A Review of the Role of Pollen in COVID-19 Infection.

There is current interest in the role of ambient pollen in the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2 or COVID-19) infection risk. The aim of this review is to summarise studies published up until January 2023 investigating the relationship between airborne pollen and the risk of COVID-19 infection. We found conflicting evidence, with some studies showing that pollen may increase the risk of COVID-19 infection by acting as a carrier, while others showed that pollen may reduce the risk by acting as an inhibiting factor. A few studies reported no evidence of an association between pollen and the risk of infection. A major limiting factor of this research is not being able to determine whether pollen contributed to the susceptibility to infection or just the expression of symptoms. Hence, more research is needed to better understand this highly complex relationship. Future investigations should consider individual and sociodemographic factors as potential effect modifiers when investigating these associations. This knowledge will help to identify targeted interventions.

Recent advances on CRISPR/Cas system-enabled portable detection devices for on-site agri-food safety assay

Agri-food safety has been considered as one of the most important public concerns worldwide. From farm to table, food crops and foods are extremely vulnerable to the contamination by a variety of pollutants from their growth and processing. Moreover, the SARS-CoV-2 detected in the food supply chain during COVID-19 pandemic has posed a greater challenge for rapid and on-site detection of agri-food contaminants in complex and volatile environments. Therefore, the development of rapid, accurate, and on-site detection technologies and portable detection devices is of great importance to ensure the agri-food security. This review comprehensively summarized the recent advances on the construction of CRISPR/Cas systems-based biosensing technologies and their portable detection devices, as well as their promising applications in the field of agri-food safety. First of all, the classification and working principles of CRISPR/Cas systems were introduced. Then, the latest advances on the CRISPR/Cas system-based on-site detection technologies and portable detection devices were also systematically summarized. Most importantly, the state-of-the-art applications of CRISPR/Cas systems-based on-site detection technologies and portable detection devices in the fields of agri-food safety were comprehensively summarized. Impressively, the future opportunities and challenges in this emerging and promising field were proposed. Emerging CRISPR/Cas system-based on-site detection technologies have showed a great potential in the detection of agri-food safety. Impressively, the integration of CRISPR/Cas systems-based biosensing technologies with portable detection devices (e.g., nanopore-based detection devices, lateral flow assay, smartphone-based detection devices, and microfluidic devices) is very promising for the on-site detection of agri-food contaminants. Additionally, CRISPR/Cas system-based biosensing technologies can be further integrated with much more innovative technologies for the development of novel detection platforms to realize the more reliable on-site detection of agri-food safety.

PROMOTING TRANSITION TO ONCOLOGY NURSING THROUGH CREATION OF A NEW-TO-SPECIALTY RN FELLOWSHIP

Professional Development Comprehensive cancer centers face serious challenges in sustaining a high-quality nursing workforce in specialized oncology care. Recruiting and retaining experienced nurses has become more challenging during the COVID-19 pandemic and nursing shortage, and efforts for recruitment and retention are often done in isolation with varying success. An NCI-designated cancer care center identified an opportunity to cultivate a successful transition to oncology practice for experienced nurses. The purpose was to create and implement a precision New-to-Specialty RN (NTS-RN) fellowship program to champion successful recruitment, onboarding, and retention in complex oncology workforce development. The nursing staff development team partnered with clinic leaders, human resources representatives, and frontline staff to design a pilot focused on recruiting experienced nurses who were new to oncology and supporting their integration into oncology practice through an innovative fellowship program. A robust program structure of foundational and specialized oncology education, individualized orientation, and reflective practice has helped NTS-RNs expand their clinical expertise to successfully transition to a new specialty and continue to integrate and grow professionally within the organization. 13 NTS-RNs were hired into the fellowship program between October 2019 and May 2022. All 13 NTS-RNs (100%) completed the program and were successfully onboarded into specialty oncology roles across three clinical departments. 11 NTS-RNs (85%) remain with the organization as of September 2022. Program graduates have become preceptors, pursued higher education and oncology certification, advanced to leadership roles, joined shared governance committees, and recruited other candidates to the NTS-RN fellowship. Historically, a bias has existed against recruiting nurses from non-oncology specialties for ambulatory oncology positions. Organizations must move away from this bias and recognize the benefits gained by engaging in the unique clinical expertise and strengths experienced nurses bring from diverse specialties. Leveraging partnerships among staff development, clinic leaders, frontline staff, and human resources fosters successful recruitment, onboarding, and retention of distinctive and highly qualified candidates who are eager to transition to oncology nursing. Under this model, the NTS-RN fellowship program has become a valuable resource used throughout the comprehensive cancer center, serving to improve oncology outcomes.

