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.

Input: Consider Input: The worldwide prevalence of herpes simplex virus (HSV) and the shortage of efficient vaccines and novel therapeutic strategies against HSV are widely global concerns. The abundance on the virion and the major stimulus for the virus-neutralizing antibodies makes gD a predominant candidate for cure of HSV infection. In this study, we generated a monoclonal antibody (mAb), termed m27f, targeting to glycoprotein D (gD) of HSV-2, which also has cross-reactivity against HSV-1 gD. It has a high level of neutralizing activity against both HSV-1 and HSV-2, and binds to a highly conserved region (residues 292-297) within the pro-fusion domain of gD. It can effectively block HSV cell-to-cell spread in vitro. The pre-or post-attachment neutralization assay and syncytium formation inhibition assay revealed that m27f neutralizes HSV at the post-binding stage. Moreover, therapeutic administration of m27f completely prevented infection-related mortality of mice challenged with a lethal dose of HSV-2. Our newly identified epitope for the neutralizing antibody would facilitate studies of gD-based HSV entry or vaccine design, and m27f itself demonstrated a high potential for adaptation as a protective or therapeutic drug against HSV.

Output: A novel glycoprotein D-specific monoclonal antibody neutralizes herpes simplex virus

Input: Consider Input: Background: While it is known that acute respiratory illness (ARI) is caused by an array of viruses, less is known about co-detections and the resultant comparative symptoms and illness burden. This study examined the co-detections, the distribution of viruses, symptoms, and illness burden associated with ARI between December 2012 and March 2013. Methods: Outpatients with ARI were assayed for presence of 18 viruses using multiplex reverse transcriptase polymerase chain reaction (MRT-PCR) to simultaneously detect multiple viruses. Results: Among 935 patients, 60% tested positive for a single virus, 9% tested positive for 1 virus and 287 (31%) tested negative. Among children (<18 years), the respective distributions were 63%, 14%, and 23%; whereas for younger adults (18-49 years), the distributions were 58%, 8%, and 34% and for older adults (50 years) the distributions were 61%, 5%, and 32% (P < 0.001). Co-detections were more common in children than older adults (P = 0.01), and less frequent in households without children (P = 0.003). Most frequently co-detected viruses were coronavirus, respiratory syncytial virus, and influenza A virus. Compared with single viral infections, those with co-detections less frequently reported sore throat (P = 0.01), missed fewer days of school (1.1 vs. 2 days; P = 0.04), or work (2 vs. 3 days; P = 0.03); other measures of illness severity did not vary. Conclusions: Among outpatients with ARI, 69% of visits were associated with a viral etiology. Co-detections of specific clusters of viruses were observed in 9% of ARI cases particularly in children, were less frequent in households without children, and were less symptomatic (e.g., lower fever) than single infections.

Output: influenza season

Input: Consider Input: High-throughput screening (HTS) of large compound libraries has become a commonly used method for the identification of drug leads, and non-physiological reducing agents have been widely used for HTS. However, a comparison of the difference in the HTS results based on the choice of reducing agent used and potency comparisons of selected inhibitors has not been done with the physiological reducing agent, reduced glutathione (GSH). Here, we compared the effects of three reducing agents: dithiothreitol (DTT), -mercaptoethanol (-MCE), and tris-(2carboxyethyl)-phosphine (TCEP), in addition to GSH, against three drug target proteins. Approximately 100,000 compounds were computationally screened for each target protein, and experimental testing of high scoring compounds (~560 compounds) with the four reducing agents surprisingly produced many non-overlapping hits. More importantly, we find that various reducing agents alter inhibitor potency (IC 50 ) from ~10 M with one reducing agent to complete loss (IC 50 > 200 M) of inhibitory activity with another reducing agent. Therefore, the choice of reducing agent in a HTS is critical as this may lead to the pursuit of falsely identified active compounds or failure to identify the true active compounds. We demonstrate the feasibility of using GSH for in vitro HTS assays with these three target enzymes. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Contributions H.L. performed all experiments with assistance of J.T. and L.T., R.C. performed computational selection of inhibitors for PLpro and NS3/4A, A.M. performed computational selection of inhibitors for 3CLpro, and H.L. and M.E.J. designed the experiments and wrote the manuscript.
Output: Reducing agents affect inhibitory activities of compounds: Results from Multiple Drug Targets