Biological Effects of Corticosteroids on Pneumococcal Pneumonia in Mice and Humans (preprint)

Background: Streptococcus pneumoniae is the most common bacterial cause of community acquired pneumonia and the acute respiratory distress syndrome (ARDS). Some clinical trials have demonstrated a beneficial effect of corticosteroid therapy in community acquired pneumonia, COVID-19, and ARDS, but the mechanisms of this benefit remain unclear. The objective of this study was to investigate the effects of corticosteroids on the pulmonary biology of pneumococcal pneumonia in an observational cohort of mechanically ventilated patients and in a mouse model of bacterial pneumonia with Streptococcus pneumoniae. Methods: We studied gene expression with lower respiratory tract transcriptomes from a cohort of mechanically ventilated patients and in mice. We also carried out comprehensive physiologic, biochemical, and histological analyses in mice to identify the mechanisms of lung injury in Streptococcus pneumoniae with and without adjunctive steroid therapy. Results: Transcriptomic analysis identified pleiotropic effects of steroid therapy on the lower respiratory tract in critically ill patients with pneumococcal pneumonia, findings that were reproducible in mice. In mice with pneumonia, dexamethasone in combination with ceftriaxone reduced (1) pulmonary edema formation, (2) alveolar protein permeability, (3) proinflammatory cytokine release, (4) histopathologic lung injury score, and (5) hypoxemia but did not increase bacterial burden. Conclusions: The gene expression studies in patients and in the mice support the clinical relevance of the mouse studies, which replicate several features of pneumococcal pneumonia and steroid therapy in humans. In combination with appropriate antibiotic therapy in mice, treatment of pneumococcal pneumonia with steroid therapy reduced hypoxemia, pulmonary edema, lung permeability, and histologic criteria of lung injury, and also altered inflammatory responses at the protein and gene expression level. The results from these studies provide evidence for the mechanisms that may explain the beneficial effects of glucocorticoid therapy in patients with community acquired pneumonia from Streptococcus Pneumoniae.

Single-cell Masked Autoencoder: An Accurate and Interpretable Automated Immunophenotyper (preprint)

High-throughput single-cell cytometry data are crucial for understanding immune system\'s involvement in diseases and responses to treatment. Traditional methods for annotating cytometry data, specifically manual gating and clustering, face challenges in scalability, robustness, and accuracy. In this study, we propose a single-cell masked autoencoder (scMAE), which offers an automated solution for immunophenotyping tasks including cell type annotation. The scMAE model is designed to uphold user-defined cell type definitions, thereby facilitating easier interpretation and cross-study comparisons. The scMAE model operates on a pre-train and fine-tune approach. In the pre-training phase, scMAE employs Masked Single-cell Modelling (MScM) to learn relationships between protein markers in immune cells solely based on protein expression, without relying on prior information such as cell identity and cell type-specific marker proteins. Subsequently, the pre-trained scMAE is fine-tuned on multiple specialized tasks via task-specific supervised learning. The pre-trained scMAE addresses the shortcomings of manual gating and clustering methods by providing accurate and interpretable predictions. Through validation across multiple cohorts, we demonstrate that scMAE effectively identifies co-occurrence patterns of bound labeled antibodies, delivers accurate and interpretable cellular immunophenotyping, and improves the prediction of subject metadata status. Specifically, we evaluated scMAE for cell type annotation and imputation at the cellular-level and SARS-CoV-2 infection prediction, secondary immune response prediction against COVID-19, and prediction the infection stage in the COVID-19 progression at the subject-level. The introduction of scMAE marks a significant step forward in immunology research, particularly in large-scale and high-throughput human immune profiling. It offers new possibilities for predicting and interpretating cellular-level and subject-level phenotypes in both health and disease.

Hybrid immunity to SARS-CoV-2 arises from serological recall of IgG antibodies distinctly imprinted by infection or vaccination (preprint)

We used plasma IgG proteomics to study the molecular composition and temporal durability of polyclonal IgG antibodies triggered by ancestral SARS-CoV-2 infection, vaccination, or their combination ("hybrid immunity"). Infection, whether primary or post-vaccination, mainly triggered an anti-spike antibody response to the S2 domain, while vaccination predominantly induced anti-RBD antibodies. Immunological imprinting persisted after a secondary (hybrid) exposure, with >60% of the ensuing serological response originating from the initial antibodies generated during the first exposure. We highlight one instance where hybrid immunity arising from breakthrough infection resulted in a marked increase in the breadth and affinity of a highly abundant vaccination-elicited plasma IgG antibody, SC27. With an intrinsic binding affinity surpassing a theoretical maximum (KD < 5 pM), SC27 demonstrated potent neutralization of various SARS-CoV-2 variants and SARS-like zoonotic viruses (IC50 ~0.1-1.75 nM) and provided robust protection in vivo. Cryo-EM structural analysis unveiled that SC27 binds to the RBD class 1/4 epitope, with both VH and VL significantly contributing to the binding interface. These findings suggest that exceptionally broad and potent antibodies can be prevalent in plasma and can largely dictate the nature of serological neutralization.

