Examining COVID-19 Tweet Diffusion Using an Integrated Social Amplification of Risk and Issue-Attention Cycle Framework.

Drawing upon the social amplification of risk (SARF) and the issue-attention cycle framework, we examined the amplification of COVID-19 risk-related tweets through (a) topics: key interests of discussion; (b) temperament: emotions of tweets; (c) topography (i.e., location); and (d) temporality (i.e., over time). We computationally analyzed 1,641,273 tweets, and conducted manual content analysis on a subset of 6,000 tweets to identify how topics, temperament, and topography of COVID-19 tweets were associated with risk amplification - retweet and favorite count - using negative binomial regression. We found 11 dominant COVID-19 topics-health impact, economic impact, reports of lockdowns, report of new cases, the need to stay home, coping with COVID-19, news about President Trump, government support, fight with COVID-19 by non-government entities, origins, and preventive measure in our corpus of tweets across the issue-attention cycle. The negative binomial regression results showed that at the pre-problem stage, topics on President Trump, speculation of origins, and initiatives to fight COVID-19 by non-government entities were most likely to be amplified, underscoring the inherent politicization of COVID-19 and erosion of trust in governments from the start of the pandemic. We also found that while tweets with negative emotions were consistently amplified throughout the issue-attention cycle, surprisingly tweets with positive emotions were amplified during the height of the pandemic - this counter-intuitive finding indicated signs of premature and misplaced optimism. Finally, our results showed that the locations of COVID-19 tweet amplification corresponded to the shifting COVID-19 hotspots across different continents across the issue-attention cycle. Theoretical and practical implications of risk amplification on social media are discussed.

Pharmacokinetics and Absorption, Distribution, Metabolism and Excretion of RGLS4326 in Mouse and Monkey, an Anti-miR-17 Oligonucleotide for the Treatment of Polycystic Kidney Disease.

RGLS4326 is a short oligonucleotide inhibitor of microRNA-17 (miR-17) that preferentially distributes to the kidney and displaces miR-17 from translationally active polysomes. Here, we present pharmacokinetics and absorption, distribution, metabolism, and excretion properties of RGLS4326 from mice and monkeys. RGLS4326 was absorbed rapidly after subcutaneous administration, distributed extensively to the kidney and liver, with preferential distribution to the kidney, and cleared rapidly from plasma by tissue uptake and renal excretion. Plasma exposure increased in a dose-proportional manner with no notable accumulation after repeat doses. Plasma protein binding of RGLS4326 across all species tested was between 79% and 96%. RGLS4326 predominantly distributed to the kidney with a long half-life (t1/2; t1/2 ranged from 8-11 days) and no marked (≤twofold) accumulation in kidney and liver after repeat doses. RGLS4326 was minimally metabolized by nucleases, not cytochrome P450 (P450) isozymes, across species and underwent sequential hydrolysis from both 3' and 5' ends to produce chain-shortened metabolites. There were no human unique metabolites observed. Renal excretion was the major route of elimination of RGLS4326, and a significant fraction (50%-79%) of the dose was recovered intact in the urine of mice and monkeys across all dose levels. RGLS4326 is not a substrate, inhibitor, or inducer of P450 isozymes, and it is not a substrate or inhibitor of uptake and most efflux transporters. Thus, RGLS4326 exhibits low potential of mediating drug-drug interactions involving P450 isozymes and drug transporters. SIGNIFICANCE STATEMENT: Pharmacokinetics (PK) and absorption, distribution, metabolism, and excretion (ADME) properties of RGLS4326 were characterized in vivo and in vitro. RGLS4326 shows similar PK and ADME properties across mice and monkeys in vivo and across human and animal matrices in vitro. Subcutaneous administration results in preferential exposure of RGLS4326 to the intended target organ (kidney) to drive maximum target engagement. These studies support the interpretation of toxicology and efficacy studies and help characterize the disposition of RGLS4326 in humans.

Examining Antecedents of Factual Knowledge and Perceived Familiarity of COVID-19 Contact Tracing App: A Modified Cognitive Mediation Model.

