Politics Go "Viral": A Computational Text Analysis of the Public Attribution and Attitude Regarding the COVID-19 Crisis and Governmental Responses on Twitter

The U.S. confronts an unprecedented public health crisis, the COVID-19 pandemic, in the presidential election year in 2020. In such a compound situation, a real-time dynamic examination of how the general public ascribe the crisis responsibilities taking account to their political ideologies is helpful for developing effective strategies to manage the crisis and diminish hostility toward particular groups caused by polarization. Social media, such as Twitter, provide platforms for the public's COVID-related discourse to form, accumulate, and visibly present. Meanwhile, those features also make social media a window to monitor the public responses in real-time. This research conducted a computational text analysis of 2,918,376 tweets sent by 829,686 different U.S. users regarding COVID-19 from January 24 to May 25, 2020. Results indicate that the public's crisis attribution and attitude toward governmental crisis responses are driven by their political identities. One crisis factor identified by this study (i.e., threat level) also affects the public's attribution and attitude polarization. Additionally, we note that pandemic fatigue was identified in our findings as early as in March 2020. This study has theoretical, practical, and methodological implications informing further health communication in a heated political environment. [ FROM AUTHOR] Copyright of Social Science Computer Review is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

HLA-II immunopeptidome profiling and deep learning reveal features of antigenicity to inform antigen discovery.

CD4+ T cell responses are exquisitely antigen specific and directed toward peptide epitopes displayed by human leukocyte antigen class II (HLA-II) on antigen-presenting cells. Underrepresentation of diverse alleles in ligand databases and an incomplete understanding of factors affecting antigen presentation in vivo have limited progress in defining principles of peptide immunogenicity. Here, we employed monoallelic immunopeptidomics to identify 358,024 HLA-II binders, with a particular focus on HLA-DQ and HLA-DP. We uncovered peptide-binding patterns across a spectrum of binding affinities and enrichment of structural antigen features. These aspects underpinned the development of context-aware predictor of T cell antigens (CAPTAn), a deep learning model that predicts peptide antigens based on their affinity to HLA-II and full sequence of their source proteins. CAPTAn was instrumental in discovering prevalent T cell epitopes from bacteria in the human microbiome and a pan-variant epitope from SARS-CoV-2. Together CAPTAn and associated datasets present a resource for antigen discovery and the unraveling genetic associations of HLA alleles with immunopathologies.

The Relationship between Practitioners' Trust in the City and Their Adoption of the Virtual Convention Platform-A Case Study of Virtual SEOUL 2.0

Many conferences, exhibitions, and trade shows planned in the early days of COVID-19 were canceled or postponed, and only some events were able to convert quickly to virtual events by using existing virtual conference and exhibition platforms. This study examined whether the virtual convention platform, combined with advanced technologies, can enhance the trust in Seoul city and further influence the attitude and intention to use Virtual SEOUL 2.0. Furthermore, this study applies the Extended Technology Acceptance Model (ETAM) framework to identify external variables that affect perceived usefulness and ease of use and describes how practitioners embrace the new convention technology of Virtual SEOUL 2.0. The 300 usable survey data were collected and used to identify the proposed hypothesized relationship of seven latent constructs. The hypothesized relationships were tested by structural equation modeling (SEM). The analytic results confirmed the proposed hypothesized relationship among these seven constructs (Personal innovativeness, Perceived ease of use, Perceived usefulness, Perceived trust of Seoul, Perceived enjoyment, Attitude toward using Virtual SEOUL 2.0, and Intention to use Virtual SEOUL 2.0). More interestingly, the study's findings provide that perceived trust in a smart city is an essential factor that directly or indirectly enhances users' intention to use technology.

Perceived China Threat, Conspiracy Belief, and Public Support for Restrictive Immigration Control During the COVID-19 Pandemic

During the COVID-19 pandemic, there has been an unprecedented increase in the level of political blame attributed to China for the health crisis and other associated xenophobic discourses. Although previous research has revealed the effects of perceived outgroup threats on popular support for policies that control outgroups, threats posed by foreign countries have received little empirical attention. This study advances previous research by focusing on the independent effects of the perceived China threat to public support for restrictive immigration control during the COVID-19 pandemic. Using a sample drawn from the 2020 American National Election Studies, the results showed that the perceived China threat substantially heightened public support for restrictive immigration control. More importantly, demand for restrictive immigration control intensified when individuals had stronger perceptions of threats and conspiracy beliefs about the virus leak from a Chinese lab. Taken together, our findings demonstrate the roles of politically constructed threats and conspiracy beliefs during the COVID-19 pandemic, revealing new mechanisms of popular attitudes toward social control.

