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.
Example: The severe acute respiratory syndrome (SARS) epidemic originating from China in 2002 was caused by a previously uncharacterized coronavirus that could be identified by specific RT-PCR amplification. Efforts to control future SARS outbreaks depend on the accurate and early identification of SARS-CoV infected patients. A real-time fluorogenic RT-PCR assay based on the 3 -noncoding region (3 -NCR) of SARS-CoV genome was developed as a quantitative SARS diagnostic tool. The ideal amplification efficiency of a sensitive SARS-CoV RT-PCR assay should yield an E value (PCR product concentration increase per amplification cycle) equal to 2.0. It was demonstrated that the 3 -NCR SARS-CoV based RT-PCR reactions could be formulated to reach excellent E values of 1.81, or 91% amplification efficacy. The SARS-CoV cDNA preparations derived from viral RNA extract and the cloned recombinant plasmid both exhibit the identical amplification characteristics, i.e. amplification efficacy using the same PCR formulation developed in this study. The viral genomic copy (or genomic equivalences, GE) per infectious unit (GE/pfu) of SARS-CoV used in this study was also established to be approximate 1200-1600:1. The assay's detection sensitivity could reach 0.005 pfu or 6-8 GE per assay. It was preliminarily demonstrated that the assay could efficiently detect SARS-CoV from clinical specimens of SARS probable and suspected patients identified in Taiwan. The 3 -NCR based SARS-CoV assay demonstrated 100% diagnostic specificity testing samples of patients with acute respiratory disease from a non-SARS epidemic region.
Example solution: Development and evaluation of an efficient 3 -noncoding region-based SARS coronavirus (SARS-CoV) RT-PCR assay for detection of SARS-CoV
Example explanation: It's a correct title because the paragraph described the development of 3 -noncoding region of SARS-CoV genome and assay efficiently detecting SARS-CoV from clinical specimens.

Problem: We examined associations between single-nucleotide polymorphisms (SNPs) of IFITM3, TLR3, and CD55 genes and influenza clinical outcomes in Chinese. A multicenter study was conducted on 275 adult cases of avian (H7N9) and pandemic (H1N1 pdm09 ) influenza. Host DNA was extracted from diagnostic respiratory samples; IFITM3 rs12252, TLR3 rs5743313, CD55 rs2564978, and TLR4 rs4986790/4986791 were targeted for genotyping (Sanger sequencing). The primary outcome analyzed was death. Results. IFITM3 and TLR3 SNPs were in Hardy-Weinberg equilibrium; their allele frequencies (IFITM3/C-allele 0.56, TLR3/Callele 0.88) were comparable to 1000 Genomes Han Chinese data. We found over-representation of homozygous IFITM3 CC (54.5% vs 33.2%; P = .02) and TLR3 CC (93.3% vs 76.9%; P = .04) genotypes among fatal cases. Recessive genetic models showed their significant independent associations with higher death risks (adjusted hazard ratio [aHR] 2.78, 95% confidence interval [CI] 1.29-6.02, and aHR 4.85, 95% CI 1.1121.06, respectively). Cumulative effects were found (aHR 3.53, 95% CI 1.647.59 per risk genotype; aHR 9.99, 95% CI 1.2778.59 with both). Results were consistent for each influenza subtype and other severity indicators. The CD55 TT genotype was linked to severity. TLR4 was nonpolymorphic. Conclusions. Host genetic factors may influence clinical outcomes of avian and pandemic influenza infections. Such findings have important implications on disease burden and patient care in at-risk populations.
Solution: IFITM3, TLR3, and CD55 Gene SNPs and Cumulative Genetic Risks for Severe Outcomes in Chinese Patients With H7N9/H1N1 pdm09 Influenza