This study employs a modified cognitive mediation model to investigate the role of health valuation and fear in shaping media attention, factual knowledge, and perceived familiarity with COVID-19 contact tracing apps. Data were collected from a national survey of 906 Singaporeans, and structural equation modeling was used to analyze the results. Findings indicated that both fear of COVID-19 and health valuation were positively associated with newspapers, television, and social media attention, with health valuation demonstrating a stronger association with each media type. This suggests that health valuation, as an intrinsic motivation, is more critical in information-seeking behavior related to emerging health technologies. However, media attention on all platforms did not correlate with factual knowledge of COVID-19 contact tracing apps, whereas attention to social media was positively associated with perceived familiarity with these apps. This result highlights the potential influence of social media in shaping public perceptions, warranting further investigation into the quality and accuracy of the information disseminated. News elaboration was found to have a positive association with both factual knowledge and perceived familiarity with COVID-19 contact tracing apps. This underscores the need for effective communication strategies to promote accurate understanding of health technologies and emphasizes the role of individual motivations in shaping media consumption and information processing.

Examining Theoretical Frameworks and Antecedents of Health Apps and Wearables Use: A Scoping Review.

The advancement of health apps and wearables has garnered substantial academic attention, particularly in examining why individuals decide to use or not use them. In response to the extensive body of research on this topic, we conducted a scoping review of 61 articles published from 2007 to 2022, aiming to examine the dominant theoretical frameworks and antecedents of health apps and wearables use. The findings demonstrated that the dominant theoretical frameworks within this domain were rooted in the human-computer interaction theories, notably the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology. Next, our review identified four levels of antecedents: technological, individual, societal, and policy. At the technological level, emphasis was placed on functionality, reliability, and technological infrastructure. Individual antecedents encompassed socio-demographics, personality traits, cognitive responses to benefits and risks, emotional and affective responses, self-efficacy, and digital literacy. Societal antecedents highlighted the role of social networks and social norms, while policy antecedents elaborated on laws, regulations, and guidelines that encouraged health technology adoption. Our discussion illuminated that the evolving trend of theoretical frameworks in health apps and wearables use research, initially rooted in human-computer interaction, is progressively moving toward more comprehensive perspectives. We further underscored the importance of delving into societal and policy antecedents, which often are overshadowed by the more commonly discussed technological and individual factors. In conclusion, we advocated for a multi-stakeholder collaborative network approach, as this would enable communication researchers to understand the use of health apps and wearables more comprehensively.

Toward an Extended Infodemiology Framework: Leveraging Social Media Data and Web Search Queries as Digital Pulse on Cancer Communication.

This study aims to extend the infodemiology framework by postulating that effective use of digital data sources for cancer communication should consider four components: (a) content: key topics that people are concerned with, (b) congruence: how interest in cancer topics differ between public posts (i.e., tweets) and private web searches, (c) context: the influence of the information environment, and (d) information conduits. We compared tweets (n = 36, 968) and Google web searches on breast, lung, and prostate cancer between the National Cancer Prevention Month and a non-cancer awareness month in 2018. There are three key findings. First, reliance on public tweets alone may result in lost opportunities to identify potential cancer misinformation detected from private web searches. Second, lung cancer tweets were most sensitive to external information environment - tweets became substantially pessimistic after the end of cancer awareness month. Finally, the cancer communication landscape was largely democratized, with no prominent conduits dominating conversations on Twitter.

Exploring the Incentive Function of Virtual Academic Degrees in a Chinese Online Smoking Cessation Community: Qualitative Content Analysis.

