Low-rank latent matrix-factor prediction modeling for generalized high-dimensional matrix-variate regression.

Motivated by diagnosing the COVID-19 disease using two-dimensional (2D) image biomarkers from computed tomography (CT) scans, we propose a novel latent matrix-factor regression model to predict responses that may come from an exponential distribution family, where covariates include high-dimensional matrix-variate biomarkers. A latent generalized matrix regression (LaGMaR) is formulated, where the latent predictor is a low-dimensional matrix factor score extracted from the low-rank signal of the matrix variate through a cutting-edge matrix factor model. Unlike the general spirit of penalizing vectorization plus the necessity of tuning parameters in the literature, instead, our prediction modeling in LaGMaR conducts dimension reduction that respects the geometric characteristic of intrinsic 2D structure of the matrix covariate and thus avoids iteration. This greatly relieves the computation burden, and meanwhile maintains structural information so that the latent matrix factor feature can perfectly replace the intractable matrix-variate owing to high-dimensionality. The estimation procedure of LaGMaR is subtly derived by transforming the bilinear form matrix factor model onto a high-dimensional vector factor model, so that the method of principle components can be applied. We establish bilinear-form consistency of the estimated matrix coefficient of the latent predictor and consistency of prediction. The proposed approach can be implemented conveniently. Through simulation experiments, the prediction capability of LaGMaR is shown to outperform some existing penalized methods under diverse scenarios of generalized matrix regressions. Through the application to a real COVID-19 dataset, the proposed approach is shown to predict efficiently the COVID-19.

[Component identification and analysis in vivo of Sanhan Huashi formula].

Sanhan Huashi formula(SHF) is the intermediate of a newly approved traditional Chinese medicine(TCM) Sanhan Huashi Granules for the treatment of COVID-19 infection. The chemical composition of SHF is complex since it contains 20 single herbal medicines. In this study, UHPLC-Orbitrap Exploris 240 was used to identify the chemical components in SHF and in rat plasma, lung and feces after oral administration of SHF, and heat map was plotted for characterizing the distribution of the chemical components. Chromatographic separation was conducted on a Waters ACQUITY UPLC BEH C_(18)(2.1 mm×100 mm, 1.7 µm) using 0.1% formic acid(A)-acetonitrile(B) as mobile phases in a gradient elution. Electrospray ionization(ESI) source was used to acquire data in positive and negative mode. By reference to quasi-molecular ions and MS/MS fragment ions and in combination with MS spectra of reference substances and compound information in literature reports, 80 components were identified in SHF, including 14 flavonoids, 13 coumarins, 5 lignans, 12 amino-compounds, 6 terpenes and 30 other compounds; 40 chemical components were identified in rat plasma, 27 in lung and 56 in feces. Component identification and characterization of SHF in vitro and in vivo lay foundations for disclosure of its pharmacodynamic substances and elucidation of the scientific connotation.

Pathogenicity, tissue tropism and potential vertical transmission of SARSr-CoV-2 in Malayan pangolins.

Malayan pangolin SARS-CoV-2-related coronavirus (SARSr-CoV-2) is closely related to SARS-CoV-2. However, little is known about its pathogenicity in pangolins. Using CT scans we show that SARSr-CoV-2 positive Malayan pangolins are characterized by bilateral ground-glass opacities in lungs in a similar manner to COVID-19 patients. Histological examination and blood gas tests are indicative of dyspnea. SARSr-CoV-2 infected multiple organs in pangolins, with the lungs the major target, and histological expression data revealed that ACE2 and TMPRSS2 were co-expressed with viral RNA. Transcriptome analysis indicated that virus-positive pangolins were likely to have inadequate interferon responses, with relative greater cytokine and chemokine activity in the lung and spleen. Notably, both viral RNA and viral proteins were detected in three pangolin fetuses, providing initial evidence for vertical virus transmission. In sum, our study outlines the biological framework of SARSr-CoV-2 in pangolins, revealing striking similarities to COVID-19 in humans.

Multi-objective optimization of mechanical ventilation with the aid of purifiers in two scenarios: Regular operation and mitigating the spread of respiratory infectious diseases.

