The design and fabrication of a visible-light-driven photoelectrochemical (PEC) device based on CdSe-Co3O4@TiO2 nanoflower are presented in this report. In addition, an application for the ultrasensitive detection of viruses, including hepatitis E virus (HEV), HEV-like particles (HEV-LPs), and SARS-CoV-2 spike protein in complex lysate solution. The photocurrent response output of a CdSe-Co3O4@TiO2 based PEC device is improved compared to the individual components, TiO2 and CdSe-Co3O4. This can be ascribed to forming a heterojunction structure obtained by the hybridization of TiO2 and CdSe-Co3O4. CdSe QDs sensitization effect and strong visible light absorption can extend interfacial carrier lifetime and enhance energy conversion efficiency coupling with a robust oxygen-evolving catalyst (Co3O4) at the hole trapping site (CdSe) to improve overall system stability. The developed PEC-based biosensing device has been effectively used for quantitative virus detection through effective hybridization among antibody and viral specimens. The effective capture of the virus resulted in a linear relationship of change in photocurrent output versus the HEV concentration ranging from 10 fg mL–1 to 100 ng mL–1 with a detection limit of 3.5 fg mL–1. This CdSe-Co3O4@TiO2-based PEC device shows a significant ability to develop an improved device with affordable and portable biosensing capabilities. Moreover, this visible-light-driven device achieved high sensitivity, good specificity, and acceptable stability and further provided an efficient method for sensitive detection of other target viruses.

Based on the big data of the Baidu index, this paper collected the search preferences of social groups in different provinces and regions, ranging from the initial stage of the outbreak to the official naming period, to measure the tendencies of social stigma of the disease source area. It then investigated its spatial homogeneity and heterogeneity; the interaction between its natural attenuation process and the intervention of external social effects over time; and the influence on these tendencies by the media. In regression analysis, it is found that the population density, economic development level, and the years of education per capita significantly increased the tendency to discriminate toward local disease source areas in the initial stage of the outbreak. In contrast, the CPI and registered unemployment rate relevant to the area; the internet penetration rate in relation to the effect of the media; and the volume of new government media are conducive to reducing the tendency toward social stigma among local people. The effect of GDP on the local public's social stigma is influenced by the local internet penetration rate, which can reduce the level of economic development and results in the increase of social stigma. However, through the analysis of the panel data from the latter half of the process, the official opinion persuasion has a positive impact on reducing the tendency toward social stigma. At the same time, its impact is affected by the mean value of the local government’s new media. When the government starts to channel public opinion, the volume of a local government’s new media plays a significant positive role in the decline of stigma.

Electrostatic intermolecular interactions are important in many aspects of biology. We have studied the main electrostatic features involved in the interaction of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein with the human receptor Angiotensin-converting enzyme 2 (ACE2). As the principal computational tool, we have used the FORTE approach, capable to model proton fluctuations and computing free energies for a very large number of protein-protein systems under different physical-chemical conditions, here focusing on the RBD-ACE2 interactions. Both the wild-type and all critical variants are included in this study. From our large ensemble of extensive simulations, we obtain, as a function of pH, the binding affinities, charges of the proteins, their charge regulation capacities, and their dipole moments. In addition, we have calculated the pKas for all ionizable residues and mapped the electrostatic coupling between them. We are able to present a simple predictor for the RBD-ACE2 binding based on the data obtained for Alpha, Beta, Gamma, Delta, and Omicron variants, as a linear correlation between the total charge of the RBD and the corresponding binding affinity. This “RBD charge rule” should work as a quick test of the degree of severity of the coming SARS-CoV-2 variants in the future. Categories and Subject Descriptors:

The role of epidemiological models is crucial for informing public health officials during a public health emergency, such as the COVID-19 pandemic. However, traditional epidemiological models fail to capture the time-varying effects of mitigation strategies and do not account for under-reporting of active cases, thus introducing bias in the estimation of model parameters. To infer more accurate parameter estimates and to reduce the uncertainty of these estimates, we extend the SIR and SEIR epidemiological models with two time-varying parameters that capture the transmission rate and the rate at which active cases are reported to health officials. Using two real data sets of COVID-19 cases, we perform Bayesian inference via our SIR and SEIR models with time-varying transmission and reporting rates and via their standard counterparts with constant rates; our approach provides parameter estimates with more realistic interpretation, and one-week ahead predictions with reduced uncertainty. Furthermore, we find consistent under-reporting in the number of active cases in the data that we consider, suggesting that the initial phase of the pandemic was more widespread than previously reported.

