TASK DEFINITION: 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".
PROBLEM: Paragraph: Infectious bronchitis (IB) is a highly contagious upper respiratory tract disease of chickens caused by infectious bronchitis virus (IBV), which has various serotypes that do not cross-protect. Vaccine control strategies for this virus are only effective when designed around the currently circulating serotypes. It is essential to not only rapidly detect IBV but also to identify the type of virus causing disease. Six TaqMan™️-based quantitative realtime RT-PCR assays (Universal, Ark, Mass, DE/GA98, GA07, GA08) were developed and examined the sensitivity and specificity for each assay. Assays were developed targeting the hypervariable region in the S1 gene subunit. The analytical sensitivity of TaqMan™️-based quantitative real-time RT-PCR assays (qRT-PCR) assays was evaluated using synthetic DNA standards that were identical with the target sequence and specificity was further validated using clinical and biological specimens. All developed assays performed equivalently when using synthetic DNA templates as standard material, as it achieved linearity over a 5 log 10 dynamic range with a reproducible limit of detection of 10 target copies per reaction, with high calculated amplification efficiencies ranging between 90%-115%. Further validation of specificity using clinical and biological specimens was also successful.
Title: Validation of specific quantitative real-time RT-PCR assay panel for Infectious Bronchitis using synthetic DNA standards and clinical specimens

SOLUTION: True

PROBLEM: Paragraph: The NIAID (National Institute for Allergy and Infectious Diseases) Biodefense Proteomics program aims to identify targets for potential vaccines, therapeutics, and diagnostics for agents of concern in bioterrorism, including bacterial, parasitic, and viral pathogens. The program includes seven Proteomics Research Centers, generating diverse types of pathogen-host data, including mass spectrometry, microarray transcriptional profiles, protein interactions, protein structures and biological reagents. The Biodefense Resource Center (www.proteomicsresource.org) has developed a bioinformatics framework, employing a protein-centric approach to integrate and support mining and analysis of the large and heterogeneous data. Underlying this approach is a data warehouse with comprehensive protein + gene identifier and name mappings and annotations extracted from over 100 molecular databases. Value-added annotations are provided for key proteins from experimental findings using controlled vocabulary. The availability of pathogen and host omics data in an integrated framework allows global analysis of the data and comparisons across different experiments and organisms, as illustrated in several case studies presented here. (1) The identification of a hypothetical protein with differential gene and protein expressions in two host systems (mouse macrophage and human HeLa cells) infected by different bacterial (Bacillus anthracis and Salmonella typhimurium) and viral (orthopox) pathogens suggesting that this protein can be prioritized for additional analysis and functional characterization. (2) The analysis of a vaccinia-human protein interaction network supplemented with protein accumulation levels led to the identification of human Keratin, type II cytoskeletal 4 protein as a potential therapeutic target. (3) Comparison of complete genomes from pathogenic variants coupled with experimental information on complete proteomes allowed the identification and prioritization of ten potential diagnostic targets from Bacillus anthracis. The integrative analysis across data sets from multiple centers can reveal potential functional significance and hidden relationships between pathogen and host proteins, thereby providing a systems approach to basic understanding of pathogenicity and target identification.
Title: Systems Integration of Biodefense Omics Data for Analysis of Pathogen-Host Interactions and Identification of Potential Targets

SOLUTION: False

PROBLEM: Paragraph: Antimicrobial stewardship program aims to reduce antibiotic use. Periodic measurement and monitoring of antibiotic use and comparison within the institution as well as with other organizations are important indicators. We analyzed antibiotic usage in a general hospital in Saudi Arabia. Antibiotic data were collected retrospectively for 2011 and from 2013 to 2015, and only adult patients (>15 year of age) were included in the study. Data were presented as days of therapy (DOT) and defined daily dose (DDD). DDD was adjusted per 100 bed-days and according to the case mix index (CMI). The total DDD was 37,557 in 2013, 36,550 in 2014 and 38,738 in 2015. The DDD per 100 patient-days was 90.7-94.5. There was a discordant findings of antibiotic measurements based on the DDD compared to DOT, and DDD/100 beddays compared to DOT/100 bed-days. There was a negative correlation between CMI and DDD per 100 bed days (r 0.696), but a positive correlation of CMI with DOT (r +0.93). Adjusted DDD/100 bed-days showed decrease in the usage of antibiotics, reflecting activities of the antibiotic stewardship program. The increase in DOT/100 bed-days may indicate the favorable utilization of combination therapy. Antibiotic usage needs to be adjusted per 100 bed-days and correlated with CMI for better reflection of optimal antibiotic utilization, activities of the antibiotic stewardship program, and to allow benchmarking.
Title: Benchmarking of antibiotic usage: An adjustment to reflect antibiotic stewardship program outcome in a hospital in Saudi Arabia

SOLUTION:
False