Plasma-based antigen persistence in the post-acute phase of SARS-CoV-2 infection (preprint)

BACKGROUND: Although RNA viruses like SARS-CoV-2 are generally thought to be transient, the persistence of viral components beyond the acute phase can be driven by a variety of virologic and immunologic factors. Recent studies have suggested that SARS-CoV-2 antigens may persist following COVID-19 but were limited by a lack of comparison to a large number of true negative control samples. METHODS: Using single molecule array (Simoa) assays for SARS-CoV-2 spike, S1, and nucleocapsid antigen in plasma from 171 pandemic-era individuals in the post-acute phase of SARS-CoV-2 infection and 250 pre-pandemic control samples, we compared prevalence of antigen detection. We used logistic regression models and prevalence ratios (PRs) to assess the relationship between demographic and disease factors and antigen persistence. RESULTS: Compared to the proportion of antigen positivity in the pre-pandemic controls (2%), detection of any SARS-CoV-2 antigen was more frequent across all post-acute COVID-19 time bins (3-6 months: 12.6%, p<0.001; 6-10 months, 10.7%, p=0.0002; 10-14 months, 7.5%, p=0.017). These differences were driven by spike protein for up to 14 months and nucleocapsid in the first 6 months after infection. The co-occurrence of multiple antigens at a single timepoint was uncommon. Hospitalization for acute COVID-19 (versus not hospitalized) and worse self-reported health during acute COVID-19 among those not hospitalized (versus more benign illness) were associated with higher prevalence of post-acute antigen detection (PR 1.86, p=0.03; PR 3.5, p=0.07, respectively) in the pandemic era. CONCLUSIONS: Our findings provide strong evidence that SARS-CoV-2 antigens can persist beyond the period of acute illness. The observation that more than 10% of plasma samples for over a year following initial SARS-CoV-2 infection contain detectable viral antigen, which are potentially immunogenic, has significant implications given the sheer number of people infected with SARS-CoV-2 to date. More work will be needed to determine whether these antigens have a causal role in post-acute sequelae of SARS-CoV-2 infection (PASC).

Assessment of Sociodemographic Factors Associated with Time to Self-reported COVID-19 Infection Among a Large Multi-Center Prospective Cohort Population in the Southeastern United States (preprint)

Objective: We aimed to investigate sociodemographic factors associated with self-reported COVID-19 infection. Methods: The study population is a multicenter prospective cohort of adult volunteers recruited from healthcare systems located in the mid-Atlantic and southern United States. Between April 2020 and October 2021 participants completed daily online questionnaires about symptoms, exposures, and risk behaviors related to COVID-19, including self-reports of positive SARS CoV-2 detection tests and COVID-19 vaccination. Analysis of time from study enrollment to self-reported COVID-19 infection used a time-varying mixed effects Cox-proportional hazards framework. Results: Overall, 1,603 of 27,214 study participants (5.9%) reported a positive COVID-19 test during the study period. The adjusted hazard ratio demonstrated lower risk for women, those with a graduate level degree, and smokers. A higher risk was observed for healthcare workers, those aged 18-34, those in rural areas, those from households where a member attends school or interacts with the public, and those who visited a health provider in the last year. Conclusions: Increased risk of self-reported COVID-19 was associated with specific demographic characteristics, which may help to inform targeted interventions for future pandemics.

Transmission bottleneck size estimation from de novo viral genetic variation (preprint)

Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, allele frequencies can change dramatically over the course of an individual's infection, such that sites that are polymorphic in the donor at the time of transmission may not be polymorphic in the donor at the time of sampling and allele frequencies at donor-polymorphic sites may change dramatically over the course of a recipient's infection. Because of this, transmission bottleneck sizes estimated using allele frequencies observed at a donor's polymorphic sites may be considerable underestimates of true bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arose de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these two respiratory viruses, using an approach that does not tend to underestimate transmission bottleneck sizes.

