–infected OSCC cells formed more metastatic foci in the lung than uninfected cells.