Big knowledge visualization of the COVID-19 CIDO ontology evolution.

BACKGROUND: The extensive international research for medications and vaccines for the devastating COVID-19 pandemic requires a standard reference ontology. Among the current COVID-19 ontologies, the Coronavirus Infectious Disease Ontology (CIDO) is the largest one. Furthermore, it keeps growing very frequently. Researchers using CIDO as a reference ontology, need a quick update about the content added in a recent release to know how relevant the new concepts are to their research needs. Although CIDO is only a medium size ontology, it is still a large knowledge base posing a challenge for a user interested in obtaining the "big picture" of content changes between releases. Both a theoretical framework and a proper visualization are required to provide such a "big picture". METHODS: The child-of-based layout of the weighted aggregate partial-area taxonomy summarization network (WAT) provides a "big picture" convenient visualization of the content of an ontology. In this paper we address the "big picture" of content changes between two releases of an ontology. We introduce a new DIFF framework named Diff Weighted Aggregate Taxonomy (DWAT) to display the differences between the WATs of two releases of an ontology. We use a layered approach which consists first of a DWAT of major subjects in CIDO, and then drill down a major subject of interest in the top-level DWAT to obtain a DWAT of secondary subjects and even further refined layers. RESULTS: A visualization of the Diff Weighted Aggregate Taxonomy is demonstrated on the CIDO ontology. The evolution of CIDO between 2020 and 2022 is demonstrated in two perspectives. Drilling down for a DWAT of secondary subject networks is also demonstrated. We illustrate how the DWAT of CIDO provides insight into its evolution. CONCLUSIONS: The new Diff Weighted Aggregate Taxonomy enables a layered approach to view the "big picture" of the changes in the content between two releases of an ontology.

Mining of EHR for interface terminology concepts for annotating EHRs of COVID patients.

BACKGROUND: Two years into the COVID-19 pandemic and with more than five million deaths worldwide, the healthcare establishment continues to struggle with every new wave of the pandemic resulting from a new coronavirus variant. Research has demonstrated that there are variations in the symptoms, and even in the order of symptom presentations, in COVID-19 patients infected by different SARS-CoV-2 variants (e.g., Alpha and Omicron). Textual data in the form of admission notes and physician notes in the Electronic Health Records (EHRs) is rich in information regarding the symptoms and their orders of presentation. Unstructured EHR data is often underutilized in research due to the lack of annotations that enable automatic extraction of useful information from the available extensive volumes of textual data. METHODS: We present the design of a COVID Interface Terminology (CIT), not just a generic COVID-19 terminology, but one serving a specific purpose of enabling automatic annotation of EHRs of COVID-19 patients. CIT was constructed by integrating existing COVID-related ontologies and mining additional fine granularity concepts from clinical notes. The iterative mining approach utilized the techniques of 'anchoring' and 'concatenation' to identify potential fine granularity concepts to be added to the CIT. We also tested the generalizability of our approach on a hold-out dataset and compared the annotation coverage to the coverage obtained for the dataset used to build the CIT. RESULTS: Our experiments demonstrate that this approach results in higher annotation coverage compared to existing ontologies such as SNOMED CT and Coronavirus Infectious Disease Ontology (CIDO). The final version of CIT achieved about 20% more coverage than SNOMED CT and 50% more coverage than CIDO. In the future, the concepts mined and added into CIT could be used as training data for machine learning models for mining even more concepts into CIT and further increasing the annotation coverage. CONCLUSION: In this paper, we demonstrated the construction of a COVID interface terminology that can be utilized for automatically annotating EHRs of COVID-19 patients. The techniques presented can identify frequently documented fine granularity concepts that are missing in other ontologies thereby increasing the annotation coverage.

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology.

BACKGROUND: The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the development of the community-based Coronavirus Infectious Disease Ontology (CIDO) in early 2020. RESULTS: As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. CONCLUSION: CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications.

Human adenovirus (HAdV) infection in children with acute respiratory tract infections in Guangzhou, China, 2010-2021: a molecular epidemiology study.

