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".

Paragraph: To analyze the course of seasonal viral infections of respiratory tract in patients hospitalized in pediatric intensive care units (PICU) of 16 centers in Turkey. Materials and methods: It is a retrospective, observational, and multicenter study conducted in 16 tertiary PICUs in Turkey includes a total of 302 children with viral cause in the nasal swab which required PICU admission with no interventions. Results: Median age of patients was 12 months. Respiratory syncytial virus (RSV) was more common in patients over one year of age whereas influenza, human Bocavirus in patients above a year of age was more common (p <0.05). Clinical presentations influencing mortality were neurologic symptoms, tachycardia, hypoxia, hypotension, elevated lactate, and acidosis. The critical pH value related with mortality was ≤7.10, and critical PCO 2 ≥60 mm Hg. Conclusion: Our findings demonstrate that patients with neurological symptoms, tachycardia, hypoxia, hypotension, acidosis, impaired liver, and renal function at the time of admission exhibit more severe mortal progressions. Presence of acidosis and multiorgan failure was found to be predictor for mortality. Knowledge of clinical presentation and age-related variations among seasonal viruses may give a clue about severe course and prognosis. By presenting the analyzed data of 302 PICU admissions, current study reveals severity of viral respiratory tract infections and release tips for handling them. 
 Title: Comprehensive Analysis of Severe Viral Infections of Respiratory Tract admitted to PICUs during the Winter Season in Turkey
True

Paragraph: Background. Experimental inoculation is an important tool for common cold and asthma research. Producing rhinovirus (RV) inocula from nasal secretions has required prolonged observation of the virus donor to exclude extraneous pathogens. We produced a RV-A16 inoculum using reverse genetics and determined the dose necessary to cause moderate colds in seronegative volunteers. Methods. The consensus sequence of RV-A16 from a previous inoculum was cloned, and inoculum virus was produced using reverse genetics techniques. After safety testing, volunteers were inoculated with either RV-A16 (n = 26) or placebo (n = 10), Jackson cold scores were recorded, and nasal secretions were tested for shedding of RV-A16 ribonucleic acid. Results. The reverse genetics process produced infectious virus that was neutralized by specific antisera and had a mutation rate similar to conventional virus growth techniques. The 1000 median tissue culture infectious dose (TCID 50 ) dose produced moderate colds in most individuals with effects similar to that of a previously tested conventional RV-A16 inoculum. Conclusions. Reverse genetics techniques produced a RV-A16 inoculum that can cause clinical colds in seronegative volunteers, and they also serve as a stable source of virus for laboratory use. The recombinant production procedures eliminate the need to derive seed virus from nasal secretions, thus precluding introduction of extraneous pathogens through this route. 
 Title: Development of a Rhinovirus Inoculum Using a Reverse Genetics Approach
False

Paragraph: Background. The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k$1), and the accuracy of confidence intervals estimated for k is typically not explored. Methodology. This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks. Conclusions. Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets. 
 Title: Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

False