Mucosal correlates of protection after influenza viral challenge of vaccinated and unvaccinated healthy volunteers.

The induction of systemic antibody titers against hemagglutinin has long been the main focus of influenza vaccination strategies, but mucosal immunity has also been shown to play a key role in the protection against respiratory viruses. By vaccinating and challenging healthy volunteers, we demonstrated that inactivated influenza vaccine (IIV) modestly reduced the rate of influenza while predominantly boosting serum antibody titers against hemagglutinin (HA) and HA stalk, a consequence of the low neuraminidase (NA) content of IIV and the intramuscular route of administration. The viral challenge induced nasal and serum responses against both HA and NA. Correlations between mucosal IgA and serum IgG against specific antigens were low, whether before or after challenge, suggesting a compartmentalization of immune responses. Even so, volunteers who developed viral shedding for multiple days had lower baseline titers across both systemic and mucosal compartments as compared to those with no shedding or a single day of shedding. Regression analysis showed that pre-challenge HA inhibition titers were the most consistent correlate of protection across clinical outcomes combining shedding and symptoms, with NA inhibition titers and HA IgG levels only predicting the duration of shedding. Despite the inclusion of data from multiple binding and functional antibody assays against HA and NA performed on both serum and nasal samples, multivariate models were unable to account for the variability in outcomes, emphasizing our imperfect understanding of immune correlates in influenza and the importance of refining models with assessments of innate and cellular immune responses.IMPORTANCEThe devastating potential of influenza has been well known for over 100 years. Despite the development of vaccines since the middle of the 20th century, influenza continues to be responsible for substantial global morbidity and mortality. To develop next-generation vaccines with enhanced effectiveness, we must synthesize our understanding of the complex immune mechanisms culminating in protection. Our study outlines the differences in immune responses to influenza vaccine and influenza infection, identifying potential gaps in vaccine-induced immunity, particularly at the level of the nasal mucosa. Furthermore, this research underscores the need to refine our imperfect models while recognizing potential pitfalls in past and future attempts to identify and measure correlates of protection.

Dynamics of SARS-CoV-2 Seroprevalence in a Large US population Over a Period of 12 Months.

Due to a combination of asymptomatic or undiagnosed infections, the proportion of the United States population infected with SARS-CoV-2 was unclear from the beginning of the pandemic. We previously established a platform to screen for SARS-CoV-2 positivity across a representative proportion of the US population, from which we reported that almost 17 million Americans were estimated to have had undocumented infections in the Spring of 2020. Since then, vaccine rollout and prevalence of different SARS-CoV-2 variants have further altered seropositivity trends within the United States population. To explore the longitudinal impacts of the pandemic and vaccine responses on seropositivity, we re-enrolled participants from our baseline study in a 6- and 12- month follow-up study to develop a longitudinal antibody profile capable of representing seropositivity within the United States during a critical period just prior to and during the initiation of vaccine rollout. Initial measurements showed that, since July 2020, seropositivity elevated within this population from 4.8% at baseline to 36.2% and 89.3% at 6 and 12 months, respectively. We also evaluated nucleocapsid seropositivity and compared to spike seropositivity to identify trends in infection versus vaccination relative to baseline. These data serve as a window into a critical timeframe within the COVID-19 pandemic response and serve as a resource that could be used in subsequent respiratory illness outbreaks.

Undiagnosed SARS-CoV-2 seropositivity during the first 6 months of the COVID-19 pandemic in the United States.

Asymptomatic SARS-CoV-2 infection and delayed implementation of diagnostics have led to poorly defined viral prevalence rates in the United States and elsewhere. To address this, we analyzed seropositivity in 9089 adults in the United States who had not been diagnosed previously with COVID-19. Individuals with characteristics that reflected the U.S. population (n = 27,716) were selected by quota sampling from 462,949 volunteers. Enrolled participants (n = 11,382) provided medical, geographic, demographic, and socioeconomic information and dried blood samples. Survey questions coincident with the Behavioral Risk Factor Surveillance System survey, a large probability-based national survey, were used to adjust for selection bias. Most blood samples (88.7%) were collected between 10 May and 31 July 2020 and were processed using ELISA to measure seropositivity (IgG and IgM antibodies against SARS-CoV-2 spike protein and the spike protein receptor binding domain). The overall weighted undiagnosed seropositivity estimate was 4.6% (95% CI, 2.6 to 6.5%), with race, age, sex, ethnicity, and urban/rural subgroup estimates ranging from 1.1% to 14.2%. The highest seropositivity estimates were in African American participants; younger, female, and Hispanic participants; and residents of urban centers. These data indicate that there were 4.8 undiagnosed SARS-CoV-2 infections for every diagnosed case of COVID-19, and an estimated 16.8 million infections were undiagnosed by mid-July 2020 in the United States.

Mapping a Pandemic: SARS-CoV-2 Seropositivity in the United States.