BACKGROUND: Previous studies on online smoking cessation communities (OSCCs) have shown how such networks contribute to members' health outcomes from behavior influence and social support perspectives. However, these studies rarely considered the incentive function of OSCCs. One of the ways OSCCs motivate smoking cessation behaviors is through digital incentives. OBJECTIVE: This study aims to explore the incentive function of a novel digital incentive in a Chinese OSCC-the awarding of academic degrees-to promote smoking cessation. It specifically focuses on "Smoking Cessation Bar," an OSCC in the popular web-based Chinese forum Baidu Tieba. METHODS: We collected discussions about the virtual academic degrees (N= 1193) from 540 members of the "Smoking Cessation Bar." The time frame of the data set was from November 15, 2012, to November 3, 2021. Drawing upon motivational affordances theory, 2 coders qualitatively coded the data. RESULTS: We identified five key topics of discussion, including members' (1) intention to get virtual academic degrees (n=38, 2.47%), (2) action to apply for the degrees (n=312, 20.27%), (3) feedback on the accomplishment of goals (n=203, 13.19%), (4) interpersonal interaction (n=794, 51.59%), and (5) expression of personal feelings (n=192, 12.48%). Most notably, the results identified underlying social and psychological motivations behind using the forum to discuss obtaining academic degrees for smoking cessation. Specifically, members were found to engage in sharing behavior (n=423, 27.49%) over other forms of interaction such as providing recommendations or encouragement. Moreover, expressions of personal feelings about achieving degrees were generally positive. It was possible that members hid their negative feelings (such as doubt, carelessness, and dislike) in the discussion. CONCLUSIONS: The virtual academic degrees in the OSCC created opportunities for self-presentation for participants. They also improved their self-efficacy to persist in smoking cessation by providing progressive challenges. They served as social bonds connecting different community members, triggering interpersonal interactions, and inducing positive feelings. They also helped realize members' desire to influence or to be influenced by others. Similar nonfinancial rewards could be adopted in various smoking cessation projects to enhance participation and sustainability.

Infectious diseases prevention and control using an integrated health big data system in China.

BACKGROUND: The Yinzhou Center for Disease Prevention and Control (CDC) in China implemented an integrated health big data platform (IHBDP) that pooled health data from healthcare providers to combat the spread of infectious diseases, such as dengue fever and pulmonary tuberculosis (TB), and to identify gaps in vaccination uptake among migrant children. METHODS: IHBDP is composed of medical data from clinics, electronic health records, residents' annual medical checkup and immunization records, as well as administrative data, such as student registries. We programmed IHBDP to automatically scan for and detect dengue and TB carriers, as well as identify migrant children with incomplete immunization according to a comprehensive set of screening criteria developed by public health and medical experts. We compared the effectiveness of the big data screening with existing traditional screening methods. RESULTS: IHBDP successfully identified six cases of dengue out of a pool of 3972 suspected cases, whereas the traditional method only identified four cases (which were also detected by IHBDP). For TB, IHBDP identified 288 suspected cases from a total of 43,521 university students, in which three cases were eventually confirmed to be TB carriers through subsequent follow up CT or T-SPOT.TB tests. As for immunization screenings, IHBDP identified 240 migrant children with incomplete immunization, but the traditional door-to-door screening method only identified 20 ones. CONCLUSIONS: Our study has demonstrated the effectiveness of using IHBDP to detect both acute and chronic infectious disease patients and identify children with incomplete immunization as compared to traditional screening methods.

Designing Effective eHealth Interventions for Underserved Groups: Five Lessons From a Decade of eHealth Intervention Design and Deployment.

