The use of bioinformatics methods to identify the effects of SARS-CoV-2 and influenza viruses on the regulation of gene expression in patients

Background SARS-CoV-2 infection is a respiratory infectious disease similar to influenza virus infection. Numerous studies have reported similarities and differences in the clinical manifestations, laboratory tests, and mortality between these two infections. However, the genetic effects of coronavirus and influenza viruses on the host that lead to these characteristics have rarely been reported. Methods COVID-19 (GSE157103) and influenza (GSE111368, GSE101702) datasets were downloaded from the Gene Expression Ominbus (GEO) database. Differential gene, gene set enrichment, protein-protein interaction (PPI) network, gene regulatory network, and immune cell infiltration analyses were performed to identify the critical impact of COVID-19 and influenza viruses on the regulation of host gene expression. Results The number of differentially expressed genes in the COVID-19 patients was significantly higher than in the influenza patients. 22 common differentially expressed genes (DEGs) were identified between the COVID-19 and influenza datasets. The effects of the viruses on the regulation of host gene expression were determined using gene set enrichment and PPI network analyses. Five HUB genes were finally identified: IFI27, OASL, RSAD2, IFI6, and IFI44L. Conclusion We identified five HUB genes between COVID-19 and influenza virus infection, which might be helpful in the diagnosis and treatment of COVID-19 and influenza. This knowledge may also guide future mechanistic studies that aim to identify pathogen-specific interventions.

Impact of inactivated vaccines on decrease of viral RNA levels in individuals with the SARS-CoV-2 Omicron (BA.2) variant: A retrospective cohort study in Shanghai, China.

Background: SARS-CoV-2 Omicron (BA.2) has stronger infectivity and more vaccine breakthrough capability than previous variants. Few studies have examined the impact of inactivated vaccines on the decrease of viral RNA levels in individuals with the Omicron variant, based on individuals' continuous daily cycle threshold (Ct) values and associated medical information from the infection to hospital discharge on a large population. Methods: We extracted 39,811 individuals from 174,371 Omicron-infected individuals according to data inclusion and exclusion criteria. We performed the survival data analysis and Generalized Estimating Equation to calculate the adjusted relative risk (aRR) to assess the effect of inactivated vaccines on the decrease of viral RNA levels. Results: Negative conversion was achieved in 54.7 and 94.3% of all infected individuals after one and 2 weeks, respectively. aRRs were shown weak effects on turning negative associated with vaccinations in asymptomatic infections and a little effect in mild diseases. Vaccinations had a protective effect on persistent positivity over 2 and 3 weeks. aRRs, attributed to full and booster vaccinations, were both around 0.7 and had no statistical significance in asymptomatic infections, but were both around 0.6 with statistical significance in mild diseases, respectively. Trends of viral RNA levels among vaccination groups were not significant in asymptomatic infections, but were significant between unvaccinated group and three vaccination groups in mild diseases. Conclusion: Inactivated vaccines accelerate the decrease of viral RNA levels in asymptomatic and mild Omicron-infected individuals. Vaccinated individuals have lower viral RNA levels, faster negative conversion, and fewer persisting positive proportions than unvaccinated individuals. The effects are more evident and significant in mild diseases than in asymptomatic infections.

The use of bioinformatics methods to identify the effects of SARS-CoV-2 and influenza viruses on the regulation of gene expression in patients.

Background: SARS-CoV-2 infection is a respiratory infectious disease similar to influenza virus infection. Numerous studies have reported similarities and differences in the clinical manifestations, laboratory tests, and mortality between these two infections. However, the genetic effects of coronavirus and influenza viruses on the host that lead to these characteristics have rarely been reported. Methods: COVID-19 (GSE157103) and influenza (GSE111368, GSE101702) datasets were downloaded from the Gene Expression Ominbus (GEO) database. Differential gene, gene set enrichment, protein-protein interaction (PPI) network, gene regulatory network, and immune cell infiltration analyses were performed to identify the critical impact of COVID-19 and influenza viruses on the regulation of host gene expression. Results: The number of differentially expressed genes in the COVID-19 patients was significantly higher than in the influenza patients. 22 common differentially expressed genes (DEGs) were identified between the COVID-19 and influenza datasets. The effects of the viruses on the regulation of host gene expression were determined using gene set enrichment and PPI network analyses. Five HUB genes were finally identified: IFI27, OASL, RSAD2, IFI6, and IFI44L. Conclusion: We identified five HUB genes between COVID-19 and influenza virus infection, which might be helpful in the diagnosis and treatment of COVID-19 and influenza. This knowledge may also guide future mechanistic studies that aim to identify pathogen-specific interventions.

