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.

[Q]: 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.
[A]: Citation: Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score


[Q]: The Tasmanian devil (Sarcophilus harrisii), so named for its blood-curdling, nocturnal shrieks and snarls, is the largest of the carnivorous marsupials. Although once widely persecuted, concerted efforts are now being made to save the devil from extinction following the emergence of a fatal transmissible malignancy known as devil facial tumour disease (DFTD). DFTD is unusual in that the infectious agent is the cancer cell itself. This chapter discusses the aetiology and pathogenesis of DFTD as well as the profound impact the spread of DFTD has had on the devil's conservation status. Strategies for managing DFTD and conserving the devil will be explored and the contribution of new sequencing technology to the field of conservation genetics and genomics will be examined with regard to the Tasmanian devil and DFTD.
[A]: Devil Facial Tumour Disease (DFTD): Using Genetics and Genomics to Investigate Infectious Disease in an Endangered Marsupial


[Q]: Discovering new binding function via a combinatorial library in small protein scaffolds requires balance between appropriate mutations to introduce favorable intermolecular interactions while maintaining intramolecular integrity. Sitewise constraints exist in a non-spatial gradient from diverse to conserved in evolved antibody repertoires; yet non-antibody scaffolds generally do not implement this strategy in combinatorial libraries. Despite the fact that biased amino acid distributions, typically elevated in tyrosine, serine, and glycine, have gained wider use in synthetic scaffolds, these distributions are still predominantly applied uniformly to diversified sites. While select sites in fibronectin domains and DARPins have shown benefit from sitewise designs, they have not been deeply evaluated. Inspired by this disparity between diversity distributions in natural libraries and synthetic scaffold libraries, we hypothesized that binders resulting from discovery and evolution would exhibit a nonspatial, sitewise gradient of amino acid diversity. To identify sitewise diversities consistent with efficient evolution in the context of a hydrophilic fibronectin domain, >10 5 binders to six targets were evolved and sequenced. Evolutionarily favorable amino acid distributions at 25 sites reveal Shannon entropies (range: 0.3-3.9; median: 2.1; standard deviation: 1.1) supporting the diversity gradient hypothesis. Sitewise constraints in evolved sequences are consistent with complementarity, stability, and consensus biases. Implementation of sitewise constrained diversity enables direct selection of nanomolar affinity binders validating an efficient strategy to balance inter-and intra-molecular interaction demands at each site.
[A]:
High-Throughput Ligand Discovery Reveals a Sitewise Gradient of Diversity in Broadly Evolved Hydrophilic Fibronectin Domains