Despite the proliferation of eHealth interventions, such as web portals, for health information dissemination or the use of mobile apps and wearables for health monitoring, research has shown that underserved groups do not benefit proportionately from these eHealth interventions. This is largely because of usability issues and the lack of attention to the broader structural, physical, and psychosocial barriers to technology adoption and use. The objective of this paper is to draw lessons from a decade of experience in designing different user-centered eHealth interventions (eg, web portals and health apps) to inform future work in leveraging technology to address health disparities. We draw these lessons from a series of interventions from the work we have done over 15 years in the Viswanath laboratory at the Dana-Farber Cancer Institute and Harvard TH Chan School of Public Health, focusing on three projects that used web portals and health apps targeted toward underserved groups. The projects were the following: Click to Connect, which was a community-based eHealth intervention that aimed to improve internet skills and health literacy among underserved groups by providing home access to high-speed internet, computer, and internet training classes, as well as a dedicated health web portal with ongoing technical support; PLANET MassCONECT, which was a knowledge translation project that built capacity among community-based organizations in Boston, Lawrence, and Worcester in Massachusetts to adopt evidence-based health promotion programs; and Smartphone App for Public Health, which was a mobile health research that facilitated both participatory (eg, surveys) and passive data (eg, geolocations and web-browsing behaviors) collection for the purpose of understanding tobacco message exposure in individuals' built environment. Through our work, we distilled five key principles for researchers aiming to design eHealth interventions for underserved groups. They are as follows: develop a strategic road map to address communication inequalities (ie, a concrete action plan to identify the barriers faced by underserved groups and customize specific solutions to each of them), engage multiple stakeholders from the beginning for the long haul, design with usability-readability and navigability-in mind, build privacy safeguards into eHealth interventions and communicate privacy-utility tradeoffs in simplicity, and strive for an optimal balance between open science aspirations and protection of underserved groups.

Examining Organizational, Cultural, and Individual-Level Factors Related to Workplace Safety and Health: A Systematic Review and Metric Analysis.

One major gap in existing health communication research is that few studies have synthesized findings from the literature to map out what are the key factors related to workplace (a) safety awareness, (b) safety risks, (c) health awareness, and (d) health risks. This study bridges the gap by systematically reviewing what these organizational, cultural, and individual-level factors are, and examine the impact of workplace safety and health publications using traditional and alternative metrics in academic and non-academic settings. Through an iterative process of coding, the results revealed six categories of organizational (management commitment, management support, organizational safety communication, safety management systems, physical work environment, and organizational environment), two cultural (interpersonal support and organizational culture), and four individual-level (perception, motivation, attitude, and behavior) factors. In terms of impact, articles that were most impactful in academia (e.g., high citation count) may not necessarily receive the same amount of online attention from the public. Theoretical and practical implications for health communication were discussed.

Examining Twitter Discourse on Electronic Cigarette and Tobacco Consumption During National Cancer Prevention Month in 2018: Topic Modeling and Geospatial Analysis.

BACKGROUND: Examining public perception of tobacco products is critical for effective tobacco policy making and public education outreach. While the link between traditional tobacco products and lung cancer is well established, it is not known how the public perceives the association between electronic cigarettes (e-cigarettes) and lung cancer. In addition, it is unclear how members of the public interact with official messages during cancer campaigns on tobacco consumption and lung cancer. OBJECTIVE: In this study, we aimed to analyze e-cigarette and smoking tweets in the context of lung cancer during National Cancer Prevention Month in 2018 and examine how e-cigarette and traditional tobacco product discussions relate to implementation of tobacco control policies across different states in the United States. METHODS: We mined tweets that contained the term "lung cancer" on Twitter from February to March 2018. The data set contained 13,946 publicly available tweets that occurred during National Cancer Prevention Month (February 2018), and 10,153 tweets that occurred during March 2018. E-cigarette-related and smoking-related tweets were retrieved, using topic modeling and geospatial analysis. RESULTS: Debates on harmfulness (454/915, 49.7%), personal experiences (316/915, 34.5%), and e-cigarette risks (145/915, 15.8%) were the major themes of e-cigarette tweets related to lung cancer. Policy discussions (2251/3870, 58.1%), smoking risks (843/3870, 21.8%), and personal experiences (776/3870, 20.1%) were the major themes of smoking tweets related to lung cancer. Geospatial analysis showed that discussion on e-cigarette risks was positively correlated with the number of state-level smoke-free policies enacted for e-cigarettes. In particular, the number of indoor and on campus smoke-free policies was related to the number of tweets on e-cigarette risks (smoke-free indoor, r49=0.33, P=.02; smoke-free campus, r49=0.32, P=.02). The total number of e-cigarette policies was also positively related to the number of tweets on e-cigarette risks (r49=0.32, P=.02). In contrast, the number of smoking policies was not significantly associated with any of the smoking themes in the lung cancer discourse (P>.13). CONCLUSIONS: Though people recognized the importance of traditional tobacco control policies in reducing lung cancer incidences, their views on e-cigarette risks were divided, and discussions on the importance of e-cigarette policy control were missing from public discourse. Findings suggest the need for health organizations to continuously engage the public in discussions on the potential health risks of e-cigarettes and raise awareness of the insidious lobbying efforts from the tobacco industry.

