Screening and characterization of 133 physiologically-relevant environmental chemicals for reproductive toxicity.

Reproduction is a functional outcome that relies on complex cellular, tissue, and organ interactions that span the developmental period to adulthood. Thus, the assessment of its disruption by environmental chemicals is remarkably painstaking in conventional toxicological animal models and does not scale up to the number of chemicals present in our environment and requiring testing. We adapted a previously described low-throughput in vivo chromosome segregation assay using C. elegans predictive of reproductive toxicity and leveraged available public data sources (ToxCast, ICE) to screen and characterize 133 physiologically-relevant chemicals in a high-throughput manner. The screening outcome was further validated in a second, independent in vivo assay assessing embryonic viability. In total, 13 chemicals were classified as reproductive toxicants with the two most active chemicals belonging to the large family of Quaternary Ammonium Compounds (QACs) commonly used as disinfectants but with limited available reproductive toxicity data. We compared the results from the C. elegans assay with ToxCast in vitro data compiled from 700+ cell response assays and 300+ signaling pathways-based assays. We did not observe a difference in the bioactivity or in average potency (AC50) between the top and bottom chemicals. However, the intended target categories were significantly different between the classified chemicals with, in particular, an over-representation of steroid hormone targets for the high Z-score chemicals. Taken together, these results point to the value of in vivo models that scale to high-throughput level for reproductive toxicity assessment and to the need to prioritize the assessment of QACs impacts on reproduction.

Distinct transcriptional profiles of maternal and fetal placental macrophages at term are associated with gravidity.

Maternal intervillous monocytes (MIMs) and fetal Hofbauer cells (HBCs) are myeloid-derived immune cells at the maternal-fetal interface. Little is known regarding the molecular phenotypes and roles of these distinct monocyte/macrophage populations. Here, we used RNA sequencing to investigate the transcriptional profiles of MIMs and HBCs in six normal term pregnancies. Our analyses revealed distinct transcriptomes of MIMs and HBCs. Genes involved in differentiation and cell organization pathways were more highly expressed in MIMs vs. HBCs. In contrast, HBCs had higher expression of genes involved in inflammatory responses and cell surface receptor signaling. Maternal gravidity influenced monocyte programming, as expression of pro-inflammatory molecules was significantly higher in MIMs from multigravidas compared to primigravidas. In HBCs, multigravidas displayed enrichment of gene pathways involved in cell-cell signaling and differentiation. In summary, our results demonstrated that MIMs and HBCs have highly divergent transcriptional signatures, reflecting their distinct origins, locations, functions, and roles in inflammatory responses. Our data further suggested that maternal gravidity influences the gene signatures of MIMs and HBCs, potentially modulating the interplay between tolerance and trained immunity. The phenomenon of reproductive immune memory may play a novel role in the differential susceptibility of primigravidas to pregnancy complications.

Minimal mRNA uptake and inflammatory response to COVID-19 mRNA vaccine exposure in human placental explants.

Despite universal recommendations for COVID-19 mRNA vaccination in pregnancy, uptake has been lower than desired. There have been limited studies of the direct impact of COVID-19 mRNA vaccine exposure in human placental tissue. Using a primary human placental explants model, we investigated the uptake of two common mRNA vaccines (BNT162b2 Pfizer-BioNTech or mRNA-1273 Moderna), and whether exposure altered villous cytokine responses. Explants derived from second or third trimester chorionic villi were incubated with vaccines at supraphysiologic concentrations and analyzed at two time points. We observed minimal uptake of mRNA vaccines in placental explants by in situ hybridization and quantitative RT-PCR. No specific or global cytokine response was elicited by either of the mRNA vaccines in multiplexed immunoassays. Our results suggest that the human placenta does not readily absorb the COVID-19 mRNA vaccines nor generate a significant inflammatory response after exposure.

Perfluorooctanoic acid induces transcriptomic alterations in second trimester human cytotrophoblasts.

