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.
One example is below.
Q: 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.
A: Development and evaluation of an efficient 3 -noncoding region-based SARS coronavirus (SARS-CoV) RT-PCR assay for detection of SARS-CoV
Rationale: 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.
Q: Geographical variations in cardiovascular disease rates have been linked to individual air pollutants. Investigating the relation between cardiovascular disease and exposure to a complex mixture of air pollutants requires holistic approaches. We assessed the relationship between exposure to multiple air pollutants and the incidence of coronary heart disease (CHD) in a general population sample. We collected data in the Lille MONICA registry (2008-2011) on 3268 incident cases (age range: 35-74). Based on 20 indicators, we derived a composite environmental score (SEnv) for cumulative exposure to air pollution. Poisson regression models were used to analyse associations between CHD rates on one hand and SEnv and each single indicator on the other (considered in tertiles, where T3 is the most contaminated). We adjusted models for age, sex, area-level social deprivation, and neighbourhood spatial structure. The incidence of CHD was a spatially heterogeneous (p=0.006). There was a significant positive association between SEnv and CHD incidence (trend p=0.0151). The relative risks [95%CI] of CHD were 1.08 [0.98-1.18] and 1.16 [1.04-1.29] for the 2nd and 3rd tertile of SEnv exposure. In the single pollutant analysis, PM 10 , NO 2 , cadmium, copper, nickel, and palladium were significantly associated with CHD rates. Multiple air pollution was associated with an increased risk of CHD. Single pollutants reflecting road traffic pollution were the most strongly associated with CHD. Our present results are consistent with the literature data on the impact of road traffic on the CHD risk in urban areas.
A:
Exposure to multiple air pollutants and the incidence of coronary heart disease: A fine-scale geographic analysis