Vascular Pericyte-Derived Exosomes Inhibit Bone Resorption via Traf3.

Purpose: Blood vessels distribute cells, oxygen, and nutrients throughout the body to support tissue growth and balance. Pericytes and endothelial cells form the inner wall of blood vessels, crucial for organ development and tissue homeostasis by producing paracrine signaling molecules. In the skeletal system, pericyte-derived vascular factors along with angiogenic factors released by bone cells regulate angiogenesis and bone formation. Although the involvement of angiogenic factors and skeletal blood vessels in bone homeostasis is relatively clear, the role of pericytes and the underlying mechanisms remain unknown. Here, our objective was to elucidate the significance of pericytes in regulating osteoclast differentiation. Methods: We used tissue staining to detect the coverage of pericytes and osteoclasts in femoral tissues of osteoporotic mice and mice of different ages, analyzing their correlation. We developed mice with conditionally deleted pericytes, observing changes in bone mass and osteoclast activity using micro-computer tomography and tissue staining to detect the regulatory effect of pericytes on osteoclasts. Pericytes-derived exosomes (PC-EVs) were collected and co-cultured with monocytes that induce osteoclast differentiation to detect the effect of the former on the exosomes. Finally, the specific mechanism of PC-EVs regulating osteoclast differentiation was verified using RNA sequencing and Western blotting. Results: Our study indicates a significant correlation between pericytes and age-related bone resorption. Conditional deletion of pericytes activated bone resorption and led to osteopenia in vivo. We discovered that PC-EVs inhibited the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway, which is mediated by tumor necrosis factor receptor-associated factor 3 (Traf3), negatively regulating osteoclast development and bone resorption. Silencing Traf3 in PC-EVs canceled their inhibitory effect on osteoclast differentiation. Conclusion: Our study provides a novel perspective into the regulatory role of pericytes on bone resorption and may provide potential strategies for developing novel anti-bone resorption therapies.

Prospective applications of extracellular vesicle-based therapies in regenerative medicine: implications for the use of dental stem cell-derived extracellular vesicles.

In the 21st century, research on extracellular vesicles (EVs) has made remarkable advancements. Recently, researchers have uncovered the exceptional biological features of EVs, highlighting their prospective use as therapeutic targets, biomarkers, innovative drug delivery systems, and standalone therapeutic agents. Currently, mesenchymal stem cells stand out as the most potent source of EVs for clinical applications in tissue engineering and regenerative medicine. Owing to their accessibility and capability of undergoing numerous differentiation inductions, dental stem cell-derived EVs (DSC-EVs) offer distinct advantages in the field of tissue regeneration. Nonetheless, it is essential to note that unmodified EVs are currently unsuitable for use in the majority of clinical therapeutic scenarios. Considering the high feasibility of engineering EVs, it is imperative to modify these EVs to facilitate the swift translation of theoretical knowledge into clinical practice. The review succinctly presents the known biotherapeutic effects of odontogenic EVs and the underlying mechanisms. Subsequently, the current state of functional cargo loading for engineered EVs is critically discussed. For enhancing EV targeting and in vivo circulation time, the review highlights cutting-edge engineering solutions that may help overcome key obstacles in the clinical application of EV therapeutics. By presenting innovative concepts and strategies, this review aims to pave the way for the adaptation of DSC-EVs in regenerative medicine within clinical settings.

Effect of glycosaminoglycans with different degrees of sulfation on chondrogenesis.

OBJECTIVES: This study aims to investigate the effects and mechanisms of chondroitin sulfate (CS), dermatan sulfate (DS), and heparin (HEP) on chondrogenesis of murine chondrogenic cell line (ATDC5) cells and the maintenance of murine articular cartilage in vitro. METHODS: ATDC5 and articular cartilage tissue explant were cultured in the medium containing different sulfated glycosaminoglycans. Cell proliferation, differentiation, cartilage formation, and mechanism were observed using cell proliferation assay, Alcian blue staining, real-time quantitative polymerase chain reaction (RT-qPCR), and Western blot, respectively. RESULTS: Results showed that HEP and DS primarily activated the bone morphogenetic protein (BMP) signal pathway, while CS primarily activated the protein kinase B (AKT) signal pathway, further promoted ATDC5 cell proliferation and matrix production, and increased Sox9, Col2a1, and Aggrecan expression. CONCLUSIONS: This study investigated the differences and mechanisms of different sulfated glycosaminoglycans in chondrogenesis and cartilage homeostasis maintenance. HEP promotes cartilage formation and maintains the normal state of cartilage tissue in vitro, while CS plays a more effective role in the regeneration of damaged cartilage tissue.

