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: The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to outperform several prominent methods in identifying strongly binding peptides. As a method with demonstrated performance in the quantitative modeling of MHCpeptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential.
Title: Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models
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False

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Paragraph: The rebirth of modern analytical ultracentrifugation (AUC) began in 1990s. Since then many advanced AUC detectors have been developed that provide a vast range of versatile choices when characterizing the physical and chemical features of macromolecules. In addition, there have been remarkable advances in software that allow the analysis of AUC data using more sophisticated models, including quaternary structures, conformational changes, and biomolecular interactions. Here we report the application of AUC to protein size-and-shape distribution analysis and structure-and-function analysis in the presence of ligands or lipids. Using band-sedimentation velocity, quaternary structural changes and an enzyme's catalytic activity can be observed simultaneously. This provides direct insights into the correlation between quaternary structure and catalytic activity of the enzyme. On the other hand, also in this study, we have applied size-and-shape distribution analysis to a lipid-binding protein in either an aqueous or lipid environment. The sedimentation velocity data for the protein with or without lipid were evaluated using the c(s,f r ) two-dimensional distribution model, which provides a precise and quantitative means of analyzing the protein's conformational changes.
Title: Applications of analytical ultracentrifugation to protein size-and-shape distribution and structure-and-function analyses
answer:
False

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Paragraph: Introduction Viral acute respiratory infections (ARIs) cause substantial child morbidity. Sensitive molecularbased assays aid virus detection, but the clinical significance of positive tests remains uncertain as some viruses may be found in both acutely ill and healthy children. We describe disease-pathogen associations of respiratory viruses and quantify virus-specific attributable risk of ARIs in healthy children during the first 2 years of life. Methods One hundred fifty-eight term newborn babies in Brisbane, Australia, were recruited progressively into a longitudinal, community-based, birth cohort study conducted between September 2010 and October 2014. A daily tick-box diary captured predefined respiratory symptoms from birth until their second birthday. Weekly parent-collected nasal swabs were batch-tested for 17 respiratory viruses by PCR assays, allowing calculation of virus-specific attributable fractions in the exposed (AFE) to determine the proportion of virus-positive children whose ARI symptoms could be attributed to that particular virus. Results Of 8100 nasal swabs analysed, 2646 (32.7%) were virus-positive (275 virus codetections, 3.4%), with human rhinoviruses accounting for 2058/2646 (77.8%) positive swabs. Viruses were detected in 1154/1530 (75.4%) ARI episodes and in 984/4308 (22.8%) swabs from asymptomatic periods. Respiratory syncytial virus (AFE: 68% (95% CI 45% to 82%)) and human metapneumovirus (AFE: 69% (95% CI 43% to 83%)) were strongly associated with higher risk of lower respiratory symptoms. Discussion The strong association of respiratory syncytial virus and human metapneumovirus with ARIs and lower respiratory symptoms in young children managed within the community indicates successful development of vaccines against these two viruses should provide substantial health benefits.
Title: Viruses causing lower respiratory symptoms in young children: findings from the ORChID birth cohort Respiratory infection
answer:
True