In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Input: Consider Input: Recent studies suggest an association between the Interferon Inducible Transmembrane 3 (IFITM3) rs12252 variant and the course of influenza infection. However, it is not clear whether the reported association relates to influenza infection severity. The aim of this study was to estimate the hospitalization risk associated with this variant in Influenza Like Illness (ILI) patients during the H1N1 pandemic influenza. A case-control genetic association study was performed, using nasopharyngeal/oropharyngeal swabs collected during the H1N1 pandemic influenza. Laboratory diagnosis of influenza infection was performed by RT-PCR, the IFITM3 rs12252 was genotyped by RFLP and tested for association with hospitalization. Conditional logistic regression was performed to calculate the confounder-adjusted odds ratio of hospitalization associated with IFITM3 rs12252. We selected 312 ILI cases and 624 matched non-hospitalized controls. Within ILI Influenza A(H1N1)pdm09 positive patients, no statistical significant association was found between the variant and the hospitalization risk (Adjusted OR: 0.73 (95%CI: 0.33-1.50)). Regarding ILI Influenza A(H1N1)pdm09 negative patients, CT/CC genotype carriers had a higher risk of being hospitalized than patients with TT genotype (Adjusted OR: 2.54 (95%CI: 1.54-4.19)). The IFITM3 rs12252 variant was associated with respiratory infection hospitalization but not specifically in patients infected with Influenza A(H1N1)pdm09.

Output: Hospitalization Risk Due to Respiratory Illness Associated with Genetic Variation at IFITM3 in Patients with Influenza A(H1N1)pdm09 Infection: A Case-Control Study


Input: Consider Input: Computational (in silico) methods have been developed and widely applied to pharmacology hypothesis development and testing. These in silico methods include databases, quantitative structure-activity relationships, similarity searching, pharmacophores, homology models and other molecular modeling, machine learning, data mining, network analysis tools and data analysis tools that use a computer. Such methods have seen frequent use in the discovery and optimization of novel molecules with affinity to a target, the clarification of absorption, distribution, metabolism, excretion and toxicity properties as well as physicochemical characterization. The first part of this review discussed the methods that have been used for virtual ligand and target-based screening and profiling to predict biological activity. The aim of this second part of the review is to illustrate some of the varied applications of in silico methods for pharmacology in terms of the targets addressed. We will also discuss some of the advantages and disadvantages of in silico methods with respect to in vitro and in vivo methods for pharmacology research. Our conclusion is that the in silico pharmacology paradigm is ongoing and presents a rich array of opportunities that will assist in expediating the discovery of new targets, and ultimately lead to compounds with predicted biological activity for these novel targets.

Output: In silico pharmacology for drug discovery: applications to targets and beyond


Input: Consider Input: Flu response centre Public health Helpline Emerging disease s u m m a r y Objective: To assess the operational experience and knowledge of staff who worked in the West Midlands Flu Response Centre (FRC) during the 'containment' phase of influenza A(H1N1)pdm09. using an online self-administered questionnaire. The questionnaire included sections related to the respondents' FRC experience, knowledge about influenza A(H1N1)pdm09 and the containment phase. Results: This study had a 51% (89/176) response rate. Of the respondents, 59% were female, 64% were of White ethnicity, 55% were clinicians, 46% were aged 25e44 years, and 67% had no previous call centre experience. A significant proportion (P < 0.001) of respondents believed that the FRC had made a positive contribution to the public health management of the containment phase. Nearly all respondents indicated that they were familiar with the terms 'pandemic flu' or 'influenza pandemic' (99%), understood the aim of the containment phase (90%), and knew the severity of the illness caused by the virus (97%). However, specific knowledge was lacking regarding a number of public health interventions, and overall knowledge scores for clinicians and non-clinicians were similar. Conclusion: This study is the first to report on the characteristics of FRC staff during the containment phase of influenza A(H1N1)pdm09 pandemic. Although overall, staff evaluation of the West Midlands FRC was very positive, a number of knowledge gaps were identified. This study provides valuable insights which can contribute to preparedness planning.


Output: Characteristics of flu response centre staff in the West Midlands