TASK DEFINITION: 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.
PROBLEM: Uniform polymeric nanoparticles with various morphologies of projection coronas like the viruses in the coronavirus group have been formed by the self-organization of macromolecular chains polymerizing in a dispersion system of styrene (St), acrylonitrile (AN) and poly(ethylene glycol) monomethoxymonomethacrylate (PEGm) in a polar solvent (water/ethanol). An increase in the water composition reduced the crystallization degree of AN units, resulting in a variety of the nanoparticle morphology such as the increased particle size, the reduced projection size, the increased projection number, and the decreased inter-projection distance. The difference in the projection morphology strongly affected a dispersibility in water. q

SOLUTION: One-step nanomorphology control of self-organized projection coronas in uniform polymeric nanoparticles *

PROBLEM: Introduction: Accurate and timely prediction for endemic infectious diseases is vital for public health agencies to plan and carry out any control methods at an early stage of disease outbreaks. Climatic variables has been identified as important predictors in models for infectious disease forecasts. Various approaches have been proposed in the literature to produce accurate and timely predictions and potentially improve public health response. Methods: We assessed how the machine learning LASSO method may be useful in providing useful forecasts for different pathogens in countries with different climates. Separate LASSO models were constructed for different disease/country/forecast window with different model complexity by including different sets of predictors to assess the importance of different predictors under various conditions. Results: There was a more apparent cyclicity for both climatic variables and incidence in regions further away from the equator. For most diseases, predictions made beyond 4 weeks ahead were increasingly discrepant from the actual scenario. Prediction models were more accurate in capturing the outbreak but less sensitive to predict the outbreak size. In different situations, climatic variables have different levels of importance in prediction accuracy. Conclusions: For LASSO models used for prediction, including different sets of predictors has varying effect in different situations. Short term predictions generally perform better than longer term predictions, suggesting public health agencies may need the capacity to respond at short-notice to early warnings.

SOLUTION: The utility of LASSO-based models for real time forecasts of endemic infectious diseases: A cross country comparison

PROBLEM: Arthritogenic alphaviruses comprise a group of enveloped RNA viruses that are transmitted to humans by mosquitoes and cause debilitating acute and chronic musculoskeletal disease 1 . The host factors required for alphavirus entry remain poorly characterized 2 . Using a genome-wide CRISPR/Cas9-based screen, we identified the cell adhesion molecule Mxra8 as an entry mediator for multiple emerging arthritogenic alphaviruses including chikungunya (CHIKV), Ross River, Mayaro, and O'nyong nyong (ONNV) viruses. Gene editing of mouse Mxra8 or human MXRA8 resulted in reduced viral infection of cells, and reciprocally, ectopic expression resulted in increased infection. Mxra8 bound directly to CHIKV particles and enhanced virus attachment and Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.

SOLUTION:
Mxra8 is a receptor for multiple arthritogenic alphaviruses