We Need the Lens of Equity in COVID-19 Communication.

The ongoing COVID-19 pandemic has brought forward the centrality of public communication as a force for information, and in highlighting the differential impact on diverse segments of the society. Information and communication technologies-led developments including social media have previously been discussed as instruments of democratization of knowledge. However, the evidence so far shows that the promise remains unfulfilled as upper socioeconomic groups acquire information at a faster rate than others. The communication inequalities have only reinforced the existing societal fault lines of race, class and place. As the first pandemic of the social media age, COVID-19 has also given rise to an "infodemic", providing fertile ground for the spread of information, misinformation and disinformation. With limited gatekeeping, an immense amount of unprocessed scientific information is being put forward to publics not trained in science. In this commentary, we offer some propositions on how disinformation on COVID-19 has become mainstreamed through social media's spiral of amplification and what role public communication has in an emergency from a lens of equity. We raise the question of whether the tremendous flow of scientific information during the COVID-19 pandemic has a differential impact on different socioeconomic groups. We propose that more systematic research is urgently needed to understand how mis/disinformation originate, spread and what their consequences are. In our view, research in health communication inequalities is foundational to mitigating the current off-line and online ravages of the pandemic.

Big Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research.

Recent advances in the collection and processing of health data from multiple sources at scale-known as big data-have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of continuing health disparities. The 2 key objectives of this paper were as follows: first, it introduced 2 main problems of health big data in the context of health disparities-data absenteeism (lack of representation from underprivileged groups) and data chauvinism (faith in the size of data without considerations for quality and contexts). Second, this paper suggested that health organizations should strive to go beyond the current fad and seek to understand and coordinate efforts across the surrounding societal-, organizational-, individual-, and data-level contexts in a realistic manner to leverage big data to address health disparities.

The Potential of Smartphone Apps in Informing Protobacco and Antitobacco Messaging Efforts Among Underserved Communities: Longitudinal Observational Study.

BACKGROUND: People from underserved communities such as those from lower socioeconomic positions or racial and ethnic minority groups are often disproportionately targeted by the tobacco industry, through the relatively high levels of tobacco retail outlets (TROs) located in their neighborhood or protobacco marketing and promotional strategies. It is difficult to capture the smoking behaviors of individuals in actual locations as well as the extent of exposure to tobacco promotional efforts. With the high ownership of smartphones in the United States-when used alongside data sources on TRO locations-apps could potentially improve tobacco control efforts. Health apps could be used to assess individual-level exposure to tobacco marketing, particularly in relation to the locations of TROs as well as locations where they were most likely to smoke. To date, it remains unclear how health apps could be used practically by health promotion organizations to better reach underserved communities in their tobacco control efforts. OBJECTIVE: This study aimed to demonstrate how smartphone apps could augment existing data on locations of TROs within underserved communities in Massachusetts and Texas to help inform tobacco control efforts. METHODS: Data for this study were collected from 2 sources: (1) geolocations of TROs from the North American Industry Classification System 2016 and (2) 95 participants (aged 18 to 34 years) from underserved communities who resided in Massachusetts and Texas and took part in an 8-week study using location tracking on their smartphones. We analyzed the data using spatial autocorrelation, optimized hot spot analysis, and fitted power-law distribution to identify the TROs that attracted the most human traffic using mobility data. RESULTS: Participants reported encountering protobacco messages mostly from store signs and displays and antitobacco messages predominantly through television. In Massachusetts, clusters of TROs (Dorchester Center and Jamaica Plain) and reported smoking behaviors (Dorchester Center, Roxbury Crossing, Lawrence) were found in economically disadvantaged neighborhoods. Despite the widespread distribution of TROs throughout the communities, participants overwhelmingly visited a relatively small number of TROs in Roxbury and Methuen. In Texas, clusters of TROs (Spring, Jersey Village, Bunker Hill Village, Sugar Land, and Missouri City) were found primarily in Houston, whereas clusters of reported smoking behaviors were concentrated in West University Place, Aldine, Jersey Village, Spring, and Baytown. CONCLUSIONS: Smartphone apps could be used to pair geolocation data with self-reported smoking behavior in order to gain a better understanding of how tobacco product marketing and promotion influence smoking behavior within vulnerable communities. Public health officials could take advantage of smartphone data collection capabilities to implement targeted tobacco control efforts in these strategic locations to reach underserved communities in their built environment.