PCR combined with serologic testing improves the yield and efficiency of SARS-CoV-2 infection hunting: A study in 40,689 consecutive overseas arrivals

Background The global epidemiological situation of COVID-19 remains serious. The rapid hunting of SARS-CoV-2 infection is the key means for preventing transmission. Methods A total of 40,689 consecutive overseas arrivals were screened for SARS-CoV-2 infection based on PCR and serologic testing. The yield and efficiency of different screening algorithms were evaluated. Result Among the 40,689 consecutive overseas arrivals, 56 (0.14%) subjects were confirmed to have SARS-CoV-2 infection. The asymptomatic rate was 76.8%. When the algorithm based on PCR alone was used, the identification yield of a single round of PCR (PCR1) was only 39.3% (95% CI: 26.1–52.5%). It took at least four rounds of PCR to achieve a yield of 92.9% (95% CI: 85.9–99.8%). Fortunately, an algorithm based on a single round of PCR combined with a single round of serologic testing (PCR1+ Ab1) greatly improved the screening yield to 98.2% (95% CI: 94.6–100.0%) and required 42,299 PCR and 40,689 serologic tests that cost 6,052,855 yuan. By achieving a similar yield, the cost of PCR1+ Ab1 was 39.2% of that of four rounds of PCR. For hunting one case in PCR1+ Ab1, 769 PCR and 740 serologic tests were required, costing 110,052 yuan, which was 63.0% of that of the PCR1 algorithm. Conclusion Comparing an algorithm based on PCR alone, PCR combined with a serologic testing algorithm greatly improved the yield and efficiency of the identification of SARS-CoV-2 infection.

PCR combined with serologic testing improves the yield and efficiency of SARS-CoV-2 infection hunting: A study in 40,689 consecutive overseas arrivals.

Background: The global epidemiological situation of COVID-19 remains serious. The rapid hunting of SARS-CoV-2 infection is the key means for preventing transmission. Methods: A total of 40,689 consecutive overseas arrivals were screened for SARS-CoV-2 infection based on PCR and serologic testing. The yield and efficiency of different screening algorithms were evaluated. Result: Among the 40,689 consecutive overseas arrivals, 56 (0.14%) subjects were confirmed to have SARS-CoV-2 infection. The asymptomatic rate was 76.8%. When the algorithm based on PCR alone was used, the identification yield of a single round of PCR (PCR1) was only 39.3% (95% CI: 26.1-52.5%). It took at least four rounds of PCR to achieve a yield of 92.9% (95% CI: 85.9-99.8%). Fortunately, an algorithm based on a single round of PCR combined with a single round of serologic testing (PCR1+ Ab1) greatly improved the screening yield to 98.2% (95% CI: 94.6-100.0%) and required 42,299 PCR and 40,689 serologic tests that cost 6,052,855 yuan. By achieving a similar yield, the cost of PCR1+ Ab1 was 39.2% of that of four rounds of PCR. For hunting one case in PCR1+ Ab1, 769 PCR and 740 serologic tests were required, costing 110,052 yuan, which was 63.0% of that of the PCR1 algorithm. Conclusion: Comparing an algorithm based on PCR alone, PCR combined with a serologic testing algorithm greatly improved the yield and efficiency of the identification of SARS-CoV-2 infection.

