Altered COVID-19 immunity in children with asthma by atopic status

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes a spectrum of clinical outcomes that may be complicated by severe asthma. Antiviral immunity is often compromised in patients with asthma; however, whether this is true for SARS-CoV-2 immunity and children is unknown.

Objective

We aimed to evaluate SARS-CoV-2 immunity in children with asthma on the basis of infection or vaccination history and compared to respiratory syncytial viral or allergen (eg, cockroach, dust mite)-specific immunity.

Methods

Fifty-three children from an urban asthma study were evaluated for medical history, lung function, and virus- or allergen-specific immunity using antibody or T-cell assays.

Results

Polyclonal antibody responses to spike were observed in most children from infection and/or vaccination history. Children with atopic asthma or high allergen-specific IgE, particularly to dust mites, exhibited reduced seroconversion, antibody magnitude, and SARS-CoV-2 virus neutralization after SARS-CoV-2 infection or vaccination. TH1 responses to SARS-CoV-2 and respiratory syncytial virus correlated with antigen-respective IgG. Cockroach-specific T-cell activation as well as IL-17A and IL-21 cytokines negatively correlated with SARS-CoV-2 antibodies and effector functions, distinct from total and dust mite IgE. Allergen-specific IgE and lack of vaccination were associated with recent health care utilization. Reduced lung function (forced expiratory volume in 1 second ≤ 80%) was independently associated with (SARS-CoV-2) peptide-induced cytokines, including IL-31, whereas poor asthma control was associated with cockroach-specific cytokine responses.

Conclusion

Mechanisms underpinning atopic and nonatopic asthma may complicate the development of memory to SARS-CoV-2 infection or vaccination and lead to a higher risk of repeated infection in these children.

Passive antibody transfer from pregnant women to their fetus are maximized after SARS-CoV-2 vaccination irrespective of prior infection

Background

Pregnancy is associated with a higher risk of adverse symptoms and outcomes for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection for both mother and neonate. Antibodies can provide protection against SARS-CoV-2 infection and are induced in pregnant women after vaccination or infection. Passive transfer of these antibodies from mother to fetus in utero may provide protection to the neonate against infection. However, it is unclear whether the magnitude or quality and kinetics of maternally derived fetal antibodies differs in the context of maternal infection or vaccination.

Objective

We aimed to determine whether antibodies transferred from maternal to fetus differed in quality or quantity between infection- or vaccination-induced humoral immune responses.

Methods

We evaluated 93 paired maternal and neonatal umbilical cord blood plasma samples collected between October 2020 and February 2022 from a birth cohort of pregnant women from New Orleans, Louisiana, with histories of SARS-CoV-2 infection and/or vaccination. Plasma was profiled for the levels of spike-specific antibodies and induction of antiviral humoral immune functions, including neutralization and Fc-mediated innate immune effector functions. Responses were compared between 4 groups according to maternal infection and vaccination.

Results

We found that SARS-CoV-2 vaccination or infection during pregnancy increased the levels of antiviral antibodies compared to naive subjects. Vaccinated mothers and cord samples had the highest anti-spike antibody levels and antiviral function independent of the time of vaccination during pregnancy.

Conclusions

These results show that the most effective passive transfer of functional antibodies against SARS-CoV-2 in utero is achieved through vaccination, highlighting the importance of vaccination in pregnant women.

Route and antigen shape immunity to dmLT-adjuvanted vaccines to a greater extent than biochemical stress or formulation excipients

A key aspect to vaccine efficacy is formulation stability. Biochemical evaluations provide information on optimal compositions or thermal stability but are routinely validated by ex vivo analysis and not efficacy in animal models. Here we assessed formulations identified to improve or reduce stability of the mucosal adjuvant dmLT being investigated in polio and enterotoxigenic E. coli (ETEC) clinical vaccines. We observed biochemical changes to dmLT protein with formulation or thermal stress, including aggregation or subunit dissociation or alternatively resistance against these changes with specific buffer compositions. However, upon injection or mucosal vaccination with ETEC fimbriae adhesin proteins or inactivated polio virus, experimental findings indicated immunization route and co-administered antigen impacted vaccine immunogenicity more so than dmLT formulation stability (or instability). These results indicate the importance of both biochemical and vaccine-derived immunity assessment in formulation optimization. In addition, these studies have implications for use of dmLT in clinical settings and for delivery in resource poor settings.