BACKGROUND: Human adenovirus (HAdV) infection can cause a variety of diseases. It is a major pathogen of pediatric acute respiratory tract infections (ARIs) and can be life-threatening in younger children. We described the epidemiology and subtypes shifting of HAdV among children with ARI in Guangzhou, China. METHODS: We conducted a retrospective study of 161,079 children diagnosed with acute respiratory illness at the Guangzhou Women and Children's Medical Center between 2010 and 2021. HAdV specimens were detected by real-time PCR and the hexon gene was used for phylogenetic analysis. RESULTS: Before the COVID-19 outbreak in Guangzhou, the annual frequency of adenovirus infection detected during this period ranged from 3.92% to 13.58%, with an epidemic peak every four to five years. HAdV demonstrated a clear seasonal distribution, with the lowest positivity in March and peaking during summer (July or August) every year. A significant increase in HAdV cases was recorded for 2018 and 2019, which coincided with a shift in the dominant HAdV subtype from HAdV-3 to HAdV-7. The latter was associated with a more severe disease compared to HAdV-3. The average mortality proportion for children infected with HAdV from 2016 to 2019 was 0.38% but increased to 20% in severe cases. After COVID-19 emerged, HAdV cases dropped to 2.68%, suggesting that non-pharmaceutical interventions probably reduced the transmission of HAdV in the community. CONCLUSION: Our study provides the foundation for the understanding of the epidemiology of HAdV and its associated risks in children in Southern China.

Virucidal and biodegradable specialty cellulose nonwovens as personal protective equipment against COVID-19 pandemic.

INTRODUCTION: Face masks are regarded as effective Personal Protective Equipment (PPE) during the COVID-19 pandemic. However, the dominant polypropylene (PP)-based masks are devoid of antiviral/antibacterial activities and create enormous environmental burdens after disposal. OBJECTIVES: Here we report a facile and potentially scalable method to fabricate biodegradable, breathable, and biocidal cellulose nonwovens (BCNWs) to address both environmental and hygienic problems of commercially available face masks. METHODS: TEMPO-oxidized cellulose nonwovens are rendered antiviral/antibacterial via covalent bonding with disinfecting polyhexamethylene guanidine or neomycin sulfate through carbodiimide coupling chemistry. RESULTS: The obtained results showed that the BCNWs have virucidal rate of >99.14%, bactericidal efficiency of >99.51%, no leaching-out effect, and excellent air permeability of >1111.5 mm s-1. More importantly, the as-prepared BCNWs can inactivate SARS-CoV-2 instantly. CONCLUSIONS: This strategy provides a new platform for the green fabrication of multifunctional cellulose nonwovens as scalable bio-protective layers with superior performance for various PPE in fighting COVID-19 or future pandemics. Additionally, replacing the non-biodegradable non-antimicrobial PP-based masks with the cellulose-based masks can reduce the plastic wastes and lower the greenhouse gas production from the incineration of disposed masks.

Factors associated with the mental health of back-to-Wuhan university students based on quantile regression model during the COVID-19 period.

BACKGROUND: The COVID-19 pandemic had brought the increased levels of depression and anxiety on people. Our study investigated the levels of mental health and influencing factors among back-to-Wuhan university students. METHODS: A cross-sectional questionnaire survey was conducted from 31 August 2020, to 14 September 2020 by convenience sampling on the back-to-Wuhan university students, which included the Generalized Anxiety Disorder Scale (GAD-7), Patient Health Questionnaire-9 (PHQ-9), the Insomnia Severity Index-7 (ISI-7), the revised Impact of Event Scale (IES-R) scales, and the basic demographic characteristics. Moreover, quantile regression analysis was used to identify the key factors related to the mental health variables of the back-to-Wuhan university students during the COVID-19 period. RESULTS: The results from 1017 participants suggested that the prevalence rates of the anxiety, depression, insomnia, and distress were 44%, 47.5%, 37.7%, 57.7%, respectively. Quantile regression showed that mental health scores were negatively associated to age, years from graduation, being discriminated against owing to the experience in Wuhan, and the attitude on the future of COVID-19, while was positively related to the education level (P < 0.05). Especially, the education level was highly related with anxiety (25th = 1.64, 50th = 2.54). CONCLUSION: The finding showed that the respondents who were near graduation, discriminated owing to the experience in Wuhan, and worried about the future trend of COVID-19 had a higher risk of negative psychologic status, especially in the bottom and median quantile, and might require more psycho-social interventions or support.