Recent advances in immunoassay technologies for the detection of human coronavirus infections.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the seventh coronavirus (CoV) that has spread in humans and has become a global pandemic since late 2019. Efficient and accurate laboratory diagnostic methods are one of the crucial means to control the development of the current pandemic and to prevent potential future outbreaks. Although real-time reverse transcription-polymerase chain reaction (rRT-PCR) is the preferred laboratory method recommended by the World Health Organization (WHO) for diagnosing and screening SARS-CoV-2 infection, the versatile immunoassays still play an important role for pandemic control. They can be used not only as supplemental tools to identify cases missed by rRT-PCR, but also for first-line screening tests in areas with limited medical resources. Moreover, they are also indispensable tools for retrospective epidemiological surveys and the evaluation of the effectiveness of vaccination. In this review, we summarize the mainstream immunoassay methods for human coronaviruses (HCoVs) and address their benefits, limitations, and applications. Then, technical strategies based on bioinformatics and advanced biosensors were proposed to improve the performance of these methods. Finally, future suggestions and possibilities that can lead to higher sensitivity and specificity are provided for further research.

Analyzing Public Conversations About Heart Disease and Heart Health on Facebook From 2016 to 2021: Retrospective Observational Study Applying Latent Dirichlet Allocation Topic Modeling.

BACKGROUND: Heart disease continues to be the leading cause of death in men and women in the United States. The COVID-19 pandemic has further led to increases in various long-term cardiovascular complications. OBJECTIVE: This study analyzed public conversations related to heart disease and heart health on Facebook in terms of their thematic topics and sentiments. In addition, it provided in-depth analyses of 2 subtopics with important practical implications: heart health for women and heart health during the COVID-19 pandemic. METHODS: We collected 34,885 posts and 51,835 comments spanning from June 2016 to June 2021 that were related to heart disease and health from public Facebook pages and groups. We used latent Dirichlet allocation topic modeling to extract discussion topics illuminating the public's interests and concerns regarding heart disease and heart health. We also used Linguistic Inquiry and Word Count (Pennebaker Conglomerates, Inc) to identify public sentiments regarding heart health. RESULTS: We observed an increase in discussions related to heart health on Facebook. Posts and comments increased from 3102 and 3632 in 2016 to 8550 (176% increase) and 14,617 (302% increase) in 2021, respectively. Overall, 35.37% (12,340/34,885) of the posts were created after January 2020, the start of the COVID-19 pandemic. In total, 39.21% (13,677/34,885) of the posts were by nonprofit health organizations. We identified 6 topics in the posts (heart health promotion, personal experiences, risk-reduction education, heart health promotion for women, educational information, and physicians' live discussion sessions). We identified 6 topics in the comments (personal experiences, survivor stories, risk reduction, religion, medical questions, and appreciation of physicians and information on heart health). During the pandemic (from January 2020 to June 2021), risk reduction was a major topic in both posts and comments. Unverified information on alternative treatments and promotional content was also prevalent. Among all posts, 14.91% (5200/34,885) were specifically about heart health for women centering on local event promotion and distinctive symptoms of heart diseases for women. CONCLUSIONS: Our results tracked the public's ongoing discussions on heart disease and heart health on one prominent social media platform, Facebook. The public's discussions and information sharing on heart health increased over time, especially since the start of the COVID-19 pandemic. Various levels of health organizations on Facebook actively promoted heart health information and engaged a large number of users. Facebook presents opportunities for more targeted heart health interventions that can reach and engage diverse populations.

Recent advances on CRISPR/Cas system-enabled portable detection devices for on-site agri-food safety assay

