In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Ex Input:
Given the high mortality rate (>50%) and potential danger of intrapersonal transmission, highly pathogenic avian influenza (HPAI) H5N1 epidemics still pose a significant threat to humans. γδ T cells, which participate on the front line of the host immune defense, demonstrate both innate, and adaptive characteristics in their immune response and have potent antiviral activity against various viruses. However, the roles of γδ T cells in HPAI H5N1 viral infection remain unclear. In this study, we found that γδ T cells provided a crucial protective function in the defense against HPAI H5N1 viral infection. HPAI H5N1 viruses could directly activate γδ T cells, leading to enhanced CD69 expression and IFN-γ secretion. Importantly, we found that the trimer but not the monomer of HPAI H5N1 virus hemagglutinin (HA) proteins could directly activate γδ T cells. HA-induced γδ T cell activation was dependent on both sialic acid receptors and HA glycosylation, and this activation could be inhibited by the phosphatase calcineurin inhibitor cyclosporin A but not by the phosphatidylinositol 3-kinase (PI3-K) inhibitors wortmannin and LY294002. Our findings provide a further understanding the mechanism underlying γδ T cell-mediated innate and adoptive immune responses against HPAI H5N1 viral infection, which helps to develop novel therapeutic strategies for the treatment of H5N1 infection in the future.

Ex Output:
γδ T Cells Provide Protective Function in Highly Pathogenic Avian H5N1 Influenza A Virus Infection


Ex Input:
Motivation: Deep sequencing of clinical samples is now an established tool for the detection of infectious pathogens, with direct medical applications. The large amount of data generated produces an opportunity to detect species even at very low levels, provided that computational tools can effectively profile the relevant metagenomic communities. Data interpretation is complicated by the fact that short sequencing reads can match multiple organisms and by the lack of completeness of existing databases, in particular for viral pathogens. Here we present metaMix, a Bayesian mixture model framework for resolving complex metagenomic mixtures. We show that the use of parallel Monte Carlo Markov chains for the exploration of the species space enables the identification of the set of species most likely to contribute to the mixture. Results: We demonstrate the greater accuracy of metaMix compared with relevant methods, particularly for profiling complex communities consisting of several related species. We designed metaMix specifically for the analysis of deep transcriptome sequencing datasets, with a focus on viral pathogen detection; however, the principles are generally applicable to all types of metagenomic mixtures. Availability and implementation: metaMix is implemented as a user friendly R package, freely available on CRAN: http://cran.r-project.org/web/packages/metaMix Contact: sofia.morfopoulou.10@ucl.ac.uk Supplementary information: Supplementary data are available at Bionformatics online.

Ex Output:
Bayesian mixture analysis for metagenomic community profiling


Ex Input:
Zika virus (ZIKV) belongs to the Flavivirus genus of the Flaviviridae family. It is an arbovirus that can cause congenital abnormalities and is sexually transmissible. A series of outbreaks accompanied by unexpected severe clinical complications have captured medical attention to further characterize the clinical features of congenital ZIKV syndrome and its underlying pathophysiological mechanisms. Endoplasmic reticulum (ER) and ER-related proteins are essential in ZIKV genome replication. This review highlights the subcellular localization of ZIKV to the ER and ZIKV modulation on the architecture of the ER. This review also discusses ZIKV interaction with ER proteins such as signal peptidase complex subunit 1 (SPCS1), ER membrane complex (EMC) subunits, and ER translocon for viral replication. Furthermore, the review covers several important resulting effects of ZIKV infection to the ER and cellular processes including ER stress, reticulophagy, and paraptosis-like death. Pharmacological targeting of ZIKVaffected ER-resident proteins and ER-associated components demonstrate promising signs of combating ZIKV infection and rescuing host organisms from severe neurologic sequelae.

Ex Output:

Endoplasmic reticulum: a focal point of Zika virus infection