SARS-CoV-2 seroprevalence rates of children seeking medical care in Louisiana during the state stay at home order

Serologic testing of residual blood samples from 812 children from a hospital in New Orleans, LA, between March and May 2020, demonstrated a SARS-CoV-2 seroprevalence of 6.8% based on S and N protein IgG; Black and Hispanic children, and children living in zip codes with lower household incomes were over-represented.

Fentanyl conjugate vaccine by injected or mucosal delivery with dmLT or LTA1 adjuvants implicates IgA in protection from drug challenge

Fentanyl is a major contributor to the devastating increase in overdose deaths from substance use disorders (SUD). A vaccine targeting fentanyl could be a powerful immunotherapeutic. Here, we evaluated adjuvant and delivery strategies for conjugate antigen vaccination with fentanyl-based haptens. We tested adjuvants derived from the heat-labile toxin of E. coli including dmLT and LTA1 by intramuscular, sublingual or intranasal delivery. Our results show anti-fentanyl serum antibodies and antibody secreting cells in the bone-marrow after vaccination with highest levels observed with an adjuvant (alum, dmLT, or LTA1). Vaccine adjuvanted with LTA1 or dmLT elicited the highest levels of anti-fentanyl antibodies, whereas alum achieved highest levels against the carrier protein. Vaccination with sublingual dmLT or intranasal LTA1 provided the most robust blockade of fentanyl-induced analgesia and CNS penetration correlating strongly to anti-FEN IgA. In conclusion, this study demonstrates dmLT or LTA1 adjuvant as well as mucosal delivery may be attractive strategies for improving the efficacy of vaccines against SUD.

Predicting dairy cattle heat stress using machine learning techniques

The objectives of the study were to use a heat stress scoring system to evaluate the severity of heat stress on dairy cows using different heat abatement techniques. The scoring system ranged from 1 to 4, where 1 = no heat stress; 2 = mild heat stress; 3 = severe heat stress; and 4 = moribund. The accuracy of the scoring system was then predicted using 3 machine learning techniques: logistic regression, Gaussian naïve Bayes, and random forest. To predict the accuracy of the scoring system, these techniques used factors including temperature-humidity index, respiration rate, lying time, lying bouts, total steps, drooling, open-mouth breathing, panting, location in shade or sprinklers, somatic cell score, reticulorumen temperature, hygiene body condition score, milk yield, and milk fat and protein percent. Three different treatments, namely, portable shade structure, portable polyvinyl chloride pipe sprinkler system, or control with no heat abatement, were considered, where each treatment was replicated 3 times with 3 second-trimester lactating cows. Results indicate that random forest outperformed the other 2 methods, with respect to both accuracy and precision, in predicting the sprinkler group's score. Both logistic regression and random forest were consistent in predicting scores for control, shade, and combined groups. The mean probability of predicting non-heat-stressed cows was highest for cows in the sprinkler group. Finally, the logistic regression method worked best for predicting heat-stressed cows in control, shade, and combined. The insights gained from these results could aid dairy producers to detect heat stress before it becomes severe, which could decrease the negative effects of heat stress, such as milk loss.

Graduate Student Literature Review: Heat abatement strategies used to reduce negative effects of heat stress in dairy cows

The southeastern United States experiences an extended hot season with a high environmental temperature and relative humidity. With increasing global temperatures, managing dairy cattle in regions with tropical, subtropical, and Mediterranean climates is becoming an increasing challenge. Heat-stressed cows will decrease feed intake, decrease productivity, and increase respiration rate in an attempt to maintain internal body temperature. Temperature-humidity index (THI) is a unitless value that has been used to measure the magnitude of heat stress on dairy cows. Many researchers have studied the THI threshold at which dairy cattle begin to experience heat stress. When housing cows in a confinement setting, a pasture-based setting, or a combination of the two, the appropriate heat abatement should be implemented to allow cows to perform to their potential and to improve overall animal welfare. This review summarizes heat abatement strategies that have been studied to reduce the negative effects of heat stress.

Invited review: Physiological and behavioral effects of heat stress in dairy cows

Animal welfare can be negatively affected when dairy cattle experience heat stress. Managing heat stress has become more of a challenge than ever before, due to the increasing number of production animals with increased milk yield, and therefore greater metabolic activity. Environmental temperatures have increased by 1.0°C since the 1800s and are expected to continue to increase by another 1.5°C between 2030 and 2052. Heat stress affects production, reproduction, nutrition, health, and welfare. Means exist to monitor and evaluate heat stress in dairy cattle, as well as different ways to abate heat, all with varying levels of effectiveness. This paper is a summary and compilation of information on dairy cattle heat stress over the years.