Background Agri-food safety has been considered as one of the most important public concerns worldwide. From farm to table, food crops and foods are extremely vulnerable to the contamination by a variety of pollutants from their growth and processing. Moreover, the SARS-CoV-2 detected in the food supply chain during COVID-19 pandemic has posed a greater challenge for rapid and on-site detection of agri-food contaminants in complex and volatile environments. Therefore, the development of rapid, accurate, and on-site detection technologies and portable detection devices is of great importance to ensure the agri-food security. Scope and approach This review comprehensively summarized the recent advances on the construction of CRISPR/Cas systems-based biosensing technologies and their portable detection devices, as well as their promising applications in the field of agri-food safety. First of all, the classification and working principles of CRISPR/Cas systems were introduced. Then, the latest advances on the CRISPR/Cas system-based on-site detection technologies and portable detection devices were also systematically summarized. Most importantly, the state-of-the-art applications of CRISPR/Cas systems-based on-site detection technologies and portable detection devices in the fields of agri-food safety were comprehensively summarized. Impressively, the future opportunities and challenges in this emerging and promising field were proposed. Key findings and conclusions Emerging CRISPR/Cas system-based on-site detection technologies have showed a great potential in the detection of agri-food safety. Impressively, the integration of CRISPR/Cas systems-based biosensing technologies with portable detection devices (e.g., nanopore-based detection devices, lateral flow assay, smartphone-based detection devices, and microfluidic devices) is very promising for the on-site detection of agri-food contaminants. Additionally, CRISPR/Cas system-based biosensing technologies can be further integrated with much more innovative technologies for the development of novel detection platforms to realize the more reliable on-site detection of agri-food safety.

Multiplicity and dynamics of social representations of the COVID-19 pandemic on Chinese social media from 2019 to 2020.

Documenting the emergent social representations of COVID-19 in public communication is necessary for critically reflecting on pandemic responses and providing guidance for global pandemic recovery policies and practices. This study documents the dynamics of changing social representations of the COVID-19 pandemic on one of the largest Chinese social media, Weibo, from December 2019 to April 2020. We draw on the social representation theory (SRT) and conceptualize topics and topic networks as a form of social representation. We analyzed a dataset of 40 million COVID-19 related posts from 9.7 million users (including the general public, opinion leaders, and organizations) using machine learning methods. We identified 12 topics and found an expansion in social representations of COVID-19 from a clinical and epidemiological perspective to a broader perspective that integrated personal illness experiences with economic and sociopolitical discourses. Discussions about COVID-19 science did not take a prominent position in the representations, suggesting a lack of effective science and risk communication. Further, we found the strongest association of social representations existed between the public and opinion leaders and the organizations' representations did not align much with the other two groups, suggesting a lack of organizations' influence in public representations of COVID-19 on social media in China.

Acupuncture for nasal congestion in COVID-19: A protocol for systematic review and meta-analysis.

BACKGROUND: From the end of 2019 to now, coronavirus disease 2019 (COVID-19) has put enormous strain on the world's health systems, causing significant deaths and economic losses worldwide. Nasal congestion, one of the symptoms of COVID-19, poses considerable problems for patients. In China, acupuncture has been widely used to treat nasal congestion caused by COVID-19, but there is still a lack of evidence-based medical evaluation. METHODS: According to the retrieval strategies, randomized controlled trials on the acupuncture for COVID-19 nasal congestion were obtained from China National Knowledge Infrastructure, WanFang, VIP, PubMed, Embase, and Cochrane Library, regardless of publication date, or language. Studies were screened based on inclusion and exclusion criteria, and the Cochrane risk bias assessment tool was used to evaluate the quality of the studies. The meta-analysis was performed using Review Manager (RevMan 5.3) and STATA 14.2 software. Ultimately, the evidentiary grade for the results will be evaluated. RESULTS: The study will provide a high-quality and convincing assessment of the efficacy and safety of acupuncture in the treatment of COVID-19's nasal congestion and will be published in peer-reviewed journals. CONCLUSION: Our findings will provide references for future clinical decision and guidance development. PROSPERO REGISTRATION NUMBER: NO.CRD42021299482.

Factors associated with prolonged duration of viral clearance in non-severe SARS-CoV-2 patients in Osaka, Japan.