Poly- and perfluroroalkylated substances (PFAS) are a major class of surfactants used in industry applications and consumer products. Despite efforts to reduce the usage of PFAS due to their environmental persistence, compounds such as perfluorooctanoic acid (PFOA) are widely detected in human blood and tissue. Although growing evidence supports that prenatal exposures to PFOA and other PFAS are linked to adverse pregnancy outcomes, the target organs and pathways remain unclear. Recent investigations in mouse and human cell lines suggest that PFAS may impact the placenta and impair trophoblast function. In this study, we investigated the effects of PFOA on cytotoxicity and the transcriptome in cultured second trimester human cytotrophoblasts (CTBs). We show that PFOA significantly reduces viability and induces cell death at 24 h, in a concentration-dependent manner. At subcytotoxic concentrations, PFOA impacted expression of hundreds of genes, including several molecules (CRH, IFIT1, and TNFSF10) linked with lipid metabolism and innate immune response pathways. Furthermore, in silico analyses suggested that regulatory factors such as peroxisome proliferator-activated receptor-mediated pathways may be especially important in response to PFOA. In summary, this study provides evidence that PFOA alters primary human CTB viability and gene pathways that could contribute to placental dysfunction and disease.

Retrospective analysis of wildfire smoke exposure and birth weight outcomes in the San Francisco Bay Area of California.

Despite the occurrence of wildfires quadrupling over the past four decades, the health effects associated with wildfire smoke exposures during pregnancy remains unknown. Particulate matter less than 2.5 µms (PM2.5) is among the major pollutants emitted in wildfire smoke. Previous studies found PM2.5 associated with lower birthweight, however, the relationship between wildfire-specific PM2.5 and birthweight is uncertain. Our study of 7923 singleton births in San Francisco between January 1, 2017 and March 12, 2020 examines associations between wildfire smoke exposure during pregnancy and birthweight. We linked daily estimates of wildfire-specific PM2.5 to maternal residence at the ZIP code level. We used linear and log-binomial regression to examine the relationship between wildfire smoke exposure by trimester and birthweight and adjusted for gestational age, maternal age, race/ethnicity, and educational attainment. We stratified by infant sex to examine potential effect modification. Exposure to wildfire-specific PM2.5 during the second trimester of pregnancy was positively associated with increased risk of large for gestational age (OR = 1.13; 95% CI: 1.03, 1.24), as was the number of days of wildfire-specific PM2.5 above 5 µg m-3 in the second trimester (OR = 1.03; 95% CI: 1.01, 1.06). We found consistent results with wildfire smoke exposure in the second trimester and increased continuous birthweight-for-gestational age z-score. Differences by infant sex were not consistent. Counter to our hypothesis, results suggest that wildfire smoke exposures are associated with increased risk for higher birthweight. We observed strongest associations during the second trimester. These investigations should be expanded to other populations exposed to wildfire smoke and aim to identify vulnerable communities. Additional research is needed to clarify the biological mechanisms in this relationship between wildfire smoke exposure and adverse birth outcomes.

Proteomic analyses of primary human villous trophoblasts exposed to flame retardant BDE-47 using SWATH-MS.

Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants and recognized developmental toxicants that are detectable in placental tissues. Higher levels of in utero PBDE exposure have been associated with an increased risk of adverse birth outcomes. During pregnancy, cytotrophoblasts (CTBs) from the placenta play critical roles in the formation of the maternal-fetal interface via uterine invasion and vascular remodeling. The differentiation of these cells towards an invasive phenotype is crucial for proper placental development. We previously have shown that BDE-47 can impact CTB viability and hinder the ability of these cells to migrate and invade. To expand on potential toxicological mechanisms, we utilized quantitative proteomic approaches to identify changes in the global proteome of mid-gestation primary human CTBs after exposure to BDE-47. Using sequential window acquisition of all theoretical fragment-ion spectra (SWATH), we identified 3024 proteins in our CTB model of differentiation/invasion. Over 200 proteins were impacted as a function of BDE-47 exposure (1 µM and 5 µM) across the treatment period (15, 24, and 39 h). The differentially expressed molecules displayed time- and concentration-dependent changes in expression and were enriched in pathways associated with aggregatory and adhesive processes. Network analysis identified CYFIP1, a molecule previously unexplored in a placental context, to be dysregulated at BDE-47 concentrations previously seen to impact CTB migration/invasion. Our SWATH-MS dataset thus demonstrates BDE-47 impacts the global proteome of differentiating CTBs and serves as a valuable resource for further understanding of the relationship between environmental chemical exposures and placental development and function. AVAILABILITY OF DATA AND MATERIAL: Raw chromatograms are deposited on the MassIVE proteomic database (https://massive.ucsd.edu) under accession number MSV000087870. Normalized relative abundances are also available as Table S1.

