Susceptibility to Human Immunodeficiency Virus Type 1 Acquisition Linked to Malaria Exposure: A Case-Control Study.

Human immunodeficiency virus (HIV) and malaria infection rates overlap across sub-Saharan Africa, but factors influencing their co-occurrence are unclear. In a case-control study, we investigated whether malaria exposure increases risk of type 1 (HIV-1) acquisition. Prior to seroconverting, HIV-positive cases had significantly higher malaria-associated antibodies compared to HIV-negative controls, linking malaria exposure to HIV-1 acquisition.

Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification.

High-throughput B-cell sequencing has opened up new avenues for investigating complex mechanisms underlying our adaptive immune response. These technological advances drive data generation and the need to mine and analyze the information contained in these large datasets, in particular the identification of therapeutic antibodies (Abs) or those associated with disease exposure and protection. Here, we describe our efforts to use artificial intelligence (AI)-based image-analyses for prospective classification of Abs based solely on sequence information. We hypothesized that Abs recognizing the same part of an antigen share a limited set of features at the binding interface, and that the binding site regions of these Abs share share common structure and physicochemical property patterns that can serve as a "fingerprint" to recognize uncharacterized Abs. We combined large-scale sequence-based protein-structure predictions to generate ensembles of 3-D Ab models, reduced the Ab binding interface to a 2-D image (fingerprint), used pre-trained convolutional neural networks to extract features, and trained deep neural networks (DNNs) to classify Abs. We evaluated this approach using Ab sequences derived from human HIV and Ebola viral infections to differentiate between two Abs, Abs belonging to specific B-cell family lineages, and Abs with different epitope preferences. In addition, we explored a different type of DNN method to detect one class of Abs from a larger pool of Abs. Testing on Ab sets that had been kept aside during model training, we achieved average prediction accuracies ranging from 71-96% depending on the complexity of the classification task. The high level of accuracies reached during these classification tests suggests that the DNN models were able to learn a series of structural patterns shared by Abs belonging to the same class. The developed methodology provides a means to apply AI-based image recognition techniques to analyze high-throughput B-cell sequencing datasets (repertoires) for Ab classification.

Implementing sequence-based antigenic distance calculation into immunological shape space model.

BACKGROUND: In 2009, a novel influenza vaccine was distributed worldwide to combat the H1N1 influenza "swine flu" pandemic. However, antibodies induced by the vaccine display differences in their specificity and cross-reactivity dependent on pre-existing immunity. Here, we present a computational model that can capture the effect of pre-existing immunity on influenza vaccine responses. The model predicts the region of the virus hemagglutinin (HA) protein targeted by antibodies after vaccination as well as the level of cross-reactivity induced by the vaccine. We tested our model by simulating a scenario similar to the 2009 pandemic vaccine and compared the results to antibody binding data obtained from human subjects vaccinated with the monovalent 2009 H1N1 influenza vaccine. RESULTS: We found that both specificity and cross-reactivity of the antibodies induced by the 2009 H1N1 influenza HA protein were affected by the viral strain the individual was originally exposed. Specifically, the level of antigenic relatedness between the original exposure HA antigen and the 2009 HA protein affected antigenic-site immunodominance. Moreover, antibody cross-reactivity was increased when the individual's pre-existing immunity was specific to an HA protein antigenically distinct from the 2009 pandemic strain. Comparison of simulation data with antibody binding data from human serum samples demonstrated qualitative and quantitative similarities between the model and real-life immune responses to the 2009 vaccine. CONCLUSION: We provide a novel method to evaluate expected outcomes in antibody specificity and cross-reactivity after influenza vaccination in individuals with different influenza HA antigen exposure histories. The model produced similar outcomes as what has been previously reported in humans after receiving the 2009 influenza pandemic vaccine. Our results suggest that differences in cross-reactivity after influenza vaccination should be expected in individuals with different exposure histories.