SAHA and cisplatin sensitize gastric cancer cells to doxorubicin by induction of DNA damage, apoptosis and perturbation of AMPK-mTOR signalling.

Chemotherapy remains the most prescribed anti-cancer therapy, despite patients suffering severe side effects and frequently developing chemoresistance. These complications can be partially overcome by combining different chemotherapeutic agents that target multiple biological pathways. However, selecting efficacious drug combinations remains challenging. We previously used fission yeast Schizosaccharomycespombe as a surrogate model to predict drug combinations, and showed that suberoylanilide hydroxamic acid (SAHA) and cisplatin can sensitise gastric adenocarcinoma cells toward the cytotoxic effects of doxorubicin. Yet, how this combination undermines cell viability is unknown. Here, we show that SAHA and doxorubicin markedly enhance the cleavage of two apoptosis markers, caspase 3 and poly-ADP ribose polymerase (PARP-1), and increase the phosphorylation of γH2AX, a marker of DNA damage. Further, we found a prominent reduction in Ser485 phosphorylation of AMP-dependent protein kinase (AMPK), and reductions in its target mTOR and downstream ribosomal protein S6 phosphorylation. We show that SAHA contributes most of the effect, as confirmed using another histone deacetylase inhibitor, trichostatin A. Overall, our results show that the combination of SAHA and doxorubicin can induce apoptosis in gastric adenocarcinoma in a synthetically lethal manner, and that fission yeast offers an efficient tool for identifying potent drug combinations against human cancer cells.

Predicting HLA alleles from high-resolution SNP data in three Southeast Asian populations.

The major histocompatibility complex (MHC) containing the classical human leukocyte antigen (HLA) Class I and Class II genes is among the most polymorphic and diverse regions in the human genome. Despite the clinical importance of identifying the HLA types, very few databases jointly characterize densely genotyped single nucleotide polymorphisms (SNPs) and HLA alleles in the same samples. To date, the HapMap presents the only public resource that provides a SNP reference panel for predicting HLA alleles, constructed with four collections of individuals of north-western European, northern Han Chinese, cosmopolitan Japanese and Yoruba Nigerian ancestry. Owing to complex patterns of linkage disequilibrium in this region, it is unclear whether the HapMap reference panels can be appropriately utilized for other populations. Here, we describe a public resource for the Singapore Genome Variation Project with: (i) dense genotyping across ∼ 9000 SNPs in the MHC; (ii) four-digit HLA typing for eight Class I and Class II loci, in 96 southern Han Chinese, 89 Southeast Asian Malays and 83 Tamil Indians. This resource provides population estimates of the frequencies of HLA alleles at these eight loci in the three population groups, particularly for HLA-DPA1 and HLA-DPB1 that were not assayed in HapMap. Comparing between population-specific reference panels and a cosmopolitan panel created from all four HapMap populations, we demonstrate that more accurate imputation is obtained with population-specific panels than with the cosmopolitan panel, especially for the Malays and Indians but even when imputing between northern and southern Han Chinese. As with SNP imputation, common HLA alleles were imputed with greater accuracy than low-frequency variants.

The Augmented Cognitive Mediation Model: Examining Antecedents of Factual and Structural Breast Cancer Knowledge Among Singaporean Women.

