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 evaluated the impact of serum uric acid (SUA) on mortality in patients with chronic dialysis. A total of 4132 adult patients on dialysis were enrolled prospectively between August 2008 and September 2014. Among them, we included 1738 patients who maintained dialysis for at least 3 months and had available SUA in the database. We categorized the time averaged-SUA (TA-SUA) into 5 groups: <5.5, 5.5-6.4, 6.5-7.4, 7.5-8.4, and 8.5 mg/dL. Cox regression analysis was used to calculate the hazard ratio (HR) of all-cause mortality according to SUA group. The mean TA-SUA level was slightly higher in men than in women. Patients with lower TA-SUA level tended to have lower body mass index (BMI), phosphorus, serum albumin level, higher proportion of diabetes mellitus (DM), and higher proportion of malnourishment on the subjective global assessment (SGA). During a median follow-up of 43.9 months, 206 patients died. Patients with the highest SUA had a similar risk to the middle 3 TA-SUA groups, but the lowest TA-SUA group had a significantly elevated HR for mortality. The lowest TA-SUA group was significantly associated with increased all-cause mortality (adjusted HR, 1.720; 95% confidence interval, 1.007-2.937; P = 0.047) even after adjusting for demographic, comorbid, nutritional covariables, and medication use that could affect SUA levels. This association was prominent in patients with well nourishment on the SGA, a preserved serum albumin level, a higher BMI, and concomitant DM although these parameters had no significant interaction in the TA-SUA-mortality relationship except DM. In conclusion, a lower TA-SUA level <5.5 mg/dL predicted all-cause mortality in patients with chronic dialysis. Abbreviations: ESRD = end-stage renal disease, TA-SUA = time-averaged serum uric acid.
Solution: Lower serum uric acid level predicts mortality in dialysis patients