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: Classifying the mechanisms of antibiotic failure has led to the development of new treatment strategies for killing bacteria. Among the currently described mechanismswhich include resistance, persistence and tolerancewe propose defiance as a subclass of antibiotic failure specific to prodrugs. Using locked antimicrobial peptides (AMP) that are activated by bacterial 5 proteases as a prototypic prodrug, we observe that although treatment eliminates bacteria across the vast majority of environmental conditions (e.g., temperature, concentration of growth nutrients), bacteria spontaneously switch from susceptibility to defiance under conditions that alter the competing rates between bacterial proliferation and prodrug activation. To identify the determinants of this switch-like behavior, we model bacteria-prodrug dynamics as a multi-rate 10 feedback system and identify a dimensionless quantity we call the Bacterial Advantage Heuristic (BAH) that perfectly classifies bacteria as either defiant or susceptible across a broad range of treatment conditions. By recognizing that the bacterial switch from susceptibility to defiance behaves analogously to electronic transistors, we construct prodrug logic gates (e.g., AND, OR, NOT, etc.) to allow assembly of an integrated 3-bit multi-prodrug circuit that kills defiant bacteria 15 under all possible combinations of BAH values (i.e., 000, 001, , 111) that represent a broad range of possible treatment conditions. Our study identifies a form of bacterial resistance specific to prodrugs that is described by a predictive dimensionless constant to reveal logic-based treatment strategies using multi-prodrug biological circuits.
A:
Prodrug defiance reveals logic-based strategies for treating bacterial resistance