ß-Hydroxybutyrate suppresses colorectal cancer.

Colorectal cancer (CRC) is among the most frequent forms of cancer, and new strategies for its prevention and therapy are urgently needed1. Here we identify a metabolite signalling pathway that provides actionable insights towards this goal. We perform a dietary screen in autochthonous animal models of CRC and find that ketogenic diets exhibit a strong tumour-inhibitory effect. These properties of ketogenic diets are recapitulated by the ketone body ß-hydroxybutyrate (BHB), which reduces the proliferation of colonic crypt cells and potently suppresses intestinal tumour growth. We find that BHB acts through the surface receptor Hcar2 and induces the transcriptional regulator Hopx, thereby altering gene expression and inhibiting cell proliferation. Cancer organoid assays and single-cell RNA sequencing of biopsies from patients with CRC provide evidence that elevated BHB levels and active HOPX are associated with reduced intestinal epithelial proliferation in humans. This study thus identifies a BHB-triggered pathway regulating intestinal tumorigenesis and indicates that oral or systemic interventions with a single metabolite may complement current prevention and treatment strategies for CRC.

Longitudinal changes in COVID-19 vaccination intent among South African adults: evidence from the NIDS-CRAM panel survey, February to May 2021.

BACKGROUND: COVID-19 vaccine hesitancy has threatened the ability of many countries worldwide to contain the pandemic. Given the severe impact of the pandemic in South Africa and disruptions to the roll-out of the vaccine in early 2021, slower-than-expected uptake is a pressing public health challenge in the country. We examined longitudinal changes in COVID-19 vaccination intent among South African adults, as well as determinants of intent to receive a vaccine. METHODS: We used longitudinal data from Wave 4 (February/March 2021) and Wave 5 (April/May 2021) of the National Income Dynamics Study: Coronavirus Rapid Mobile Survey (NIDS-CRAM), a national and broadly representative panel survey of adults in South Africa. We conducted cross-sectional analyses on aggregate and between-group variation in vaccination intent, examined individual-level changes between waves, and modeled demographic predictors of intent. RESULTS: We analysed data for 5629 (Wave 4; 48% male, mean age 41.5 years) and 5862 (Wave 5; 48% male, mean age 41.6 years) respondents. Willingness to get a COVID-19 vaccine significantly increased from 70.8% (95% CI: 68.5-73.1) in Wave 4 to 76.1% (95% CI: 74.2-77.8) in Wave 5. Individual-level analyses indicated that only 6.6% of respondents remained strongly hesitant between survey waves. Although respondents aged 18-24 years were 8.5 percentage points more likely to report hesitancy, hesitant respondents in this group were 5.6 percentage points more likely to change their minds by Wave 5. Concerns about rushed testing and safety of the vaccines were frequent and strongly-held reasons for hesitancy. CONCLUSIONS: Willingness to receive a COVID-19 vaccine has increased among adults in South Africa, and those who were entrenched in their reluctance make up a small proportion of the country's population. Younger adults, those in formal housing, and those who trusted COVID-19 information on social media were more likely to be hesitant. Given that stated vaccination intent may not translate into behaviour, our finding that three-quarters of the population were willing to accept the vaccine may reflect an upper bound. Vaccination promotion campaigns should continue to frame vaccine acceptance as the norm and tailor strategies to different demographic groups.

"Do not inject our babies": a social listening analysis of public opinion about authorizing pediatric COVID-19 vaccines.

Designing effective childhood vaccination counseling guidelines, public health campaigns, and school-entry mandates requires a nuanced understanding of the information ecology in which parents make vaccination decisions. However, evidence is lacking on how best to "catch the signal" about the public's attitudes, beliefs, and misperceptions. In this study, we characterize public sentiment and discourse about vaccinating children against SARS-CoV-2 with mRNA vaccines to identify prevalent concerns about the vaccine and to understand anti-vaccine rhetorical strategies. We applied computational topic modeling to 149 897 comments submitted to regulations.gov in October 2021 and February 2022 regarding the Food and Drug Administration's Vaccines and Related Biological Products Advisory Committee's emergency use authorization of the COVID-19 vaccines for children. We used a latent Dirichlet allocation topic modeling algorithm to generate topics and then used iterative thematic and discursive analysis to identify relevant domains, themes, and rhetorical strategies. Three domains emerged: (1) specific concerns about the COVID-19 vaccines; (2) foundational beliefs shaping vaccine attitudes; and (3) rhetorical strategies deployed in anti-vaccine arguments. Computational social listening approaches can contribute to misinformation surveillance and evidence-based guidelines for vaccine counseling and public health promotion campaigns.