COVID-19 and its impact on society have raised concerns about scaling up mechanical ventilation (MV) systems and the energy consequences. This paper attempted to combine MV and portable air cleaners (PACs) to achieve acceptable indoor air quality (IAQ) and energy reduction in two scenarios: regular operation and mitigating the spread of respiratory infectious diseases (RIDs). We proposed a multi-objective optimization method that combined the NSGA-II and TOPSIS techniques to determine the total equivalent ventilation rate of the MV-PAC system in both scenarios. The concentrations of PM2.5 and CO2 were primary indicators for IAQ. The modified Wells-Riley equation was adopted to predict RID transmissions. An open office with an MV-PAC system was used to demonstrate the method's applicability. Meanwhile, a field study was conducted to validate the method and evaluate occupants' perceptions of the MV-PAC system. Results showed that optimal solutions of the combined system can be obtained based on various IAQ requirements, seasons, outdoor conditions, etc. For regular operation, PACs were generally prioritized to maintain IAQ while reducing energy consumption even when outdoor PM2.5 concentration was high. MV can remain constant or be reduced at low occupancies. In RID scenarios, it is possible to mitigate transmissions when the quanta were < 48 h-1. No significant difference was found in the subjective perception of the MV and PACs. Moreover, the effects of infiltration on the optimal solution can be substantial. Nonetheless, our results suggested that an MV-PAC system can replace the MV system for offices for daily use and RID mitigation. Electronic Supplementary Material ESM: The Appendix is available in the online version of this article at 10.1007/s12273-023-0999-z.

SARS-CoV-2 infection aggravates chronic comorbidities of cardiovascular diseases and diabetes in mice.

Background: Cardiovascular diseases (CVDs) and diabetes mellitus (DM) are top two chronic comorbidities that increase the severity and mortality of COVID-19. However, how SARS-CoV-2 alters the progression of chronic diseases remain unclear. Methods: We used adenovirus to deliver h-ACE2 to lung to enable SARS-CoV-2 infection in mice. SARS-CoV-2's impacts on pathogenesis of chronic diseases were studied through histopathological, virologic and molecular biology analysis. Results: Pre-existing CVDs resulted in viral invasion, ROS elevation and activation of apoptosis pathways contribute myocardial injury during SARS-CoV-2 infection. Viral infection increased fasting blood glucose and reduced insulin response in DM model. Bone mineral density decreased shortly after infection, which associated with impaired PI3K/AKT/mTOR signaling. Conclusion: We established mouse models mimicked the complex pathological symptoms of COVID-19 patients with chronic diseases. Pre-existing diseases could impair the inflammatory responses to SARS-CoV-2 infection, which further aggravated the pre-existing diseases. This work provided valuable information to better understand the interplay between the primary diseases and SARS-CoV-2 infection.

Local Fiscal Pressure and Public Health: Evidence from China.

Under the dual challenges of global downward economic pressure and the COVID-19 pandemic, studying the impact of local government fiscal pressure on public health is a meaningful endeavor. First, this paper analyzes the impact of local government fiscal pressure on public health and clarifies its impact mechanisms. Second, by utilizing panel data of 31 Chinese provinces from 2000 to 2020, two-way fixed-effects and mediating-effects models are developed to identify the effects and impact mechanisms of local government fiscal pressure on public health. The results show that local government fiscal pressure can be detrimental to public health through three main mechanisms: reducing public health fiscal expenditures, hindering industrial structure upgrading, and exacerbating environmental pollution. Heterogeneity analysis finds that the negative effects of local government fiscal pressure on public health mainly exist in Central and Western China. Accordingly, three policy implications are proposed: optimizing the fiscal system, accelerating industrial upgrading, and improving the appraisal system of local officers.

Ordered Assembly of DNA on Topological Insulator Bi2Se3 and Octadecylamine for a Sensitive Biosensor.

Controlling the assembly of DNA in order on a suitable electrode surface is of great significance for biosensors and disease diagnosis, but it is full of challenges. In this work, we creatively assembled DNA on the surface of octadecylamine (ODA)-modified topological insulator (Tls) Bi2Se3 and developed an electrochemical biosensor to detect biomarker DNA of coronavirus disease 2019 (COVID-19). A high-quality Bi2Se3 sheet was obtained from a single crystal synthesized in our lab. A uniform ODA layer was coated in argon by chemical vapor deposition (CVD). We observed and analyzed the assembly and mechanism of single-strand DNA (ssDNA) and double-strand DNA (dsDNA) on the Bi2Se3 surface through atomic force microscopy (AFM) and molecular dynamics (MD) simulations. The electrochemical signal revealed that the biosensor based on the DNA/ODA/Bi2Se3 electrode has a wide linear detection range from 1.0 × 10-12 to 1.0 × 10-8 M, with the limit of detection as low as 5 × 10-13 M. Bi2Se3 has robust surface states and improves the electrochemical signal-to-noise ratio, while the uniform ODA layer guides high-density ordered DNA, enhancing the sensitivity of the biosensor. Our work demonstrates that the ordered DNA/ODA/Bi2Se3 electrode surface has great application potential in the field of biosensing and disease diagnosis.

