Health activism, vaccine, and mpox discourse: BERTopic based mixed-method analyses of tweets from sexual minority men and gender diverse (SMMGD) individuals in the U.S.

Objectives: To synthesize discussions among sexual minority men and gender diverse (SMMGD) individuals on mpox, given limited representation of SMMGD voices in existing mpox literature. Methods: BERTopic (a topic modeling technique) was employed with human validations to analyze mpox-related tweets (n = 8,688; October 2020-September 2022) from 2,326 self-identified SMMGD individuals in the U.S.; followed by content analysis and geographic analysis. Results: BERTopic identified 11 topics: health activism (29.81%); mpox vaccination (25.81%) and adverse events (0.98%); sarcasm, jokes, emotional expressions (14.04%); COVID-19 and mpox (7.32%); government/public health response (6.12%); mpox symptoms (2.74%); case reports (2.21%); puns on the virus' naming (i.e., monkeypox; 0.86%); media publicity (0.68%); mpox in children (0.67%). Mpox health activism negatively correlated with LGB social climate index at U.S. state level, ρ = -0.322, p = 0.031. Conclusions: SMMGD discussions on mpox encompassed utilitarian (e.g., vaccine access, case reports, mpox symptoms) and emotionally-charged themes-advocating against homophobia, misinformation, and stigma. Mpox health activism was more prevalent in states with lower LGB social acceptance. Public Health Implications: Findings illuminate SMMGD engagement with mpox discourse, underscoring the need for more inclusive health communication strategies in infectious disease outbreaks to control associated stigma.

Spatiotemporal dynamics of dissolved organic matter and disinfection by-products formation potential of Shengzhong Lake in southwest China.

The quality and quantity of dissolved organic matter (DOM) in lakes as well as its environmental effects associated with the unintended disinfection by-products (DBPs) have received continuous attention. This work investigated the spatiotemporal dynamics of DOM in Shengzhong Lake in southwest China and the formed DBPs during the chlorine disinfection process. The results showed that lake water in summer had significantly higher dissolved oxygen and dissolved organic carbon than that in winter. In contrast, DOM in winter demonstrated an obviously higher aromaticity and molecular weight than that in summer. Four fluorescence components, i.e., terrestrial humic-like substances (C1), protein-like substances (C2), and microbial humic-like substances (C3 and C4), were identified, and their relative abundance followed in the order of C3 > C4 > C2 > C1 in winter and C4 > C3 > C1 > C2 in summer. The formation potential of trihalomethanes and haloacetic acids in winter was higher and lower than that in summer, which was mainly ascribed to the content of aromatic and hydrophobic substances. Compared to the significant seasonal dynamic, the spatial variation of DOM and the formed DBPs was not obvious. This work sheds light on the spatial-temporal distribution of DOM and the potentially formed DBPs in Shengzhong Lake, and will be helpful for understanding the biogeochemical cycle of carbon and assessing the drinking water safety.

Pharmacophore-Based Virtual Screening and Structural Modification of Novel Benzamide Derivatives as HBV Capsid Assembly Modulators.

Hepatitis B virus (HBV) infection is the most common cause of death from liver disease worldwide. The use of capsid assembly modulators is considered a prominent strategy for the development of novel anti-HBV therapies. We performed a pharmacophore-based virtual screening strategy, and a benzamide scaffold hit, WAI-5, was chosen for further structural optimization. A series of novel HBV capsid assembly modulators (CAMs) were found. Compared with the lead hit, the representative compounds 11g and 11n exhibited a 10-fold increase in anti-HBV activity with 50% effective concentration (EC50) values of 1.74 and 1.90 µM, respectively.

The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review.

