BACKGROUND Prophylactic vaccines are critical in preventing hand, foot, and mouth disease (HFMD) primarily caused by human enterovirus 71 (EV71) infection. Children aged less than 5 years are especially susceptible to EV71 infections. In addition to the development of vaccines containing the inactivated virus, those containing virus-like particles (VLPs) with repeated antigens also constitute an effective preventive strategy for EV71 infections, with safety and productivity advantages. We previously developed a fusion protein composed with truncated peptides of the EV71 capsid protein, which assembled into spherical particles. This study aimed to assess the immunoprotective effects of this fusion protein as a vaccine candidate in a mouse model of EV71 infection. METHODS To evaluate the protective effect of fusion protein vaccine candidate, neonatal mice born by immunized female mice, as well as normal neonatal mice immunized twice were infected with EV71 virus. https://www.selleckchem.com/products/ski-ii.html Whereafter, the survival rates, clinical scores and viral loads were measured. RESULTS The high dosage and booster immunization helped induce specific serum antibodies with high neutralization titers, which were transferred to neonatal mice, thereby facilitating effective resistance towards EV71 infection. An active immune response was also observed in neonatal mice which generated following immunization. CONCLUSIONS The present results suggest that this fusion protein is a suitable vaccine candidate in treating EV71 infections.BACKGROUND Itch is an unpleasant sensation that can be debilitating, especially if it is chronic and of non-histaminergic origin, as treatment options are limited. Endothelin-1 (ET-1) is a potent endogenous vasoconstrictor that also has the ability to induce a burning, non-histaminergic pruritus when exogenously administered, by activating the endothelin A receptor (ETAR) on primary afferents. ET-1 is released endogenously by several cell-types found in the skin, including macrophages and keratinocytes. Mast cells express ETARs and can thereby be degranulated by ET-1, and mast cell proteases chymase and carboxypeptidase A3 (CPA3) are known to either generate or degrade ET-1, respectively, suggesting a role for mast cell proteases in the regulation of ET-1-induced itch. The mouse mast cell proteases (mMCPs) mMCP4 (chymase), mMCP6 (tryptase), and CPA3 are found in connective tissue type mast cells and are the closest functional homologs to human mast cell proteases, but little is known about their role in endothelin-induced itch. METHODS In this study, we evaluated the effects of mast cell protease deficiency on scratching behavior induced by ET-1. To investigate this, mMCP knock-out and transgenic mice were injected intradermally with ET-1 and their scratching behavior was recorded and analyzed. RESULTS CPA3-deficient mice and mice lacking all three proteases demonstrated highly elevated levels of scratching behavior compared with wild-type controls. A modest increase in the number of scratching bouts was also seen in mMCP6-deficient mice, while mMCP4-deficiency did not have any effect. CONCLUSION Altogether, these findings identify a prominent role for the mast cell proteases, in particular CPA3, in the protection against itch induced by ET-1.BACKGROUND SARS-CoV-2 is a RNA coronavirus responsible for the pandemic of the Severe Acute Respiratory Syndrome (COVID-19). RNA viruses are characterized by a high mutation rate, up to a million times higher than that of their hosts. Virus mutagenic capability depends upon several factors, including the fidelity of viral enzymes that replicate nucleic acids, as SARS-CoV-2 RNA dependent RNA polymerase (RdRp). Mutation rate drives viral evolution and genome variability, thereby enabling viruses to escape host immunity and to develop drug resistance. METHODS We analyzed 220 genomic sequences from the GISAID database derived from patients infected by SARS-CoV-2 worldwide from December 2019 to mid-March 2020. SARS-CoV-2 reference genome was obtained from the GenBank database. Genomes alignment was performed using Clustal Omega. Mann-Whitney and Fisher-Exact tests were used to assess statistical significance. RESULTS We characterized 8 novel recurrent mutations of SARS-CoV-2, located at positions 1397, 2891, 14408iety in a SARS-CoV-2 RdRp hydrophobic cleft, which is adjacent to the 14408 mutation we identified. Consequently, it is important to study and characterize SARS-CoV-2 RdRp mutation in order to assess possible drug-resistance viral phenotypes. It is also important to recognize whether the presence of some mutations might correlate with different SARS-CoV-2 mortality rates.BACKGROUND Trigger finger is a common hand disease, which is caused by a mismatch in diameter between the tendon and the pulley. Ultrasound images are typically used to diagnose this disease, which are also used to guide surgical treatment. However, background noise and unclear tissue boundaries in the images increase the difficulty of the process. To overcome these problems, a computer-aided tool for the identification of finger tissue is needed. RESULTS Two datasets were used for evaluation one comprised different cases of individual images and another consisting of eight groups of continuous images. Regarding result similarity and contour smoothness, our proposed deeply supervised dilated fully convolutional DenseNet (D2FC-DN) is better than ATASM (the state-of-art segmentation method) and representative CNN methods. As a practical application, our proposed method can be used to build a tendon and synovial sheath model that can be used in a training system for ultrasound-guided trigger finger surgery. CONCLUSION We proposed a D2FC-DN for finger tendon and synovial sheath segmentation in ultrasound images. The segmentation results were remarkably accurate for two datasets. It can be applied to assist the diagnosis of trigger finger by highlighting the tissues and generate models for surgical training systems in the future. METHODS We propose a novel finger tendon segmentation method for use with ultrasound images that can also be used for synovial sheath segmentation that yields a more complete description for analysis. In this study, a hybrid of effective convolutional neural network techniques are applied, resulting in a deeply supervised dilated fully convolutional DenseNet (D2FC-DN), which displayed excellent segmentation performance on the tendon and synovial sheath.