As knowledge acquisition is an important component of health communication research, this study examines factors associated with Singaporean women's breast cancer knowledge using an augmented cognitive mediation model. We conducted a nationally representative study that surveyed 802 women between the ages of 30 and 70 using random-digit dialing. The results supported the augmented cognitive mediation model, which proposes the inclusion of risk perception as a motivator of health information seeking and structural knowledge as an additional knowledge dimension. There was adequate support for the hypothesized paths in the model. Risk perception was positively associated with attention to newspaper, television, Internet, and interpersonal communication. Attention to the three media channels was associated with interpersonal communication, but only newspaper and television attention were associated with elaboration. Interpersonal communication was positively associated with structural knowledge, whereas elaboration was associated with both factual and structural knowledge. Differential indirect effects between media attention and knowledge dimensions via interpersonal communication and elaboration were found. Theoretical and practical implications are discussed.

For Fit's Sake: A Norms-Based Approach to Healthy Behaviors Through Influence of Presumed Media Influence.

Based on the influence of presumed media influence (IPMI) model as the theoretical framework, this study examines how injunctive norms and personal norms mediate the influence of healthy lifestyle media messages on public intentions to engage in two types of healthy lifestyle behaviors-physical activity and healthy diet. Nationally representative data collected from 1,055 adults in Singapore demonstrate partial support for the key hypotheses that make up the extended IPMI model, highlighting the importance of a norms-based approach in health communication. Our results indicate that perceived media influence on others indirectly shaped public intentions to engage in healthy lifestyle behaviors through personal norms and attitude, providing partial theoretical support for the extended IPMI model. Practical implications for health communicators in designing health campaigns media messages to motivate the public to engage in healthy lifestyle are discussed.

Effect of mushroom diet on pharmacokinetics of gabapentin in healthy Chinese subjects.

AIMS: This study evaluated the pharmacokinetics of gabapentin in Chinese subjects who received a diet rich in shiitake mushrooms. Shiitake mushrooms have been shown to contain high amount of ergothioneine. In vitro studies have shown that OCTN1-mediated secretion of gabapentin is trans-stimulated by ergothioneine. This study also investigated the concentrations of ergothioneine in plasma at baseline and following mushroom consumption. METHODS: Ten healthy male subjects were recruited and received a diet containing no mushrooms (treatment A) or a high mushroom diet (treatment B; after at least a 7 day washout period) 1 day prior to administration of a single oral dose of gabapentin 600 mg. RESULTS: Ingestion of shiitake mushrooms produced significant increases in plasma ergothioneine concentrations that were sustained for more than 48 h. A statistically significant but modest increase in the renal clearance (CLR ) of gabapentin occurred after intake of the mushroom diet (91.1 ± 25.1 vs. 76.9 ± 20.6 ml min(-1) , P = 0.031). No significant changes in AUC(0,tlast ) of gabapentin were observed (P = 0.726). Creatinine clearance did not correlate with CLR of gabapentin at baseline (treatment A). After ingestion of the mushroom diet, creatinine clearance accounted for 65.3% of the variance in CLR of gabapentin. CONCLUSIONS: These data suggest that diet-drug pharmacokinetic interactions may occur during co-exposure to gabapentin and mushroom constituents. However, as it does not affect the AUC(0,tlast ) of gabapentin, it may not have clinically important consequences. Shiitake mushrooms can also be used as a source of ergothioneine for future clinical studies.

Pharmacogenetic effects of regulatory nuclear receptors (PXR, CAR, RXRα and HNF4α) on docetaxel disposition in Chinese nasopharyngeal cancer patients.