Mucosal and systemic immune dynamics associated with COVID-19 outcomes: a longitudinal prospective clinical study (preprint)

Rationale: COVID-19 severity varies widely; children and African Americans have low and high risk, respectively. Mechanistic data from these groups and the mucosa is lacking. Objectives: To quantify mucosal and systemic viral and immune dynamics in a diverse cohort to identify mechanisms underpinning COVID-19 severity and outcome predictors. Methods: In this prospective study of unvaccinated children and adults COVID-19 outcome was based on an ordinal clinical severity scale. We quantified viral RNA, antigens, antibodies, and cytokines by PCR, ELISA, and Luminex from 579 longitudinally collected blood and nasal specimens from 78 subjects including 45 women and used modeling to determine functional relationships between these data. Measurements and Main Results: COVID-19 induced unique immune responses in African Americans (n=26) and children (n=20). Mild outcome was associated with more effective coordinated responses whereas moderate and severe outcomes had rapid seroconversion, significantly higher antigen, mucosal sCD40L, MCP-3, MCP-1, MIP-1, and MIP-1{beta}, and systemic IgA, IgM, IL-6, IL-8, IL-10, IL-15, IL-1RA, and IP-10, and uncoordinated early immune responses that went unresolved. Mucosal IL-8, IL-1{beta}, and IFN-{gamma} with systemic IL-1RA and IgA predicted COVID-19 outcomes. Conclusions: We present novel mucosal data, biomarkers, and therapeutic targets from a diverse cohort. Based on our findings, children and African Americans with COVID-19 have significantly lower IL-6 and IL-17 levels which may reduce responsiveness to drugs targeting IL-6 and IL-17. Unregulated immune responses persisted indicating moderate to severe COVID-19 cases may require prolonged treatments. Reliance on slower acting adaptive responses may cause immune crisis for some adults who encounter a novel virus.

COVID-19 mitigation behaviors and policies limited SARS-CoV-2 transmission in the United States from September 2020 through November 2021 (preprint)

United States jurisdictions implemented varied policies to slow SARS-CoV-2 transmission. Understanding patterns of these policies alongside individuals behaviors can inform effective outbreak response. To do so, we estimated the time-varying reproduction number (Rt), a weekly measure of real-time transmission using US COVID-19 cases from September 2020-November 2021. We then assessed the association between Rt and policies, personal COVID-19 mitigation behaviors, variants, immunity, and social vulnerability indicators using two multi-level regression models. First, we fit a model with state-level policy stringency according to the Oxford Stringency Index, a composite indicator reflecting the strictness of COVID-19 policies and strength of pandemic-related communication. Our second model included a subset of specific policies. We found that personal mitigation behaviors and vaccination were more strongly associated with decreased transmission than policies. Importantly, transmission was reduced not by a single measure, but by various layered measures. These results underscore the need for policy, behavior change, and risk communication integration to reduce virus transmission during epidemics.

Informing pandemic response in the face of uncertainty. An evaluation of the U.S. COVID-19 Scenario Modeling Hub (preprint)

Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make 6-month ahead projections of the number of SARS-CoV-2 cases, hospitalizations and deaths. The SMH released nearly 1.8 million national and state-level projections between February 2021 and November 2022. SMH performance varied widely as a function of both scenario validity and model calibration. Scenario assumptions were periodically invalidated by the arrival of unanticipated SARS-CoV-2 variants, but SMH still provided projections on average 22 weeks before changes in assumptions (such as virus transmissibility) invalidated scenarios and their corresponding projections. During these periods, before emergence of a novel variant, a linear opinion pool ensemble of contributed models was consistently more reliable than any single model, and projection interval coverage was near target levels for the most plausible scenarios (e.g., 79% coverage for 95% projection interval). SMH projections were used operationally to guide planning and policy at different stages of the pandemic, illustrating the value of the hub approach for long-term scenario projections.

Viral modernity? Epidemics, infodemics, and the ‘bioinformational' paradigm

Viral modernity is a concept based upon the nature of viruses, the ancient and critical role they play in evolution and culture, and the basic application to understanding the role of information and forms of bioinformation in the social world. The concept draws a close association between viral biology on the one hand, and information science on the other – it is an illustration and prime example of bioinformationalism that brings together two of the most powerful forces that now drive cultural evolution. The concept of viral modernity applies to viral technologies, codes and ecosystems in information, publishing, education and emerging knowledge (journal) systems. This paper traces the relationship between epidemics, quarantine, and public health management and outlines elements of viral-digital philosophy (VDP) based on the fusion of living and technological systems. We discuss Covid-19 as a ‘bioinformationalist' response that represents historically unprecedented level of sharing information from the sequencing of the genome to testing for a vaccination. Finally, we look at the US response to Covid-19 through the lens of infodemics and post-truth. The paper is followed by three open reviews, which further refine its conclusions as they relate to (educational) philosophy and the notion of the virus as Pharmakon.

Philosophy of education in a new key: Who remembers Greta Thunberg? Education and environment after the coronavirus

This paper explores relationships between environment and education after the Covid-19 pandemic through the lens of philosophy of education in a new key developed by Michael Peters and the Philosophy of Education Society of Australasia (PESA). The paper is collectively written by 15 authors who responded to the question: Who remembers Greta Thunberg? Their answers are classified into four main themes and corresponding sections. The first section, ‘As we bake the earth, let's try and bake it from scratch', gathers wider philosophical considerations about the intersection between environment, education, and the pandemic. The second section, ‘Bump in the road or a catalyst for structural change?', looks more closely into issues pertaining to education. The third section, ‘If you choose to fail us, we will never forgive you', focuses to Greta Thunberg's messages and their responses. The last section, ‘Towards a new (educational) normal', explores future scenarios and develops recommendations for critical emancipatory action. The concluding part brings these insights together, showing that resulting synergy between the answers offers much more then the sum of articles' parts. With its ethos of collectivity, interconnectedness, and solidarity, philosophy of education in a new key is a crucial tool for development of post-pandemic (philosophy of) education.