Antithrombin Activity Is Associated with Persistent Thromboinflammation and Mortality in Patients with Severe COVID-19 Illness.

INTRODUCTION: Severe COVID-19 illness can lead to thrombotic complications, organ failure, and death. Antithrombin (AT) regulates thromboinflammation and is a key component of chemical thromboprophylaxis. Our goal was to examine the link between AT activity and responsiveness to thromboprophylaxis, markers of hypercoagulability, and inflammation among severe COVID-19 patients. METHODS: This was a single-center, prospective observational study enrolling SARS-CoV-2-positive patients admitted to the intensive care unit on prophylactic enoxaparin. Blood was collected daily for 7 days to assess AT activity and anti-factor Xa levels. Patient demographics, outcomes, and hospital laboratory results were collected. Continuous variables were compared using Mann-Whitney tests, and categorical variables were compared using χ2 tests. Multivariable logistic regression was used to determine the association between AT activity and mortality. RESULTS: In 36 patients, 3 thromboembolic events occurred, and 18 (50%) patients died. Patients who died had higher fibrinogen, D-dimer, and C-reactive protein (CRP) levels and lower AT activity. Reduced AT activity was independently associated with mortality and correlated with both markers of hypercoagulability (D-dimer) and inflammation (CRP). CONCLUSION: Low AT activity is associated with mortality and persistent hypercoagulable and proinflammatory states in severe COVID-19 patients. The anti-thromboinflammatory properties of AT make it an appealing therapeutic target for future studies.

Pediatric Outpatient Occupational Therapy: Transitioning From In-Person Services to Telehealth.

The COVID-19 pandemic necessitated rapid adoption of telehealth for outpatient pediatric occupational therapy practice. The dose of therapy may have varied across diagnostic and geographical groups despite efforts to ensure access for all patients. The objective of the study was to describe the visit length of outpatient pediatric occupational therapy practice for three diagnostic groups at one institution both during and prior to the COVID-19 pandemic. Retrospective review of electronic health records for two time periods using both practitioner-entered and telecommunications data. Data were analyzed using descriptive statistics and generalized linear mixed model. Prior to the pandemic, average treatment length did not vary by primary diagnosis. During the pandemic, average visit length varied by primary diagnosis, with feeding disorder (FD) visits significantly shorter than cerebral palsy (CP) and autism spectrum disorder (ASD) visits. During the pandemic, visit length was associated with rurality for the whole sample and for patients with ASD and CP, but not FD. Patients with FD may have been seen for shorter durations during telehealth visits. The technology gap may affect services for patients living in rural communities.

Targeted protein S-nitrosylation of ACE2 inhibits SARS-CoV-2 infection.

Prevention of infection and propagation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a high priority in the Coronavirus Disease 2019 (COVID-19) pandemic. Here we describe S-nitrosylation of multiple proteins involved in SARS-CoV-2 infection, including angiotensin-converting enzyme 2 (ACE2), the receptor for viral entry. This reaction prevents binding of ACE2 to the SARS-CoV-2 spike protein, thereby inhibiting viral entry, infectivity and cytotoxicity. Aminoadamantane compounds also inhibit coronavirus ion channels formed by envelope (E) protein. Accordingly, we developed dual-mechanism aminoadamantane nitrate compounds that inhibit viral entry and, thus, the spread of infection by S-nitrosylating ACE2 via targeted delivery of the drug after E protein channel blockade. These non-toxic compounds are active in vitro and in vivo in the Syrian hamster COVID-19 model and, thus, provide a novel avenue to pursue therapy.

Exploring the potential mechanisms of impairment on genitourinary system associated with coronavirus disease 2019 infection: Bioinformatics and molecular simulation analyses.