BACKGROUND: Adverse drug events (ADEs) are a considerable public health burden resulting in disability, hospitalization, and death. Even those ADEs deemed nonserious can severely impact a patient's quality of life and adherence to intervention. Monitoring medication safety, however, is challenging. Social media may be a useful adjunct for obtaining real-world data on ADEs. While many studies have been undertaken to detect adverse events on social media, a consensus has not yet been reached as to the value of social media in pharmacovigilance or its role in pharmacovigilance in relation to more traditional data sources. OBJECTIVE: The aim of the study is to evaluate and characterize the use of social media in ADE detection and pharmacovigilance as compared to other data sources. METHODS: A scoping review will be undertaken. We will search 11 bibliographical databases as well as Google Scholar, hand-searching, and forward and backward citation searching. Records will be screened in Covidence by 2 independent reviewers at both title and abstract stage as well as full text. Studies will be included if they used any type of social media (such as Twitter or patient forums) to detect any type of adverse event associated with any type of medication and then compared the results from social media to any other data source (such as spontaneous reporting systems or clinical literature). Data will be extracted using a data extraction sheet piloted by the authors. Important data on the types of methods used (such as machine learning), any limitations of the methods used, types of adverse events and drugs searched for and included, availability of data and code, details of the comparison data source, and the results and conclusions will be extracted. RESULTS: We will present descriptive summary statistics as well as identify any patterns in the types and timing of ADEs detected, including but not limited to the similarities and differences in what is reported, gaps in the evidence, and the methods used to extract ADEs from social media data. We will also summarize how the data from social media compares to conventional data sources. The literature will be organized by the data source for comparison. Where possible, we will analyze the impact of the types of adverse events, the social media platform used, and the methods used. CONCLUSIONS: This scoping review will provide a valuable summary of a large body of research and important information for pharmacovigilance as well as suggest future directions of further research in this area. Through the comparisons with other data sources, we will be able to conclude the added value of social media in monitoring adverse events of medications, in terms of type of adverse events and timing. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/47068.

Molecular insights into the dissolved organic matter of leather wastewater in leather industrial park wastewater treatment plant.

Leather wastewater (LW) effluent is characterized by complex organic matter, high salinity, and poor biodegradability. To meet the discharge standards, LW effluent is often mixed with municipal wastewater (MW) before being treated at a leather industrial park wastewater treatment plant (LIPWWTP). However, whether this method efficiently removes the dissolved organic matter (DOM) from LW effluent (LWDOM) remains debatable. In this study, the transformation of DOM during full-scale treatment was revealed using spectroscopy and Fourier transform ion cyclotron resonance mass spectrometry. LWDOM exhibited higher aromaticity and lower molecular weight than DOM in MW (MWDOM). The DOM properties in mixed wastewater (MixW) were similar to those in LWDOM and MWDOM. The MixW was treated using a flocculation/primary sedimentation tank (FL1/PST), anoxic/oxic (A/O) process, secondary sedimentation tank (SST), flocculation/sedimentation tank, denitrification filter (FL2/ST-DNF), and an ozonation contact reactor (O3). The FL1/PST unit preferentially removed the peptide-like compounds. The A/O-SST units had the highest removal efficiencies for dissolved organic carbon (DOC) (61.34 %) and soluble chemical oxygen demand (SCOD) (52.2 %). The FL2/ST-DNF treatment removed the lignin-like compounds. The final treatment showed poor DOM mineralization efficiency. The correlation between water quality indices, spectral indices, and molecular-level parameters indicated that lignin-like compounds were strongly correlated with spectral indices and CHOS compounds considerably contributed to the SCOD and DOC. Although the effluent SCOD met the discharge standard, some refractory DOM from LW remained in the effluent. This study illustrates the composition and transformation of DOM and provides theoretical guidance for improving the current treatment processes.

Discovery of 5-alkyl-2-pyrazol-oxazolidin-4-one derivatives as novel hepatitis B virus capsid assembly modulators.

The "magic methyl effect" strategy was used to design a series of 5-alkyl-2-pyrazol-oxazolidin-4-one derivatives as novel hepatitis B virus (HBV) capsid assembly modulators. Most of these compounds exhibited potent HBV inhibitory activities with low cytotoxicities in HepG2.2.15 cells. The most promising compounds 9d and 10b had single-digit nanomolar IC50 values with a high selectivity index. Compared with the lead compound (3.0%), they caused 15% and 18% decreases in HBe antigen secretion at 1.0 µM, respectively. In addition, compounds 9d and 10b possessed good pharmacokinetic profiles with oral bioavailability values of 56.1% and 48.9%, respectively. These results indicated that the two compounds were potential therapeutic agents for HBV infection.