Study on web pillar failure mechanism during auger mining and its associated risk assessment.

To safely and efficiently recover trapped coal under final endwalls in open cut mines, theoretical analysis and numerical calculation were used to study the stability of web pillar during auger mining. The partial ordered set (poset) evaluation model was used to develop a risk assessment methodology, and auger mining at Pingshuo Antaibao open cut coal mine was used as a field example for validation. Based on the catastrophe theory, the failure criterion of web pillar was established. From the limit equilibrium theory, the maximum allowable plastic yield zone width and minimum web pillar width were proposed under various Factor of Safety (FoS) thresholds. This in turn provides a new method for web pillar design. Based on the poset theory and combining with the risk evaluation and proposed hazard levels, input data were standardized and weighted. Subsequently, the comparison matrix, HASSE matrix and HASSE diagram were established. The study shows that: when the width of the plastic zone of web pillar exceeds 88% of the total width, web pillar may be unstable. Based on the calculation formula for the required width of web pillar, the required pillar width was 4.93 m and it was deemed as "mostly stable". This was consistent with the field condition on site. Such that this method was validated.

Modification of the small intestinal submucosa membrane with oligopeptides screened from intrinsically disordered regions to promote angiogenesis and accelerate wound healing.

A slow vascularization rate is considered one of the major disadvantages of biomaterials used for accelerating wound healing. Several efforts, including cellular and acellular technologies, have been made to facilitate biomaterial-induced angiogenesis. However, no well-established techniques for promoting angiogenesis have been reported. In this study, a small intestinal submucosa (SIS) membrane modified by an angiogenesis-promoting oligopeptide (QSHGPS) screened from intrinsically disordered regions (IDRs) of MHC class II was used to promote angiogenesis and accelerate wound healing. Because the main component of SIS membranes is collagen, the collagen-binding peptide sequence TKKTLRT and the pro-angiogenic oligopeptide sequence QSHGPS were used to construct chimeric peptides to obtain specific oligopeptide-loaded SIS membranes. The resulting chimeric peptide-modified SIS membranes (SIS-L-CP) significantly promoted the expression of angiogenesis-related factors in umbilical vein endothelial cells. Furthermore, SIS-L-CP exhibited excellent angiogenic and wound-healing abilities in a mouse hindlimb ischaemia model and a rat dorsal skin defect model. The high biocompatibility and angiogenic capacity of the SIS-L-CP membrane make it promising in angiogenesis- and wound healing-related regenerative medicine.

Impact of COVID-19 on HIV Prevention Access: A Multi-platform Social Media Infodemiology Study.

This study seeks to identify and characterize key barriers associated with PrEP therapy as self-reported by users on social media platforms. We used data mining and unsupervised machine learning approaches to collect and analyze COVID-19 and PrEP-related posts from three social media platforms including Twitter, Reddit, and Instagram. Predominant themes detected by unsupervised machine learning and manual annotation included users expressing uncertainty about PrEP treatment adherence due to COVID-19, challenges related to accessibility of clinics, concerns about PrEP costs and insurance coverage, perceived lower HIV risk leading to lack of adherence, and misinformation about PrEP use for COVID-19 prevention.

Exploring substance use disorder discussions in Native American communities: a retrospective Twitter infodemiology study.