Objective: The novel coronavirus (severe acute respiratory syndrome coronavirus 2) has been spreading worldwide since December 2019, posing a serious danger to human health and socioeconomic development. A large number of clinical trials have revealed that coronavirus disease 2019 (COVID-19) results in multi-organ damage including the urogenital system. This study aimed to explore the potential mechanisms of genitourinary damage associated with COVID-19 infection through bioinformatics and molecular simulation analysis. Methods: We used multiple publicly available databases to explore the expression patterns of ACE2, TMPRSS2, and CD147 (Basigin [BSG]) in major organs in the healthy and disease-specific populations, particularly the genitourinary organs. Single-cell RNA sequencing was used to analyze the cell-specific expression patterns of ACE2, TMPRSS2, CD147, cytokine receptors, and cytokine interacting proteins in genitourinary organs, such as the bladder, kidney, prostate, and testis. Additionally, gene set enrichment analysis was used to investigate the relationship between testosterone levels and COVID-19 vulnerability in patients with prostate cancer. Results: The results revealed that ACE2, TMPRSS2, and CD147 were highly expressed in normal urogenital organs. Then, they were also highly expressed in multiple tumors and chronic kidney diseases. Additionally, ACE2, TMPRSS2, and CD147 were significantly expressed in a range of cells in urogenital organs according to single-cell RNA sequencing. Cytokine receptors and cytokine interacting proteins, especially CCL2, JUN, and TIMP1, were commonly highly expressed in urogenital organs. Finally, gene set enrichment analysis results showed that high testosterone levels in prostate cancer patients were significantly related to the JAK/STAT signaling pathway and the Toll-like receptor signaling pathway which were associated with COVID-19. Conclusion: Our study provides new insights into the potential mechanisms of severe acute respiratory syndrome coronavirus 2 damage to urogenital organs from multiple perspectives, which may draw the attention of urologists to COVID-19 and contribute to the development of targeted drugs.

Cascading impacts of global metal mining on climate change and human health caused by COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) pandemic has significantly disrupted global metal mining and associated supply chains. Here we analyse the cascading effects of the metal mining disruption associated with the COVID-19 pandemic on the economy, climate change, and human health. We find that the pandemic reduced global metal mining by 10-20% in 2020. This reduction subsequently led to losses in global economic output of approximately 117 billion US dollars, reduced CO2 emissions by approximately 33 million tonnes (exceeding Hungary's emissions in 2015), and reduced human health damage by 78,192 disability-adjusted life years. In particular, copper and iron mining made the most significant contribution to these effects. China and rest-of-the-world America were the most affected. The cascading effects of the metal mining disruption associated with the pandemic on the economy, climate change, and human health should be simultaneously considered in designing green economic stimulus policies.

Using Probe-Based Speed Data and Interactive Maps for Long-Term and COVID-Era Congestion Monitoring in San Francisco

Probe data that provide roadway speeds and travel times are increasingly being used for a variety of purposes in the transportation domain. A key use of these datasets has been roadway performance monitoring by state and local transportation agencies that are mandated to measure and report performance of their transportation networks. The San Francisco County Transportation Authority (SFCTA) monitors roadway performance as a part of the biennial Congestion Management Program (CMP) and primarily uses probe-based speed data for that purpose. Despite considerable savings in time and effort for data collection, integrating and processing the probe data still required a significant amount of manual work. This study highlights these challenges and proposes a data processing pipeline which includes an automated network conflation process, an efficient large data processing framework, and an interactive web-based visualization. In addition, all the scripts and code developed were made open source and are readily accessible from a public repository on GitHub. The value of the pipeline is demonstrated through the development of web-based interactive maps to monitor both long-term and short-term congestion in San Francisco. The short-term congestion monitoring application is timely given the spread of the COVID-19 pandemic and the region?s rapidly changing traffic conditions. Several valuable lessons learned from use of probe data for roadway performance monitoring are shared. Developing tools to ensure consistency of the data product and to reduce reliance on any one data vendor is of key importance.

Applications of Social Media and Digital Technologies in COVID-19 Vaccination: Scoping Review.

BACKGROUND: Social media and digital technologies have played essential roles in disseminating information and promoting vaccination during the COVID-19 pandemic. There is a need to summarize the applications and analytical techniques of social media and digital technologies in monitoring vaccine attitudes and administering COVID-19 vaccines. OBJECTIVE: We aimed to synthesize the global evidence on the applications of social media and digital technologies in COVID-19 vaccination and to explore their avenues to promote COVID-19 vaccination. METHODS: We searched 6 databases (PubMed, Scopus, Web of Science, Embase, EBSCO, and IEEE Xplore) for English-language articles from December 2019 to August 2022. The search terms covered keywords relating to social media, digital technology, and COVID-19 vaccines. Articles were included if they provided original descriptions of applications of social media or digital health technologies/solutions in COVID-19 vaccination. Conference abstracts, editorials, letters, commentaries, correspondence articles, study protocols, and reviews were excluded. A modified version of the Appraisal Tool for Cross-Sectional Studies (AXIS tool) was used to evaluate the quality of social media-related studies. The review was undertaken with the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. RESULTS: A total of 178 articles were included in our review, including 114 social media articles and 64 digital technology articles. Social media has been applied for sentiment/emotion analysis, topic analysis, behavioral analysis, dissemination and engagement analysis, and information quality analysis around COVID-19 vaccination. Of these, sentiment analysis and topic analysis were the most common, with social media data being primarily analyzed by lexicon-based and machine learning techniques. The accuracy and reliability of information on social media can seriously affect public attitudes toward COVID-19 vaccines, and misinformation often leads to vaccine hesitancy. Digital technologies have been applied to determine the COVID-19 vaccination strategy, predict the vaccination process, optimize vaccine distribution and delivery, provide safe and transparent vaccination certificates, and perform postvaccination surveillance. The applied digital technologies included algorithms, blockchain, mobile health, the Internet of Things, and other technologies, although with some barriers to their popularization. CONCLUSIONS: The applications of social media and digital technologies in addressing COVID-19 vaccination-related issues represent an irreversible trend. Attention should be paid to the ethical issues and health inequities arising from the digital divide while applying and promoting these technologies.