Neurological effects of COVID-19 and long-COVID-19 as well as neuroinvasion by SARS-CoV-2 still pose several questions and are of both clinical and scientific relevance. We described the cellular and molecular effects of the human brain microvascular endothelial cells (HBMECs) in vitro infection by SARS-CoV-2 to understand the underlying mechanisms of viral transmigration through the Blood-Brain Barrier. Despite the low to non- productive viral replication, SARS-CoV-2-infected cultures displayed increased apoptotic cell death and tight junction protein expression and immunolocalization. Transcriptomic profiling of infected cultures revealed endothelial activation via NF-κB non-canonical pathway, including RELB overexpression, and mitochondrial dysfunction. Additionally, SARS-CoV-2 led to altered secretion of key angiogenic factors and to significant changes in mitochondrial dynamics, with increased mitofusin-2 expression and increased mitochondrial networks. Endothelial activation and remodeling can further contribute to neuroinflammatory processes and lead to further BBB permeability in COVID-19.

Zika virus (ZIKV) infection is a major public health threat, making the study of its biology a matter of great importance. By analyzing the viral-host protein interactions and proposing them as new drug targets, we would diminish the emergence of new resistant strains. In this work, we have shown that human cytoplasmic dynein-1 (Dyn) interacts with the ZIKV. We additionally demonstrate that the envelope protein of the ZIKV and the dimerization domain of the heavy chain of Dyn binds directly without dynactin or cargo adaptor. In addition, we have analyzed this interaction in Vero cells, where we are proposing that the interaction ZIKV-Dyn is finely tuned within the replication cycle. Altogether, our data suggest a new step in the previously described replication cycle of the ZIKV, introducing a suitable molecular target to modulate infection by ZIKV.

Automated information extraction with natural language processing (NLP) tools is required to gain systematic insights from the large number of COVID-19 publications, reports and social media posts, which far exceed human processing capabilities. A key challenge for NLP is the extensive variation in terminology used to describe medical entities, which was especially pronounced for this newly emergent disease. Here we present an NLP toolbox comprising very large English dictionaries of synonyms for SARS-CoV-2 (including variant names) and COVID-19, which can be used with dictionary-based NLP tools. We also present a silver standard corpus generated with the dictionaries, and a gold standard corpus, consisting of PubMed abstracts manually annotated for disease, virus, symptom, protein/gene, cell type, chemical and species terms, which can be used to train and evaluate COVID-19-related NLP tools. Code for annotation, which can be used to expand the silver standard corpus or for text mining is also included. This toolbox is freely available on GitHub (on https://github.com/Aitslab/corona) and zenodo (https://doi.org/10.5281/zenodo.6642275). The toolbox can be used for a variety of text analytics tasks related to the COVID-19 crisis and has already been used to create a COVID-19 knowledge graph, study the variability and evolution of COVID-19-related terminology and develop and benchmark text mining tools.