SARS-CoV-2 causes a significant stress response mediated by small RNAs in the blood of COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a serious impact on the world. In this study, small RNAs from the blood of COVID-19 patients with moderate or severe symptoms were extracted for high-throughput sequencing and analysis. Interestingly, the levels of a special group of tRNA-derived small RNAs (tsRNAs) were found to be dramatically upregulated after SARS-CoV-2 infection, particularly in coronavirus disease 2019 (COVID-19) patients with severe symptoms. In particular, the 3'CCA tsRNAs from tRNA-Gly were highly consistent with the inflammation indicator C-reactive protein (CRP). In addition, we found that the majority of significantly changed microRNAs (miRNAs) were associated with endoplasmic reticulum (ER)/unfolded protein response (UPR) sensors, which may lead to the induction of proinflammatory cytokine and immune responses. This study found that SARS-CoV-2 infection caused significant changes in the levels of stress-associated small RNAs in patient blood and their potential functions. Our research revealed that the cells of COVID-19 patients undergo tremendous stress and respond, which can be reflected or regulated by small non-coding RNA (sncRNAs), thus providing potential thought for therapeutic intervention in COVID-19 by modulating small RNA levels or activities.

Visual comprehension and orientation into the COVID-19 CIDO ontology.

The current intensive research on potential remedies and vaccinations for COVID-19 would greatly benefit from an ontology of standardized COVID terms. The Coronavirus Infectious Disease Ontology (CIDO) is the largest among several COVID ontologies, and it keeps growing, but it is still a medium sized ontology. Sophisticated CIDO users, who need more than searching for a specific concept, require orientation and comprehension of CIDO. In previous research, we designed a summarization network called "partial-area taxonomy" to support comprehension of ontologies. The partial-area taxonomy for CIDO is of smaller magnitude than CIDO, but is still too large for comprehension. We present here the "weighted aggregate taxonomy" of CIDO, designed to provide compact views at various granularities of our partial-area taxonomy (and the CIDO ontology). Such a compact view provides a "big picture" of the content of an ontology. In previous work, in the visualization patterns used for partial-area taxonomies, the nodes were arranged in levels according to the numbers of relationships of their concepts. Applying this visualization pattern to CIDO's weighted aggregate taxonomy resulted in an overly long and narrow layout that does not support orientation and comprehension since the names of nodes are barely readable. Thus, we introduce in this paper an innovative visualization of the weighted aggregate taxonomy for better orientation and comprehension of CIDO (and other ontologies). A measure for the efficiency of a layout is introduced and is used to demonstrate the advantage of the new layout over the previous one. With this new visualization, the user can "see the forest for the trees" of the ontology. Benefits of this visualization in highlighting insights into CIDO's content are provided. Generality of the new layout is demonstrated.

Kidney manifestations of mild, moderate and severe coronavirus disease 2019: a retrospective cohort study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a pandemic that has affected more than 3 million patients globally. Previous data from Wuhan city showed that acute kidney injury (AKI), proteinuria and hematuria occurred frequently in patients with severe COVID-19. However, the prevalence of kidney injury in milder cases remains unclear. METHODS: This retrospective study included two major consecutive cohorts of COVID-19 patients in Sichuan Province. Baseline characteristics, laboratory data including renal function, proteinuria and dipstick hematuria, and other laboratory parameters were collected. A subgroup of patients was followed up for 2-4 weeks to evaluate the short-term outcome of renal impairment. RESULTS: Overall, 168 COVID-19-positive patients were included in the study. The majority of patients (79.7%) were diagnosed with mild or moderate disease. Half of patients presented with fever; however, in The Tibetan cohort, fever only occurred in 13.4% of patients. On hospital admission, proteinuria and dipstick hematuria were noted in 18.4% and 17.4% of patients, respectively, while AKI only occurred in one patient. Further analysis showed that severe or critical COVID-19 was associated with higher risk of proteinuria [relative risk (RR) 7.37, 95% confidence interval (CI) 2.45-22.18, P = 3.8 × 10-4] and dipstick hematuria (RR 8.30, 95% CI 2.69-25.56, P = 2.3 × 10-4). Proteinuria, dipstick hematuria, or the combination of proteinuria and hematuria could significantly predict severe or critical severe COVID-19. CONCLUSIONS: Proteinuria and dipstick hematuria are not uncommon in patients with COVID-19 infection, especially in severe or critical cases.