BACKGROUND: We investigated factors associated with prolonged viral clearance of SARS-CoV-2 among non-severe adult patients in Osaka, Japan. A total of 706 laboratory-confirmed COVID-19 patients were enrolled in this longitudinal observational study between 29 January 2020 and 31 May 2020, across 62 hospitals and three non-hospital recuperation facilities. METHODS: Logistic regression analysis was performed to investigate the factors associated with prolonged (29 days: upper 25% in duration) viral clearance of SARS-CoV-2. Linear regression analysis was conducted to assess these factors 14 days after symptom onset. RESULTS: The median duration of viral clearance was 22 days from symptom onset. After adjustment for sex, age, symptoms, comorbidity, and location of recuperation, comorbidities were associated with prolonged duration: (OR, 1.77 [95% CI, 1.11-2.82]) for one, (OR, 2.47 [95% CI, 1.32-4.61]) for two or more comorbidities. Viral clearance 14 days after symptom onset was 3 days longer for one comorbidity and 4 days longer for two or more comorbidities compared to clearance when there was no comorbidity. CONCLUSION: The presence of comorbidity was a robust factor associated with a longer duration of viral clearance, extending by 3 to 4 days compared to patients with no comorbidity.

Risk factors associated with mortality of COVID-19 in 3125 counties of the United States.

BACKGROUND: The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. The risk factors associated with county-level mortality of COVID-19 with various levels of prevalence are not well understood. METHODS: Using the data obtained from the County Health Rankings and Roadmaps program, this study applied a negative binomial design to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies. Clustering analysis and Kruskal-Wallis tests were used in our statistical analysis. RESULTS: A total of 3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153, P < 0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median (0.049, P < 0.001) and high (0.114, P < 0.001) prevalence counties. The segregation between non-Whites and Whites (low: 0.015, P < 0.001; median:0.025, P < 0.001; high: 0.019, P = 0.005) and higher Hispanic population (low and median: 0.020, P < 0.001; high: 0.014, P = 0.009) had higher likelihood of risk of the deaths in all infected counties. CONCLUSIONS: The mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may help decision makers, the public health officials, and the general public better control the risk of pandemic, particularly in the reduction in the mortality of COVID-19.

Effects of fact-checking social media vaccine misinformation on attitudes toward vaccines.

Social media vaccine misinformation can negatively influence vaccine attitudes. It is urgent to develop communication approaches to reduce the misinformation's impact. This study aimed to test the effects of fact-checking labels for misinformation on attitudes toward vaccines. An online survey experiment with 1198 participants recruited from a U.S. national sample was conducted in 2018. Participants were randomly assigned to six conditions: misinformation control, or fact-checking label conditions attributed to algorithms, news media, health institutions, research universities, or fact-checking organizations. We analyzed differences in vaccine attitudes between the fact-checking label and control conditions. Further, we compared perceived expertise and trustworthiness of the five categories of fact-checking sources. Fact-checking labels attached to misinformation posts made vaccine attitudes more positive compared to the misinformation control condition (P = .003, Cohen's d= 0.21). Conspiracy ideation moderated the effect of the labels on vaccine attitudes (P = .02). Universities and health institutions were rated significantly higher on source expertise than other sources. Mediation analyses showed labels attributed to universities and health institutions indirectly resulted in more positive attitudes than other sources through perceived expertise. Exposure to fact-checking labels on misinformation can generate more positive attitudes toward vaccines in comparison to exposure to misinformation. Incorporating labels from trusted universities and health institutions on social media platforms is a promising direction for addressing the vaccine misinformation problem. This points to the necessity for closer collaboration between public health and research institutions and social media companies to join efforts in addressing the current misinformation threat.

The characteristics and clinical course of patients with COVID-19 who received invasive mechanical ventilation in Osaka, Japan.