Background Long COVID-19 symptoms appeared in many COVID-19 survivors. However, the prevalence and symptoms associated with long COVID and its comorbidities have not been established. Methods Between May and September 2020, we included 312 patients with post-COVID-19 from 21 primary care centers if they had any persistent symptoms for at least three months from the first onset of the disease. On the 6 months follow up, their lung function was assessed by CT and spirometry, whereas cardiac function was assessed by electrocardiogram (ECG), Holter ECG, Echocardiography, and 24-hour blood pressure monitoring. A six-minute test (6MWT) was conducted on 308 participants during the follow-up visit. All participants were given a questionnaire with items on demographic information, current complaints, comorbidities, and medications, and Chalder Fatigue Scale (CFS) questionnaire. Statistical analysis was done using R vs. 4.1.2. Two-group comparison of continuous variables was performed using a T-test for normally distributed data, and the Mann-Whitney Wilcoxon test, ANOVA, and Kruskal-Wallis tests were applied for multiple comparisons following with Tukey and Dunn tests as post-hoc methods. Hochberg p-value adjustment was used to reduce the false discovery rate during multiple comparisons. Categorical variables were analyzed with Fisher’s Exact test. Results Of 312 persons investigated, there was no significant gender difference between post-COVID-19 clinical manifestations except for memory dysfunction and anxiety, more prevalent among female participants. Chalder Fatigue Score ≥4 was predominant in female participants (243, 78%). 39 (12.5%) participants reported having type 2 diabetes mellitus, and 158 (50.64%) had hypertension. Among the tested parameters, those positively correlated with comorbid conditions include age, BMI, D-dimers, NT-proBNP, C-reactive protein, neutrophils, fasting glucose, and HbA1c; hypertension also shows three associations that were not found in patients when examining the role of diabetes: increased hemoglobin, fibrinogen, and ferritin. 24-hour blood pressure monitoring revealed significantly higher systolic and diastolic blood pressure, left ventricular hypertrophy, and elevated NT-proBNP in participants with hypertension and subjects with type 2 diabetes. Left ventricular diastolic dysfunction is more frequently present in patients with hypertension. Chest CT was conducted on 227 (72.8%) participants 5.8±0.9 months after the onset of COVID-19. The most common registered CT abnormality was chronic bronchitis (198, 87.2%), followed by fibrotic changes in (83, 36.6%) and mediastinal lymphadenopathy (23, 10.1%). Immunological test results showed that SARS-CoV19 IgG antibodies were present in 241 subjects (77.2%), and SARS-CoV19 IgM antibodies were present in 9 subjects (2.88%). Conclusions Our study provides valuable clues for long-term post-sequelae in a cohort of the Long COVID-19 subjects. We demonstrated a strong association of signs of cardiac dysfunction, lung fibrotic changes, increased hemoglobin, fibrinogen, and ferritin with hypertension but not with other comorbidities. Our results are of importance for understanding the Long Covid-19 syndrome.

ABSTRACT Introduction Arboviruses and malaria are both mosquito-borne diseases, with overlapping symptoms and geographic distribution in tropical settings. However, little information is available on the co-occurrence of arboviruses and malaria in areas highly endemic for malaria in Africa. This study was conducted with the aim to determine the frequency of recent Dengue (DENV), Chikungunya (CHIKV) and Zika (ZIKV) infections and their co-occurrence with malaria in six highly endemic districts for malaria in Mozambique. Methods Blood samples were collected from febrile outpatients between January 2017 and December 2018 and were then tested for Malaria using RDT. Serum samples from these patients were also tested using commercially available ELISA for the presence of IgM antibodies against CHIKV, ZIKV and DENV, as well as NS1 antigen for DENV. Concurrently, a questionnaire was administered to collect socio-demographic characteristics of patients. Results Of the 906 participants enrolled, IgM antibodies against CHIKV, DENV and ZIKV were identified in 134 (14.8%), 64 (7.4%) and 83 (9.2%) individuals, respectively. Malaria was diagnosed in 56 (6.2%) participants, of which 16 (28.6%) were also positive for IgM anti CHIKV, 1 (1.8%) for DENV-NS1, 3 (5.4%) for IgM anti-DENV and 10 (17.8%) for IgM anti-ZIKV. There was a trend towards an increase in the frequency of IgM anti CHIKV positive samples, from 7.0% in 2014 to 14.8% in 2018 and IgM anti-ZIKV positive samples increased from 4.9% in 2015 to 9.2% in 2018. Conclusion This study showed an increased frequency of arbovirus in Mozambique thus far, as well as a frequent occurrence of arbovirus among malaria positive patients. This highlighted the urgency for the establishment of sentinel surveillance sites for arboviruses and the need for an integrated management of febrile illnesses in places where arboviruses and malaria are both prevalent. AUTHOR SUMMARY Arbovirus and malaria share clinical features, which might make the differential diagnosis of acute febrile illnesses significantly difficult, leading to frequent over diagnosis of malaria and under diagnosis of arbovirus in places where both co-occur. In Mozambique and other sub-Saharan countries, epidemiological data on the burden and temporal trend of arbovirus, as well as on co-occurrence with malaria are Chikungunya virus (CHIKV) and Dengue virus (DENV) and its co-occurrence with malaria among 609 febrile patients in six health centres located in five provinces in Mozambique. Recent CHIKV, DENV and ZIKV infection, as measured by presence of IgM antibodies, were found in 14.8%, 7.4% and 9.2% of participants and among 28.6%, 5.4% and 17.8%, of malaria positive patients. These findings suggest that arboviruses are frequent among malaria and non-malaria febrile patients, reinforcing the need for increased awareness of arbovirus in the management of acute febrile illness.