Comparison of ELISA with electro-chemiluminescence technology for the qualitative and quantitative assessment of serological responses to vaccination.

BACKGROUND: Profiling immune responses induced by either infection or vaccination can provide insight into identification of correlates of protection. Furthermore, profiling of serological responses can be used to identify biomarkers indicative of exposure to pathogens. Conducting such immune surveillance requires readout methods that are high-throughput, robust, and require small sample volumes. While the enzyme-linked immunosorbent assay (ELISA) is the classical readout method for assessing serological responses, the advent of multiplex assays has significantly increased the throughput and capacity for immunoprofiling. This report describes the development and assay performance (sensitivity, linearity of detection, requirement for multiple dilutions for each sample, intra- and inter-assay variability) of an electro-chemiluminescence (ECLIA)-based multiplex assay. METHODS: The current study describes the development of a multiplex ECLIA-based assay and characterizes the sensitivity, linear range, and inter- and intra-assay variability of the ECLIA platform and its agreement with the traditional ELISA. Special emphasis was placed on potential antigenic competition when testing closely related antigens in the multiplex format. RESULTS: Multiplexing of antigens in ECLIA provides significant practical benefits in terms of reducing sample volume requirements and experimental time. Beyond the practical advantages of multiplexing, the ECLIA provides superior assay performance when compared to the ELISA. Not only does ECLIA show good agreement with the ELISA assay, but the linear range of ECLIA is also sufficiently wide to permit single-dilution measurements of concentration without the need to do serial dilutions. The lack of antigenic competition allows the simultaneous testing of closely related antigens, such as plate antigens representing different alleles of the same protein, which can inform about cross-reactivities-or lack thereof-of serological responses. CONCLUSION: The advantages of the newly developed tool for assessing the antigen profiles of serological responses may ultimately lead to the identification of biomarkers associated with various disease stages and or protection against disease.

Modeling the Role of Epitope Arrangement on Antibody Binding Stoichiometry in Flaviviruses.

Cryo-electron-microscopy (cryo-EM) structures of flaviviruses reveal significant variation in epitope occupancy across different monoclonal antibodies that have largely been attributed to epitope-level differences in conformation or accessibility that affect antibody binding. The consequences of these variations for macroscopic properties such as antibody binding and neutralization are the results of the law of mass action-a stochastic process of innumerable binding and unbinding events between antibodies and the multiple binding sites on the flavivirus in equilibrium-that cannot be directly imputed from structure alone. We carried out coarse-grained spatial stochastic binding simulations for nine flavivirus antibodies with epitopes defined by cryo-EM or x-ray crystallography to assess the role of epitope spatial arrangement on antibody-binding stoichiometry, occupancy, and neutralization. In our simulations, all epitopes were equally competent for binding, representing the upper limit of binding stoichiometry that results from epitope spatial arrangement alone. Surprisingly, our simulations closely reproduced the relative occupancy and binding stoichiometry observed in cryo-EM, without having to account for differences in epitope accessibility or conformation, suggesting that epitope spatial arrangement alone may be sufficient to explain differences in binding occupancy and stoichiometry between antibodies. Furthermore, we found that there was significant heterogeneity in binding configurations even at saturating antibody concentrations, and that bivalent antibody binding may be more common than previously thought. Finally, we propose a structure-based explanation for the stoichiometric threshold model of neutralization.

Vinorelbine and epirubicin share common features with polysialic acid and modulate neuronal and glial functions.