Safe at home: Acceptance of surveillance technology among caregivers for persons with dementia.

The increasing incidence of dementia calls for effective and innovative approaches to alleviate societal and personal burdens. Aging in place is a sustainable paradigm which ensures the best utilization of societal resources, supports caregivers, secures normalcy, and optimizes care for persons with dementia (PwD). Home-based surveillance technology can support PwD in safely aging in place. This study examines factors associated with the adoption of home-based surveillance technologies among unpaid dementia caregivers. Through an online survey (N = 203), we apply ordinal logistic regression to identify five variables that predict the likelihood of caregivers' surveillance technology adoption for dementia care. The predictors are caregivers': (1) trouble concerns about PwD, (2) online support group membership, (3) perceived social norms regarding surveillance technology use, (4) perceived usefulness of surveillance devices, and (5) depth of information and communication technologies (ICT) use. Theoretical and practical implications for dementia healthcare are discussed.

Moralization of E-cigarette Use and Regulation: A Mixed-Method Computational Analysis of Opinion Polarization.

E-cigarette use, or vaping, is undergoing a process of moralization in which issues about vaping evolve from being morally neutral to having discernible moral implications. Using Moral Foundations Theory, this study compared the moral narratives underlying polarized views about e-cigarette use and regulation. We integrated computational and human strategies by conducting the Chow test on the time series data and classification, topic modeling, and Chi-square tests on posts (N = 2,669) from 26 pro-vaping and 19 anti-vaping Facebook Pages. The observation period (August 1, 2019 to March 5, 2020) encompassed the outbreak of "e-cigarette or vaping product use associated lung injury" (EVALI), deaths and subsequent legislation. Results revealed that pro-vaping posts were more likely than anti-vaping posts to mention Fairness/cheating and Authority/subversion, involving a conspiracy belief in an "e-cigarettes vs. Big Tobacco" rivalry, while anti-vaping posts were more likely to mention Sanctity/degradation. There were no significant differences between pro-vaping and anti-vaping posts in the likelihood of mentioning Care/harm or Loyalty/betrayal. Nevertheless, according to the topic modeling results, the use of moral foundations varied between pro-vaping and anti-vaping narratives, with the meanings of Care/harm and Loyalty/betrayal dependent on the post author's group affiliation. Health interventions can tailor persuasive messages to different moral values and debunk misinformation about public health policies to mitigate the vaping epidemic. Theoretical implications are also discussed.

Causal relationship between particulate matter 2.5 and hypothyroidism: A two-sample Mendelian randomization study.

Background: Epidemiological surveys have found that particulate matter 2.5 (PM2.5) plays an important role in hypothyroidism. However, due to the methodological limitations of traditional observational studies, it is difficult to make causal inferences. In the present study, we assessed the causal association between PM2.5 concentrations and risk of hypothyroidism using two-sample Mendelian randomization (TSMR). Methods: We performed TSMR by using aggregated data from genome-wide association studies (GWAS) on the IEU Open GWAS database. We identified seven single nucleotide polymorphisms (SNPs) associated with PM2.5 concentrations as instrumental variables (IVs). We used inverse-variance weighting (IVW) as the main analytical method, and we selected MR-Egger, weighted median, simple model, and weighted model methods for quality control. Results: MR analysis showed that PM2.5 has a positive effect on the risk of hypothyroidism: An increase of 1 standard deviation (SD) in PM2.5 concentrations increases the risk of hypothyroidism by ~10.0% (odds ratio 1.10, 95% confidence interval 1.06-1.13, P = 2.93E-08, by IVW analysis); there was no heterogeneity or pleiotropy in the results. Conclusion: In conclusion, increased PM2.5 concentrations are associated with an increased risk of hypothyroidism. This study provides evidence of a causal relationship between PM2.5 and the risk of hypothyroidism, so air pollution control may have important implications for the prevention of hypothyroidism.