Comparing dairy farm milk yield and components, somatic cell score, and reproductive performance among United States regions using summer to winter ratios

Heat stress abatement is a challenge for dairy producers in the United States, especially in the southern states. Thus, managing heat stress is critical to maintain dairy cow performance in the summer. The ability to employ a metric to measure heat stress and evaluate abatement strategies may benefit dairy producers by providing meaningful feedback on the effectiveness of current and future management strategies with the goal of improving heat stress management. Therefore, this study aimed to explore the use of the summer to winter performance ratio metric to quantify and compare farm performance variables among regions of the United States. Monthly performance data recorded by the Dairy Herd Improvement Association from 2007 to 2016, for all US Dairy Herd Improvement Association herds processing records through Dairy Records Management Systems (Raleigh, NC), were obtained. Season dates were based on the astronomical definition of the Northern Hemisphere with summer as June 21 to September 21 and winter as December 21 to March 19. States were grouped into regions based on climate zone classification. Performance records included a total of 16,573 herds [Northeast (n = 7,955), Midwest (n = 6,555), Northern Plains (n = 305), Southeast (n = 1,370), and Southern Plains (n = 388) regions]. Herd test day performance variables energy-corrected milk, somatic cell score, milk fat and protein percentage, conception rate, heat detection rate, and pregnancy rate in summer and winter were used to calculate summer to winter ratios for each region. The MIXED procedure of SAS 9.4 (SAS Institute Inc., Cary, NC) was used to compare test day performance variables. The effects of year, mean days in milk, mean 150-d milk, mean herd size, and number of milkings per day were included as covariates in the models. Dairy cattle performance in all climate regions was negatively affected by summer heat stress, but some regions greater than others. A difference was also observed among regions when comparing summer to winter ratios for each performance parameter. This indicates that summer performance varies by climate region identified by the summer to winter ratio and demonstrates usefulness of the metric to monitor degree of heat stress based on performance.

Machine-learning-based calving prediction from activity, lying, and ruminating behaviors in dairy cattle

The objective of this study was to use automated activity, lying, and rumination monitors to characterize prepartum behavior and predict calving in dairy cattle. Data were collected from 20 primiparous and 33 multiparous Holstein dairy cattle from September 2011 to May 2013 at the University of Kentucky Coldstream Dairy. The HR Tag (SCR Engineers Ltd., Netanya, Israel) automatically collected neck activity and rumination data in 2-h increments. The IceQube (IceRobotics Ltd., South Queensferry, United Kingdom) automatically collected number of steps, lying time, standing time, number of transitions from standing to lying (lying bouts), and total motion, summed in 15-min increments. IceQube data were summed in 2-h increments to match HR Tag data. All behavioral data were collected for 14 d before the predicted calving date. Retrospective data analysis was performed using mixed linear models to examine behavioral changes by day in the 14 d before calving. Bihourly behavioral differences from baseline values over the 14 d before calving were also evaluated using mixed linear models. Changes in daily rumination time, total motion, lying time, and lying bouts occurred in the 14 d before calving. In the bihourly analysis, extreme values for all behaviors occurred in the final 24 h, indicating that the monitored behaviors may be useful in calving prediction. To determine whether technologies were useful at predicting calving, random forest, linear discriminant analysis, and neural network machine-learning techniques were constructed and implemented using R version 3.1.0 (R Foundation for Statistical Computing, Vienna, Austria). These methods were used on variables from each technology and all combined variables from both technologies. A neural network analysis that combined variables from both technologies at the daily level yielded 100.0% sensitivity and 86.8% specificity. A neural network analysis that combined variables from both technologies in bihourly increments was used to identify 2-h periods in the 8 h before calving with 82.8% sensitivity and 80.4% specificity. Changes in behavior and machine-learning alerts indicate that commercially marketed behavioral monitors may have calving prediction potential.