PURPOSE: This exploratory study was aimed at elucidating the pharmacogenetics of regulatory nuclear receptors (PXR, CAR, RXRα and HNF4α) and their implications on docetaxel pharmacokinetics and pharmacodynamics in local Chinese nasopharyngeal cancer patients. METHODS: A total of 59 single nucleotide polymorphisms (SNPs), including tag-SNPs and functionally relevant SNPs of the genes encoding these regulatory nuclear receptors (PXR/NR1I2, CAR/NR1I3, RXRα/NR2B1 and HNF4α/NR2A1), were profiled in the patients enrolled in our study by direct sequencing (N = 50). The generalized linear model was employed to estimate the haplotypic effects on the pharmacokinetics and pharmacodynamics of the patients. RESULTS: The pharmacokinetic profiles of docetaxel in these patients were characterized by marked interindividual variability, with approximately four- to sixfold variations observed in Cmax, AUC0-∞ and CL. Individual SNP association tests revealed that polymorphisms in NR2B1 and NR2A1 were significantly correlated with altered docetaxel pharmacokinetics. Subsequent haplotype association analysis identified the NR2B1 LD block 2 AG haplotype [*+4458G>A(rs3132291) and *+4988A>G(rs4842198)] to be significantly associated with altered pharmacokinetics, in which patients carrying two copies of the AG haplotype had approximately a 20 % decreased Cmax and AUC0-∞ and a 21 % increased CL compared to those who carried only one copy or no copies of the haplotype. A number of SNPs in NR1I2, NR1I3, NR2B1 and NR2A1 were also associated with a significant decrease in blood counts from baseline. No haplotype was found to exert any effects on the pharmacodynamics parameters. CONCLUSIONS: The present exploratory study identified several SNPs in the genes encoding regulatory nuclear receptors which may account for the interpatient variability in docetaxel pharmacokinetics and pharmacodynamics. These findings highlight the important role of regulatory nuclear receptors on the disposition of docetaxel.

The Roles of Trust in Government and Sense of Community in the COVID-19 Contact Tracing Privacy Calculus: Mixed Method Study Using a 2-Wave Survey and In-Depth Interviews.

BACKGROUND: Contact tracing technology has been adopted in many countries to aid in identifying, evaluating, and handling individuals who have had contact with those infected with COVID-19. Singapore was among the countries that actively implemented the government-led contact tracing program known as TraceTogether. Despite the benefits the contact tracing program could provide to individuals and the community, privacy issues were a significant barrier to individuals' acceptance of the program. OBJECTIVE: Building on the privacy calculus model, this study investigates how the perceptions of the 2 key groups (ie, government and community members) involved in the digital contact tracing factor into individuals' privacy calculus of digital contact tracing. METHODS: Using a mixed method approach, we conducted (1) a 2-wave survey (n=674) and (2) in-depth interviews (n=12) with TraceTogether users in Singapore. Using structural equation modeling, this study investigated how trust in the government and the sense of community exhibited by individuals during the early stage of implementation (time 1) predicted privacy concerns, perceived benefits, and future use intentions, measured after the program was fully implemented (time 2). Expanding on the survey results, this study conducted one-on-one interviews to gain in-depth insights into the privacy considerations involved in digital contact tracing. RESULTS: The results from the survey showed that trust in the government increased perceived benefits while decreasing privacy concerns regarding the use of TraceTogether. Furthermore, individuals who felt a connection to community members by participating in the program (ie, the sense of community) were more inclined to believe in its benefits. The sense of community also played a moderating role in the influence of government trust on perceived benefits. Follow-up in-depth interviews highlighted that having a sense of control over information and transparency in the government's data management were crucial factors in privacy considerations. The interviews also highlighted surveillance as the most prevalent aspect of privacy concerns regarding TraceTogether use. In addition, our findings revealed that trust in the government, particularly the perceived transparency of government actions, was most strongly associated with concerns regarding the secondary use of data. CONCLUSIONS: Using a mixed method approach involving a 2-wave survey and in-depth interview data, we expanded our understanding of privacy decisions and the privacy calculus in the context of digital contact tracing. The opposite influences of privacy concerns and perceived benefit on use intention suggest that the privacy calculus in TraceTogether might be viewed as a rational process of weighing between privacy risks and use benefits to make an uptake decision. However, our study demonstrated that existing perceptions toward the provider and the government in the contact tracing context, as well as the perception of the community triggered by TraceTogether use, may bias user appraisals of privacy risks and the benefits of contact tracing.