BACKGROUND: The opioid epidemic has had a devastating impact on youth from American Indian and Alaska Native (AI/AN) Tribes and Villages, which also experience disparate suicide rates. The use of publicly available social media data originating from AI/AN communities may enhance public health response time to substance use disorder (SUD)-related overdose and augment Tribal public health surveillance systems, but these concepts have yet to be adequately explored. The goal of this exploratory analysis was to identify primary and secondary accounts of overdose and characterize relevant contextual factors in the AI/AN population on social media. METHODS: The Twitter application programming interface was queried for all Tweets containing geocoded data between March 2014 and June 2020 and filtered for the keyword ['overdose']. This sample of Tweets (n = 146,236) was then restricted to those geolocated from US Tribal lands (n = 619). Tweets were manually annotated for primary or secondary accounts of overdose as well as suicidal ideation, substance(s) used, stigma of drug use, and community-wide incidents. RESULTS: We collected a total of 146,235 tweets that were geocoded and contained the word 'overdose,' of which 9.5% were posted on Tribal lands (n = 619). 9.4% of these tweets (n = 58) met our study inclusion criteria and were mainly posted from Oklahoma (n = 26, 45%) and North Carolina (n = 13, 22.4%). Most Tweets (n = 41, 71%) described a primary account of an overdose and were mostly posted from 2014 to 2015. Less than half of the Tweets (n = 27, 46.5%) referenced a specific substance. Those substances mentioned included alcohol, marijuana, methamphetamine, heroin, laundry softener, cocaine, K2-Spice (synthetic cannabinoid), codeine, morphine, Nyquil, and Xanax. DISCUSSION: Though exploratory, our study identified SUD-related content self-reported by AI/AN communities on Twitter, especially in Oklahoma and North Carolina. These results may assist in the future design and detection of infodemiology trends and early warning signs that can better facilitate intervention specific to the ongoing Tribal opioid epidemic. While all data were collected from the public domain, additional care should be given to individual and community privacy.

Activation of farnesoid X receptor signaling by geniposidic acid promotes osteogenesis.

BACKGROUND: New targets and strategies are urgently needed for the identification and development of anabolic drugs for osteoporosis. Farnesoid X receptor (FXR) is a promising novel therapeutic target for bone metabolism diseases. Although used clinically, FXR agonists have obvious side effects; therefore, the development of new FXR agonists for the treatment of osteoporosis would be welcomed. Geniposidic acid (GPA) is a bioactive compound extracted from Eucommiae cortex, which is used for treating arthritis, osteoporotic fractures, and hypertension. However, the therapeutic effects of GPA against osteoporosis remain underexplored. PURPOSE: This study aims to reveal the potential osteogenic effects of FXR and to explore the effect of GPA on bone formation, osteoporosis treatment, and FXR signaling. STUDY DESIGN & METHODS: The role of FXR in promoting bone formation was evaluated in Fxr knockout (Fxr-/-) mice and cell models. GPA activation of FXR was evaluated by molecular docking and luciferase reporter gene assays. Thirty female C57BL/6J mice were randomly assigned into a sham operation group (Sham) and four ovariectomized (OVX) groups (n=6 each) and were treated with vehicle or different doses of GPA (25, 50, and 100 mg/kg/day). The therapeutic effect of GPA on osteoporosis was systematically analyzed by performing bone histomorphometry and measuring serum biochemical parameters, and the molecular mechanism was also evaluated. Furthermore, the action of GPA in Fxr-/- mice was evaluated to investigate its dependency on FXR in promoting bone formation and treating osteoporosis. RESULTS: We found that FXR was highly expressed in bone tissues and enriched in osteoblasts. Notably, deletion of FXR significantly reduced the bone formation rate and bone mass of the Fxr-/- mice compared with wild-type mice. Furthermore, using a high throughput drug screening strategy based on fluorescent reporter genes, we found that GPA functions as a natural agonist of FXR. We confirmed the activities of GPA on FXR activation and osteogenesis in both osteoblast differentiation models and OVX-induced osteoporosis models. We revealed that GPA strongly promotes bone formation by activating FXR/RUNX2 signaling. Moreover, the osteoporotic therapeutic effect of GPA was abolished in Fxr-/- mice. CONCLUSION: This study demonstrated that FXR is a promising target for treating osteoporosis and that GPA promotes bone formation in OVX-induced osteoporosis by activating FXR signaling. These findings provide novel insight into the mechanism by which GPA promotes bone formation and more evidence for its application in the treatment of osteoporosis.

Generation of functional oligopeptides that promote osteogenesis based on unsupervised deep learning of protein IDRs.