Polysialic acid (PSA), a large, linear glycan composed of 8 to over 100 α2,8-linked sialic acid residues, modulates development of the nervous system by enhancing cell migration, axon pathfinding, and synaptic targeting and by regulating differentiation of progenitor cells. PSA also functions in developing and adult immune systems and is a signature of many cancers. In this study we identified vinorelbine, a semi-synthetic third generation vinca alkaloid, and epirubicin, an anthracycline and 4'-epimer of doxorubicin, as PSA mimetics. Similar to PSA, vinorelbine and epirubicin bind to the PSA-specific monoclonal antibody 735 and compete with the bacterial analog of PSA, colominic acid in binding to monoclonal antibody 735. Vinorelbine and epirubicin stimulate neurite outgrowth of cerebellar neurons via the neural cell adhesion molecule, via myristoylated alanine-rich C kinase substrate, and via fibroblast growth factor receptor, signaling through Erk pathways. Furthermore, the two compounds enhance process formation of Schwann cells and migration of cerebellar neurons in culture, and reduce migration of astrocytes after injury. These novel results show that the structure and function of PSA can be mimicked by the small organic compounds vinorelbine and epirubicin, thus raising the possibility to re-target drugs used in treatment of cancers to nervous system repair. Vinorelbine and epirubicin, identified as PSA mimetics, enhance, like PSA, neuronal migration, neuritogenesis, and formation of Schwann cell processes, and reduce astrocytic migration. Ablating NCAM, inhibiting fibroblast growth factor (FGFR) receptor, or adding the effector domain of myristoylated alanine-rich C kinase substrate (MARCKS) minimize the vinorelbine and epirubicin effects, indicating that they are true PSA mimetics triggering PSA-mediated functions.

The biological function of antibodies induced by the RTS,S/AS01 malaria vaccine candidate is determined by their fine specificity.

BACKGROUND: Recent vaccine studies have shown that the magnitude of an antibody response is often insufficient to explain efficacy, suggesting that characteristics regarding the quality of the antibody response, such as its fine specificity and functional activity, may play a major role in protection. Previous studies of the lead malaria vaccine candidate, RTS,S, have shown that circumsporozoite protein (CSP)-specific antibodies and CD4(+) T cell responses are associated with protection, however the role of fine specificity and biological function of CSP-specific antibodies remains to be elucidated. Here, the relationship between fine specificity, opsonization-dependent phagocytic activity and protection in RTS,S-induced antibodies is explored. METHODS: A new method for measuring the phagocytic activity mediated by CSP-specific antibodies in THP-1 cells is presented and applied to samples from a recently completed phase 2 RTS,S/AS01 clinical trial. The fine specificity of the antibody response was assessed using ELISA against three antigen constructs of CSP: the central repeat region, the C-terminal domain and the full-length protein. A multi-parameter analysis of phagocytic activity and fine-specificity data was carried out to identify potential correlates of protection in RTS,S. RESULTS: Results from the newly developed assay revealed that serum samples from RTS,S recipients displayed a wide range of robust and repeatable phagocytic activity. Phagocytic activity was correlated with full-length CSP and C-terminal specific antibody titres, but not to repeat region antibody titres, suggesting that phagocytic activity is primarily driven by C-terminal antibodies. Although no significant difference in overall phagocytic activity was observed with respect to protection, phagocytic activity expressed as 'opsonization index', a relative measure that normalizes phagocytic activity with CS antibody titres, was found to be significantly lower in protected subjects than non-protected subjects. CONCLUSIONS: Opsonization index was identified as a surrogate marker of protection induced by the RTS,S/AS01 vaccine and determined how antibody fine specificity is linked to opsonization activity. These findings suggest that the role of opsonization in protection in the RTS,S vaccine may be more complex than previously thought, and demonstrate how integrating multiple immune measures can provide insight into underlying mechanisms of immunity and protection.

Simulation of B cell affinity maturation explains enhanced antibody cross-reactivity induced by the polyvalent malaria vaccine AMA1.