"It Encourages Family Discussion": A Mixed-Methods Examination of the This Is Us Alzheimer's Disease & Caregiving Storyline.

The average United States (U.S.) adult spends approximately one hour interacting directly with a healthcare professional but 2,000 hours watching primetime television annually. Thus, television storylines may be a powerful vehicle for promoting awareness about Alzheimer's disease and caregiving, which affect an estimated 9 million U.S. adults. We used a mixed-methods approach consisting of an online survey of U.S. adult This Is Us viewers (n = 720) and 4 focus groups (n = 12) with a subset of survey respondents to systematically assess viewer perceptions of an Alzheimer's disease and caregiving storyline from the This Is Us television show and the storyline's influence on viewer behavioral intent toward planning for aging. Triangulation of survey and focus group results suggests the storyline may motivate viewers to discuss plans for aging with their family because of a reduction in stigma and seeing on-screen family tensions related to senior care. Results suggest investments in collaborative partnerships between public health and the entertainment industry may be a valuable way to positively impact those affected by Alzheimer's disease and caregiving. Clips from this storyline could also be used as part of health communication campaigns to encourage advanced care planning discussions.

Automatic Cohort Determination from Twitter for HIV Prevention amongst Black and Hispanic Men.

Recruiting people from diverse backgrounds to participate in health research requires intentional and culture-driven strategic efforts. In this study, we utilize publicly available Twitter posts to identify targeted populations to recruit for our HIV prevention study. Natural language processing and machine learning classification methods were used to find self-declarations of ethnicity, gender, age group, and sexually-explicit language. Using the official Twitter API we collected 47.4 million tweets posted over 8 months from two areas geo-centered around Los Angeles. Using available tools (Demographer and M3), we identified the age and race of 5,392 users as likely young Black or Hispanic men living in Los Angeles. We then collected and analyzed their timelines to automatically find sex-related tweets, yielding 2,166 users. Despite a limited precision, our results suggest that it is possible to automatically identify users based on their demographic attributes and Twitter language characteristics for enrollment into epidemiological studies.

Best Practices on Big Data Analytics to Address Sex-Specific Biases in Our Understanding of the Etiology, Diagnosis, and Prognosis of Diseases.

A bias in health research to favor understanding diseases as they present in men can have a grave impact on the health of women. This paper reports on a conceptual review of the literature on machine learning or natural language processing (NLP) techniques to interrogate big data for identifying sex-specific health disparities. We searched Ovid MEDLINE, Embase, and PsycINFO in October 2021 using synonyms and indexing terms for (a) "women," "men," or "sex"; (b) "big data," "artificial intelligence," or "NLP"; and (c) "disparities" or "differences." From 902 records, 22 studies met the inclusion criteria and were analyzed. Results demonstrate that the inclusion by sex is inconsistent and often unreported, although the inclusion of men in these studies is disproportionately less than women. Even though artificial intelligence and NLP techniques are widely applied in healthresearch, few studies use them to take advantage of unstructured text to investigate sex-related differences or disparities. Researchers are increasingly aware of sex-based data bias, but the process toward correction is slow. We reflect on best practices on using big data analytics to address sex-specific biases in understanding the etiology, diagnosis, and prognosis of diseases.

Overcoming the Mental Health Stigma Through m-Health Apps: Results from the Healthy Minds Study.

Background: The advance in digital media technologies has enabled the development of technologically mediated health care solutions. Mobile health app for mental health care is one of such innovative tools to monitor and manage users' mental health and psychological well-being. Objective: This study examines the factors predicting the acceptance of mental health app (MHA) that are: technological (i.e., perceived ease of use and perceived usefulness) and sociocultural (i.e., perceived stigma toward mental health treatment and prior experience of face-to-face mental health service utilization). Methods: Using structural equation modeling, we tested an extended Technology Acceptance Model with data from the Healthy Minds Study, a web-based national survey of U.S. college students (N = 429). Results: In addition to the technological factors, the sociocultural factors significantly influenced MHA acceptance. Notably, college students with higher levels of stigma toward mental health treatment were less likely to have experience of using face-to-face mental health service. This, in turn, led to more openness to accepting MHA that does not involve in-person visits but rather private and mediated communication. Conclusions: Findings of this study provide critical insight into the increasing needs for and use of mobile apps for mental health care. Implications are discussed and future research directions are suggested.