Deep learning (DL) is currently revolutionizing peptide drug development due to both computational advances and the substantial recent expansion of digitized biological data. However, progress in oligopeptide drug development has been limited, likely due to the lack of suitable datasets and difficulty in identifying informative features to use as inputs for DL models. Here, we utilized an unsupervised deep learning model to learn a semantic pattern based on the intrinsically disordered regions of ~171 known osteogenic proteins. Subsequently, oligopeptides were generated from this semantic pattern based on Monte Carlo simulation, followed by in vivo functional characterization. A five amino acid oligopeptide (AIB5P) had strong bone-formation-promoting effects, as determined in multiple mouse models (e.g., osteoporosis, fracture, and osseointegration of implants). Mechanistically, we showed that AIB5P promotes osteogenesis by binding to the integrin α5 subunit and thereby activating FAK signaling. In summary, we successfully established an oligopeptide discovery strategy based on a DL model and demonstrated its utility from cytological screening to animal experimental verification.

Osteogenic peptides in periodontal ligament stem cell-containing three-dimensional bioscaffolds promote bone healing.

Bone tissue engineering shows great potential in bone regeneration; however, the lack of bone growth factors with high biocompatibility and efficiency is a major concern. Oligopeptides have drawn great attention due to their high biological efficacy, low toxicity, and low molecular weight. The oligopeptide SDSSD promotes the osteogenesis of human periodontal ligament stem cells (hPDLSCs) in vitro. The SDSSD-modified three-dimensional (3D) bioscaffolds promote osteogenesis and bone formation in the subcutaneous pockets of BALB/c nude mice and facilitate bone healing in vivo. Mechanistically, SDSSD promoted bone formation by binding to G protein-coupled receptors and regulating the AKT signaling pathway. 3D-printing bioscaffolds with SDSSD may be potential bone tissue engineering materials for treating bone defects.

A mouse model of disuse osteoporosis based on a movable noninvasive 3D-printed unloading device.

OBJECTIVE: Disuse osteoporosis is a major type of bone loss disease characterized by regional bone loss and microstructure alterations. The condition is induced by a marked decrease in weight bearing over time, which usually occurs due to limb immobilization, therapeutic bed rest or space flight. To date, the most commonly used mouse model of disuse osteoporosis is constructed using the classical tail suspension method, which causes tail injury, movement inconvenience and mental stress. This study aimed to propose a noninvasive and effective method for the establishment of a mouse model of disuse osteoporosis and compared this method with the tail suspension method. METHODS: 3D printing technology was applied to construct a movable unloading device. A movable noninvasive 3D-printed unloading device (3D-ULD) was used to unload the hindlimbs of the mice. The bone microstructure and bone volume of unloaded femurs were analysed through micro-CT and H&E staining, and von Kossa staining was performed for the detection of bone mineralization in the femurs. TRAP staining, IHC-CTSK and Q-PCR were performed for evaluation of the bone resorption ability, and double labelling, IHC-DMP1, ALP staining and Q-PCR assays were conducted to assess the osteogenic ability. The mechanical properties of disused bone were detected using the three-point bending test. The body, thymus and spleen weights of the mice were recorded, and the serum corticosterone level of the mice was assayed by enzyme-linked immunosorbent assay (ELISA). RESULTS: The micro-CT results showed significant trabecular bone loss, and 3D-ULD induced cortical bone loss in disused femurs as well as a decrease in the bone mineral density in the unloaded mice. TRAP staining and IHC-CTSK staining results indicated increases in the osteoclast number per bone perimeter (Oc.N/B.Pm) and the osteoclast surface per bone surface (Oc.S/BS) in the unloaded mice. The Ctsk, Trap and Mmp9 expression levels were significantly increased in the unloaded mice. Decreases in the ratio of the mineral surface to bone surface (MS/BS), mineral apposition rate (MAR) and bone formation rate per bone surface (BFR/BS) were found in unloaded mice in the 3D-ULD by double labelling. The IHC-DMP1 and ALP staining results showed decreases in the osteoblast number per bone perimeter (Ob.N/B.Pm) and osteoblast surface per bone surface (Ob. S/BS) in the mice unloaded in the 3D-ULD, and these mice also showed decreased Runx2, Alp and Dmp1 expression levels. Three-point bending test results showed that the mechanical properties were attenuated in the disused femurs of the unloaded mice. Less skin rupture and rare alterations in the thymus and spleen weights were found in the unloaded mice in the 3D-ULD. The ELISA results indicated the serum corticosterone level of the mice unloaded in the 3D-ULD was significantly lower than that of mice suspended by their tail. CONCLUSION: This new disuse osteoporosis mouse model based on 3D-ULD could induce effective disuse bone loss with significantly alleviated side effects. TRANSLATIONAL POTENTIAL OF THIS ARTICLE: This study proposes a new disuse osteoporosis mouse model based on 3D-ULD that can be used to better understand disuse bone loss in the future.

