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.

[EX Q]: An oligonucleotide array (microarray) incorporating 13,000 elements representing selected strains of hepatitis A virus (HAV), human coxsackieviruses A and B (CVA and CVB), genogroups I and II of Norovirus (NV), and human rotavirus (RV) gene segments 3,4,10, and 11 was designed based on the principle of tiling. Each oligonucleotide was 29 bases long, starting at every 5 th base of every sequence, resulting in an overlap of 24 bases in two consecutive oligonucleotides. The applicability of the array for virus identification was examined using PCR amplified products from multiple HAV and CV strains. PCR products labeled with biotin were hybridized to the array, and the biotin was detected using a brief reaction with Cy3-labeled streptavidin, the array subjected to laser scanning, and the hybridization data plotted as fluorescence intensity against each oligonucleotide in the array. The combined signal intensities of all probes representing a particular strain of virus were calculated and plotted against all virus strains identified on a linear representation of the array. The profile of the total signal intensity identified the strain that is most likely represented in the amplified cDNA target. The results obtained with HAV and CV indicated that the hybridization profile thus generated can be used to identify closely related viral strains. This represents a significant improvement over current methods for virus identification using PCR amplification and amplicon sequencing.
[EX A]: A Microarray Based Approach for the Identification of Common Foodborne Viruses

[EX Q]: Cellular receptor-mediated signaling pathways play critical roles during the initial immune response to Human Cytomegalovirus (HCMV) infection. However, the involvement of type-I transmembrane glycoprotein CD147/EMMPRIN (extracellular matrix metalloproteinase inducer) in the antiviral response to HCMV infection is still unknown. Here, we demonstrated the specific knockdown of CD147 significantly decreased HCMV-induced activation of NF-κB and Interferon-beta (IFN-β), which contribute to the cellular antiviral responses. Next, we confirmed that HCMV-encoded miR-US25-1-5p could target the 3 UTR (Untranslated Region) of CD147 mRNA, and thus facilitate HCMV lytic propagation at a low multiplicity of infection (MOI). The expression and secretion of Cyclophilin A (sCyPA), as a ligand for CD147 and a proinflammatory cytokine, were up-regulated in response to HCMV stimuli. Finally, we confirmed that CD147 mediated HCMV-triggered antiviral signaling via the sCyPA-CD147-ERK (extracellular regulated protein kinases)/NF-κB axis signaling pathway. These findings reveal an important HCMV mechanism for evading antiviral innate immunity through its encoded microRNA by targeting transmembrane glycoprotein CD147, and a potential cause of HCMV inflammatory disorders due to the secretion of proinflammatory cytokine CyPA.
[EX A]: Human Cytomegalovirus Encoded miR-US25-1-5p Attenuates CD147/EMMPRIN-Mediated Early Antiviral Response

[EX Q]: Mathematical models have become invaluable management tools for epidemiologists, both shedding light on the mechanisms underlying observed dynamics as well as making quantitative predictions on the effectiveness of different control measures. Here, we explain how substantial biases are introduced by two important, yet largely ignored, assumptions at the core of the vast majority of such models. First, we use analytical methods to show that (i) ignoring the latent period or (ii) making the common assumption of exponentially distributed latent and infectious periods (when including the latent period) always results in underestimating the basic reproductive ratio of an infection from outbreak data. We then proceed to illustrate these points by fitting epidemic models to data from an influenza outbreak. Finally, we document how such unrealistic a priori assumptions concerning model structure give rise to systematically overoptimistic predictions on the outcome of potential management options. This work aims to highlight that, when developing models for public health use, we need to pay careful attention to the intrinsic assumptions embedded within classical frameworks. PLoS Medicine | www.plosmedicine.org July 2005 | Volume 2 | Issue 7 | e174 0621 Open access, freely available online PL o S MEDICINE
[EX A]:
Appropriate Models for the Management of Infectious Diseases