Accurate Measurements and Simulations of the Evaporation and Trajectories of Individual Solution Droplets.

A refined numerical model for the evaporation and transport of droplets of binary solutions is introduced. Benchmarking is performed against other models found in the literature and experimental measurements of both electrodynamically trapped and freefalling droplets. The model presented represents the microphysical behavior of solutions droplets in the continuum and transition regimes, accounting for the unique hygroscopic behavior of different solutions, including the Fuchs-Sutugin and Cunningham slip correction factors, and accounting for the Kelvin effect. Simulations of pure water evaporation are experimentally validated for temperatures between 290 K and 298 K and between relative humidity values of approximately 0% and 85%. Measurements and simulations of the spatial trajectories and evaporative behavior of aqueous sodium chloride droplets are compared for relative humidity values between 0 and 40%. Simulations are shown to represent experimental data within experimental uncertainty in initial conditions. Calculations of a time-dependent Péclet number, including the temperature dependence of solute diffusion, are related to morphologies of sodium chloride particles dried at different rates. For sodium chloride solutions, dried particles are composed of collections of reproducibly shaped crystals, with higher evaporation rates resulting in higher numbers of crystals, which are smaller.

Society for Birth Defects Research and Prevention 2022-2027 strategic plan.

BACKGROUND: The sixth Strategic Planning Session of the Society for Birth Defects Research and Prevention (BDRP) was held on April 24-25, 2022, in Alexandria, VA. METHODS: This effort built upon previous strategic planning sessions, conducted every 5 years. RESULTS: The overall process was designed to identify BDRP's vision, purpose, culture, and potential, as well as to communicate the value that BDRP brings to its members, volunteers, partners, and the greater community. CONCLUSIONS: The BDRP 2022-2027 Strategic Plan provides the BDRP leadership, members, and staff with a clearly articulated framework and direction to support long-term sustainability and growth of the society.

Minimal mRNA uptake and inflammatory response to COVID-19 mRNA vaccine exposure in human placental explants.

Despite universal recommendations for COVID-19 mRNA vaccination in pregnancy, uptake has been lower than desired. There have been limited studies of the direct impact of COVID-19 mRNA vaccine exposure in human placental tissue. Using a primary human villous explant model, we investigated the uptake of two common mRNA vaccines (BNT162b2 Pfizer-BioNTech or mRNA-1273 Moderna), and whether exposure altered villous cytokine responses. Explants derived from second or third trimester chorionic villi were incubated with vaccines at supraphysiologic concentrations and analyzed at two time points. We observed minimal uptake of mRNA vaccines in placental explants by in situ hybridization and quantitative RT-PCR. No specific or global cytokine response was elicited by either of the mRNA vaccines in multiplexed immunoassays. Our results suggest that the human placenta does not readily absorb the COVID-19 mRNA vaccines nor generate a significant inflammatory response after exposure.

A science-based agenda for health-protective chemical assessments and decisions: overview and consensus statement.

The manufacture and production of industrial chemicals continues to increase, with hundreds of thousands of chemicals and chemical mixtures used worldwide, leading to widespread population exposures and resultant health impacts. Low-wealth communities and communities of color often bear disproportionate burdens of exposure and impact; all compounded by regulatory delays to the detriment of public health. Multiple authoritative bodies and scientific consensus groups have called for actions to prevent harmful exposures via improved policy approaches. We worked across multiple disciplines to develop consensus recommendations for health-protective, scientific approaches to reduce harmful chemical exposures, which can be applied to current US policies governing industrial chemicals and environmental pollutants. This consensus identifies five principles and scientific recommendations for improving how agencies like the US Environmental Protection Agency (EPA) approach and conduct hazard and risk assessment and risk management analyses: (1) the financial burden of data generation for any given chemical on (or to be introduced to) the market should be on the chemical producers that benefit from their production and use; (2) lack of data does not equate to lack of hazard, exposure, or risk; (3) populations at greater risk, including those that are more susceptible or more highly exposed, must be better identified and protected to account for their real-world risks; (4) hazard and risk assessments should not assume existence of a "safe" or "no-risk" level of chemical exposure in the diverse general population; and (5) hazard and risk assessments must evaluate and account for financial conflicts of interest in the body of evidence. While many of these recommendations focus specifically on the EPA, they are general principles for environmental health that could be adopted by any agency or entity engaged in exposure, hazard, and risk assessment. We also detail recommendations for four priority areas in companion papers (exposure assessment methods, human variability assessment, methods for quantifying non-cancer health outcomes, and a framework for defining chemical classes). These recommendations constitute key steps for improved evidence-based environmental health decision-making and public health protection.