Polyvalent vaccines use a mixture of Ags representing distinct pathogen strains to induce an immune response that is cross-reactive and protective. However, such approaches often have mixed results, and it is unclear how polyvalency alters the fine specificity of the Ab response and what those consequences might be for protection. In this article, we present a coarse-grain theoretical model of B cell affinity maturation during monovalent and polyvalent vaccinations that predicts the fine specificity and cross-reactivity of the Ab response. We stochastically simulate affinity maturation using a population dynamics approach in which the host B cell repertoire is represented explicitly, and individual B cell subpopulations undergo rounds of stimulation, mutation, and differentiation. Ags contain multiple epitopes and are present in subpopulations of distinct pathogen strains, each with varying degrees of cross-reactivity at the epitope level. This epitope- and strain-specific model of affinity maturation enables us to study the composition of the polyclonal response in granular detail and identify the mechanisms driving serum specificity and cross-reactivity. We applied this approach to predict the Ab response to a polyvalent vaccine based on the highly polymorphic malaria Ag apical membrane antigen-1. Our simulations show how polyvalent apical membrane Ag-1 vaccination alters the selection pressure during affinity maturation to favor cross-reactive B cells to both conserved and strain-specific epitopes and demonstrate how a polyvalent vaccine with a small number of strains and only moderate allelic coverage may be broadly neutralizing. Our findings suggest that altered fine specificity and enhanced cross-reactivity may be a universal feature of polyvalent vaccines.

Nonyloxytryptamine mimics polysialic acid and modulates neuronal and glial functions in cell culture.

Polysialic acid (PSA) is a major regulator of cell-cell interactions in the developing nervous system and in neural plasticity in the adult. As a polyanionic molecule with high water-binding capacity, PSA increases the intercellular space generating permissive conditions for cell motility. PSA enhances stem cell migration and axon path finding and promotes repair in the lesioned peripheral and central nervous systems, thus contributing to regeneration. As a next step in developing an improved PSA-based approach to treat nervous system injuries, we searched for small organic compounds that mimic PSA and identified as a PSA mimetic 5-nonyloxytryptamine oxalate, described as a selective 5-hydroxytryptamine receptor 1B (5-HT1B ) agonist. Similar to PSA, 5-nonyloxytryptamine binds to the PSA-specific monoclonal antibody 735, enhances neurite outgrowth of cultured primary neurons and process formation of Schwann cells, protects neurons from oxidative stress, reduces migration of astrocytes and enhances myelination in vitro. Furthermore, nonyloxytryptamine treatment enhances expression of the neural cell adhesion molecule (NCAM) and its polysialylated form PSA-NCAM and reduces expression of the microtubule-associated protein MAP2 in cultured neuroblastoma cells. These results demonstrate that 5-nonyloxytryptamine mimics PSA and triggers PSA-mediated functions, thus contributing to the repertoire of molecules with the potential to improve recovery in acute and chronic injuries of the mammalian peripheral and central nervous systems. Polysialic acid (PSA) plays important roles in nervous system development, as well as synaptic plasticity and regeneration in the adult. 5-Nonyloxytryptamine oxalate (5-NOT) mimics PSA and triggers PSA-mediated functions in neurons and glial cells. 5-NOT stimulates neuritogenesis, myelination and Schwann cell migration. This study sets the basis to develop a PSA-mediated therapy of acute and chronic nervous system diseases.

Synthesis and evaluation of Strychnos alkaloids as MDR reversal agents for cancer cell eradication.

Natural products represent the fourth generation of multidrug resistance (MDR) reversal agents that resensitize MDR cancer cells overexpressing P-glycoprotein (Pgp) to cytotoxic agents. We have developed an effective synthetic route to prepare various Strychnos alkaloids and their derivatives. Molecular modeling of these alkaloids docked to a homology model of Pgp was employed to optimize ligand-protein interactions and design analogues with increased affinity to Pgp. Moreover, the compounds were evaluated for their (1) binding affinity to Pgp by fluorescence quenching, and (2) MDR reversal activity using a panel of in vitro and cell-based assays and compared to verapamil, a known inhibitor of Pgp activity. Compound 7 revealed the highest affinity to Pgp of all Strychnos congeners (Kd=4.4µM), the strongest inhibition of Pgp ATPase activity, and the strongest MDR reversal effect in two Pgp-expressing cell lines. Altogether, our findings suggest the clinical potential of these synthesized compounds as viable Pgp modulators justifies further investigation.

