instruction:
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".
question:
Paragraph: Porcine epidemic diarrhea virus (PEDV) invades porcine intestinal epithelial cells (IECs) and causes diarrhea and dehydration in pigs. In the present study, we showed a suppression of PEDV infection in porcine jejunum intestinal epithelial cells (IPEC-J2) by an increase in autophagy. Autophagy was activated by rapamycin at a dose that does not affect cell viability and tight junction permeability. The induction of autophagy was examined by LC3I/LC3II conversion. To confirm the autophagic-flux (entire autophagy pathway), autophagolysosomes were examined by an immunofluorescence assay. Pretreatment with rapamycin significantly restricted not only a 1 h infection but also a longer infection (24 h) with PEDV, while this effect disappeared when autophagy was blocked. Co-localization of PEDV and autophagosomes suggests that PEDV could be a target of autophagy. Moreover, alleviation of PEDVinduced cell death in IPEC-J2 cells pretreated with rapamycin demonstrates a protective effect of rapamycin against PEDV-induced epithelial cell death. Collectively, the present study suggests an early prevention against PEDV infection in IPEC-J2 cells via autophagy that might be an effective strategy for the restriction of PEDV, and opens up the possibility of the use of rapamycin in vivo as an effective prophylactic and prevention treatment. 
 Title: Rapamycin-induced autophagy restricts porcine epidemic diarrhea virus infectivity in porcine intestinal epithelial cells
answer:
False


question:
Paragraph: Mycoplasma haemofelis" and "Candidatus Mycoplasma turicensis" are feline hemoplasmas that induce hemolytic anemia. Protection from homologous re-challenge was recently demonstrated in cats recovered from primary infection. Here, we determined if cats recovered from "Cand. M. turicensis" infection were protected against infections with the more pathogenic M. haemofelis. Ten specified pathogen-free cats were exposed to M. haemofelis. Five of the ten cats had recovered from "Cand. M. turicensis" bacteremia (group A), and five cats were naïve controls (group B). No cross-protection was observed. By contrast, the "Cand. M. turicensis"-recovered cats displayed faster M. haemofelis infection onset (earlier PCR-positive and anemic) than the controls. No "Cand. M. turicensis" was detected in any cat. M. haemofelis shedding was observed in saliva, feces and urine. In both groups, evidence of a Th1 response was observed (high IFN-γ, low IL-4), but IL-10 levels were also high. In group A, total, CD4+ and CD8+ T cells increased within days after M. haemofelis exposure. At times of maximal bacteremia, macrocytic hypochromic anemia, neutropenia, monocytosis and a decrease in leukocyte, eosinophil, and lymphocyte counts and subsets thereof (B-and T-cells, CD4+, CD8+ and CD4+CD25+ cells) were particularly significant in group A. Moreover, an increase in protein concentrations, hypoalbuminemia and a polyclonal hypergammaglobulinemia were observed. Five of ten M. haemofelis-infected cats subsequently cleared bacteremia without antibiotic treatment. In conclusion, the study suggests that a previous hemoplasma infection, even when the cat has ostensibly recovered, may influence subsequent infections, lead to an enhancement phenomenon and other differences in infection kinetics. 
 Title: Lack of cross-protection against Mycoplasma haemofelis infection and signs of enhancement in "Candidatus Mycoplasma turicensis"-recovered cats
answer:
True


question:
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
answer:

True