Unsupervised Machine Learning to Detect and Characterize Barriers to Pre-exposure Prophylaxis Therapy: Multiplatform Social Media Study.

Background: Among racial and ethnic minority groups, the risk of HIV infection is an ongoing public health challenge. Pre-exposure prophylaxis (PrEP) is highly effective for preventing HIV when taken as prescribed. However, there is a need to understand the experiences, attitudes, and barriers of PrEP for racial and ethnic minority populations and sexual minority groups. Objective: This infodemiology study aimed to leverage big data and unsupervised machine learning to identify, characterize, and elucidate experiences and attitudes regarding perceived barriers associated with the uptake and adherence to PrEP therapy. This study also specifically examined shared experiences from racial or ethnic populations and sexual minority groups. Methods: The study used data mining approaches to collect posts from popular social media platforms such as Twitter, YouTube, Tumblr, Instagram, and Reddit. Posts were selected by filtering for keywords associated with PrEP, HIV, and approved PrEP therapies. We analyzed data using unsupervised machine learning, followed by manual annotation using a deductive coding approach to characterize PrEP and other HIV prevention-related themes discussed by users. Results: We collected 522,430 posts over a 60-day period, including 408,637 (78.22%) tweets, 13,768 (2.63%) YouTube comments, 8728 (1.67%) Tumblr posts, 88,177 (16.88%) Instagram posts, and 3120 (0.6%) Reddit posts. After applying unsupervised machine learning and content analysis, 785 posts were identified that specifically related to barriers to PrEP, and they were grouped into three major thematic domains: provider level (13/785, 1.7%), patient level (570/785, 72.6%), and community level (166/785, 21.1%). The main barriers identified in these categories included those associated with knowledge (lack of knowledge about PrEP), access issues (lack of insurance coverage, no prescription, and impact of COVID-19 pandemic), and adherence (subjective reasons for why users terminated PrEP or decided not to start PrEP, such as side effects, alternative HIV prevention measures, and social stigma). Among the 785 PrEP posts, we identified 320 (40.8%) posts where users self-identified as racial or ethnic minority or as a sexual minority group with their specific PrEP barriers and concerns. Conclusions: Both objective and subjective reasons were identified as barriers reported by social media users when initiating, accessing, and adhering to PrEP. Though ample evidence supports PrEP as an effective HIV prevention strategy, user-generated posts nevertheless provide insights into what barriers are preventing people from broader adoption of PrEP, including topics that are specific to 2 different groups of sexual minority groups and racial and ethnic minority populations. Results have the potential to inform future health promotion and regulatory science approaches that can reach these HIV and AIDS communities that may benefit from PrEP.

Digital Surveillance to Identify California Alternative and Emerging Tobacco Industry Policy Influence and Mobilization on Facebook.

Growing popularity of electronic nicotine-delivery systems (ENDS) has coincided with a need to strengthen tobacco-control policy. In response, the ENDS industry has taken actions to mobilize against public health measures, including coordination on social media platforms. To explore this phenomenon, data mining was used to collect public posts on two Facebook public group pages: the California Consumer Advocates for Smoke Free Alternatives Association (CCASAA) and the community page of the Northern California Chapter of SFATA (NC-SFATA). Posts were manually annotated to characterize themes associated with industry political interference and user interaction. We collected 288 posts from the NC-SFATA and 411 posts from CCASAA. A total of 522 (74.7%) posts were categorized as a form of political interference, with 339 posts (64.9%) from CCASAA and 183 posts (35.1%) from NC-SFATA. We identified three different categories of policy interference-related posts: (1) providing updates on ENDS-related policy at the federal, state, and local levels; (2) sharing opinions about ENDS-related policies; (3) posts related to scientific information related to vaping; and (4) calls to action to mobilize against tobacco/ENDS policies. Our findings indicate that pro-tobacco social media communities on Facebook, driven by strategic activities of trade associations and their members, may act as focal points for anti-policy information dissemination, grass-roots mobilization, and industry coordination that needs further research.

