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".

Ex Input:
Paragraph: The rapid emergence and subsequent spread of the novel 2009 Influenza A/H1N1 virus (2009 H1N1) has prompted the World Health Organization to declare the first pandemic of the 21 st century, highlighting the threat of influenza to public health and healthcare systems. Widespread resistance to both classes of influenza antivirals (adamantanes and neuraminidase inhibitors) occurs in both pandemic and seasonal viruses, rendering these drugs to be of marginal utility in the treatment modality. Worldwide, virtually all 2009 H1N1 and seasonal H3N2 strains are resistant to the adamantanes (rimantadine and amantadine), and the majority of seasonal H1N1 strains are resistant to oseltamivir, the most widely prescribed neuraminidase inhibitor (NAI). To address the need for more effective therapy, we evaluated the in vitro activity of a triple combination antiviral drug (TCAD) regimen composed of drugs with different mechanisms of action against drugresistant seasonal and 2009 H1N1 influenza viruses. Amantadine, ribavirin, and oseltamivir, alone and in combination, were tested against amantadine-and oseltamivir-resistant influenza A viruses using an in vitro infection model in MDCK cells. Our data show that the triple combination was highly synergistic against drug-resistant viruses, and the synergy of the triple combination was significantly greater than the synergy of any double combination tested (P,0.05), including the combination of two NAIs. Surprisingly, amantadine and oseltamivir contributed to the antiviral activity of the TCAD regimen against amantadine-and oseltamivir-resistant viruses, respectively, at concentrations where they had no activity as single agents, and at concentrations that were clinically achievable. Our data demonstrate that the TCAD regimen composed of amantadine, ribavirin, and oseltamivir is highly synergistic against resistant viruses, including 2009 H1N1. The TCAD regimen overcomes baseline drug resistance to both classes of approved influenza antivirals, and thus may represent a highly active antiviral therapy for seasonal and pandemic influenza. 
 Title: Triple Combination of Amantadine, Ribavirin, and Oseltamivir Is Highly Active and Synergistic against Drug Resistant Influenza Virus Strains In Vitro

Ex Output:
True


Ex Input:
Paragraph: Background: Adverse events are associated with significant morbidity, mortality and cost in hospitalized patients. Measuring adverse events is necessary for quality improvement, but current detection methods are inaccurate, untimely and expensive. The advent of electronic health records and the development of automated methods for encoding and classifying electronic narrative data, such as natural language processing, offer an opportunity to identify potentially better methods. The objective of this study is to determine the accuracy of using automated methods for detecting three highly prevalent adverse events: a) hospital-acquired pneumonia, b) catheter-associated bloodstream infections, and c) in-hospital falls. Methods/design: This validation study will be conducted at two large Canadian academic health centres: the McGill University Health Centre (MUHC) and The Ottawa Hospital (TOH). The study population consists of all medical, surgical and intensive care unit patients admitted to these centres between 2008 and 2014. An automated detection algorithm will be developed and validated for each of the three adverse events using electronic data extracted from multiple clinical databases. A random sample of MUHC patients will be used to develop the automated detection algorithms (cohort 1, development set). The accuracy of these algorithms will be assessed using chart review as the reference standard. Then, receiver operating characteristic curves will be used to identify optimal cut points for each of the data sources. Multivariate logistic regression and the areas under curve (AUC) will be used to identify the optimal combination of data sources that maximize the accuracy of adverse event detection. The most accurate algorithms will then be validated on a second random sample of MUHC patients (cohort 1, validation set), and accuracy will be measured using chart review as the reference standard. The most accurate algorithms validated at the MUHC will then be applied to TOH data (cohort 2), and their accuracy will be assessed using a reference standard assessment of the medical chart. Discussion: There is a need for more accurate, timely and efficient measures of adverse events in acute care hospitals. This is a critical requirement for evaluating the effectiveness of preventive interventions and for tracking progress in patient safety through time. 
 Title: Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol

Ex Output:
True


Ex Input:
Paragraph: A recombinant Fab that recognizes a neutralizing epitope located in the (296 -400) region of protein E of dengue virus was obtained from cloned hybridoma cells secreting the mouse monoclonal antibody (mAb) 4E11. The Fd and light chain antibody genes were amplified by polymerase chain reaction, cloned into the phagemid vector pMad, expressed in bacteria to produce Fab fragments and sequenced. The mAb 4E11, in particular its light chain complementary-determining regions, shared homologies with two other anti-viral mAbs. The affinity of the parental mAb and the cloned Fab to the MalE-E(296-400) fusion protein were shown to be of the same magnitude, i.e. nanomolar. Fab 4E11 neutralization capacity was found between 8 and 4-times or less lower than that of mAb 4E11, depending on serotypes, thus the Fab could have a smaller antiviral activity than the mAb in vitro. 
 Title: A recombinant Fab neutralizes dengue virus in vitro

Ex Output:

True