A Blockchain-Based Life-Cycle Environmental Management Framework for Hospitals in the COVID-19 Context.

During the coronavirus disease 2019 (COVID-19) emergency, many hospitals were built or renovated around the world to meet the challenges posed by the rising number of infected cases. Environmental management in the hospital life cycle is vital in preventing nosocomial infection and includes many infection control procedures. In certain urgent situations, a hospital must be completed quickly, and work process approval and supervision must therefore be accelerated. Thus, many works cannot be checked in detail. This results in a lack of work liability control and increases the difficulty of ensuring the fulfillment of key infection prevention measures. This study investigates how blockchain technology can transform the work quality inspection workflow to assist in nosocomial infection control under a fast delivery requirement. A blockchain-based life-cycle environmental management framework is proposed to track the fulfillment of crucial infection control measures in the design, construction, and operation stages of hospitals. The proposed framework allows for work quality checking after the work is completed, when some work cannot be checked on time. Illustrative use cases are selected to demonstrate the capabilities of the developed solution. This study provides new insights into applying blockchain technology to address the challenge of environmental management brought by rapid delivery requirements.

Genetic screening for hypertension and COVID-19 reveals functional variation of SPEG potentially associated with severe COVID-19 in women.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to more than 6.4 million deaths worldwide. The prevalent comorbidity between hypertension and severe COVID-19 suggests common genetic factors may affect the outcome of both diseases. As both hypertension and severe COVID-19 demonstrate sex-biased prevalence, common genetic factors between the two diseases may display sex-biased differential associations. By evaluating COVID-19 association signals of 172-candidate hypertension single nucleotide polymorphisms (SNPs) derived from more than 1 million European individuals in two sex-stratified severe COVID-19 genome-wide association studies from UK BioBank with European ancestry, we revealed one functional cis expression quantitative trait locus of SPEG (rs12474050) showing sex-biased association with severe COVID-19 in women. The risk allele rs12474050*T associates with higher blood pressure. In our study, we found it is significantly correlated with lower SPEG expression in muscle-skeletal but with higher expression in both brain cerebellum and cerebellar hemisphere. Additionally, nominal significances were detected for the association between rs12474050*T and lower SPEG expression in both heart left ventricle and atrial appendage; among these tissues, the SPEG expression is nominally significantly higher in females than in males. Further analysis revealed SPEG is mainly expressed in cardiomyocytes in heart and is upregulated upon SARS-CoV-2 infection, with significantly higher upregulation of SPEG only observed in female but not in male COVID-19 patients compared to both normal female and male individuals, suggesting upregulation of SPEG is a female-specific protective mechanism against COVID-19 induced heart damage. Taken together, our analyses suggest the involvement of SPEG in both hypertension and severe COVID-19 in women, which provides new insights for sex-biased effect of severe COVID-19 in women.

Neutralizing monoclonal antibodies elicited by mosaic RBD nanoparticles bind conserved sarbecovirus epitopes.

Increased immune evasion by SARS-CoV-2 variants of concern highlights the need for new therapeutic neutralizing antibodies. Immunization with nanoparticles co-displaying spike receptor-binding domains (RBDs) from eight sarbecoviruses (mosaic-8 RBD-nanoparticles) efficiently elicits cross-reactive polyclonal antibodies against conserved sarbecovirus RBD epitopes. Here, we identified monoclonal antibodies (mAbs) capable of cross-reactive binding and neutralization of animal sarbecoviruses and SARS-CoV-2 variants by screening single mouse B cells secreting IgGs that bind two or more sarbecovirus RBDs. Single-particle cryo-EM structures of antibody-spike complexes, including a Fab-Omicron complex, mapped neutralizing mAbs to conserved class 1/4 RBD epitopes. Structural analyses revealed neutralization mechanisms, potentials for intra-spike trimer cross-linking by IgGs, and induced changes in trimer upon Fab binding. In addition, we identified a mAb-resembling Bebtelovimab, an EUA-approved human class 3 anti-RBD mAb. These results support using mosaic RBD-nanoparticle vaccination to generate and identify therapeutic pan-sarbecovirus and pan-variant mAbs.