Quantitative predictions of binding free energy changes in drug-resistant influenza neuraminidase.

Quantitatively predicting changes in drug sensitivity associated with residue mutations is a major challenge in structural biology. By expanding the limits of free energy calculations, we successfully identified mutations in influenza neuraminidase (NA) that confer drug resistance to two antiviral drugs, zanamivir and oseltamivir. We augmented molecular dynamics (MD) with Hamiltonian Replica Exchange and calculated binding free energy changes for H274Y, N294S, and Y252H mutants. Based on experimental data, our calculations achieved high accuracy and precision compared with results from established computational methods. Analysis of 15 micros of aggregated MD trajectories provided insights into the molecular mechanisms underlying drug resistance that are at odds with current interpretations of the crystallographic data. Contrary to the notion that resistance is caused by mutant-induced changes in hydrophobicity of the binding pocket, our simulations showed that drug resistance mutations in NA led to subtle rearrangements in the protein structure and its dynamics that together alter the active-site electrostatic environment and modulate inhibitor binding. Importantly, different mutations confer resistance through different conformational changes, suggesting that a generalized mechanism for NA drug resistance is unlikely.

Human transcriptional signature of protection after Plasmodium falciparum immunization and infectious challenge via mosquito bites.

The identification of immune correlates of protection against infectious pathogens will accelerate the design and optimization of recombinant and subunit vaccines. Systematic analyses such as immunoprofiling including serological, cellular, and molecular assessments supported by computational tools are key to not only identify correlates of protection but also biomarkers of disease susceptibility. The current study expands our previous cellular and serological profiling of vaccine-induced responses to a whole parasite malaria vaccine. The irradiated sporozoite model was chosen as it is considered the most effective vaccine against malaria. In contrast to whole blood transcriptomics analysis, we stimulated peripheral blood mononuclear cells (PBMC) with sporozoites and enriched for antigen-specific cells prior to conducting transcriptomics analysis. By focusing on transcriptional events triggered by antigen-specific stimulation, we were able to uncover quantitative and qualitative differences between protected and non-protected individuals to controlled human malaria infections and identified differentially expressed genes associated with sporozoite-specific responses. Further analyses including pathway and gene set enrichment analysis revealed that vaccination with irradiated sporozoites induced a transcriptomic profile associated with Th1-responses, Interferon-signaling, antigen-presentation, and inflammation. Analyzing longitudinal time points not only post-vaccination but also post-controlled human malaria infection further revealed that the transcriptomic profile of protected vs non-protected individuals was not static but continued to diverge over time. The results lay the foundation for comparing protective immune signatures induced by various vaccine platforms to uncover immune correlates of protection that are common across platforms.

Reduced maternal immunity and vertical transfer of immunity against SARS-CoV-2 variants of concern with COVID-19 exposure or initial vaccination in pregnancy.