Behavioral and physiological changes around estrus events identified using multiple automated monitoring technologies

This study included 2 objectives. The first objective was to describe estrus-related changes in parameters automatically recorded by the CowManager SensOor (Agis Automatisering, Harmelen, the Netherlands), DVM bolus (DVM Systems LLC, Greeley, CO), HR Tag (SCR Engineers Ltd., Netanya, Israel), IceQube (IceRobotics Ltd., Edinburgh, UK), and Track a Cow (Animart Inc., Beaver Dam, WI). This objective was accomplished using 35 cows in 3 groups between January and June 2013 at the University of Kentucky Coldstream Dairy. We used a modified Ovsynch with G7G protocol to partially synchronize ovulation, ending after the last PGF2α injection (d 0) to allow estrus expression. Visual observation for standing estrus was conducted for four 30-min periods at 0330, 1000, 1430, and 2200h on d 2, 3, 4, and 5. Eighteen of the 35 cows stood to be mounted at least once during the observation period. These cows were used to compare differences between the 6h before and after the first standing event (estrus) and the 2wk preceding that period (nonestrus) for all technology parameters. Differences between estrus and nonestrus were observed for CowManager SensOor minutes feeding per hour, minutes of high ear activity per hour, and minutes ruminating per hour; twice daily DVM bolus reticulorumen temperature; HR Tag neck activity per 2h and minutes ruminating per 2h; IceQube lying bouts per hour, minutes lying per hour, and number of steps per hour; and Track a Cow leg activity per hour and minutes lying per hour. No difference between estrus and nonestrus was observed for CowManager SensOor ear surface temperature per hour. The second objective of this study was to explore the estrus detection potential of machine-learning techniques using automatically collected data. Three machine-learning techniques (random forest, linear discriminant analysis, and neural network) were applied to automatically collected parameter data from the 18 cows observed in standing estrus. Machine learning accuracy for all technologies ranged from 91.0 to 100.0%. When we compared visual observation with progesterone profiles of all 32 cows, we found 65.6% accuracy. Based on these results, machine-learning techniques have potential to be applied to automatically collected technology data for estrus detection.

Stall cleanliness and stall temperature of two different freestall bases

The objective of this study was to describe the differences in freestall cleanliness and stall temperature between a barn with Dual Chamber Cow Waterbeds (DCCW; Advanced Comfort Technology, Reedsburg, WI) and a barn with rubber-filled mattresses at the University of Kentucky Coldstream Dairy Research Farm from January 18, 2012, to May 3, 2013. Stall cleanliness was measured twice weekly (n=134) by the same 2 observers using a 0.91 m×0.91 m wire grid containing 128 equally sized rectangles (10.16 cm×5.08 cm). This grid was centered at the rear portion of the stall; a rectangle that was visibly wet or had any amount of feces present was defined as a dirty rectangle. Weekly stall temperature (n=66) was measured by the same observer during a.m. milkings in the same predetermined stalls. Feces and wet sawdust were removed from the stalls before stall temperatures were acquired. Temperatures were obtained using a handheld thermometer at 30.48 cm above the stall base as determined via dual laser measurements. Stall temperature was measured on the front, middle, and back of the stall first with clean sawdust and then with the sawdust removed from the stall and wiped clean with a towel. Daily temperature-humidity index (THI) was calculated using Kentucky climate data calculated through the University of Kentucky College of Agriculture via a data logger, located 5.63 km from the Coldstream Dairy Farm. Stall cleanliness was not different between the DCCW barn (26.09±0.89 rectangles) and the rubber-filled mattress barn (23.70±0.89 rectangles). Mean THI throughout the study was 64.39±0.82. Stall temperature was different among THI categories. Temperature-humidity index categories 1 (coldest), 2, 3, and 4 (warmest) had THI ranges of 22.94 to 50.77, 50.77 to 64.88, 64.88 to 78.75, and 78.75 to 101.59, respectively. Stall temperatures (°C; least squares means±SE) were 2.26±0.30, 8.86±0.30, 15.52±0.30, and 20.95±0.30 for THI categories 1 to 4, respectively. Stalls with rubber-filled mattresses had a lower temperature (°C) than DCCW with least squares means±SE of 10.52±0.21°C and 13.29±0.21°C, respectively. The DCCW were probably significantly warmer because water holds heat well. The DCCW may have more of a heat-insulating effect compared with rubber-filled mattresses.