Characterizing Vaping Industry Political Influence and Mobilization on Facebook: Social Network Analysis.

BACKGROUND: In response to recent policy efforts to regulate tobacco and vaping products, the vaping industry has been aggressive in mobilizing opposition by using a network of manufacturers, trade associations, and tobacco user communities, and by appealing to the general public. One strategy the alternative tobacco industry uses to mobilize political action is coordinating on social media platforms, such as the social networking site Facebook. However, few studies have specifically assessed how platforms such as Facebook are used to influence public sentiment and attitudes towards tobacco control policy. OBJECTIVE: This study used social network analysis to examine how the alternative tobacco industry uses Facebook to mobilize online users to influence tobacco control policy outcomes with a focus on the state of California. METHODS: Data were collected from local and national alternative tobacco Facebook groups that had affiliations with activities in the state of California. Network ties were constructed based on users' reactions to posts (eg, "like" and "love") and comments to characterize political mobilization networks. RESULTS: Findings show that alternative tobacco industry employees were more likely to engage within these networks and that these employees were also more likely to be influential members (ie, be more active) in the network. Comparisons between subnetworks show that communication within the local alternative tobacco advocacy group network was less dense and more centralized in contrast to a national advocacy group that had overall higher levels of engagement among members. A timeline analysis found that a higher number of influential posts that disseminated widely across networks occurred during e-cigarette-related legislative events, suggesting strategic online engagement and increased mobilization of online activity for the purposes of influencing policy outcomes. CONCLUSIONS: Results from this study provide important insights into how tobacco industry-related advocacy groups leverage the Facebook platform to mobilize their online constituents in an effort to influence public perceptions and coordinate to defeat tobacco control efforts at the local, state, and federal level. Study results reveal one part of a vast network of socially enabled alternative tobacco industry actors and constituents that use Facebook as a mobilization point to support goals of the alternative tobacco industry.

A functional motif of long noncoding RNA Nron against osteoporosis.

Long noncoding RNAs are widely implicated in diverse disease processes. Nonetheless, their regulatory roles in bone resorption are undefined. Here, we identify lncRNA Nron as a critical suppressor of bone resorption. We demonstrate that osteoclastic Nron knockout mice exhibit an osteopenia phenotype with elevated bone resorption activity. Conversely, osteoclastic Nron transgenic mice exhibit lower bone resorption and higher bone mass. Furthermore, the pharmacological overexpression of Nron inhibits bone resorption, while caused apparent side effects in mice. To minimize the side effects, we further identify a functional motif of Nron. The delivery of Nron functional motif to osteoclasts effectively reverses bone loss without obvious side effects. Mechanistically, the functional motif of Nron interacts with E3 ubiquitin ligase CUL4B to regulate ERα stability. These results indicate that Nron is a key bone resorption suppressor, and the lncRNA functional motif could potentially be utilized to treat diseases with less risk of side effects.

Physicians payment in the United States between 2014 and 2018: An analysis of the CMS Open Payments database.

The Open Payments database reports payments made to physicians by industry. Given the potential for financial conflicts of interest relating to patient outcomes, further scrutiny of these data is valuable. Therefore, the objective of this study was to analyze physician-industry relationships by specialty type, payment type, geospatial trend, and longitudinal trend between 2014-2018. We conducted an observational, retrospective data analysis of payments from the Open Payments database for licensed United States physicians listed in the National Plan & Provider Enumeration System (NPPES). Datasets from 2013-2018 were joined using the Python programming language. Aggregation and sub-setting by characteristics of interest was done in R to calculate means and frequencies of reported general physician payments from industry across different specialties, locations, timeframes, and payment types. Normalization was applied for numbers of physicians or payments. Geospatial statistical hot spot analysis was conducted in ArcGIS. 51.73 million payment records were analyzed. In total, 50,047,930 payments were issued to 771,113 allopathic or osteopathic physicians, representing $8,702,631,264 transferred from industry to physicians over the five-year period between 2014 and 2018. The mean payment amount was $179, with a standard deviation of $12,685. Variability in physicians' financial relationships with industry were apparent across specialties, regions, time, and payment type. A limited match rate between records in the NPPES and Open Payments databases may have resulted in selection bias of trends related to physician characteristics. Further research is necessary, particularly in the context of changing industry payment trends and public perceptions of the appropriateness of these relationships.

