In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

[Q]: Paragraph: In ostriches, the population densities resulting from intensive rearing increases susceptibility to pathogens such as mycoplasmas. In addition to good management practices, vaccination offers an attractive alternative for controlling mycoplasma infections in food animals, instead of using antibiotics, which often leave unacceptable residues. The use of live attenuated vaccines, however, carry the concern of reversion to virulence or genetic recombination with field strains. Currently there are no commercially available vaccines against ostrich-infecting mycoplasmas and this study therefore set out to develop and evaluate the use of a DNA vaccine against mycoplasma infections in ostriches using an OppA protein as antigen. To this end, the oppA gene of "Mycoplasma nasistruthionis sp. nov." str. Ms03 was cloned into two DNA vaccine expression vectors after codon correction by site-directed mutagenesis. Three-months-old ostriches were then vaccinated intramuscularly at different doses followed by a booster vaccination after 6 weeks. The ability of the DNA vaccines to elicit an anti-OppA antibody response was evaluated by ELISA using the recombinant OppA protein of Ms03 as coating antigen. A statistically significant anti-OppA antibody response could be detected after administration of a booster vaccination indicating that the OppA protein was successfully immunogenic. The responses were also both dose and vector dependent. In conclusion, the DNA vaccines were able to elicit an immune response in ostriches and can therefore be viewed as an option for the development of vaccines against mycoplasma infections.
Title: DNA Vaccines Against Mycoplasma Elicit Humoral Immune Responses in Ostriches
[A]: False

[Q]: Paragraph: Viruses evolve extremely quickly, so reliable methods for viral host prediction are necessary to safeguard biosecurity and biosafety alike. Novel human-infecting viruses are difficult to detect with standard bioinformatics workflows. Here, we predict whether a virus can infect humans directly from next-generation sequencing reads. We show that deep neural architectures significantly outperform both shallow machine learning and standard, homology-based algorithms, cutting the error rates in half and generalizing to taxonomic units distant from those presented during training. We propose a new approach for convolutional filter visualization to disentangle the information content of each nucleotide from its contribution to the final classification decision. Nucleotide-resolution maps of the learned associations between pathogen genomes and the infectious phenotype can be used to detect virulencerelated genes in novel agents, as we show here for the SARS-CoV-2 coronavirus, unknown before it caused a COVID-19 pandemic in 2020.
Title: Interpretable detection of novel human viruses from genome sequencing data
[A]: True

[Q]: Paragraph: Viruses readily mutate and gain the ability to infect novel hosts, but few data are available regarding the number of possible host range-expanding mutations allowing infection of any given novel host, and the fitness consequences of these mutations on original and novel hosts. To gain insight into the process of host range expansion, we isolated and sequenced 69 independent mutants of the dsRNA bacteriophage 6 able to infect the novel host, Pseudomonas pseudoalcaligenes. In total, we found at least 17 unique suites of mutations among these 69 mutants. We assayed fitness for 13 of 17 mutant genotypes on P. pseudoalcaligenes and the standard laboratory host, P. phaseolicola. Mutants exhibited significantly lower fitnesses on P. pseudoalcaligenes compared to P. phaseolicola. Furthermore, 12 of the 13 assayed mutants showed reduced fitness on P. phaseolicola compared to wildtype 6, confirming the prevalence of antagonistic pleiotropy during host range expansion. Further experiments revealed that the mechanistic basis of these fitness differences was likely variation in host attachment ability. In addition, using computational protein modeling, we show that host-range expanding mutations occurred in hotspots on the surface of the phage's host attachment protein opposite a putative hydrophobic anchoring domain.
Title: Frequency and Fitness Consequences of Bacteriophage 6 Host Range Mutations
[A]:
True