Background: Recognition of viral invasion by innate antiviral immune system triggers activation of the Type I-interferon (IFN-I) and proinflammatory signaling pathways. Subsequently, IFN-I induction regulates expression of a group of genes known as IFN-I-stimulated genes (ISGs) to block viral infection. The Tripartite Ring Interaction Motif 22 (TRIM22) is an ISG with strong antiviral functions. Results: : Here we have shown that the TRIM22 has been strongly upregulated both transcriptionally and translationally upon zika virus (ZIKV) infection. ZIKV infection is associated with a wide range of clinical manifestations in human from mild to severe symptoms including abnormal fetal brain development. We found that the antiviral function of TRIM22 plays a crucial role in counterattacking ZIKV infection. Overexpression of TRIM22 protein inhibited ZIKV growth whereas deletion of TRIM22 in host cells increased ZIKV infectivity. Mechanistically, TRIM22, as a functional E3 ubiquitin ligase, promoted the ubiquitination and degradation of ZIKV nonstructural protein 1 (NS1) and nonstructural protein 3 (NS3). Further studies showed that the SPRY domain and Ring domain of TRIM22 played important roles in protein interaction and degradation, respectively. In addition, we found that TRIM22 also inhibited other flaviviruses infection including dengue virus (DENV) and yellow fever virus (YFV). Conclusion: Thus, TRIM22 is an ISG with critical role in host defense against flaviviruses through binding and degradation of the NS1 and NS3 proteins.

Health-related rumors spreading online during a public crisis may pose a serious threat to people's well-being. Existing crisis informatics research lacks in-depth insights into the characteristics of health rumors and the efforts to debunk them on social media in a pandemic. To fill this gap, we conduct a comprehensive analysis of four months of rumor-related online discussion during COVID-19 on Weibo, a Chinese microblogging site. Results suggest that the dread (cause fear) type of health rumors provoked significantly more discussions and lasted longer than the wish (raise hope) type. We further explore how four kinds of social media users (i.e., government, media, organization, and individual) combat health rumors, and identify their preferred way of sharing debunking information and the key rhetoric strategies used in the process. We examine the relationship between debunking and rumor discussions using a Granger causality approach, and show the efficacy of debunking in suppressing rumor discussions, which is time-sensitive and varies across rumor types and debunkers. Our results can provide insights into crisis informatics and risk management on social media in pandemic settings.

Background: The SARS-CoV-2 (COVID-19) pandemic impacted the health systems between and within countries, and sexual and reproductive health (SRH) services were the most disrupted. Findings from high-income settings have reported significant changes in preterm birth (PTB) prevalence during the pandemic period. Our goal was to assess the PTB rates at the Brazilian national level during the COVID-19 pandemic year 2020 compared to three previous years. Methods: We conducted a population-based cross-sectional study including data from January 2017 to December 2020. We extracted individual-level live birth data from the Brazilian Live Birth Information System (SINASC), which includes all live births from 22 weeks of pregnancy. The main outcome was the PTB rate. We estimated the odds ratio (OR) of PTB using propensity score weighting analysis. In addition to the analysis for the country, we performed a stratified analysis by region. Two-sided p-value of < 1% (0.01) was considered significant. All statistical analysis was conducted using statistical packages in python 3.9 languages. Findings: The prevalence of preterm birth had a higher significant variation within Brazilian regions in 2020 compared to the pre-pandemic period (2017-2019). In Brazil, the OR of preterm births increased by 5.6% (OR: 1.052; 95% CI [1.044; 1.059]). Among the preterm births, the chance of childbirth by caesarean delivery also increased in the pairwise 2019-2020 (OR: 1.121; 95% CI [1.112 - 1.130]). Interpretation: The OR of preterm birth increased during the first year of the COVID-19 pandemic in Brazil. Among the preterm births, the chance of childbirth by caesarean delivery was higher in 2020 than in previous years, suggesting a provider-initiated PTB.Funding: SRH, part of the UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction, a cosponsored programme executed by the World Health Organisation. Funding Information: This work was supported by SRH, part of the UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction, a cosponsored programme executed by the World Health Organisation. Declaration of Interests: The authors declare that they have no conflict of interest. Ethics Approval Statement: This study was part of the REBRACO initiative, and the study protocol was approved by the Institutional Review Board (Letters of Approval numbers 4.047.168).

