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: The recent Ebola virus disease outbreak emphasized the potential misuse of personal protective equipment (PPE) by health care workers (HCWs) during such an event. We aimed to compare selfperceived proficiency of PPE use and objective performance, and identify predictors of low compliance and PPE misuse. Methods: An observational study combined with subjective questionnaires were carried out during a bioterror simulation drill. Forty-two observers evaluated performance under PPE. Mistakes were recorded and graded using a structured observational format and were correlated with the subjective questionnaires and with demographic parameters. Results: One hundred seventy-eight HCWs from community clinics and hospitals were included. The mean self-perceived proficiency was high (6.1 out of 7), mean level of comfort was moderate (4.0 out of 7), and mean objective performance was intermediate (9.5 out of 13). There was no correlation between comfort and objective performance scores. Self-perceived proficiency was in correlation with donning and continuous performance with PPE but not with doffing. Clinic personnel performed better than personnel in hospitals (40.3% vs 67.8% with 3 or more mistakes, respectively; P = .001). Demographic characteristics had no correlation with objective or self-perceived performance. Conclusions: Self-perceived proficiency is a poor predictor of appropriate PPE use. The results suggest poor awareness of the possibility of PPE misuse. 
 Title: The association between self-perceived proficiency of personal protective equipment and objective performance: An observational study during a bioterrorism simulation drill
[A]: False


[Q]: Paragraph: Background: Pseudomonas aeruginosa (PA) is an opportunistic Gram-negative bacterium that causes serious life threatening and nosocomial infections including pneumonia. PA has the ability to alter host genome to facilitate its invasion, thus increasing the virulence of the organism. Sphingosine-1-phosphate (S1P), a bioactive lipid, is known to play a key role in facilitating infection. Sphingosine kinases (SPHK) 1&2 phosphorylate sphingosine to generate S1P in mammalian cells. We reported earlier that Sphk2 −/− mice offered significant protection against lung inflammation, compared to wild type (WT) animals. Therefore, we profiled the differential expression of genes between the protected group of Sphk2 −/− and the wild type controls to better understand the underlying protective mechanisms related to the Sphk2 deletion in lung inflammatory injury. Whole transcriptome shotgun sequencing (RNA-Seq) was performed on mouse lung tissue using NextSeq 500 sequencing system. Results: Two-way analysis of variance (ANOVA) analysis was performed and differentially expressed genes following PA infection were identified using whole transcriptome of Sphk2 −/− mice and their WT counterparts. Pathway (PW) enrichment analyses of the RNA seq data identified several signaling pathways that are likely to play a crucial role in pneumonia caused by PA such as those involved in: 1. Immune response to PA infection and NF-κB signal transduction; 2. PKC signal transduction; 3. Impact on epigenetic regulation; 4. Epithelial sodium channel pathway; 5. Mucin expression; and 6. Bacterial infection related pathways. Our genomic data suggests a potential role for SPHK2 in PA-induced pneumonia through elevated expression of inflammatory genes in lung tissue. Further, validation by RT-PCR on 10 differentially expressed genes showed 100% concordance in terms of vectoral changes as well as significant fold change. (Continued on next page) 
 Title: Genetic deletion of Sphk2 confers protection against Pseudomonas aeruginosa mediated differential expression of genes related to virulent infection and inflammation in mouse lung
[A]: False


[Q]: Paragraph: Infectious diseases exert a large and in many contexts growing burden on human health, but violate most of the assumptions of classical epidemiological statistics and hence require a mathematically sophisticated approach. Viral shedding data are collected during human studies-either where volunteers are infected with a disease or where existing cases are recruited-in which the levels of live virus produced over time are measured. These have traditionally been difficult to analyse due to strong, complex correlations between parameters. Here, we show how a Bayesian approach to the inverse problem together with modern Markov chain Monte Carlo algorithms based on information geometry can overcome these difficulties and yield insights into the disease dynamics of two of the most prevalent human pathogens-influenza and norovirus-as well as Ebola virus disease. 
 Title: Bayesian uncertainty quantification for transmissibility of influenza, norovirus and Ebola using information geometry
[A]:
True