A longitudinal and geospatial analysis of COVID-19 tweets during the early outbreak period in the United States.

INTRODUCTION: Early reports of COVID-19 cases and deaths may not accurately convey community-level concern about the pandemic during early stages, particularly in the United States where testing capacity was initially limited. Social media interaction may elucidate public reaction and communication dynamics about COVID-19 in this critical period, during which communities may have formulated initial conceptions about the perceived severity of the pandemic. METHODS: Tweets were collected from the Twitter public API stream filtered for keywords related to COVID-19. Using a pre-existing training set, a support vector machine (SVM) classifier was used to obtain a larger set of geocoded tweets with characteristics of user self-reporting COVID-19 symptoms, concerns, and experiences. We then assessed the longitudinal relationship between identified tweets and the number of officially reported COVID-19 cases using linear and exponential regression at the U.S. county level. Changes in tweets that included geospatial clustering were also assessed for the top five most populous U.S. cities. RESULTS: From an initial dataset of 60 million tweets, we analyzed 459,937 tweets that contained COVID-19-related keywords that were also geolocated to U.S. counties. We observed an increasing number of tweets throughout the study period, although there was variation between city centers and residential areas. Tweets identified as COVID-19 symptoms or concerns appeared to be more predictive of active COVID-19 cases as temporal distance increased. CONCLUSION: Results from this study suggest that social media communication dynamics during the early stages of a global pandemic may exhibit a number of geospatial-specific variations among different communities and that targeted pandemic communication is warranted. User engagement on COVID-19 topics may also be predictive of future confirmed case counts, though further studies to validate these findings are needed.

Characterizing Weibo Social Media Posts From Wuhan, China During the Early Stages of the COVID-19 Pandemic: Qualitative Content Analysis.

BACKGROUND: The COVID-19 pandemic has reached 40 million confirmed cases worldwide. Given its rapid progression, it is important to examine its origins to better understand how people's knowledge, attitudes, and reactions have evolved over time. One method is to use data mining of social media conversations related to information exposure and self-reported user experiences. OBJECTIVE: This study aims to characterize the knowledge, attitudes, and behaviors of social media users located at the initial epicenter of the outbreak by analyzing data from the Sina Weibo platform in Chinese. METHODS: We used web scraping to collect public Weibo posts from December 31, 2019, to January 20, 2020, from users located in Wuhan City that contained COVID-19-related keywords. We then manually annotated all posts using an inductive content coding approach to identify specific information sources and key themes including news and knowledge about the outbreak, public sentiment, and public reaction to control and response measures. RESULTS: We identified 10,159 COVID-19 posts from 8703 unique Weibo users. Among our three parent classification areas, 67.22% (n=6829) included news and knowledge posts, 69.72% (n=7083) included public sentiment, and 47.87% (n=4863) included public reaction and self-reported behavior. Many of these themes were expressed concurrently in the same Weibo post. Subtopics for news and knowledge posts followed four distinct timelines and evidenced an escalation of the outbreak's seriousness as more information became available. Public sentiment primarily focused on expressions of anxiety, though some expressions of anger and even positive sentiment were also detected. Public reaction included both protective and elevated health risk behavior. CONCLUSIONS: Between the announcement of pneumonia and respiratory illness of unknown origin in late December 2019 and the discovery of human-to-human transmission on January 20, 2020, we observed a high volume of public anxiety and confusion about COVID-19, including different reactions to the news by users, negative sentiment after being exposed to information, and public reaction that translated to self-reported behavior. These findings provide early insight into changing knowledge, attitudes, and behaviors about COVID-19, and have the potential to inform future outbreak communication, response, and policy making in China and beyond.