Mosaic RBD nanoparticles protect against challenge by diverse sarbecoviruses in animal models

To combat future SARS-CoV-2 variants and spillovers of SARS-like betacoronaviruses (sarbecoviruses) threatening global health, we designed mosaic nanoparticles presenting randomly-arranged sarbecovirus spike receptor-binding domains (RBDs) to elicit antibodies against epitopes that are conserved and relatively occluded, rather than variable, immunodominant, and exposed. We compared immune responses elicited by mosaic-8 (SARS-CoV-2 and seven animal sarbecoviruses) and homotypic (only SARS-CoV-2) RBD-nanoparticles in mice and macaques, observing stronger responses elicited by mosaic-8 to mismatched (not on nanoparticles) strains including SARS-CoV and animal sarbecoviruses. Mosaic-8 immunization showed equivalent neutralization of SARS-CoV-2 variants including Omicrons and protected from SARS-CoV-2 and SARS-CoV challenges, whereas homotypic SARS-CoV-2 immunization protected only from SARS-CoV-2 challenge. Epitope mapping demonstrated increased targeting of conserved epitopes after mosaic-8 immunization. Together, these results suggest mosaic-8 RBD-nanoparticles could protect against SARS-CoV-2 variants and future sarbecovirus spillovers. Description

Massive Nonfatal Hydroxychloroquine Ingestion in a Pediatric Patient.

BACKGROUND: Hydroxychloroquine overdose is rare but potentially lethal. Hydroxychloroquine overdose symptoms are characterized by central nervous system toxicity, cardiac toxicity, and hypokalemia. Recommended treatment consists of epinephrine, high-dose diazepam, and careful potassium repletion. Few pediatric hydroxychloroquine overdoses have been reported. CASE REPORT: We describe a 14-year-old girl who ingested 10 g (172 mg/kg) of hydroxychloroquine. She developed tachycardia, hypotension, and hypokalemia. She was intubated and treated with diazepam and epinephrine infusions and potassium supplementation. Her serum hydroxychloroquine concentration obtained 10 h after ingestion was 13,000 ng/mL (reference range 500-2000 ng/mL). The patient made a full medical recovery. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Pediatric hydroxychloroquine overdoses are reported rarely, and the toxic and lethal doses of hydroxychloroquine ingestion have not been established. This case of a teenaged patient who ingested 10 g of hydroxychloroquine and survived provides additional information that may be used to help establish toxic and lethal doses of ingestion.

ACE2 in the Gut: The Center of the 2019-nCoV Infected Pathology.

The 2019-nCoV is a rapidly contagious pneumonia caused by the recently discovered coronavirus. Although generally the most noticeable symptoms are concentrated in the lungs, the disorders in the gastrointestinal tract are of great importance in the diagnosis of 2019-nCoV. The angiotensin-converting enzyme 2 (ACE2), an important regulator of many physiological functions, including blood pressure and nutrients absorption, is recently identified as a vital entry for 2019-nCoV to enter host cells. In this review, we summarize its functions both physiologically and pathologically. We also elaborate its conflicting roles from the clews of contemporary researches, which may provide significant indications for pharmacological investigations and clinical uses.

A novel crop classification method based on ppfSVM classifier with time-series alignment kernel from dual-polarization SAR datasets