Current practice and recommendations for advancing how human variability and susceptibility are considered in chemical risk assessment.

A key element of risk assessment is accounting for the full range of variability in response to environmental exposures. Default dose-response methods typically assume a 10-fold difference in response to chemical exposures between average (healthy) and susceptible humans, despite evidence of wider variability. Experts and authoritative bodies support using advanced techniques to better account for human variability due to factors such as in utero or early life exposure and exposure to multiple environmental, social, and economic stressors.This review describes: 1) sources of human variability and susceptibility in dose-response assessment, 2) existing US frameworks for addressing response variability in risk assessment; 3) key scientific inadequacies necessitating updated methods; 4) improved approaches and opportunities for better use of science; and 5) specific and quantitative recommendations to address evidence and policy needs.Current default adjustment factors do not sufficiently capture human variability in dose-response and thus are inadequate to protect the entire population. Susceptible groups are not appropriately protected under current regulatory guidelines. Emerging tools and data sources that better account for human variability and susceptibility include probabilistic methods, genetically diverse in vivo and in vitro models, and the use of human data to capture underlying risk and/or assess combined effects from chemical and non-chemical stressors.We recommend using updated methods and data to improve consideration of human variability and susceptibility in risk assessment, including the use of increased default human variability factors and separate adjustment factors for capturing age/life stage of development and exposure to multiple chemical and non-chemical stressors. Updated methods would result in greater transparency and protection for susceptible groups, including children, infants, people who are pregnant or nursing, people with disabilities, and those burdened by additional environmental exposures and/or social factors such as poverty and racism.

Gestational age-dependent decrease in fetal Hofbauer cells in placentas from pregnancies exposed to wildfire smoke in California.

OBJECTIVE: Wildfires are more common over the last decade and the frequency of wildfire events has been accelerated by climate change. The existing body of literature suggests that exposure to wildfire smoke during pregnancy contributes to adverse perinatal outcomes such as preterm birth and fetal growth restriction. We hypothesize that exposures to wildfire smoke and its constituents triggers a fetal inflammatory response which contributes to pathological changes that underlie these adverse pregnancy outcomes. In this study, we quantified the presence of fetal macrophages (i.e., Hofbauer cells) in human placentas obtained between 2018 and 2020 to assess the relationship between fetal immune status and wildfire exposure. STUDY DESIGN: We collected placentas from pregnancies from two hospitals in San Francisco over a two-year period that included two severe major wildfires. The average particulate matter < 2.5 µm (PM2.5) or wildfire specific PM2.5 levels were estimated over the gestational duration of each sample. Immunostaining against CK7 and CD68 was performed to identify intravillous fetal Hofbauer cells. We assessed the gestational-age dependent relationship between placental CD68+ cell density and mean daily PM2.5 or wildfire-specific PM2.5 via linear regression and Welch's t-test. Additionally, we compared placental CD68+ cell density with estimated peak wildfire exposures during the gestation to determine if timing of exposure during pregnancy may influence the occurrence of Hofbauer cells in the placenta. RESULTS: The gestational ages ranged from 7-41 weeks (n = 67). The majority of samples were collected during one of two major wildfire events in Northern California (70%; n = 47). In general, we observed a significant inverse relationship between placental CD68 density and PM2.5 or wildfire specific PM2.5, however, these associations were only observed in first or second trimester samples, and not in term samples. For example, among first trimester samples (n=22), we observed lower mean CD68 density among samples likely to be exposed to wildfire events (mean = 1.42, SD = 0.8) as compared to those not exposed (mean = 3.73, SD = 1.983) (p = 0.0015). Based on our linear regression model results, we predicted that a one µg/m3 increase in daily mean wildfire PM2.5 was associated with a 0.457 decrease in CD68 density (ß =-0.457; 95% CI: -0.722, -0.193). This association was also significant for daily mean overall PM2.5, though smaller in magnitude (ß = -0.139; 95% CI: -0.218, -0.059). CONCLUSIONS: Our results suggest that wildfire smoke exposures are associated with decreased presence of fetal Hofbauer cells in first and second trimester placentas, suggesting exposure may lead to impaired placental function via altered presence of fetal Hofbauer cells and changes in immune status.