The impact of peer review on the contribution potential of scientific papers.

The peer-reviewing process has long been regarded as an indispensable tool in ensuring the quality of a scientific publication. While previous studies have tried to understand the process as a whole, not much effort has been devoted to investigating the determinants and impacts of the content of the peer review itself. This study leverages open data from nearly 5,000 PeerJ publications that were eventually accepted. Using sentiment analysis, Latent Dirichlet Allocation (LDA) topic modeling, mixed linear regression models, and logit regression models, we examine how the peer-reviewing process influences the acceptance timeline and contribution potential of manuscripts, and what modifications were typically made to manuscripts prior to publication. In an open review paradigm, our findings indicate that peer reviewers' choice to reveal their names in lieu of remaining anonymous may be associated with more positive sentiment in their review, implying possible social pressure from name association. We also conduct a taxonomy of the manuscript modifications during a revision, studying the words added in response to peer reviewer feedback. This study provides insights into the content of peer reviews and the subsequent modifications authors make to their manuscripts.

Lipoxin A4 protects against paraquat­induced acute lung injury by inhibiting the TLR4/MyD88­mediated activation of the NF­κB and PI3K/AKT pathways.

Paraquat (PQ) causes serious oxidative stress and inflammatory responses, particularly to the lungs. Since lipoxin A4 (LXA4) functions as an anti­inflammatory mediator, the present study aimed to explore its effects on PQ­induced acute lung injury (ALI) and to elucidate the possible underlying mechanisms. PQ was administered to male SD rats and RAW264.7 cells to establish a model of poisoning, and LXA4 was used as an intervention drug. LXA4 treatment attenuated PQ­induced lung injury, and this was accompanied by decreased tumor necrosis factor (TNF)­α and interleukin (IL)­1ß secretion levels, and reduced oxidative stress damage. Additionally, LXA4 treatment inhibited the activation of the inflammation­related signaling molecules, Toll­like receptor 4 (TLR4), myeloid differentiation primary response 88 (MyD88), nuclear factor (NF)­κB p65, p­phosphoinositide 3­kinase (PI3K) and p­AKT. Furthermore, the in vitro experiments further confirmed that the beneficial effects of LXA4 on PQ­induced damage were TLR4­dependent. Hence, the present study demonstrated that LXA4 attenuated PQ­induced toxicity in lung tissue and RAW264.7 macrophages, and that this protective effect may be closely related to the mitigation of inflammatory responses, oxidative stress damage and the TLR4/MyD88­mediated activation of the PI3K/AKT/NF­κB pathway.

Discovery of novel HBV capsid assembly modulators by structure-based virtual screening and bioassays.

HBV capsid assembly has been regarded as an attractive potential target for anti-HBV therapy. In this study, we discovery the Novel HBV capsid assembly modulators (CAMs) through structure-based virtual screening and bioassays. A total of 16 structurally diverse compounds were purchased and assayed, including three compounds with inhibition rate > 50% at 20 µM. Further lead optimization based on the most potent compound II-1-7 (EC50 = 5.6 ± 0.1 µM) were performed by using substructure searching strategy, resulting in compound II-2-9 with an EC50 value of 1.8 ± 0.6 µM. In bimolecular fluorescence complementation (BiFC) assay, compound II-2-9 inhibited the HBV by disrupting the HBV capsid interactions. In summary, this study provides a highly efficient way to discover novel CAMs, and 2-aryl-4-quinolyl amide derivatives could serve as the starting point for development of novel anti-HBV drugs.

Multiple roles of dissolved organic matter released from decomposing rice straw at different times in organic pollutant photodegradation.