Introduction: As the SARS-CoV-2 pandemic continues to evolve, we face new variants of concern with a concurrent decline in vaccine booster uptake. We aimed to evaluate the difference in immunity gained from the original SARS-CoV-2 mRNA vaccine series in pregnancy versus SARS-CoV-2 exposure during pregnancy against recent variants of concern. Study Design: This is a retrospective analysis of previously collected samples from 192 patients who delivered between February 2021 and August 2021. Participants were categorized as 1) COVID vaccine: mRNA vaccine in pregnancy, 2) COVID-exposed, and 3) controls. The primary outcome was neutralizing capacity against wild-type, Delta, and Omicron-B1 between cohorts. Secondary outcomes include a comparison of cord-blood ID50 as well as the efficiency of vertical transfer, measured by cord-blood:maternal blood ID50 for each variant. Results: Pregnant women with COVID-19 vaccination had a greater spike in IgG titers compared to both those with COVID-19 disease exposure and controls. Both COVID exposure and vaccination resulted in immunity against Delta, but only COVID vaccination resulted in significantly greater Omicron ID-50 versus controls. The neutralizing capacity of serum from newborns was lower than that of their mothers, with COVID-vaccination demonstrating higher cord-blood ID50 vs wildtype and Delta variants compared to control or COVID-exposed, but neither COVID-exposure nor vaccination demonstrated significantly higher Omicron ID50 in cord-blood compared to controls. There was a 0.20 (0.07-0.33, p=0.004) and 0.12 (0.0-0.24, p=0.05) increase in cord-blood:maternal blood ID50 with COVID vaccination compared to COVID-19 exposure for wild-type and Delta respectively. In pair-wise comparison, vertical transfer of neutralization capacity (cord-blood:maternal blood ID50) was greatest for wild-type and progressively reduced for Delta and Omicron ID50. Conclusion: Pregnant patients with either an initial mRNA vaccination series or COVID-exposure demonstrated reduced immunity against newer variants compared to wild-type as has been reported for non-pregnant individuals; however, the COVID-vaccination series afforded greater cross-variant immunity to pregnant women, specifically against Omicron, than COVID-disease. Vertical transfer of immunity is greater in those with COVID vaccination vs COVID disease exposure but is reduced with progressive variants. Our results reinforce the importance of bivalent booster vaccination in pregnancy for both maternal and infant protection and also provide a rationale for receiving updated vaccines as they become available.

Profiling of serum factors associated with Staphylococcus aureus skin and soft tissue infections as a foundation for biomarker identification.

Background: People living in close quarters, such as military trainees, are at increased risk for skin and soft tissue infections (SSTI), especially those caused by methicillin-resistant Staphylococcus aureus (MRSA). The serum immune factors associated with the onset of SSTI are not well understood. Methods: We conducted a longitudinal study of SSTIs, enrolling US Army trainees before starting military training and following up for 14 weeks. Samples were collected on Day 0, 56, and 90. Serum chemokines and cytokines among 16 SSTI cases and 51 healthy controls were evaluated using an electro-chemiluminescence based multiplex assay platform. Results: Of 54 tested cytokines, 12 were significantly higher among SSTI cases as compared to controls. Among the cases, there were correlations between factors associated with vascular injury (i.e., VCAM-1, ICAM-1, and Flt1), the angiogenetic factor VEGF, and IL-10. Unsupervised machine learning (Principal Component Analysis) revealed that IL10, IL17A, C-reactive protein, ICAM1, VCAM1, SAA, Flt1, and VGEF were indicative of SSTI. Conclusion: The study demonstrates the power of immunoprofiling for identifying factors predictive of pre-illness state of SSTI thereby identifying early stages of an infection and individuals susceptible to SSTI.

QSAR classification model for antibacterial compounds and its use in virtual screening.

As novel and drug-resistant bacterial strains continue to present an emerging health threat, the development of new antibacterial agents is critical. This includes making improvements to existing antibacterial scaffolds as well as identifying novel ones. The aim of this study is to apply a Bayesian classification QSAR approach to rapidly screen chemical libraries for compounds predicted to have antibacterial activity. Toward this end we assembled a data set of 317 known antibacterial compounds as well as a second data set of diverse, well-validated, non-antibacterial compounds from 215 PubChem Bioassays against various bacterial species. We constructed a Bayesian classification model using structural fingerprints and physicochemical property descriptors and achieved an accuracy of 84% and precision of 86% on an independent test set in identifying antibacterial compounds. To demonstrate the practical applicability of the model in virtual screening, we screened an independent data set of ~200k compounds. The results show that the model can screen top hits of PubChem Bioassay actives with accuracy up to ~76%, representing a 1.5-2-fold enrichment. The top screened hits represented a mixture of both known antibacterial scaffolds as well as novel scaffolds. Our study suggests that a well-validated Bayesian classification QSAR approach could compliment other screening approaches in identifying novel and promising hits. The data sets used in constructing and validating this model have been made publicly available.

