ABSTRACT
Introduction: SARS-CoV-2 is the newest beta coronavirus family member to demonstrate neuroinvasive capability in severe cases of infection. Despite much research activity in the SARS-CoV-2/COVID-19 space, the gene-level biology of this phenomenon remains poorly understood. In the present analysis, we leveraged spatial transcriptomics methodologies to examine relevant gene heterogeneity in tissue retrieved from the human prefrontal cortex. Methods: Expression profiles of genes with established relations to the SARS-CoV-2 neuroinvasion process were spatially resolved in dorsolateral prefrontal cortex tissue (N = 4). Spotplots were generated with mapping to six (6) previously defined gray matter layers. Results: Docking gene BSG, processing gene CTSB, and viral defense gene LY6E demonstrated similar spatial enrichment. Docking gene ACE2 and transmembrane series proteases involved in spike protein processing were lowly expressed across DLPFC samples. Numerous other findings were obtained. Conclusion: Efforts to spatially represent expression levels of key SARS-CoV-2 brain infiltration genes remain paltry to date. Understanding the sobering history of beta coronavirus neuroinvasion represents a weak point in viral research. Here we provide the first efforts to characterize a motley of such genes in the dorsolateral prefrontal cortex.
ABSTRACT
Introduction The emergence and rapid spread of the coronavirus disease 2019 (COVID-19) pandemic have revealed the limitations in current healthcare systems to handle patient records securely and transparently, and novel protocols are required to address these shortcomings. An attractive option is the use of Ethereum smart contracts to secure the storage of medical records and concomitant data logs. Ethereum is an open-source platform that can be used to construct smart contracts, which are collections of code that allow transactions under certain parameters and are self-executable. Methods The present study developed a proof-of-concept smart contract that stores COVID-19 patient data such as the patient identifier (ID), variant, chest CT grade, and significant comorbidities. A sample, fictitious patient data for the purpose of testing was configured to a private network. A smart contract was created in the Ethereum state and tested by measuring the time to insert and query patient data. Results Testing with a private, Proof of Authority (PoA) network required only 191 milliseconds and 890 MB of memory per insertion to insert 50 records while inserting 350 records required 674 milliseconds and similar memory per insertion, as memory per insertion was nearly constant with the increasing number of records inserted. Retrieving required 912 MB for a query involving all three fields and no wildcards in a 350-record database. Only 883 MB was needed to procure a similar observation from a 50-record database. Conclusion This study exemplifies the use of smart contracts for efficient retrieval/insertion of COVID-19 patient data and provides a case use of secure and efficient data logging for sensitive COVID-19 data.
ABSTRACT
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has exhibited different clinical manifestations amongst various age cohorts. As the immune microenvironment may play a role in clinical progression, it is crucial to examine molecular interactions to gain insight into host response. Therefore, to elucidate any differences in host response related to age, the present study imputed ligand-receptor interactions within the nasopharyngeal immune microenvironment in patients affected with SARS-COV-2. Tissue purities, the proportion of non-immune cells in the tissue sample, of 467 nasopharyngeal transcriptome profiles were estimated using known mRNA expression signatures of stromal/immune cells. Using the purity estimates and bulk tissue expression values, non-negative linear regression was used to estimate average expression of each gene in the tissue/stroma compartments. The inferred expression profiles were annotated with a curated database of ligand-receptor interactions and assumed as reasonable proxies for the law of mass action, allowing for quantification of directional ligand-receptor complex concentrations under equilibrium. It was found that older patients (>60 years) exhibited decreased interactions with receptors selectin L receptor SELL and increased interactions with pro-inflammatory chemokine receptors CXCR2 and CCR1. Younger patients showed increased interactions with various members of the TNF receptor super family (TNFRSF). The interactions were further related to immune cell subtypes, with older patients predicted to have less CD8+ and CD4+ resting T cells but increased neutrophil proportions. Collectively, the results suggest certain ligand-receptor interactions of the nasopharyngeal immune microenvironment are age-associated in response to SARS-CoV-2.