COVID-19 Public Opinion: A Twitter Healthcare Data Processing Using Machine Learning Methodologies.

The COVID-19 pandemic has shattered the whole world, and due to this, millions of people have posted their sentiments toward the pandemic on different social media platforms. This resulted in a huge information flow on social media and attracted many research studies aimed at extracting useful information to understand the sentiments. This paper analyses data imported from the Twitter API for the healthcare sector, emphasizing sub-domains, such as vaccines, post-COVID-19 health issues and healthcare service providers. The main objective of this research is to analyze machine learning models for classifying the sentiments of people and analyzing the direction of polarity by considering the views of the majority of people. The inferences drawn from this analysis may be useful for concerned authorities as they work to make appropriate policy decisions and strategic decisions. Various machine learning models were developed to extract the actual emotions, and results show that the support vector machine model outperforms with an average accuracy of 82.67% compared with the logistic regression, random forest, multinomial naïve Bayes and long short-term memory models, which present 78%, 77%, 68.67% and 75% accuracy, respectively.

Steps toward translocation-independent RNA polymerase inactivation by terminator ATPase ρ.

Factor-dependent transcription termination mechanisms are poorly understood. We determined a series of cryo-electron microscopy structures portraying the hexameric adenosine triphosphatase (ATPase) ρ on a pathway to terminating NusA/NusG-modified elongation complexes. An open ρ ring contacts NusA, NusG, and multiple regions of RNA polymerase, trapping and locally unwinding proximal upstream DNA. NusA wedges into the ρ ring, initially sequestering RNA. Upon deflection of distal upstream DNA over the RNA polymerase zinc-binding domain, NusA rotates underneath one capping ρ subunit, which subsequently captures RNA. After detachment of NusG and clamp opening, RNA polymerase loses its grip on the RNA:DNA hybrid and is inactivated. Our structural and functional analyses suggest that ρ, and other termination factors across life, may use analogous strategies to allosterically trap transcription complexes in a moribund state.