Rapid and accurate crop type mapping is of great significance for agricultural management and sustainable development. Time-series multi-polarization synthetic aperture radar (SAR) data is suitable for obtaining the large-scale distribution of crop types and continuously monitoring crops. At present, the classification method based on the time-series alignment of time-varying feature curves has been widely used, which can take the uncertainty of the phenological cycles of crops into account. The most classical method is the nearest neighbor (NN) classifier based on the dynamic time warping (DTW) alignment. While the DTW alignment does not consider the local shape of the curves and temporal ranges, and the NN classifier is inadequate in generalization, which restricts the accuracy of crop type mapping. In this paper, a pairwise proximity function support vector machine (ppfSVM) classification method with the time-weighted shapeDTW (TWshapeDTW) alignment is proposed. Firstly, the novel alignment method simultaneously considers the local shape of the curve and the temporal range of crops. Besides, the novel ppfSVM classifier with the time-series alignment kernel is established. Such kernel matrix considers dual-similarity metrics of multiple features, and it is positive semi-definite (PSD) in this classifier. With 42 Sentinel-1 dual-polarization SAR images located in Gansu Province, China, the crop classification maps in 2018 and 2019 are generated respectively. The proposed method in this paper obtains the overall accuracies of more than 90% in both two years, and the changes of crop types from 2018 to 2019 are also in line with the actual crop rotation. Compared with traditional classification methods (SVM and the NN method with the DTW alignment), it is found that the proposed method has higher overall accuracy (OA) and better robustness in the case of small number of samples. The OA's improvements of our method compared with the SVM method are 3% and 1% in 2018 and 2019, respectively. Such improvements are 14% and 12% respect to the NN method with the DTW alignment. This method can achieve more obvious improvement under the condition of less training samples and unaligned phenological sequences. Furthermore, the novel TWshapeDTW alignment is superior to the DTW and the time-weighted DTW alignment under the ppfSVM classifier. The OA's improvement introduced by the TWshapeDTW alignment respect to the DTW alignment can obtain 5% and 4% in 2018 and 2019, respectively. • The proposed TWshapeDTW method reduces matching errors between feature curves. • The ppfSVM classifier with time-series alignment kernel improves generalization. • The proposed method adapts to the uncertainty of crop phenology and finite samples. • The proposed method has accuracies over 90%, which is superior to traditional methods. [ABSTRACT FROM AUTHOR] Copyright of Remote Sensing of Environment is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Accounting downside risk measures and credit spreads

PurposeThis study aims to examine the association between predictive accounting downside risk measures and changes in credit spreads. Building upon the earnings downside risk (EDR) measure developed in prior literature, this paper introduces cash flow downside risk (CFDR).Design/methodology/approachThis study modifies an existing empirical framework (root lower partial moment) to calculate CFDR and applies it to a sample of firms between 2002 and 2013 for which credit default swap data are available.FindingsAfter validating the measure, this study identifies a positive association between CFDR and changes in credit spreads. This paper further shows the association between CFDR and credit spread changes is stronger than that between EDR and credit spread changes. Financial stability moderates the relationship between CFDR and credit spreads.Originality/valueThis study proposes a novel measure of accounting downside risk, CFDR and demonstrates a negative association between this measure and future cash flow and a positive association between this measure and future credit spreads.

Asymptomatic and Symptomatic Patients With Non-severe Coronavirus Disease (COVID-19) Have Similar Clinical Features and Virological Courses: A Retrospective Single Center Study.

The current outbreak of coronavirus disease 2019 (COVID-19) has been defined as a pandemic by the World Health Organization. We aimed to evaluate the clinical features and virological course of non-severe COVID-19 patients with or without symptoms who were admitted to a Chinese cabin hospital. In this retrospective single center study, we reviewed 252 laboratory-confirmed COVID-19 patients treated at one temporary cabin hospital in Wuhan, China. Demographic, clinical, serial chest computed tomography (CT), and serial viral test data were compared between asymptomatic and symptomatic patients. The association between clinical features and symptomatic status or patient referral status was analyzed. Among all 252 patients, 74 (29.4%) were asymptomatic and 138 (54.76%) had more than two family members who developed COVID-19. The probability for family clustering was similar between asymptomatic and symptomatic patients (59.70 vs. 61.64%, P = 0.79). Asymptomatic patients and symptomatic patients were equally likely to reach a virus-free state during their stay at the cabin hospital (93.15 vs. 86.44%, P = 0.13). The initial chest CT screening showed that 81 (32.1%) patients had no visible pneumonia, 52 (20.6%) had unilateral pneumonia, and 119 (47.2%) had bilateral pneumonia. Symptomatic patients had a higher chance to have bilateral pneumonia (P < 0.0001) and were less likely to show improvement on the follow-up CT scan (P = 0.0002). In total, 69 (27.4%) patients were referred to the designated hospital and only 23 (9.1%) patients were referred due to the progression of pneumonia. Non-severe COVID-19 patients can transmit the disease regardless of their symptomatic status. It is highly recommended that asymptomatic patients be identified and quarantined to eliminate the transmission of COVID-19.