Protocol for designing INVITES-IN, a tool for assessing the internal validity of in vitro studies.

This protocol describes the design and development of a tool for evaluation of the internal validity of in vitro studies, which is needed to include the data as evidence in systematic reviews and chemical risk assessments. The tool will be designed specifically to be applied to cell culture studies, including, but not restricted to, studies meeting the new approach methodology (NAM) definition. The tool is called INVITES-IN (IN VITro Experimental Studies INternal validity). In this protocol, three of the four studies that will be performed to create the release version of INVITES-IN are described. In the first study, evaluation of existing assessment tools will be combined with focus group discussions to identify how characteristics of the design or conduct of an in vitro study can affect its internal validity. Bias domains and items considered to be of relevance for in vitro studies will be identified. In the second study, group agreement on internal validity domains and items of importance for in vitro studies will be identified via a modified Delphi methodology. In the third study, the draft version of the tool will be created, based on the data on relevance and importance of bias domains and items collected in Studies 1 and 2. A separate protocol will be prepared for the fourth study, which includes the user testing and validation of the tool, and collection of users' experience.

Wildfire Smoke Exposure during Pregnancy: A Review of Potential Mechanisms of Placental Toxicity, Impact on Obstetric Outcomes, and Strategies to Reduce Exposure.

Climate change is accelerating the intensity and frequency of wildfires globally. Understanding how wildfire smoke (WS) may lead to adverse pregnancy outcomes and alterations in placental function via biological mechanisms is critical to mitigate the harms of exposure. We aim to review the literature surrounding WS, placental biology, biological mechanisms underlying adverse pregnancy outcomes as well as interventions and strategies to avoid WS exposure in pregnancy. This review includes epidemiologic and experimental laboratory-based studies of WS, air pollution, particulate matter (PM), and other chemicals related to combustion in relation to obstetric outcomes and placental biology. We summarized the available clinical, animal, and placental studies with WS and other combustion products such as tobacco, diesel, and wood smoke. Additionally, we reviewed current recommendations for prevention of WS exposure. We found that there is limited data specific to WS; however, studies on air pollution and other combustion sources suggest a link to inflammation, oxidative stress, endocrine disruption, DNA damage, telomere shortening, epigenetic changes, as well as metabolic, vascular, and endothelial dysregulation in the maternal-fetal unit. These alterations in placental biology contribute to adverse obstetric outcomes that disproportionally affect the most vulnerable. Limiting time outdoors, wearing N95 respirator face masks and using high quality indoor air filters during wildfire events reduces exposure to related environmental exposures and may mitigate morbidities attributable to WS.

Many-Body Correlations Are Non-negligible in Both Fragile and Strong Glassformers.

It is widely believed that the emergence of slow glassy dynamics is encoded in a material's microstructure. First-principles theory [mode-coupling theory (MCT)] is able to predict the dramatic slowdown of the dynamics from only static two-point correlations as input, yet it cannot capture all of the observed dynamical behavior. Here we go beyond two-point spatial correlation functions by extending MCT systematically to include higher-order static and dynamic correlations. We demonstrate that only adding the static triplet direct correlations already qualitatively changes the predicted glass-transition diagram of binary hard spheres and silica. Moreover, we find a nontrivial competition between static triplet correlations that work to stabilize the glass state and dynamic higher-order correlations that destabilize it for both materials. We conclude that the conventionally neglected static triplet direct correlations as well as higher-order dynamic correlations are, in fact, non-negligible in both fragile and strong glassformers.

Modeling the transplacental transfer of small molecules using machine learning: a case study on per- and polyfluorinated substances (PFAS).