Renal dysfunction and prognosis of COVID-19 patients: a hospital-based retrospective cohort study.

INTRODUCTION: Increasing evidence indicate that coronavirus disease 2019 (COVID-19) is companied by renal dysfunction. However, the association of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2)-induced renal dysfunction with prognosis remains obscure. MATERIALS AND METHODS: All 154 patients with COVID-19 were recruited from the Second People's Hospital of Fuyang City in Anhui, China. Demographic characteristics and laboratory data were extracted. Renal dysfunction was evaluated and its prognosis was followed up based on a retrospective cohort study. RESULTS: There were 125 (81.2%) mild and 29 (18.8%) severe cases in 154 COVID-19 patients. On admission, 16 (10.4%) subjects were accompanied with renal dysfunction. Serum creatinine and cystatin C were increased and estimated glomerular filtration rate (eGFR) was decreased in severe patients compared with those in mild patients. Renal dysfunction was more prevalent in severe patients. Using multivariate logistic regression, we found that male gender, older age and hypertension were three importantly independent risk factors for renal dysfunction in COVID-19 patients. Follow-up study found that at least one renal function marker of 3.33% patients remained abnormal in 2 weeks after discharge. CONCLUSION: Male elderly COVID-19 patients with hypertension elevates the risk of renal dysfunction. SARS-CoV-2-induced renal dysfunction are not fully recovered in 2 weeks after discharge.

COVID-19-Related Intolerance of Uncertainty and Mental Health among Back-To-School Students in Wuhan: The Moderation Effect of Social Support.

The current wave and future trend of the novel coronavirus disease 2019 (COVID-19) has triggered public uncertainty, causing unbearable psychological pressure on people. A cross-sectional online questionnaire was conducted among back-to-school students in Wuhan from 31 August 2020, to 14 September 2020, by using convenience sampling. A total of 1017 participants voluntarily provided sociodemographic characteristics and accomplished the following scales: the Intolerance of Uncertainty Scale (IUS-12), the Social Support Scale (SSQ), the Generalized Anxiety Disorder Scale (GAD-7), the Patient Health Questionnaire-9 (PHQ-9), and the Insomnia Severity Index-7 (ISI-7). Results revealed that the levels of anxiety, depression, and insomnia were moderate, moderate and subthreshold, respectively. A one-way multivariate analysis of variance indicated that those with different attitudes toward the trajectory of the COVID-19 epidemic in China showed significantly different results in anxiety and depression (p < 0.001). Moderation modeling implicated that social support significantly moderated the predictive relationship between intolerance of uncertainty and mental health variables including anxiety and depression, but failed on insomnia. Findings indicate that back-to-school students in Wuhan experience mental health problems and improving social support measures could buffer the effect of intolerance of uncertainty with respect to COVID-19 on mental health.

Improving Detection Efficiency of SARS-CoV-2 Nucleic Acid Testing.

