Streamlining Social Media Information Retrieval for COVID-19 Research with Deep Learning (preprint)

Objective: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-matching. This study develops a system to streamline the process of curating colloquial medical dictionaries. We demonstrate the pipeline by curating a UMLS-colloquial symptom dictionary from COVID-19-related tweets as proof of concept. Methods: COVID-19-related tweets from February 1, 2020, to April 30, 2022 were used. The pipeline includes three modules: a named entity recognition module to detect symptoms in tweets; an entity normalization module to aggregate detected entities; and a mapping module that iteratively maps entities to Unified Medical Language System concepts. A random 500 entity sample were drawn from the final dictionary for accuracy validation. Additionally, we conducted a symptom frequency distribution analysis to compare our dictionary to a pre-defined lexicon from previous research. Results: We identified 498,480 unique symptom entity expressions from the tweets. Pre-processing reduces the number to 18,226. The final dictionary contains 38,175 unique expressions of symptoms that can be mapped to 966 UMLS concepts (accuracy = 95%). Symptom distribution analysis found that our dictionary detects more symptoms and is effective at identifying psychiatric disorders like anxiety and depression, often missed by pre-defined lexicons. Conclusions: This study advances public health research by implementing a novel, systematic pipeline for curating symptom lexicons from social media data. The final lexicon's high accuracy, validated by medical professionals, underscores the potential of this methodology to reliably interpret and categorize vast amounts of unstructured social media data into actionable medical insights across diverse linguistic and regional landscapes.

Study on the mechanism of Lianhua Qingwen capsule absorbed components in prevention and treatment of COVID-19 by intervening on cytokines storm based on network pharmacology and molecular docking

To analyze the possible mechanism of the intervention of absorbed components of Lianhua Qingwen Capsule on COVID-19 from the perspective of cytokine storm based on network pharmacology and molecular docking. Through literature mining, the components of Lianhua Qingwen capsules into blood were determined, and the related action targets of the components were searched by TCMSP and BATMAN-TCM databases. The related targets of COVID-19 and cytokine storm were screened by GeneCards, OMIM and Drugbank databases. The protein interaction PPI network was constructed through String database. DAVID database was used for GO analysis and KEGG pathway analysis. Cytoscape 3.8.0 software was used to build the network diagram. Molecular docking was performed by AutoDock software.In addition, multiple organ tissue injury, immune injury and SARS related targets were retrieved and intersected with cytokine storm.A total of 17 absorbed components of Lianhua Qingwen Capsules were collected, 237 corresponding targets and 47 targets intersected with diseases obtained, and 22 core targets screened out.GO analysis and KEGG pathway analysis presented 174 entries and 83 entries respectively (P < 0.01). The molecular docking results showed that the compounds of Emodin, Formononetin, Rutin, Gallic acid, Liquiritigenin had good binding ability with the core target of AKT1, IL-6, TP53, JUN, TNF. The proportion of intersecting target of Lianhua Qingwen Capsule and multiple organ tissue injury and immune injury was 1.6%-2.0%, and the proportion of intersecting target and SARS was 4.3%. Absorbed components of Lianhua Qingwen Capsule could effectively prevent and treat COVID-19 by intervening cytokine storm through multi-component, multi-target and multi-pathway synergistic action, and its mechanism may be related to antigen-scavenging, immune-regulating and tissue and organ protection.

Risk factors associated with PCR repositivity in patients with COVID-19 after recovery in Guangzhou, China: a retrospective cohort study (preprint)

Some patients retested positive for SARS-CoV-2 following negative testing results and discharge. However, the potential risk factors associated with redetectable positive test results in a large sample of patients who recovered from COVID-19 have not been well estimated. A total of 745 discharged COVID-19 patients were enrolled between January 30, 2020, and September 9, 2020, in Guangzhou, China. Data on the clinical characteristics, comorbidities, drug therapy, RT-PCR testing, and contact modes to close contacts were collected. Patients who tested positive for SARS-CoV-2 after discharge (positive retest patients) were confirmed by guidelines issued by China. The repositive rate in different settings was calculated. Among 745 discharged patients, 157 (21.1%; 95% CI, 18.2% to 24.0%) retested positive, of which 55 (35.0%) were asymptomatic, 15 (9.6%) had mild symptoms, 83 (52.9%) had moderate symptoms and 4 (2.6%) had severe symptoms at the first admission. The median time from discharge to repositivity was 8.0 days (IQR, 8.0 to 14.0 days). Most positive retest patients were without clinical symptoms, and lymphocyte cell counts were higher than before being discharged. The likelihood of repositive testing for SARS-CoV-2 RNA was significantly higher among patients who were younger age (OR, 3.88; 95% CI, 1.74 to 8.66, 0 to 17 years old), had asymptomatic severity (OR, 4.36; 95% CI, 1.47 to 12.95) and did not have clinical symptoms (OR, 1.89; 95% CI, 1.32 to 2.70, without fever). We found that the positive retest rate of COVID-19 was relatively high, and these patients tested positive again with a median of 8.0 to 14.0 days after discharge. Positive retest results were mainly observed in young patients without severe clinical symptoms. These findings suggest that a significant proportion of patients could carry viral fragments for a long time, and effective management, such as a prolonged quarantine phase for discharged patients, is necessary.