ABSTRACT We previously identified GADPH as one of the cyclic adenosine diphosphoribose (cADPR)’s binding proteins and found that GADPH participates in cADPR-mediated Ca 2+ release from ER via RyRs. Based on the simulated cADPR-GAPDH complex structure, we performed the structure-based drug screening, identified several small chemicals with high docking scores to cADPR’s binding pocket in GAPDH, and showed that two of these compounds, C244 and C346, are potential cADPR antagonists. We further synthesized several analogs of C346, and found that its analog, G42, also mobilized Ca 2+ release from lysosomes. G42 alkalized lysosomal pH, and inhibited autophagosome-lysosome fusion. Moreover, G42 markedly inhibited Zika virus (ZIKV, a flavivirus) or murine hepatitis virus (MHV, a β-coronavirus) infections of host cells. These results suggest that G42 inhibits virus infection, likely by triggering lysosomal Ca 2+ mobilization and inhibiting autophagy.

While a common symptom of influenza and coronavirus disease 2019 (COVID-19) is fever, its physiological role on host resistance to viral infection remains less clear. Here, we demonstrate that exposure of mice to the high ambient temperature of 36 °C increase host resistance to viral pathogens including influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). High heat-exposed mice increase basal body temperature over 38 °C to enable more bile acids production in a gut microbiota-dependent manner. The gut microbiota-derived deoxycholic acid (DCA) and its plasma membrane-bound receptor Takeda G-protein-coupled receptor 5 (TGR5) signaling increase host resistance to influenza virus infection by suppressing virus replication and neutrophil-dependent tissue damage. Furthermore, the DCA and its nuclear farnesoid X receptor (FXR) agonist protect Syrian hamster from lethal SARS-CoV-2 infection. Moreover, we demonstrate that certain bile acids are reduced in the plasma of COVID-19 patients who developed moderate I/II disease compared with minor illness group. These findings uncover an unexpected mechanism by which virus-induced high fever increases host resistance to influenza virus and SARS-CoV-2 in a gut microbiota-dependent manner.

Cognitive dysfunction is often reported in post-COVID patients, but its underlying mechanisms remain unknown. While some evidence indicate that SARS-CoV-2 can reach and directly impact the brain, others suggest viral neuroinvasion as a rare event. Independently of brain viral infection, the ability of SARS-CoV-2 spike (S) protein to cross the BBB and reach memory-related brain regions has already been shown. Here, we demonstrate that brain infusion of S protein in mice induces late cognitive impairment and increases serum levels of neurofilament light chain (NFL), which recapitulates post-COVID features. Neuroinflammation, hippocampal microgliosis and synapse loss are induced by S protein. Increased engulfment of hippocampal presynaptic terminals late after S protein brain infusion were found to temporally correlate with cognitive deficit in mice. Blockage of TLR4 signaling prevented S-associated detrimental effects on synapse and memory loss. In a cohort of 86 patients recovered from mild COVID-19, genotype GG TLR4 -2604G>A (rs10759931) was associated with poor cognitive outcome. Collectively, these findings indicate that S protein directly impacts the brain and suggest that TLR4 is a potential target to prevent post-COVID cognitive dysfunction. One Sentence Summary TLR4 mediates long-term cognitive impairment in mice and its genetic variant increases the risk of poor cognitive outcome in post-COVID patients.