Effects Of An Employee COVID-19 Vaccination Mandate At A Long-Term Care Network.

We assessed COVID-19 vaccination and employment status among employees of a long-term care network that announced an employee vaccination mandate on July 29, 2021. The day before the announcement, 1,208 employees were unvaccinated; of these workers, 56.2 percent subsequently were vaccinated, whereas 20.9 percent (3.7 percent of active employees) were terminated because of noncompliance with the mandate.

Dear Pandemic: A topic modeling analysis of COVID-19 information needs among readers of an online science communication campaign.

BACKGROUND: The COVID-19 pandemic was accompanied by an "infodemic"-an overwhelming excess of accurate, inaccurate, and uncertain information. The social media-based science communication campaign Dear Pandemic was established to address the COVID-19 infodemic, in part by soliciting submissions from readers to an online question box. Our study characterized the information needs of Dear Pandemic's readers by identifying themes and longitudinal trends among question box submissions. METHODS: We conducted a retrospective analysis of questions submitted from August 24, 2020, to August 24, 2021. We used Latent Dirichlet Allocation topic modeling to identify 25 topics among the submissions, then used thematic analysis to interpret the topics based on their top words and submissions. We used t-Distributed Stochastic Neighbor Embedding to visualize the relationship between topics, and we used generalized additive models to describe trends in topic prevalence over time. RESULTS: We analyzed 3839 submissions, 90% from United States-based readers. We classified the 25 topics into 6 overarching themes: 'Scientific and Medical Basis of COVID-19,' 'COVID-19 Vaccine,' 'COVID-19 Mitigation Strategies,' 'Society and Institutions,' 'Family and Personal Relationships,' and 'Navigating the COVID-19 Infodemic.' Trends in topics about viral variants, vaccination, COVID-19 mitigation strategies, and children aligned with the news cycle and reflected the anticipation of future events. Over time, vaccine-related submissions became increasingly related to those surrounding social interaction. CONCLUSIONS: Question box submissions represented distinct themes that varied in prominence over time. Dear Pandemic's readers sought information that would not only clarify novel scientific concepts, but would also be timely and practical to their personal lives. Our question box format and topic modeling approach offers science communicators a robust methodology for tracking, understanding, and responding to the information needs of online audiences.

Partisanship, Messaging, and the COVID-19 Vaccine: Evidence From Survey Experiments.

PURPOSE: To investigate partisanship in COVID-19 attitudes, and assess partisan or scientific messaging effects on COVID-19 vaccination intentions. DESIGN: Two-wave survey with two-arm randomized experiment. SETTING: Recruited Pennsylvania residents online. SAMPLE: 2037 (May 2020) and 1577 (October 2020) Pennsylvania residents, aged 18-94 years. INTERVENTION: Respondents saw messaging that presented either President Trump or scientists endorsing the vaccine, then reported their vaccination intentions. MEASURES: Likert scale items measuring COVID-19 attitudes (May), including mask wearing and vaccination intentions (May and October). ANALYSIS: Partisan differences in attitudes were analyzed by chi-square; differences in support for mask wearing and vaccination intentions were also analyzed by Mann-Whitney U. The messaging experiment was analyzed by chi-square, Mann-Whitney U, and survey-weighted multivariate logistic regression. RESULTS: Significant partisan differences were found in all attitudes. The partisan split in support for mask wearing increased from May to October, whereas the split in vaccination intentions decreased. Compared to partisan messaging, scientific messaging increased overall odds of intending to vaccinate by 32% in May (adjusted odds ratio [AOR]=1.32, 95% confidence interval [CI] = 1.06-1.65), and increased odds among Democrats by 142% in October (AOR = 2.42, CI = 1.29-4.55). Scientific messaging had no significant effect on independents or Republicans. CONCLUSION: Partisan COVID-19 attitudes were widespread and persistent. Partisan endorsement of the vaccine positively influenced those with congruent beliefs, while scientific messaging produced consistent effects across political affiliation.