OBJECTIVE: To describe the detailed clinical course of patients with coronavirus disease 2019 (COVID-19) who received invasive mechanical ventilation. METHODS: We conducted a case series of patients with COVID-19 who received invasive mechanical ventilation in Osaka, Japan, between January 29 and May 28, 2020. We describe the patient characteristics and clinical course from onset. Additionally, we fitted logistic regression models to investigate the associations between patient characteristics and the 30-day mortality rate. RESULTS: A total of 125 patients who received invasive mechanical ventilation (median age [interquartile range], 68 [57-73] years; male, 77.6%) were enrolled. Overall, the 30-day mortality was 24.0%, and the median (interquartile range) length of ICU stay and length of invasive mechanical ventilation use were 16 (12-29) days and 13 (9-26) days, respectively. From clinical onset, 121 patients (96.8%) were intubated within 14 days. In multivariable logistic regression analysis, age of 65 years or older (odds ratio, 3.56; 95% confidence interval, 1.21-10.49; P = 0.02) and male sex (odds ratio, 3.75; 95% confidence interval, 1.00-11.24, P = 0.04) were significantly associated with a higher 30-day mortality rate. CONCLUSIONS: In this case series of patients with COVID-19 who received invasive mechanical ventilation in Japan, the 30-day mortality rate was 24.0%, and age 65 years or older and male sex were associated with higher 30-day mortality rate.

The Impacts on the Strategies of Gourmet Video We-media Due to the Outbreak of COVID-19: Taking Bilibili as an Example

Based on the principle of combination of theory and practice, this paper starts with two hypotheses, and studies the changes of target strategies of gourmet we-media, represented by the 10 most influential gourmet we-media in Bilibili. Some relevant calculations and questionnaire results are taken as research samples for data analysis and content analysis, and the following conclusions are drawn: firstly, due to the COVID- 19, the content of gourmet we-media has been adjusted in different degrees, and the proportion of homemade food teaching videos has increased. Videos related to the social problems caused by the COVID-19 have gained more attention. Secondly, during the pandemic, the time for audiences to watch the food video increased. At the same time, the audience has a variety of expectations for the contents of food we-media. Thirdly, the strategy change of we-media is effective, which is not only conducive to improving their popularity, discussion and actual income, but also can meet the five needs of audience's personal use of media, especially to reduce anxiety. The research result has timeliness, innovation and exploration in the field of media. It is helpful to guide the gourmet we-media to adjust the target strategy in response to public emergencies in time, so as to achieve sustained and good development, with high reference and inspiration value for the gourmet we-media industry.

Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study.

BACKGROUND: Coronavirus disease (COVID-19) has affected more than 200 countries and territories worldwide. This disease poses an extraordinary challenge for public health systems because screening and surveillance capacity is often severely limited, especially during the beginning of the outbreak; this can fuel the outbreak, as many patients can unknowingly infect other people. OBJECTIVE: The aim of this study was to collect and analyze posts related to COVID-19 on Weibo, a popular Twitter-like social media site in China. To our knowledge, this infoveillance study employs the largest, most comprehensive, and most fine-grained social media data to date to predict COVID-19 case counts in mainland China. METHODS: We built a Weibo user pool of 250 million people, approximately half the entire monthly active Weibo user population. Using a comprehensive list of 167 keywords, we retrieved and analyzed around 15 million COVID-19-related posts from our user pool from November 1, 2019 to March 31, 2020. We developed a machine learning classifier to identify "sick posts," in which users report their own or other people's symptoms and diagnoses related to COVID-19. Using officially reported case counts as the outcome, we then estimated the Granger causality of sick posts and other COVID-19 posts on daily case counts. For a subset of geotagged posts (3.10% of all retrieved posts), we also ran separate predictive models for Hubei province, the epicenter of the initial outbreak, and the rest of mainland China. RESULTS: We found that reports of symptoms and diagnosis of COVID-19 significantly predicted daily case counts up to 14 days ahead of official statistics, whereas other COVID-19 posts did not have similar predictive power. For the subset of geotagged posts, we found that the predictive pattern held true for both Hubei province and the rest of mainland China regardless of the unequal distribution of health care resources and the outbreak timeline. CONCLUSIONS: Public social media data can be usefully harnessed to predict infection cases and inform timely responses. Researchers and disease control agencies should pay close attention to the social media infosphere regarding COVID-19. In addition to monitoring overall search and posting activities, leveraging machine learning approaches and theoretical understanding of information sharing behaviors is a promising approach to identify true disease signals and improve the effectiveness of infoveillance.