Physical interactions between viral and host proteins are responsible for almost all aspects of the viral life cycle and the host’s immune response. Studying viral-host protein-protein interactions is thus crucial for identifying strategies for treatment and prevention of viral infection. Here, we use high-throughput yeast two-hybrid and affinity purification followed by mass spectrometry to generate a comprehensive SARS-CoV-2-human protein-protein interactome network consisting of both binary and co-complex interactions. We report a total of 739 high-confidence interactions, showing the highest overlap of interaction partners among published datasets as well as the highest overlap with genes differentially expressed in samples (such as upper airway and bronchial epithelial cells) from patients with SARS-CoV-2 infection. Showcasing the utility of our network, we describe a novel interaction between the viral accessory protein ORF3a and the host zinc finger transcription factor ZNF579 to illustrate a SARS-CoV-2 factor mediating a direct impact on host transcription. Leveraging our interactome, we performed network-based drug screens for over 2,900 FDA-approved/investigational drugs and obtained a curated list of 23 drugs that had significant network proximities to SARS-CoV-2 host factors, one of which, carvedilol, showed promising antiviral properties. We performed electronic health record-based validation using two independent large-scale, longitudinal COVID-19 patient databases and found that carvedilol usage was associated with a significantly lowered probability (17%-20%, P < 0.001) of obtaining a SARS-CoV-2 positive test after adjusting various confounding factors. Carvedilol additionally showed anti-viral activity against SARS-CoV-2 in a human lung epithelial cell line [half maximal effective concentration (EC 50 ) value of 4.1 µM], suggesting a mechanism for its beneficial effect in COVID-19. Our study demonstrates the value of large-scale network systems biology approaches for extracting biological insight from complex biological processes.

SARS-CoV-2 infection causes COVID-19, a severe acute respiratory disease associated with cardiovascular complications including long-term outcomes. The presence of virus in cardiac tissue of patients with COVID-19 suggests this is a direct, rather than secondary, effect of infection. By expressing individual SARS-CoV-2 proteins in the Drosophila heart we demonstrated interaction of virus Nsp6 with host proteins of the MGA/MAX complex (MGA, PCGF6 and TFDP1). Complementing transcriptomic data from the fly heart revealed that this interaction blocks the antagonistic MGA/MAX complex, which shifts the balance towards MYC/MAX and activates glycolysis—with similar findings in mouse cardiomyocytes. Further, the Nsp6-induced glycolysis disrupted cardiac mitochondrial function, known to increase reactive oxygen species (ROS) in heart failure; this could explain COVID-19-associated cardiac pathology. Furthermore, inhibiting the glycolysis pathway by 2-deoxy-D-glucose (2DG) treatment attenuated the Nsp6-induced cardiac phenotype in fly and mice; thus, suggesting glycolysis as a potential pharmacological target for treating COVID-19-associated heart failure.

ABSTRACT A novel uncapped mRNA platform was developed. Five lipid nanoparticle (LNP)-encapsulated mRNA constructs were made to evaluate several aspects of our platform, including transfection efficiency and durability in vitro and in vivo and the activation of humoral and cellular immunity in several animal models. The constructs were eGFP-mRNA-LNP (for enhanced green fluorescence mRNA), Fluc-mRNA-LNP (for firefly luciferase mRNA), S δT -mRNA-LNP (for Delta strain SARS-CoV-2 spike protein trimer mRNA), gD ED -mRNA-LNP (for truncated glycoprotein D mRNA coding ectodomain from herpes simplex virus type 2 (HSV2)) and gD FR -mRNA-LNP (for truncated HSV2 glycoprotein D mRNA coding amino acids 1∼400). Quantifiable target protein expression was achieved in vitro and in vivo with eGFP-and Fluc-mRNA-LNP. S δT -mRNA-LNP, gD ED -mRNA-LNP and gD FR -mRNA-LNP induced both humoral and cellular immune responses comparable to those obtained by previously reported capped mRNA-LNP constructs. Notably, S δT -mRNA-LNP elicited neutralizing antibodies in hamsters against the Omicron and Delta strains. Additionally, gD ED -mRNA-LNP and gD FR -mRNA-LNP induced potent neutralizing antibodies in rabbits and mice. The mRNA constructs with uridine triphosphate (UTP) outperformed those with N1-methylpseudouridine triphosphate (N1mψTP) in the induction of antibodies via S δT -mRNA-LNP. Our uncapped, process-simplified, and economical mRNA platform may have broad utility in vaccines and protein replacement drugs.