Asymptomatic SARS-CoV-2 infection and delayed implementation of diagnostics have led to poorly defined viral prevalence rates. To address this, we analyzed seropositivity in US adults who have not previously been diagnosed with COVID-19. Individuals with characteristics that reflect the US population (n = 11,382) and who had not previously been diagnosed with COVID-19 were selected by quota sampling from 241,424 volunteers (ClinicalTrials.gov NCT04334954). Enrolled participants provided medical, geographic, demographic, and socioeconomic information and 9,028 blood samples. The majority (88.7%) of samples were collected between May 10th and July 31st, 2020. Samples were analyzed via ELISA for anti-Spike and anti-RBD antibodies. Estimation of seroprevalence was performed by using a weighted analysis to reflect the US population. We detected an undiagnosed seropositivity rate of 4.6% (95% CI: 2.6 - 6.5%). There was distinct regional variability, with heightened seropositivity in locations of early outbreaks. Subgroup analysis demonstrated that the highest estimated undiagnosed seropositivity within groups was detected in younger participants (ages 18-45, 5.9%), females (5.5%), Black/African American (14.2%), Hispanic (6.1%), and Urban residents (5.3%), and lower undiagnosed seropositivity in those with chronic diseases. During the first wave of infection over the spring/summer of 2020 an estimate of 4.6% of adults had a prior undiagnosed SARS-CoV-2 infection. These data indicate that there were 4.8 (95% CI: 2.8-6.8) undiagnosed cases for every diagnosed case of COVID-19 during this same time period in the United States, and an estimated 16.8 million undiagnosed cases by mid-July 2020.

Randomized controlled trial of insulin supplementation for correction of bedtime hyperglycemia in hospitalized patients with type 2 diabetes.

OBJECTIVE: Clinical guidelines recommend point-of-care glucose testing and the use of supplemental doses of rapid-acting insulin before meals and at bedtime for correction of hyperglycemia. The efficacy and safety of this recommendation, however, have not been tested in the hospital setting. RESEARCH DESIGN AND METHODS: In this open-label, randomized controlled trial, 206 general medicine and surgery patients with type 2 diabetes treated with a basal-bolus regimen were randomized to receive either supplemental insulin (n = 106) at bedtime for blood glucose (BG) >7.8 mmol/L or no supplemental insulin (n = 100) except for BG >19.4 mmol/L. Point-of-care testing was performed before meals, at bedtime, and at 3:00 a.m. The primary outcome was the difference in fasting BG. In addition to the intention-to-treat analysis, an as-treated analysis was performed where the primary outcome was analyzed for only the bedtime BG levels between 7.8 and 19.4 mmol/L. RESULTS: There were no differences in mean fasting BG for the intention-to-treat (8.8 ± 2.4 vs. 8.6 ± 2.2 mmol/L, P = 0.76) and as-treated (8.9 ± 2.4 vs. 8.8 ± 2.4 mmol/L, P = 0.92) analyses. Only 66% of patients in the supplement and 8% in the no supplement groups received bedtime supplemental insulin. Hypoglycemia (BG <3.9 mmol/L) did not differ between groups for either the intention-to-treat (30% vs. 26%, P = 0.50) or the as-treated (4% vs. 8%, P = 0.37) analysis. CONCLUSIONS: The use of insulin supplements for correction of bedtime hyperglycemia was not associated with an improvement in glycemic control. We conclude that routine use of bedtime insulin supplementation is not indicated for management of inpatients with type 2 diabetes.

A new golden age: testing general relativity with cosmology.

Gravity drives the evolution of the Universe and is at the heart of its complexity. Einstein's field equations can be used to work out the detailed dynamics of space and time and to calculate the emergence of large-scale structure in the distribution of galaxies and radiation. Over the past few years, it has become clear that cosmological observations can be used not only to constrain different world models within the context of Einstein gravity but also to constrain the theory of gravity itself. In this article, we look at different aspects of this new field in which cosmology is used to test theories of gravity with a wide range of observations.

Constraints on gravity on cosmic scales with upcoming large-scale structure surveys.

We consider how upcoming, prospective large-scale structure surveys, measuring galaxy weak lensing and position in tandem with the cosmic microwave background temperature anisotropies, constrain cosmic scale modifications to general relativity. In such theories, both the homogeneous expansion history and the growth of large-scale structure can have signatures of the modification. We consider an equation of state figure of merit parameter, and introduce an analogous figure of merit parameter for modified gravity, to quantify the relative constraints. We discuss how assumptions about the presence of astrophysical and instrumental systematics such as galaxy bias, intrinsic alignments, weak lensing shear calibration uncertainties and photometric redshift offsets can impact the prospective dark energy constraints.

Probing gravity at cosmological scales by measurements which test the relationship between gravitational lensing and matter overdensity.

The standard cosmology is based on general relativity (GR) and includes dark matter and dark energy and predicts a fixed relationship between the gravitational potentials responsible for gravitational lensing and the matter overdensity. Alternative theories of gravity often make different predictions. We propose a set of measurements which can test this relationship, thereby distinguishing between dark energy or matter models and models in which gravity differs from GR. Planned surveys will be able to measure E(G), an observational quantity whose expectation value is equal to the ratio of the Laplacian of the Newtonian potentials to the peculiar velocity divergence, to percent accuracy. This will easily separate alternatives such as the cold dark matter model with a cosmological constant, Dvali-Gabadadze-Porrati, TeVeS, and f(R) gravity.