BACKGROUND: Despite their large numbers and widespread use, very little is known about the extent to which per- and polyfluoroalkyl substances (PFAS) can cross the placenta and expose the developing fetus. OBJECTIVE: The aim of our study is to develop a computational approach that can be used to evaluate the of extend to which small molecules, and in particular PFAS, can cross to cross the placenta and partition to cord blood. METHODS: We collected experimental values of the concentration ratio between cord and maternal blood (RCM) for 260 chemical compounds and calculated their physicochemical descriptors using the cheminformatics package Mordred. We used the compiled database to, train and test an artificial neural network (ANN). And then applied the best performing model to predict RCM for a large dataset of PFAS chemicals (n = 7982). We, finally, examined the calculated physicochemical descriptors of the chemicals to identify which properties correlated significantly with RCM. RESULTS: We determined that 7855 compounds were within the applicability domain and 127 compounds are outside the applicability domain of our model. Our predictions of RCM for PFAS suggested that 3623 compounds had a log RCM > 0 indicating preferable partitioning to cord blood. Some examples of these compounds were bisphenol AF, 2,2-bis(4-aminophenyl)hexafluoropropane, and nonafluoro-tert-butyl 3-methylbutyrate. SIGNIFICANCE: These observations have important public health implications as many PFAS have been shown to interfere with fetal development. In addition, as these compounds are highly persistent and many of them can readily cross the placenta, they are expected to remain in the population for a long time as they are being passed from parent to offspring. IMPACT: Understanding the behavior of chemicals in the human body during pregnancy is critical in preventing harmful exposures during critical periods of development. Many chemicals can cross the placenta and expose the fetus, however, the mechanism by which this transport occurs is not well understood. In our study, we developed a machine learning model that describes the transplacental transfer of chemicals as a function of their physicochemical properties. The model was then used to make predictions for a set of 7982 per- and polyfluorinated alkyl substances that are listed on EPA's CompTox Chemicals Dashboard. The model can be applied to make predictions for other chemical categories of interest, such as plasticizers and pesticides. Accurate predictions of RCM can help scientists and regulators to prioritize chemicals that have the potential to cause harm by exposing the fetus.

Associations of per- and polyfluoroalkyl substances (PFAS) and their mixture with oxidative stress biomarkers during pregnancy.

BACKGROUND: Oxidative stress from excess reactive oxygen species (ROS) is a hypothesized contributor to preterm birth. Per- and polyfluoroalkyl substances (PFAS) exposure is reported to generate ROS in laboratory settings, and is linked to adverse birth outcomes globally. However, to our knowledge, the relationship between PFAS and oxidative stress has not been examined in the context of human pregnancy. OBJECTIVE: To investigate the associations between prenatal PFAS exposure and oxidative stress biomarkers among pregnant people. METHODS: Our analytic sample included 428 participants enrolled in the Illinois Kids Development Study and Chemicals In Our Bodies prospective birth cohorts between 2014 and 2019. Twelve PFAS were measured in second trimester serum. We focused on seven PFAS that were detected in >65 % of participants. Urinary levels of 8-isoprostane-prostaglandin-F2α, prostaglandin-F2α, 2,3-dinor-8-iso-PGF2α, and 2,3-dinor-5,6-dihydro-8-iso-PGF2α were measured in the second and third trimesters as biomarkers of oxidative stress. We fit linear mixed-effects models to estimate individual associations between PFAS and oxidative stress biomarkers. We used quantile g-computation and Bayesian kernel machine regression (BKMR) to assess associations between the PFAS mixture and averaged oxidative stress biomarkers. RESULTS: Linear mixed-effects models showed that an interquartile range increase in perfluorooctane sulfonic acid (PFOS) was associated with an increase in 8-isoprostane-prostaglandin-F2α (ß = 0.10, 95 % confidence interval = 0, 0.20). In both quantile g-computation and BKMR, and across all oxidative stress biomarkers, PFOS contributed the most to the overall mixture effect. The six remaining PFAS were not significantly associated with changes in oxidative stress biomarkers. CONCLUSIONS: Our study is the first to investigate the relationship between PFAS exposure and biomarkers of oxidative stress during human pregnancy. We found that PFOS was associated with elevated levels of oxidative stress, which is consistent with prior work in animal models and cell lines. Future research is needed to understand how prenatal PFAS exposure and maternal oxidative stress may affect fetal development.

