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.

[Q]: Background: Avian leukosis virus (ALV) is a major infectious disease that impacts the poultry industry worldwide. Despite intensive efforts, no effective vaccine has been developed against ALV because of mutations that lead to resistant forms. Therefore, there is a dire need to develop antiviral agents for the treatment of ALV infections and RNA interference (RNAi) is considered an effective antiviral strategy. Results: In this study, the avian leukosis virus subgroup J (ALV-J) proviral genome, including the gag genes, were treated as targets for RNAi. Four pairs of miRNA sequences were designed and synthesized that targeted different regions of the gag gene. The screened target (i.e., the gag genes) was shown to effectively suppress the replication of ALV-J by 19.0-77.3%. To avoid the generation of escape variants during virus infection, expression vectors of multi-target miRNAs were constructed using the multi-target serial strategy (against different regions of the gag, pol, and env genes). Multi-target miRNAs were shown to play a synergistic role in the inhibition of ALV-J replication, with an inhibition efficiency of viral replication ranging from 85.0-91.2%. Conclusion: The strategy of multi-target miRNAs might be an effective method for inhibiting ALV replication and the acquisition of resistant mutations.
[A]: Enhanced inhibition of Avian leukosis virus subgroup J replication by multi-target miRNAs


[Q]: Background: Feline leishmaniosis caused by Leishmania infantum is considered a rare disease in endemic areas, whereas subclinical infections are common. Immune response plays a key role in driving the course of L. infantum infection in other host species; however, the feline cell-mediated immune response to L. infantum infection has not yet been investigated. The aim of this study was to determine the cell-mediated immune response specific to L. infantum by means of interferon (IFN)-γ release in whole blood assay from cats living in endemic areas (66 in Sicily and 113 in Catalonia) and to compare with antibody levels to L. infantum [enzyme-linked immunosorbent assay (ELISA) and immunofluorescence antibody test (IFAT)], blood parasite load and retroviral infections. Results: Most cats (n = 140) were L. infantum antibody negative and only 22% (n = 39) were positive. Only 9 and 2% of tested cats had a feline immunodeficency virus (FIV) infection or a feline leukemia virus (FeLV) infection, respectively. Thirty-two cats out of 179 (18%) produced IFN-γ after stimulation with L. infantum soluble antigen (LSA) while the majority of cats (93%) produced IFN-γ after stimulation with concanavalin A (ConA). Six LSA-IFN-γ-producer cats were seropositive (three to ELISA and five to IFAT) but they were polymerase chain reaction (PCR) negative, while only one cat was antibody-and PCR-positive. Significant positive correlations were found between IFN-γ concentrations after stimulation with LSA and ConA, and between serology and PCR testing. No association was found between FIV status and LSA or ConA-IFN-γ production. Combining PCR, serology and specific IFN-γ concentration results, we found that 36% of cats studied were exposed to L. infantum. As expected, cats from endemic areas produce IFN-γ after ex vivo blood stimulation with LSA and therefore are able to activate a cell-mediated adaptive immune response against the parasite that is variably associated with antibody or blood PCR positivity. The association of this assay to serological and molecular tests provides a better estimate of cat exposure to L. infantum.
[A]: Leishmania infantum-specific IFN-γ production in stimulated blood from cats living in areas where canine leishmaniosis is endemic


[Q]: Although there are a large number of thesauri for the biomedical domain many of them lack coverage in terms and their variant forms. Automatic thesaurus construction based on patterns was first suggested by Hearst [1], but it is still not clear how to automatically construct such patterns for different semantic relations and domains. In particular it is not certain which patterns are useful for capturing synonymy. The assumption of extant resources such as parsers is also a limiting factor for many languages, so it is desirable to find patterns that do not use syntactical analysis. Finally to give a more consistent and applicable result it is desirable to use these patterns to form synonym sets in a sound way. We present a method that automatically generates regular expression patterns by expanding seed patterns in a heuristic search and then develops a feature vector based on the occurrence of term pairs in each developed pattern. This allows for a binary classifications of term pairs as synonymous or non-synonymous. We then model this result as a probability graph to find synonym sets, which is equivalent to the well-studied problem of finding an optimal set cover. We achieved 73.2% precision and 29.7% recall by our method, out-performing hand-made resources such as MeSH and Wikipedia. We conclude that automatic methods can play a practical role in developing new thesauri or expanding on existing ones, and this can be done with only a small amount of training data and no need for resources such as parsers. We also concluded that the accuracy can be improved by grouping into synonym sets.
[A]:
Synonym set extraction from the biomedical literature by lexical pattern discovery