In last few decades, several cities have adopted smart growth policies to vibrant and sustainable urban environments, often characterized by high densities, smaller home sizes, and greater access to public transit. However, as we experience successive waves of the COVID pandemic, there is growing concern that in the post-pandemic world, public support for such policies is likely to decrease. This study analyzes data from an online survey conducted in March 2022 in the Seattle metropolitan area to assess the relationship between COVID concern and public support for smart growth policy outcomes. Analysis of the survey data suggests that increased COVID concern is negatively related to public support for higher density, smaller home sizes, and greater access to public transit. Respondents living in single-family homes and those who relied primarily on mass media for COVID information are also less likely to support these policies. These findings are concerning because lack of public support may be force cities on a path of de-densification, and private automobile centered development. To avoid an unsustainable future, it is imperative that cities proactively start to address public health concerns about the relationship between urban built-form and virus transmission.

ABSTRACT Single-cells RNA sequencing (scRNA-seq) is currently one of the most powerful techniques available to study the transcriptional response of cells to external perturbations. However, the use of conventional bulked RNA-seq analysis methods can miss important patterns underlying in the scRNA-seq data. Here, we present a reanalysis of scRNA-seq data from human bronchial epithelial cells and colon and ileum organoids using pseudo-time profiles based on the degree of virus accumulation which reflect the progress of infection. Our analysis revealed a transcriptional response to infection characterized by three distinct up- and down-regulatory phases, that cannot be detected using classical two-group comparisons. Interrogation of results, focused on genes involved in interferon-response, transcription factors and RNA-binding proteins, suggests a highly correlated transcriptional response for most genes. In addition, correlation network analysis revealed a distinct response of genes involved in translation and mitochondrially-encoded genes. Based on our data, we propose a model where modulation of nucleocytoplasmic traffic by the viral protein nsp1 explains the triphasic transcriptional response to SARS-CoV-2 infection.

ABSTRACT The ongoing coronavirus disease 2019 (COVID-19) pandemic has highlighted the need to better understand virus-host interactions. We developed a network-based algorithm that expands the SARS-CoV-2-host protein interaction network and identifies host targets that modulate viral infection. To disrupt the SARS-CoV-2 interactome, we systematically probed for potent compounds that selectively target the identified host proteins with high expression in cells relevant to COVID-19. We experimentally tested seven chemical inhibitors of the identified host proteins for modulation of SARS-CoV-2 infection in human cells that express ACE2 and TMPRSS2. Inhibition of the epigenetic regulators bromodomain-containing protein 4 (BRD4) and histone deacetylase 2 (HDAC2), along with ubiquitin specific peptidase (USP10), enhanced SARS-CoV-2 infection. Such proviral effect was observed upon treatment with compounds JQ1, vorinostat, romidepsin, and spautin-1, when measured by cytopathic effect and validated by viral RNA assays, suggesting that HDAC2, BRD4 and USP10 host proteins have antiviral functions. Mycophenolic acid and merimepodib, two inhibitors of inosine monophosphate dehydrogenase (IMPDH 1 and IMPDH 2), showed modest antiviral effects with no toxicity in mock-infected control cells. The network-based approach enables systematic identification of host-targets that selectively modulate the SARS-CoV-2 interactome, as well as reveal novel chemical tools to probe virus-host interactions that regulate virus infection. Synopsis Viruses exploit host machinery and therefore it is important to understand the virus-host dependencies to gain better insight of the key regulators of viral infection. Using a context-specific SARS-COV-2 PPI network, a computational framework was developed to identify host modulators of viral infection. Chromatin modifying host proteins HDAC2 and BRD4, along with deubiquitinating enzyme USP10, act as antiviral proteins. IMPDH inhibitors mycophenolic acid and merimipodib showed modest antiviral response to SARS-COV-2 infection, and no toxic effects. Cell context specificity is a critical factor when identifying selective modulators of viral infection and potential antiviral therapeutics. Topology-based network models cannot distinguish between host-proteins, the inhibition of which leads to either virus suppressive or enhancing effects.