Bacterial modification of the host glycosaminoglycan heparan sulfate modulates SARS-CoV-2 infectivity (preprint)

The human microbiota has a close relationship with human disease and it remodels components of the glycocalyx including heparan sulfate (HS). Studies of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) spike protein receptor binding domain suggest that infection requires binding to HS and angiotensin converting enzyme 2 (ACE2) in a codependent manner. Here, we show that commensal host bacterial communities can modify HS and thereby modulate SARS-CoV-2 spike protein binding and that these communities change with host age and sex. Common human-associated commensal bacteria whose genomes encode HS-modifying enzymes were identified. The prevalence of these bacteria and the expression of key microbial glycosidases in bronchoalveolar lavage fluid (BALF) was lower in adult COVID-19 patients than in healthy controls. The presence of HS-modifying bacteria decreased with age in two large survey datasets, FINRISK 2002 and American Gut, revealing one possible mechanism for the observed increase in COVID-19 susceptibility with age. In vitro, bacterial glycosidases from unpurified culture media supernatants fully blocked SARS-CoV-2 spike binding to human H1299 protein lung adenocarcinoma cells. HS-modifying bacteria in human microbial communities may regulate viral adhesion, and loss of these commensals could predispose individuals to infection. Understanding the impact of shifts in microbial community composition and bacterial lyases on SARS-CoV-2 infection may lead to new therapeutics and diagnosis of susceptibility. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/238444v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@14ff1ecorg.highwire.dtl.DTLVardef@193d84corg.highwire.dtl.DTLVardef@15d6f9eorg.highwire.dtl.DTLVardef@14b16c6_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract. Diagram of hypothesis for bacterial mediation of SARS-CoV-2 infection through heparan sulfate (HS).It is well known that host microbes groom the mucosa where they reside. Recent investigations have shown that HS, a major component of mucosal layers, is necessary for SARS-CoV-2 infection. In this study we examine the impact of microbial modification of HS on viral attachment. C_FIG

KG-COVID-19: a framework to produce customized knowledge graphs for COVID-19 response (preprint)

Integrated, up-to-date data about SARS-CoV-2 and coronavirus disease 2019 (COVID-19) is crucial for the ongoing response to the COVID-19 pandemic by the biomedical research community. While rich biological knowledge exists for SARS-CoV-2 and related viruses (SARS-CoV, MERS-CoV), integrating this knowledge is difficult and time consuming, since much of it is in siloed databases or in textual format. Furthermore, the data required by the research community varies drastically for different tasks - the optimal data for a machine learning task, for example, is much different from the data used to populate a browsable user interface for clinicians. To address these challenges, we created KG-COVID-19, a flexible framework that ingests and integrates biomedical data to produce knowledge graphs (KGs) for COVID-19 response. This KG framework can also be applied to other problems in which siloed biomedical data must be quickly integrated for different research applications, including future pandemics. BIGGER PICTUREAn effective response to the COVID-19 pandemic relies on integration of many different types of data available about SARS-CoV-2 and related viruses. KG-COVID-19 is a framework for producing knowledge graphs that can be customized for downstream applications including machine learning tasks, hypothesis-based querying, and browsable user interface to enable researchers to explore COVID-19 data and discover relationships.

A Lymph Node Targeted Amphiphile Vaccine Induces Potent Cellular and Humoral Immunity to SARS-CoV-2 (preprint)

The SARS-CoV-2 pandemic has led to public health, economic, and social consequences that mandate urgent development of effective vaccines to contain or eradicate infection. To that end, we evaluated a novel amphiphile (AMP) vaccine adjuvant, AMP-CpG, composed of diacyl lipid-modified CpG, admixed with the SARS-CoV-2 Spike-2 receptor binding domain protein as a candidate vaccine (ELI-005) in mice. AMP immunogens are efficiently delivered to lymph nodes, where innate and adaptive immune responses are generated. Compared to alum, AMP immunization induced >25-fold higher antigen-specific T cells which produced multiple Th1 cytokines and trafficked into lung parenchyma and respiratory secretions. Antibody responses favored Th1 isotypes (IgG2bc, IgG3) and potently neutralized Spike-2-ACE2 receptor binding, with titers 265-fold higher than the natural immune response from convalescent COVID-19 patients; responses were maintained despite 10-fold dose-reduction in Spike antigen. Both cellular and humoral immune responses were preserved in aged mice. These advantages merit clinical translation to SARS-CoV-2 and other protein subunit vaccines.

Association between supportive attitudes and adoptive practice of control strategy against COVID-19 among college students in China, a cross-sectional study (preprint)

Background: This study aimed to explore college students’ attitudes and compliance toward the prevention strategy of using non-pharmaceutical interventions (NPIs) in containing coronavirus disease 2019. Methods: We conducted a cross-sectional online survey in four universities in Guangdong Province (China) based on purposive sampling. We used a self-made questionnaire to measure the supportive attitude towards outbreak control strategy and adoption of NPIs in respondents. Results: A total of 44,446 college students participated between 31 January and 10 February 2020; 92.7% of respondents supported the outbreak control strategy. 94.8% would avoid public places, 92.8% would wear a facemask, 91.2% would avoid of gatherings and 86.9% would wash hands more frequent. 76.5% respondents adopted all four measures. Supportive attitude was associated with NPI adoption. Students who were female, postgraduate, anxious, and not depressed tended to have higher supportive attitude and higher NPI adoption rate. Conclusions: Higher supportiveness towards the disease control strategy for public may lead to higher adoption rate of NPIs for individuals. Psychosocial factors are related to supportive attitude and adoption of the NPIs. We believe that our findings are instructive about the prevention and control of emerging infectious diseases like COVID-19.