Neutralizing antibody activity against SARS-CoV-2 variants in gestational age-matched mother-infant dyads after infection or vaccination.

Pregnancy confers unique immune responses to infection and vaccination across gestation. To date, there are limited data comparing vaccine- and infection-induced neutralizing Abs (nAbs) against COVID-19 variants in mothers during pregnancy. We analyzed paired maternal and cord plasma samples from 60 pregnant individuals. Thirty women vaccinated with mRNA vaccines (from December 2020 through August 2021) were matched with 30 naturally infected women (from March 2020 through January 2021) by gestational age of exposure. Neutralization activity against the 5 SARS-CoV-2 spike sequences was measured by a SARS-CoV-2-pseudotyped spike virion assay. Effective nAbs against SARS-CoV-2 were present in maternal and cord plasma after both infection and vaccination. Compared with WT spike protein, these nAbs were less effective against the Delta and Mu spike variants. Vaccination during the third trimester induced higher cord-nAb levels at delivery than did infection during the third trimester. In contrast, vaccine-induced nAb levels were lower at the time of delivery compared with infection during the first trimester. The transfer ratio (cord nAb level divided by maternal nAb level) was greatest in mothers vaccinated in the second trimester. SARS-CoV-2 vaccination or infection in pregnancy elicits effective nAbs with differing neutralization kinetics that are influenced by gestational time of exposure.

Integrated analysis of transcriptomic datasets to identify placental biomarkers of spontaneous preterm birth.

INTRODUCTION: Preterm birth (PTB) remains the leading cause of neonatal morbidity and mortality in the United States. The mechanisms underlying spontaneous PTB (SPTB) involve multiple physiological processes and molecular transformations at the level of the placenta. This study aimed to identify consistent molecular correlates in the placenta linked with SPTB by cross-examining publicly available transcriptomic datasets within two publicly available repositories. METHODS: The National Center for Biotechnology Information and the European Bioinformatics Institute were queried, and relevant datasets were independently normalized, and then merged based on similarity in design. Differentially expressed genes between SPTB and term delivery (TD) were identified using a fixed effects linear model (p < 0.0001) and were evaluated for enrichment of biological processes and pathways. In general, global signatures associated with SPTB were unique to each study. RESULTS: A total of three datasets were used in the meta-analysis to assess the placental transcriptome in SPTB (11 samples) as compared to TD (15 samples). We identified 174 differentially expressed genes consistently correlated with SPTB across all studies, including previously proposed and new candidate biomarkers of SPTB. Differentially expressed genes were significantly enriched for master regulatory pathways relevant to placental development and disease, including chromatin organization and cellular response to stress. DISCUSSION: Identification of differentially expressed genes and associated pathways across multiple studies may identify transcriptomic biomarkers that can be applied in clinical investigations of SPTB and provide researchers enhanced insight into the underlying etiologies of SPTB.

Modeling the filtration efficiency of a woven fabric: The role of multiple lengthscales.

During the COVID-19 pandemic, many millions have worn masks made of woven fabric to reduce the risk of transmission of COVID-19. Masks are essentially air filters worn on the face that should filter out as many of the dangerous particles as possible. Here, the dangerous particles are the droplets containing the virus that are exhaled by an infected person. Woven fabric is unlike the material used in standard air filters. Woven fabric consists of fibers twisted together into yarns that are then woven into fabric. There are, therefore, two lengthscales: the diameters of (i) the fiber and (ii) the yarn. Standard air filters have only (i). To understand how woven fabrics filter, we have used confocal microscopy to take three-dimensional images of woven fabric. We then used the image to perform lattice Boltzmann simulations of the air flow through fabric. With this flow field, we calculated the filtration efficiency for particles a micrometer and larger in diameter. In agreement with experimental measurements by others, we found that for particles in this size range, the filtration efficiency is low. For particles with a diameter of 1.5 µm, our estimated efficiency is in the range 2.5%-10%. The low efficiency is due to most of the air flow being channeled through relatively large (tens of micrometers across) inter-yarn pores. So, we conclude that due to the hierarchical structure of woven fabrics, they are expected to filter poorly.