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: In the last 20 years, surface plasmon resonance (SPR) and its advancement with imaging (SPRi) emerged as a suitable and reliable platform in clinical analysis for labelfree, sensitive, and real-time monitoring of biomolecular interactions. Thus, we report in this review the state of the art of clinical target detection with SPR-based biosensors in complex matrices (e.g., serum, saliva, blood, and urine) as well as in standard solution when innovative approaches or advanced instrumentations were employed for improved detection. The principles of SPR-based biosensors are summarized first, focusing on the physical properties of the transducer, on the assays design, on the immobilization chemistry, and on new trends for implementing system analytical performances (e.g., coupling with nanoparticles (NPs). Then we critically review the detection of analytes of interest in molecular diagnostics, such as hormones (relevant also for anti-doping control) and biomarkers of interest in inflammatory, cancer, and heart failure diseases. Antibody detection is reported in relation to immune disorder diagnostics. Subsequently, nucleic acid targets are considered for revealing genetic diseases (e.g., point mutation and single nucleotides polymorphism, SNPs) as well as new emerging clinical markers (microRNA) and for pathogen detection. Finally, examples of pathogen detection by immunosensing were also analyzed. A parallel comparison with the reference methods was duly made, indicating the progress brought about by SPR technologies in clinical routine analysis.
Solution: Surface plasmon resonance applications in clinical analysis