A culturally tailored personaliseD nutrition intErvention in South ASIan women at risk of Gestational Diabetes Mellitus (DESI-GDM): a randomised controlled trial protocol.

INTRODUCTION: South Asians are more likely to develop gestational diabetes mellitus (GDM) than white Europeans. Diet and lifestyle modifications may prevent GDM and reduce undesirable outcomes in both the mother and offspring. Our study seeks to evaluate the effectiveness and participant acceptability of a culturally tailored, personalised nutrition intervention on the glucose area under the curve (AUC) after a 2-hour 75 g oral glucose tolerance test (OGTT) in pregnant women of South Asian ancestry with GDM risk factors. METHODS AND ANALYSIS: A total of 190 South Asian pregnant women with at least 2 of the following GDM risk factors-prepregnancy body mass index>23, age>29, poor-quality diet, family history of type 2 diabetes in a first-degree relative or GDM in a previous pregnancy will be enrolled during gestational weeks 12-18, and randomly assigned in a 1:1 ratio to: (1) usual care, plus weekly text messages to encourage walking and paper handouts or (2) a personalised nutrition plan developed and delivered by a culturally congruent dietitian and health coach; and FitBit to track steps. The intervention lasts 6-16 weeks, depending on week of recruitment. The primary outcome is the glucose AUC from a three-sample 75 g OGTT 24-28 weeks' gestation. The secondary outcome is GDM diagnosis, based on Born-in-Bradford criteria (fasting glucose>5.2 mmol/L or 2 hours post load>7.2 mmol/L). ETHICS AND DISSEMINATION: The study has been approved by the Hamilton Integrated Research Ethics Board (HiREB #10942). Findings will be disseminated among academics and policy-makers through scientific publications along with community-orientated strategies. TRIAL REGISTRATION NUMBER: NCT03607799.

Repurposing Metformin for Vascular Disease.

Metformin has seen use as an oral anti-hyperglycaemic drug since the late 1950s; however, following the release in 1998 of the findings of the 20-year United Kingdom Prospective Diabetes Study (UKPDS) metformin use rapidly increased and today is the first-choice anti-hyperglycaemic drug for patients with type 2 diabetes (T2D). Metformin is in daily use by an estimated 150 million people worldwide. Historically, the benefits of metformin as an anti-diabetic and cardiovascular-protective drug have been linked to effects in the liver, where it acts to inhibit gluconeogenesis and lipogenesis, as well as reducing insulin resistance and enhancing peripheral glucose utilization. However, direct protective effects on the endothelium and effects in the gut prior to metformin absorption are now recognized as being important. In the gut, metformin modulates the glucagon-like peptide-1 (GLP-1)- gut-brain axis as well as impacting the intestinal microbiota. As the apparent number of putative tissue and cellular targets for metformin has increased, so has interest in re-purposing metformin to treat other diseases that include polycystic ovary syndrome (PCOS), cancer, neurodegenerative diseases and COVID-19. Metformin is also being investigated as an anti-ageing drug. Of particular interest is whether metformin provides the same level of vascular protection in individuals other than those with T2D, including obese individuals with metabolic syndrome, or in the setting of vascular thromboinflammation caused by SARS-CoV-2. In this review we critically evaluate the literature to highlight clinical settings in which metformin might be therapeutically repurposed for the prevention and treatment of vascular disease.

Acute febrile illness in a teenage female with history of Graves' disease.

Thyroid storm is a rare, life-threatening condition that is usually precipitated by Graves' disease in children and adolescents. COVID-19 (SARS-CoV-2) can cause multisystem inflammatory syndrome in children (MIS C), which shares some features of Graves' disease. We present a case of acute thyroid storm following SARS-CoV-2 infection in a 16-year-old female with poorly controlled Graves' disease. She initially presented to the emergency department for fever and palpitations. Initial laboratory results suggested thyroid storm, for which she was started on propranolol. She remained tachycardic with new gallop rhythm on exam. An echocardiogram demonstrated a depressed left ventricular ejection fraction and mild pulmonary hypertension. Her SARS-CoV-2 antibodies were positive. She was started on intravenous immunoglobulin for suspected MIS-C. She responded to combined treatment of thyroid storm and MIS-C. She was discharged home on propranolol, methimazole, cholestyramine and aspirin.