Zika virus (ZIKV) and dengue virus (DENV) are two closely related flaviviruses with similar symptoms; understanding differences in their molecular impact on the host is therefore of high interest. Viruses interact with the host’s post-translational modifications, inducing changes visible in serum. As modifications are diverse and of low abundance, they typically require additional sample processing which is not feasible for large cohort studies. Therefore, we tested the potential of next-generation proteomics data in its ability to prioritize specific modifications for later targeted analysis. We re-mined published mass spectra from 122 unenriched serum samples from ZIKV and DENV patients for the presence of phosphorylated, methylated, oxidized, glycosylated/glycated, sulfated, and carboxylated peptides. We identified 272 modified peptides with significantly differential abundance in ZIKV and DENV patients. Amongst these, methionine-oxidized peptides from apolipoproteins and glycosylated peptides from immunoglobulin proteins were more abundant in ZIKV patient serum and generate hypotheses on the potential roles of the modification in the infection. The results demonstrate how data-independent acquisition techniques can help prioritize future analyses of peptide modifications.

Cell fusing agent virus (CFAV) is an insect specific flavivirus (ISF) found in field and laboratory populations of Aedes aegypti . ISFs have recently demonstrated the ability to block the transmission of arboviruses such as dengue, West Nile and Zika viruses. It is thought that vertical transmission is the main route for ISF infections. This has been observed with CFAV, but there is evidence of horizontal and venereal transmission in other ISFs. Understanding the route of transmission can inform strategies to spread ISFs to wild vector populations as a method of controlling pathogenic arboviruses. We crossed individually reared male and female mosquitoes from both a naturally occurring CFAV-positive Ae. aegypti colony and its negative counterpart to provide information on maternal, paternal, and horizontal transmission. RT-PCR was used to detect CFAV in individual female mosquito pupal exuviae and was 89% sensitive, but only 41% in male mosquito pupal exuviae. This is a possible way to screen individuals for infection without destroying the adults. Female-to-male horizontal transmission was not observed during this study, however there was a 31% transmission rate from mating pairs of CFAV-positive males to negative female mosquitoes. Maternal vertical transmission was observed with a filial infection rate of 93%. The rate of paternal transmission was 85% when the female remained negative, 61% when the female acquired CFAV horizontally, and 76% overall. Maternal and paternal transmission of CFAV could allow the introduction of this virus into wild Ae. aegypti populations through male or female mosquito releases, and thus provides a potential strategy for ISF-derived arbovirus control.

Since its outbreak the corona virus-19 disease has been particularly aggressive for the lower respiratory tract, and lungs in particular. The dynamics of the abnormal immune response leading to lung damage with fatal outcomes is not yet fully understood. We present a mathematical model describing the dynamics of corona virus disease-19 starting from virus seeding inside the human respiratory tract, taking into account its interaction with the components of the innate immune system as classically and alternatively activated macrophages, interleukin-6 and-10. The numerical simulations have been performed for two different parameter values related to the pro-inflammatory interleukin, searching for a correlation among components dynamics during the early stage of infection, in particular pro-and anti-inflammatory polarizations of the immune response. We found that in the initial stage of infection the immune machinery is unable to stop or weaken the virus progression. Also an abnormal anti-inflammatory interleukin response is predicted, induced by the disease progression and clinically associated to tissue damages. The numerical results well reproduce experimental results found in literature.

The development of antibody therapies against SARS-CoV-2 remains a challenging task during the ongoing COVID-19 pandemic. All approved therapeutic antibodies are directed against the receptor binding domain (RBD) of Spike and lost neutralization efficacy against continuously emerging SARS-CoV-2 variants, which especially mutate in the RBD region. Previously, phage display has been used to identify epitopes of antibody responses against several diseases. Such epitopes have been applied to design vaccines or neutralizing antibodies. Here, we constructed an ORFeome phage display library for the SARS-CoV-2 genome. Open reading frames (ORFs) representing the SARS-CoV-2 genome were displayed on the surface of phage particles in order to identify enriched immunogenic epitopes from COVID-19 patients. Library quality was assessed by both, NGS and epitope mapping of a monoclonal antibody with known binding site. The most prominent epitope captured represented parts of Spike´s fusion peptide (FP). It is associated with the cell entry mechanism of SARS-CoV-2 into the host cell and the serine protease TMPRSS2 cleaves Spike within this sequence. Blocking of this mechanism could be a potential target for non-RBD binding therapeutic anti-SARS-CoV-2 antibodies. As mutations within the FP amino acid sequence were rather rare among SARS-CoV-2 variants so far, this may be an advantage in the fight against future virus variants.