Exploring polypharmacology using a ROCS-based target fishing approach.

Polypharmacology has emerged as a new theme in drug discovery. In this paper, we studied polypharmacology using a ligand-based target fishing (LBTF) protocol. To implement the protocol, we first generated a chemogenomic database that links individual protein targets with a specified set of drugs or target representatives. Target profiles were then generated for a given query molecule by computing maximal shape/chemistry overlap between the query molecule and the drug sets assigned to each protein target. The overlap was computed using the program ROCS (Rapid Overlay of Chemical Structures). We validated this approach using the Directory of Useful Decoys (DUD). DUD contains 2950 active compounds, each with 36 property-matched decoys, against 40 protein targets. We chose a set of known drugs to represent each DUD target, and we carried out ligand-based virtual screens using data sets of DUD actives seeded into DUD decoys for each target. We computed Receiver Operator Characteristic (ROC) curves and associated area under the curve (AUC) values. For the majority of targets studied, the AUC values were significantly better than for the case of a random selection of compounds. In a second test, the method successfully identified off-targets for drugs such as rimantadine, propranolol, and domperidone that were consistent with those identified by recent experiments. The results from our ROCS-based target fishing approach are promising and have potential application in drug repurposing for single and multiple targets, identifying targets for orphan compounds, and adverse effect prediction.

Sleep and Infantry Battle Drill Performance in Special Operations Soldiers.

BACKGROUND: Although multiple studies have documented the impact of insufficient sleep on soldier performance, most studies have done so using artificial measures of performance (e.g., tablet or simulator tests). The current study sought to test the relationship between sleep and soldier performance during infantry battle drill training, a more naturalistic measure of performance.METHODS: Subjects in the study were 15 junior Special Operations infantry soldiers. Soldiers wore an actigraph and reported their subjective sleep duration and quality prior to close quarter battle (CQB) drills. Experienced leaders monitored each iteration of the CQB exercise and recorded the number of errors committed.RESULTS: The number of errors committed during the live ammunition iterations was negatively correlated with subjective number of hours slept and subjective sleep efficiency/quality during the month prior. Soldiers with subjective sleep duration ≥7 h had a significantly lower number of errors than soldiers with subjective sleep duration <7 h (1.71 vs. 0.63 errors), and soldiers with sleep quality <85% committed more errors than those with sleep quality ≥85% (1.50 vs. 0.40 errors).DISCUSSION: These data preliminarily suggest that sleep quality and duration may influence subsequent performance on infantry battle drill training, particularly for soldiers with limited experience in battle drill conduction who have not yet perfected battle drill techniques. Future studies should enact sleep augmentation to determine the causal influence of sleep on performance in this setting.Mantua J, Shevchik JD, Chaudhury S, Eldringhoff HP, Mickelson CA, McKeon AB. Sleep and infantry battle drill performance in Special Operations soldiers. Aerosp Med Hum Perform. 2022; 93(7):557-561.

Assessing Prevalence and Transmission Rates of Malaria through Simultaneous Profiling of Antibody Responses against Plasmodium and Anopheles Antigens.