Rice straw returning causes a considerable amount of dissolved organic matter (DOM) release into aquatic croplands in a relatively short-term. The presence of rice straw-derived DOM in cropland waters may alter the photochemical behaviors of organic pollutants. However, the photochemical activity and photosensitization role of the DOMs are poorly understood. Here, eight DOM samples were extracted from decomposing rice straw at different times in 49 days to explore their photosensitizing capacities toward diuron (DIU), 17ß-estradiol (E2), and sulfamethoxazole (SMX). All of the DOMs were photosensitive and mainly composed of tryptophan-, tyrosine- and fulvic-like substances. Over the decomposition period, the amount of photochemically produced reactive intermediates (PPRIs) by the DOMs peaked on days 7 and 14. The evolution of the DOM photosensitizing capacity towards DIU and E2 was consistent with the variations of PPRIs, and HO· was confirmed as a critical factor. However, the influence of the DOMs on SMX photodegradation was opposite to that on DIU and E2. The positive role of the DOMs in SMX photodegradation was attributed to the tryptophan-like components. The results suggest that straw-derived DOM is an important photosensitizer and that its photosensitization towards organic pollutants is dependent on straw decomposing time and pollutant type.

Inhibition of TBK1 by amlexanox attenuates paraquat-induced acute lung injury.

The specific mechanism of paraquat (PQ)-induced acute lung injury (ALI) is unclear, though inflammation is a likely contributor. Amlexanox, a TANK binding kinase 1 (TBK1) inhibitor, is a strong anti-inflammatory drug. We investigated the role of TBK1 and the potential therapeutic effect of amlexanox in the pathogenesis of PQ-induced ALI. After 30 mg/kg PQ treatment for 72 h, mouse lung pathological injury occurred, and the protein concentration in alveolar lavage fluid was increased. Next, RAW264.7 mouse macrophages were treated with 100 µM PQ for 24 h, which decreased cell viability. PQ induced oxidative damage and increased IL-1ß, IFNß, NF-κBp65, IRF3, and pTBK1/TBK1 levels in mouse lungs and RAW264.7 cells. Inhibiting the activation of TBK1 with amlexanox (100 mg/kg in mice and 50 µM in RAW264.7 cells) attenuated mouse lung injury and decreased the protein concentration in alveolar lavage fluid. Further, amlexanox relieved the oxidative damage in mouse lungs and RAW264.7 cells, reduced the levels of inflammatory factors such as IL-1ß and IFNß, and inhibited the activation of NF-κBp65 and IRF3. These results suggest that TBK1 plays a key role in the pathogenesis of PQ-induced ALI. Further, amlexanox treatment alleviates PQ-induced ALI by inhibiting the TBK1-NF-κB/IRF3 signalling pathway. Our study provides evidence that TBK1 inhibition by amlexanox alleviates PQ-induced ALI and may be a new therapeutic strategy.

Automatic regional analysis of myocardial native T1 values: left ventricle segmentation and AHA parcellations.

Native T1 value is emerging as a reliable indicator of abnormal heart conditions related to myocardial fibrosis. Investigators have extensively used the standardized myocardial segmentation of the American Heart Association (AHA) to measure regional T1 values of the left ventricular (LV) walls. In this paper, we present a fully automatic system to analyze modified Look-Locker inversion recovery images and to report regional T1 values of AHA segments. Ten healthy individuals participated in the T1 mapping study with a 3.0 T scanner after providing informed consent. First, we obtained masks of an LV blood-pool region and LV walls by using an image synthesis method and a layer-growing method. Subsequently, the LV walls were divided into AHA segments by identifying the boundaries of the septal regions and by using a radial projection method. The layer-growing method significantly enhanced the accuracy of the derived myocardium mask. We compared the T1 values that were obtained using manual region of interest selections and those obtained using the automatic system. The average T1 difference of the calculated segments was 4.6 ± 1.5%. This study demonstrated a practical and robust method of obtaining native T1 values of AHA segments in LV walls.