Abstract P4-06-16: TWEAK/Fn14 Signaling Axis as a Driver of Breast Cancer Cell Invasion and Metastasis

The molecular events associated with the multi-step process of cell invasion and metastasis are poorly understood. Tumor necrosis factor receptor family member fibroblast growth factor-inducible 14 (Fn14) and its ligand TWEAK (tumor necrosis factor-like weak inducer of apoptosis) have recently emerged as a pro-invasive signaling mechanism and indicator of poor prognosis in breast cancer. Our laboratory has recently reported enhanced Fn14 expression in a significant proportion of breast tumor samples, but not in normal breast epithelium. Analysis of publicly available breast cancer data indicates that high Fn14 expression positively correlates with HER2/neu positivity, estrogen receptor negativity, high tumor grade, positive lymph nodes, and metastasis. Modulation of Fn14 expression in breast cancer cell lines either by exogenous overexpression or siRNA-mediated blockade is sufficient to regulate breast cancer cell invasive behavior in vitro. However, the mechanisms leading to Fn14 overexpression, and how activation of the TWEAK/Fn14 signaling axis contributes to breast tumor malignant progression remain unclear. We hypothesized that genomic alterations and inappropriate autocrine or paracrine growth factor signaling may play a role in aberrant Fn14 regulation. Using array genomic hybridization and fluorescence in situ hybridization, we found increased Fn14 gene copy number relative to centromere 16 in two out of four Fn14-expressing, invasive breast cancer cell lines and in 28% of primary breast tumors. We also investigated the role of exogenous growth factors known to play important roles in the breast tumor microenvironment in stimulating Fn14 expression in vitro. TWEAK, EGF, IGF1, HRG and HGF/SF were sufficient to stimulate Fn14 expression de novo in a variety of biologic contexts. Many of these growth factors converge on the MAPK signaling axis. We have confirmed a functional role for the MAPK pathway in facilitating Fn14-mediated invasion. Consistent with this observation, Fn14 expression in primary breast tumors is high in the context of K-RAS mutation. We are currently evaluating the presence of important key regulatory regions within the Fn14 promoter that may be contributing Fn14 over expression in breast cancer cells. To define mechanisms by which Fn14 contributes to a malignant cell phenotype we have identified an Fn14-specific invasion signature using gene expression microarray profiling. Analysis of this data points to key malignant mechanisms likely to be impacted by Fn14 activation within different biologic contexts that warrants further investigation.

Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P4-06-16.

Functional coupling of oxygen binding and vasoactivity in S-nitrosohemoglobin

S-Nitrosohemoglobin (SNO-Hb) is a vasodilator whose activity is allosterically modulated by oxygen ("thermodyamic linkage"). Blood vessel contractions are favored in the oxygenated structure, and vasorelaxant activity is "linked" to deoxygenation, as illustrated herein. We further show that transnitrosation reactions between SNO-Hb and ambient thiols transduce the NO-related bioactivity, whereas NO itself is inactive. One remaining problem is that the amounts of SNO-Hb present in vivo are so large as to be incompatible with life were all the S-nitrosothiols transformed into bioactive equivalents during each arterial-venous cycle. Experiments were therefore undertaken to address how SNO-Hb conserves its NO-related activity. Our studies show that 1) increased O(2) affinity of SNO-Hb (which otherwise retains allosteric responsivity) restricts the hypoxia-induced allosteric transition that exchanges NO groups with ambient thiols for vasorelaxation; 2) some NO groups released from Cys(beta93) upon transition to T structure are autocaptured by the hemes, even in the presence of glutathione; and 3) an O(2)-dependent equilibrium between SNO-Hb and iron nitrosylhemoglobin acts to conserve NO. Thus, by sequestering a significant fraction of NO liberated upon transition to T structure, Hb can conserve NO groups that would otherwise be released in an untimely or deleterious manner.

Isolation, culture, and characterization of rat lung microvascular endothelial cells

Highly pure primary cultures of rat lung microvascular endothelial cells were obtained from peripheral lung tissue using a combination of selective culture strategies. The cells had a characteristic morphology consistent with an endothelial origin and were positive for a number of endothelial cell markers, including uptake of fluorescent acetylated lactate dehydrogenase, binding of the lectin Bandeiraea simplicifolia I, and positive immunofluorescence staining with two endothelial cell monoclonal antibodies. The cells behaved as microvascular endothelial cells using an in vitro angiogenesis assay. This isolation method provides a simple method for culturing the pulmonary microvasculature of the rat and these studies support the idea that endothelial cells from different vessels exhibit phenotypic heterogeneity. This method should prove useful for studying specialized endothelial cell function and differentiation in vitro.