Background: SARS-CoV-2 nucleic acid testing (NAT) has been routinely used for COVID-19 diagnosis during this pandemic; however, there have been concerns about its high false negative rate. We dissected its detection efficiency with a large COVID-19 cohort study. Methods: We analyzed SARS-CoV-2 NAT positive rates of 4,275 specimens from 532 COVID-19 patients in Sichuan Province with different disease severities, statuses, and stages, as well as different types and numbers of specimens. Results: The total positive rate of the 4,275 specimens was 37.5%. Among seven specimen types, BALF generated a 77.8% positive rate, followed by URT specimens (38.5%), sputum (39.8%), and feces/rectal swabs (34.1%). Specimens from critical cases generated a 43.4% positive rate, which was significantly higher than that of other severities. With specimens from patients at stable status, the SARS-CoV-2 positive rate was 40.6%, which was significantly higher than that of improved status (17.1%), but lower than that of aggravated status (61.5%). Notably, the positive rate of specimens from COVID-19 patients varied significantly from 85 to 95% during 3 days before and after symptom onset, to 20% at around 18 days after symptom onset. In addition, the detection rate increased from 72.1% after testing one throat swab, to 93.2% after testing three consecutive respiratory specimens from each patient. Conclusions: SARS-CoV-2 NAT detection rates vary with patient disease severity and status, specimen type, number of specimens, and especially disease progression. Sampling as close to symptom onset as possible, and consecutively collecting more than one respiratory specimen could effectively improve SARS-CoV-2 NAT detection efficiency.

The Mediating Role of Internalized Stigma and Shame on the Relationship between COVID-19 Related Discrimination and Mental Health Outcomes among Back-to-School Students in Wuhan.

Outbreaks of an epidemic, such as coronavirus disease 2019 (COVID-19), always brings about far-ranging discrimination and stigmatization to the epicenter. This was a cross-sectional survey conducted to assess experienced discrimination, internalized stigma, shame, and mental health (anxiety, depression, distress, insomnia) among college students who merely had a perceived linkage with COVID-19, and explore the linkage between discrimination and negative mental health outcomes through the mediating effects of shame and internalized stigma. A total of 995 participants (53% female) were involved in this study, in which 40.9% of college students were reported to be discriminated against because of their experience in Wuhan. The experience of COVID-19-related discrimination is indirectly associated with anxiety, depression, and insomnia, in which shame and internalized stigma play a complete mediating effect. Meanwhile, it is both directly and indirectly associated with distress through shame and internalized stigma. The findings of this study suggest that COVID-19-related discrimination is associated with shame and internalized stigma, which in turn predict psychological symptoms over time.

A Comparative Study on the Clinical Features of Coronavirus 2019 (COVID-19) Pneumonia With Other Pneumonias.

BACKGROUND: A novel coronavirus (COVID-19) has raised world concern since it emerged in Wuhan, China in December 2019. The infection may result in severe pneumonia with clusters of illness onsets. Its impacts on public health make it paramount to clarify the clinical features with other pneumonias. METHODS: Nineteen COVID-19 and 15 other patients with pneumonia (non-COVID-19) in areas outside of Hubei were involved in this study. Both COVID-19 and non-COVID-19 patients were confirmed to be infected using throat swabs and/or sputa with/without COVID-2019 by real-time RT-PCR. We analyzed the demographic, epidemiological, clinical, and radiological features from those patients, and compared the differences between COVID-19 and non-COVID-19. RESULTS: All patients had a history of exposure to confirmed cases of COVID-19 or travel to Hubei before illness. The median (IQR) duration was 8 (6-11) and 5 (4-11) days from exposure to onset in COVID-19 and non-COVID-19 cases, respectively. The clinical symptoms were similar between COVID-19 and non-COVID-19. The most common symptoms were fever and cough. Fifteen (78.95%) COVID-19 but 4 (26.67%) non-COVID-19 patients had bilateral involvement while 17 COVID-19 patients (89.47%) but 1 non-COVID-19 patient (6.67%) had multiple mottling and ground-glass opacity on chest CT images. Compared with non-COVID-19, COVID-19 presents remarkably more abnormal laboratory tests, including AST, ALT, γ-GT, LDH, and α-HBDH. CONCLUSIONS: The COVID-19 infection has onsets similar to other pneumonias. CT scan may be a reliable test for screening COVID-19 cases. Liver function damage is more frequent in COVID-19 than non-COVID-19 patients. LDH and α-HBDH may be considerable markers for evaluation of COVID-19.