Politics Go “Viral”: A Computational Text Analysis of the Public Attribution and Attitude Regarding the COVID-19 Crisis and Governmental Responses on Twitter

The U.S. confronts an unprecedented public health crisis, the COVID-19 pandemic, in the presidential election year in 2020. In such a compound situation, a real-time dynamic examination of how the general public ascribe the crisis responsibilities taking account to their political ideologies is helpful for developing effective strategies to manage the crisis and diminish hostility toward particular groups caused by polarization. Social media, such as Twitter, provide platforms for the public?s COVID-related discourse to form, accumulate, and visibly present. Meanwhile, those features also make social media a window to monitor the public responses in real-time. This research conducted a computational text analysis of 2,918,376 tweets sent by 829,686 different U.S. users regarding COVID-19 from January 24 to May 25, 2020. Results indicate that the public?s crisis attribution and attitude toward governmental crisis responses are driven by their political identities. One crisis factor identified by this study (i.e., threat level) also affects the public?s attribution and attitude polarization. Additionally, we note that pandemic fatigue was identified in our findings as early as in March 2020. This study has theoretical, practical, and methodological implications informing further health communication in a heated political environment.

Bridging Endocrine Therapy for HR+/HER2- Resectable Breast Cancer: Is it Safe?

BACKGROUND: The COVID-19 pandemic has required new treatment paradigms to limit exposures and optimize hospital resources, including the use of neoadjuvant endocrine therapy (NAET) as bridging therapy for HR+/HER2-invasive tumors and DCIS. While this approach has been used in locally advanced disease, it is unclear how it may affect outcomes in resectable HR+/HER2- tumors. METHODS: Women ≥18 years diagnosed with in situ (Tis) or non-metastatic HR+/HER2- breast cancer from March-May 2019 and 2020 were included. Fisher's exact test and two-sample t test were used to compare baseline characteristics and surgical outcomes between strata. Sub-analysis was performed between patients who received primary surgery vs a bridging NAET approach. RESULTS: Despite similar clinical characteristics, patients in 2019 were more likely to have a surgery-first approach (75% vs 42%, P-value = .0007), receive surgery sooner (22 vs 29 days, P-value < .001), and within 60 days from diagnosis date (100% vs 85%, P-value = .0301). Neoadjuvant endocrine therapy was a more prevalent approach in 2020 (48% vs 7%, P-value < .0001). Rates of clinical to pathologic up-staging remained consistent across primary surgery vs bridging NAET subgroups (P-value = .9253). DISCUSSION: Pandemic-driven treatment protocols provide a unique opportunity to assess the utility of bridging endocrine therapy for resectable HR+/HER2- tumors. Differences in clinical and pathologic staging were similar across groups and did not appear to be affected by receipt of NAET. Our limited cohort demonstrates this strategic therapeutic avenue can optimize health care utilization and may be a reasonable approach when delaying surgery is preferred.

Quantitative Proteomic Analysis of the Expression of SARS-CoV-2 Receptors in the Gut of Patients with Chronic Enterocolitis.

The cellular entry of severe respiratory syndrome coronavirus-2 (SARS-CoV-2) is mediated by interaction with the human angiotensin-converting enzyme 2 (ACE2), a receptor that is expressed on both lung and intestinal epithelial cells. We performed a quantitative proteomic analysis to investigate the expression of possible receptors for SARS-CoV-2 in the intestinal mucosa of 23 patients with chronic colitis. ACE2 expression was low and remained unaltered in the gut of patients with ulcerative colitis (UC), Crohn's disease (CD), intestinal Behcet's disease (BD), and intestinal tuberculosis (TB), when compared with that of healthy individuals. Additionally, the expression levels of some probable co-receptors, including dipeptidyl peptidase 4 (DPP4), aminopeptidase N (AMPN), and glutamyl aminopeptidase (AMPE), were unchanged in the affected UC, CD, intestinal BD, and intestinal TB colon mucosa samples. In conclusion, gut inflammation associated with chronic colitis does not mediate a further increase in the cellular entry of SARS-CoV-2.