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 Input: The high mutation rate of the human immunodeficiency virus type 1 (HIV-1) virus is a major problem since it evades the function of antibodies and chemical inhibitors. Here, we demonstrate a viral detection strategy based on synthetic biology principles to detect a specific viral function rather than a particular viral protein. The resistance caused by mutations can be circumvented since the mutations that cause the loss of function also incapacitate the virus. Many pathogens encode proteases that are essential for their replication and that have a defined substrate specificity. A genetically encoded sensor composed of a fused membrane anchor, viral protease target site, and an orthogonal transcriptional activator was engineered into a human cell line. The HIV-1 protease released the transcriptional activator from the membrane, thereby inducing transcription of the selected genes. The device was still strongly activated by clinically relevant protease mutants that are resistant to protease inhibitors. In the future, a similar principle could be applied to detect also other pathogens and functions.
Example Output: Function-Based Mutation-Resistant Synthetic Signaling Device Activated by HIV-1 Proteolysis

Example Input: Both antiseptic hand rubbing (AHR) using ethanol-based disinfectants (EBDs) and antiseptic hand washing (AHW) are important means of infection control to prevent seasonal influenza A virus (IAV) outbreaks. However, previous reports suggest a reduced efficacy of ethanol disinfection against pathogens in mucus. We aimed to elucidate the situations and mechanisms underlying the reduced efficacy of EBDs against IAV in infectious mucus. We evaluated IAV inactivation and ethanol concentration change using IAV-infected patients' mucus (sputum). Additionally, AHR and AHW effectiveness against infectious mucus adhering to the hands and fingers was evaluated in 10 volunteers. Our clinical study showed that EBD effectiveness against IAV in mucus was extremely reduced compared to IAV in saline. IAV in mucus remained active despite 120 s of AHR; however, IAV in saline was completely inactivated within 30 s. Due to the low rate of diffusion/convection because of the physical properties of mucus as a hydrogel, the time required for the ethanol concentration to reach an IAV inactivation level and thus for EBDs to completely inactivate IAV was approximately eight times longer in mucus than in saline. On the other hand, AHR inactivated IAV in mucus within 30 s when the mucus dried completely because the hydrogel characteristics were lost. Additionally, AHW rapidly inactivated IAV. Until infectious mucus has completely dried, infectious IAV can remain on the hands and fingers, even after appropriate AHR using EBD, thereby increasing the risk of IAV transmission. We clarified the ineffectiveness of EBD use against IAV in infectious mucus. IMPORTANCE Antiseptic hand rubbing (AHR) and antiseptic hand washing (AHW) are important to prevent the spread of influenza A virus (IAV). This study elucidated the situations/mechanisms underlying the reduced efficacy of AHR against infectious mucus derived from IAV-infected individuals and indicated the weaknesses of the current hand hygiene regimens. Due to the low rate of diffusion/convection because of the physical properties of mucus as a hydrogel, the efficacy of AHR using ethanolbased disinfectant against mucus is greatly reduced until infectious mucus adhering to the hands/fingers has completely dried. If there is insufficient time before treating the next patient (i.e., if the infectious mucus is not completely dry), medical staff should be aware that effectiveness of AHR is reduced. Since AHW is effective against both dry and nondry infectious mucus, AHW should be adopted to compensate for these weaknesses of AHR. FIG 1 Analysis of the physical properties of mucus from 19 influenza A virus-infected patients. (A) Rheological analysis: mean, maximum, and minimum viscosities of mucus (sputum) samples at different shear rates (left panel). Shown is a comparison of mucus and saline viscosities at different shear rates (right panel). (B) Average parameters measured for saline and mucus samples: contact angles, surface tension, and densities at different temperatures. (C) Time required for saline and mucus to completely dry (complete drying time). (D) Ethanol diffusion coefficients of saline and mucus exposed to an 80% ethanol concentration. Situations of Reduced Hand Hygiene Effectiveness September/October 2019 Volume 4 Issue 5 e00474-19 msphere.asm.org 3 FIG 6 Additional fluid simulation of changes in the ethanol concentrations in mucus. (A) Addition of 95 l of 80% ethanol to 5 l saline was modeled in OpenFOAM, demonstrating the disappearance over time of the region with Ͻ31% ethanol (shown in red). See also Movie S1. (B) Addition of 95 l of 80% ethanol to 5 l mucus was modeled. The simulation was performed under conditions of reduced viscosity (16.7% of the actual measurement value) because of the long time required for disappearance of the concentration region of Ͻ31%. See also Movie S2.
Example Output: Situations Leading to Reduced Effectiveness of Current Hand Hygiene against Infectious Mucus from Influenza Virus- Infected Patients

Example Input: Objective: The aim of this study was to further clarify clinical characteristics and predict mortality risk among patients with viral pneumonia. Methods: A total of 528 patients with viral pneumonia at RuiJin hospital in Shanghai from May 2015 to May 2019 were recruited. Multiplex real-time RT-PCR was used to detect respiratory viruses. Demographic information, comorbidities, routine laboratory examinations, immunological indexes, etiological detections, radiological images and treatment were collected on admission. Results: 76 (14.4%) patients died within 90 days in hospital. A predictive MuLBSTA score was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included multilobular infiltrates (OR = 5.20, 95% CI 1.41-12.52, p = 0.010; 5 points), lymphocyte ≤ 0.8 * 10 9 /L (OR = 4.53, 95% CI 2.55-8.05, p < 0.001; 4 points), bacterial coinfection (OR = 3.71, 95% CI 2.11-6.51, p < 0.001; 4 points), acute-smoker (OR = 3.19, 95% CI 1.34-6.26, p = 0.001; 3 points), quit-smoker (OR = 2.18, 95% CI 0.99-4.82, p = 0.054; 2 points), hypertension (OR = 2.39, 95% CI 1.55-4.26, p = 0.003; 2 points) and age ≥60 years (OR = 2.14, 95% CI 1.04-4.39, p = 0.038; 2 points). 12 points was used as a cut-off value for mortality risk stratification. This model showed sensitivity of 0.776, specificity of 0.778 and a better predictive ability than CURB-65 (AUROC = 0.773 vs. 0.717, p < 0.001). Conclusion: Here, we designed an easy-to-use clinically predictive tool for assessing 90-day mortality risk of viral pneumonia. It can accurately stratify hospitalized patients with viral pneumonia into relevant risk categories and could provide guidance to make further clinical decisions.
Example Output:
Citation: Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score