Reliably assessing exposure to mosquitoes carrying malaria parasites continues to be a challenge due to the lack of reliable, highly sensitive diagnostics with high-throughput potential. Here, we describe an approach that meets these requirements by simultaneously measuring immune responses to both disease vector and pathogen, using an electro-chemiluminescence-based multiplex assay platform. While using the same logistical steps as a classic ELISA, this platform allows for the multiplexing of up to ten antigens in a single well. This simple, reproducible, quantitative readout reports the magnitude, incidence, and prevalence of malaria infections in residents of malaria-endemic areas. By reporting exposure to both insect vectors and pathogen, the approach also provides insights into the efficacy of drugs and/or other countermeasures deployed against insect vectors aimed at reducing or eliminating arthropod-borne diseases. The high throughput of the assay enables the quick and efficient screening of sera from individuals for exposure to Plasmodium even if they are taking drug prophylaxis. We applied this assay to samples collected from controlled malaria infection studies, as well as those collected in field studies in malaria-endemic regions in Uganda and Kenya. The assay was sensitive to vector exposure, malaria infection, and endemicity, demonstrating its potential for use in malaria serosurveillance.

Comprehensive serologic profile and specificity of maternal and neonatal cord blood SARS-CoV-2 antibodies.

BACKGROUND: Initial studies on COVID-19 in pregnancy have demonstrated a range of neutralizing activity, but little has been published on the full profile of SARS CoV-2 related antibodies in maternal and cordblood. OBJECTIVE: This study aimed to describe the profile and specificity of maternal and neonatal cord blood antibody profiles in response to SARS-CoV-2 virus exposure. STUDY DESIGN: This was a prospective cohort study of delivering patients at Thomas Jefferson University Hospital from April 2020 to February 2021. The primary objective was to describe unique maternal and fetal antibody epitope titers and specificity in patients with COVID-19 history. Serologic profile was assessed with a multiplex platform. Antigens used were hemagglutinin trimer influenza A (Hong Kong H3); spike trimers for SARS-CoV-2, SARS-CoV-1, Middle East respiratory syndrome coronavirus, and betacoronaviruses HKU-1 and OC43; and spike N-terminal domain, spike receptor-binding domain, and nucleocapsid protein (full length) for SARS-CoV-2. RESULTS: Here, 112 maternal samples and 101 maternal and cord blood pairs were analyzed. Of note, 37 patients had a known history of COVID-19 (positive polymerase chain reaction test) during pregnancy. Of 36 patients, 16 (44%) were diagnosed with COVID-19 within 7 days of delivery. Moreover, 15 of the remaining 76 patients (20%) without a known diagnosis had positive maternal serology. For those with a history of COVID-19, we identified robust immunoglobulin G response in maternal blood to CoV-2 nucleocapsid, spike (full length), and spike (receptor-binding domain) antigens with more modest responses to the spike (N-terminal domain) antigen. In contrast, the maternal blood immunoglobulin M response seemed more specific to spike (full length) epitopes than nucleocapsid, spike (receptor-binding domain), or spike (N-terminal domain) epitopes. There were significantly higher maternal and cord blood immunoglobulin G responses not only to CoV-2 spike (127.1-fold; standard deviation, 2.0; P<.00001) but also to CoV-1 spike (21.1-fold higher; standard deviation, 1.8; P<.00001) and Middle East respiratory syndrome spike (6.9-fold higher; standard deviation, 2.5; P<.00001). In contrast, maternal immunoglobulin M responses were more specific to CoV-2 spike (15.8-fold; standard deviation, 2.1; P<.00001) but less specific to CoV-1 (2.5-fold higher; standard deviation, 0.71; P<.00001) and no significant difference for Middle East respiratory syndrome. Maternal and cord blood immunoglobulin G antibodies were highly correlated for both spike and nucleocapsid (R2=0.96 and 0.94, respectively). CONCLUSION: Placental transfer was efficient, with robust nucleocapsid and spike responses. Both nucleocapsid and spike antibody responses should be studied for a better understanding of COVID-19 immunity. Immunoglobulin G antibodies were cross-reactive with related CoV-1 and Middle East respiratory syndrome spike epitopes, whereas immunoglobulin M antibodies, which cannot cross the placenta to provide neonatal passive immunity, were more SARS-CoV-2 specific. Neonatal cord blood may have significantly different fine specificity than maternal blood, despite the high efficiency of immunoglobulin G transfer.