Real-time reverse transcription recombinase polymerase amplification for rapid detection of murine hepatitis virus.

Murine hepatitis virus (MHV) is a highly infectious murine coronavirus that has a high potential for causing harm to host animals. This study aimed to develop a real-time reverse transcription recombinase polymerase amplification (RT-RPA) method for rapid detection of MHV in laboratory mice. Methods: Specific primers and probes for RT-RPA assay were designed targeting the conserved region in the M gene of the MHV reference strain (accession no. FJ6647223) according to the TwistDx manual instructions. The specificity, sensitivity, and reproducibility of the RT-RPA method were evaluated and compared with those of the standard RT-qPCR method. The clinical applicability of this assay was evaluated using 68 field samples. Results: Amplification using the newly developed RT-RPA assay was completed within 20 min at 37°C, while that using the RT-qPCR method required nearly 60 min. The RT-RPA method exhibited an obvious time-saving advantage. Both RT-RPA and RT-PCR methods had the same limit of detection, which was 4.45 × 101 copies/µL. The specificity was indicated by a lack of cross-reaction with MHV, pneumonia virus of mice, Sendai virus, hantavirus, minute virus of mice, and reovirus type III. The MHV detection rate of RT-RPA assays was 13.63% (9/66) and RT-qPCR assays was 15.15% (10/66). Cohen's "kappa" (κ) analysis results exhibited a very good agreement between two methods with the value of κ ≥ 0.750(since κ = 0.939) and p < 0.0005 (since p = 0.000). Conclusion: The RT-RPA assay offers an alternative tool for simple, rapid, and reliable detection of MHV in laboratory mice and has significant potential for application in laboratories.

Cascading impacts of global metal mining on climate change and human health caused by COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic has significantly disrupted global metal mining and associated supply chains. Here we analyse the cascading effects of the metal mining disruption associated with the COVID-19 pandemic on the economy, climate change, and human health. We find that the pandemic reduced global metal mining by 10-20% in 2020. This reduction subsequently led to losses in global economic output of approximately 117 billion US dollars, reduced CO2 emissions by approximately 33 million tonnes (exceeding Hungary's emissions in 2015), and reduced human health damage by 78,192 disability-adjusted life years. In particular, copper and iron mining made the most significant contribution to these effects. China and rest-of-the-world America were the most affected. The cascading effects of the metal mining disruption associated with the pandemic on the economy, climate change, and human health should be simultaneously considered in designing green economic stimulus policies.

The impact of eating behaviors during COVID-19 in health-care workers: A conditional process analysis of eating, affective disorders, and PTSD.

Objective: The incidence of post-traumatic stress disorder (PTSD) increased among healthcare workers (HCWs) during the outbreak of COVID-19. The purpose of this study was to examine the relationship between eating behavior and PTSD, considering the mediation effect of anxiety, depression and sleep. Methods: A total of 101 HCWs completed a survey. The Food-Frequency Questionnaires (FFQ) were used to evaluate the diet. A special survey was conducted on the eating time of each shift mode. The PTSD Checklist-Civilian Version (PCL-C), Self-Rating Anxiety Scale (SAS), Self-Rating Depression Scale (SDS), Pittsburgh Sleep Quality Index (PSQI), and Morning-Evening Questionnaire (MEQ) were utilized to assess clinical symptoms. Results: There was a statistically significant correlation between the night shift eat midpoint (NEMP) and PTSD symptoms, anxiety and depression as significant mediators. The last meal jet lag between night shift and day shift (NDLM) was related to PTSD symptoms significantly, and sleep and anxiety were significant mediators. The relationship between animal-based protein pattern and PTSD symptoms was statistically significant, and anxiety was the significant mediator. Conclusions: The earlier the HCWs eat in the night shift, the lighter the symptoms of PTSD. This is mediated by improving anxiety, depression and sleep disorder. Furthermore, the consumption of animal protein could reduce symptoms of PTSD by improving anxiety.