In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

Q: Paragraph: The present study was undertaken to evaluate chikungunya virus (CHIKV) proteins for RNAi suppressor activity. We systematically analyzed all nine CHIKV proteins for RNAi suppressor activity using Sf21 RNAi sensor cell line based assay. Two non-structural proteins, namely, nsP2 and nsP3 were found to exhibit RNAi suppressor activity. We further validated the findings in natural hosts, namely in Aedes and in mammalian cell lines and further through EMSA and Agrobacterium infiltration in GFP silenced transgenic tobacco plants. Domains responsible for maximum RNAi suppressor activity were also identified within these proteins. RNA binding motifs in these domains were identified and their participation in RNAi suppression evaluated using site directed mutagenesis. Sequence alignment of these motifs across all species of known alphaviruses revealed conservation of these motifs emphasizing on a similar role of action in other species of alphaviruses as well. Further validation of RNAi suppressor activity of these proteins awaits establishment of specific virus infection models. RNA interference (RNAi) is a conserved evolutionary mechanism designed to impart an antiviral defence system across organisms ranging from plants, fungi, arthropods and nematodes 1-4 . The phenomenon, triggered by the production of double stranded RNA (dsRNA) by the pathogen upon infection, leads to the activation of the RNA interference silencing complex (RISC) by loading of dsRNA/siRNA into the complex ultimately leading to cleavage of the viral RNA 5,6,7 . Several components of RISC participate in the cleavage, most important being ribonuclease III Dicer (DCR) and Argonaute protein (AGO). Dicer acts on dsRNA to generate small RNA (sRNA) that are loaded into the AGO, resulting in cleavage 8,9 ; however, some RNAi pathways are independent of Dicer and other components like RNA-dependent RNA polymerase (RdRP) produce short RNA transcripts that directly bind to AGO 10 . Similarly, much is now known about the Piwi pathway that is specifically active in the germline 11 . In response to RNAi in plants and insects, viruses infecting these systems utilise some of their own proteins/sequence elements that counteract the antiviral RNAi pathway 12 . These viral suppressors of RNAi (VSRs) act through different mechanisms, either by binding to long dsRNA and protecting them from Dicer 7,13 or short RNAs 14 or through multi-mode mechanisms 15,16 . Recently it has been shown that some viruses encode host-specific VSRs due to co-evolution of the virus and the host, emphasising on the importance of analysing suppressor activity in relevant host 17 . Amongst medically important pathogenic viruses, arboviruses form an important subset of viruses due to the complexity of their host preferences 18 . These viruses, mainly constituted by genera flavivirus and alphavirus, 
 Title: Analysis of chikungunya virus proteins reveals that non-structural proteins nsP2 and nsP3 exhibit RNA interference (RNAi) suppressor activity OPEN

A: False
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Q: Paragraph: Rational design of proteins with novel binding specificities and increased affinity is one of the major goals of computational protein design. Epitope-scaffolds are a new class of antigens engineered by transplanting viral epitopes of pre-defined structure to protein scaffolds, or by building protein scaffolds around such epitopes. Epitope-scaffolds are of interest as vaccine components to attempt to elicit neutralizing antibodies targeting the specified epitope. In this study we developed a new computational protocol, MultiGraft Interface, that transplants epitopes but also designs additional scaffold features outside the epitope to enhance antibody-binding specificity and potentially influence the specificity of elicited antibodies. We employed MultiGraft Interface to engineer novel epitope-scaffolds that display the known epitope of HIV-1 neutralizing antibody 2F5 and that also interact with the functionally important CDR H3 antibody loop. MultiGraft Interface generated an epitope-scaffold that bound 2F5 with sub-nanomolar affinity (K D = 400 pM) and that interacted with the antibody CDR H3 loop through computationally designed contacts. Substantial structural modifications were necessary to engineer this antigen, with the 2F5 epitope replacing a helix in the native scaffold and with 15% of the native scaffold sequence being modified in the design stage. This epitope-scaffold represents a successful example of rational protein backbone engineering and protein-protein interface design and could prove useful in the field of HIV vaccine design. MultiGraft Interface can be generally applied to engineer novel binding partners with altered specificity and optimized affinity. § 
 Title: Computational design of protein antigens that interact with the CDR H3 loop of HIV broadly neutralizing antibody 2F5 HHS Public Access

A: False
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Q: Paragraph: The ongoing novel coronavirus disease pandemic has rapidly spread in early 2020, causing tens of thousands of deaths, over a million cases and widespread socioeconomic disruption. With no vaccine available and numerous national healthcare systems reaching or exceeding capacity, interventions to limit transmission are urgently needed. While there is broad agreement that travel restrictions and closure of non-essential businesses and schools are beneficial in limiting local and regional spread, recommendations around the use of face masks for the general population are less consistent internationally. In this study, we examined the role of face masks in mitigating the spread of COVID-19 in the general population, using epidemic models to estimate the total reduction of infections and deaths under various scenarios. In particular, we examined the optimal deployment of face masks when resources are limited, and explored a range of supply and demand dynamics. We found that face masks, even with a limited protective effect, can reduce infections and deaths, and can delay the peak time of the epidemic. We consistently found that a random distribution of masks in the population was a suboptimal strategy when resources were limited. Prioritizing coverage among the elderly was more beneficial, while allocating a proportion of available resources for diagnosed infected cases provided further mitigation under a range of scenarios. In summary, face mask use, particularly for a pathogen with relatively common asymptomatic carriage, can effectively provide some mitigation of transmission, while balancing provision between vulnerable healthy persons and symptomatic persons can optimize mitigation efforts when resources are limited. The rapid global spread of SARS-CoV-2 and the resulting coronavirus disease pandemic has led to urgent efforts to contain and mitigate transmission, leading to significant and widespread socioeconomic disruption. As of April 3rd 2020, over one million cases have been reported worldwide, as well as over 60,000 deaths, with ongoing spread in most parts of the world [1]. While infection is frequently asymptomatic, or associated with only mild symptoms in many people [2, 3] , it can cause severe and life-threatening illness in the immunocompromised and the elderly, with a case fatality ratio of over 10% in the latter group [3] [4] [5] . The rapid spread of the virus has raised concerns that healthcare systems lack sufficient resources and will be unable to bear the burden of accommodating patients suffering from COVID-19, resulting in significantly increased morbidity and mortality. There is an urgent need . CC-BY-NC 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the (which was not peer-reviewed) The copyright holder for this preprint . 
 Title: Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic

A:
True
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