Solving the Puzzle of Preterm Birth.

Solving the puzzle of preterm birth has been challenging and will require novel integrative solutions as preterm birth likely arises from many etiologies. It has been demonstrated that many sociodemographic and psychological determinants of preterm birth relate to its complex biology. It is this understanding that has enabled the development of a novel preventative strategy, which integrates the omics profile (genome, epigenome, transcriptome, proteome, metabolome, microbiome) with sociodemographic, environmental, and psychological determinants of individual pregnant people to solve the puzzle of preterm birth.

Understanding the effects of oxytocin receptor variants on OXT-OXT receptor binding: A mathematical model.

Approximately half of U.S. women giving birth annually receive Pitocin, the synthetic form of oxytocin (OXT), yet its effective dose can vary significantly. This variability presents safety concerns due to unpredictable responses, which may lead to adverse outcomes for both mother and baby. To address the need for improved dosing, we developed a data-driven mathematical model to predict OXT receptor (OXTR) binding. Our study focuses on five prevalent OXTR variants (V45L, P108A, L206V, V281M, and E339K) and their impact on OXT-OXTR binding dynamics in two distinct cell types: human embryonic kidney cells (HEK293T), commonly used in experimental systems, and human myometrial smooth muscle cells, containing endogenous OXTR. We parameterized the model with cell-specific OXTR surface localization measurements. To strengthen the robustness of our study, we conducted a comprehensive meta-analysis of OXT- OXTR binding, enabling parameterization of our model with cell-specific OXT-OXTR binding kinetics (myometrial OXT-OXTR K d = 1.6 nM, kon = 6.8 × 10 5 M -1 min -1 , and koff = 0.0011 min -1 ). Our meta-analysis revealed significant homogeneity in OXT-OXTR affinity across experiments and species with a K d = 0.52 - 9.32 nM and mean K d = 1.48 ± 0.36 nM. Our model achieves several valuable insights into designing dosage strategies. First, we predicted that the OXTR complex reaches maximum occupancy at 10 nM OXT in myometrial cells and at 1 µM in HEK293T cells. This information is pivotal for guiding experimental design and data interpretation when working with these distinct cell types, emphasizing the need to consider effects for specific cell types when choosing OXTR-transfected cell lines. Second, our model recapitulated the significant effects of genetic variants for both experimental and physiologically relevant systems, with V281M and E339K substantially compromising OXT-OXTR binding capacity. These findings suggest the need for personalized oxytocin dosing based on individual genetic profiles to enhance therapeutic efficacy and reduce risks, especially in the context of labor and delivery. Third, we demonstrated the potential for rescuing the attenuated cell response observed in V281M and E339K variants by increasing the OXT dosage at specific, early time points. Cellular responses to OXT, including Ca 2+ release, manifest within minutes. Our model indicates that providing V281M- and E339K-expressing cells with doubled OXT dose during the initial minute of binding can elevate OXT-OXTR complex formation to levels comparable to wild-type OXTR. In summary, our study provides a computational framework for precision oxytocin dosing strategies, paving the way for personalized medicine.

Dietary risk factors for hypertensive disorders of pregnancy.

OBJECTIVE: To assess whether diet quality and specific dietary components are associated with hypertensive disorders of pregnancy (HDP). STUDY DESIGN: Nested case control study in a prospectively collected cohort of 450 participants with singleton pregnancies who completed the National Institutes of Health Diet Health Questionnaire II (DHQ-II) in the third trimester or within 3 months of delivery. Patients with fetal anomalies, conception by in-vitro fertilization, and deliveries at outside hospitals were excluded from the original prospective cohort study. Cases were patients diagnosed with HDP and controls were patients without HDP. Cases and controls were matched by BMI class in a 1:2 ratio. Exposures of interest were HEI-2015 score components and other DHQ-II dietary components including minerals, caffeine, and water. These dietary components were compared between cohorts using univariate analyses. MAIN OUTCOME MEASURES: HEI-2015 total scores representing diet quality, component scores, and objective background data between patients with HDP and patients without HDP. RESULTS: 150 patients with HDP were matched to 300 controls without HDP. Baseline demographics were similar between groups, including BMI. Patients with HDP were less likely to have high quality diets (HEI ≥ 70) than controls (7.3 % v 15.7 %, P = 0.02). HDP were associated with significantly higher dairy, saturated fat, and sodium intake compared to controls. Other components were similar between groups. CONCLUSION: Patients with HDP are more likely to have lower diet quality and higher consumption of sodium, dairy, and saturated fats. These results can be used to study antenatal diet modification in patients at high risk of HDP.

Quantification of surface-localized and total oxytocin receptor in myometrial smooth muscle cells.

Oxytocin acts through the oxytocin receptor (OXTR) to modulate uterine contractility. We previously identified OXTR genetic variants and showed that, in HEK293T cells, two of the OXTR protein variants localized to the cell surface less than wild-type OXTR. Here, we sought to measure OXTR in the more native human myometrial smooth muscle cell (HMSMC) line on both the cell-surface and across the whole cell, and used CRISPR editing to add an HA tag to the endogenous OXTR gene for anti-HA measurement. Quantitative flow cytometry revealed that these cells possessed 55,000 ± 3200 total OXTRs and 4900 ± 390 cell-surface OXTRs per cell. To identify any differential wild-type versus variant localization, we transiently transfected HMSMCs to exogenously express wild-type or variant OXTR with HA and green fluorescent protein tags. Total protein expression of wild-type OXTR and all tested variants were similar. However, the two variants with lower surface localization in HEK293T cells also presented lower surface localization in HMSMCs. Overall, we confirm the differential surface localization of variant OXTR in a more native cell type, and further demonstrate that the quantitative flow cytometry technique is adaptable to whole-cell measurements.

Mapping uterine calcium dynamics during the ovulatory cycle in live mice.

Uterine contraction patterns vary during the ovulatory cycle and throughout pregnancy but prior measurements have produced limited and conflicting information on these patterns. We combined a virally delivered genetically encoded calcium reporter (GCaMP8m) and ultra-widefield imaging in live nonpregnant mice to characterize uterine calcium dynamics at organ scale throughout the estrous cycle. Prior to ovulation (proestrus and estrus) uterine excitations primarily initiated in a region near the oviduct, but after ovulation (metestrus and diestrus), excitations initiated at loci homogeneously distributed throughout the organ. The frequency of excitation events was lowest in proestrus and estrus, higher in metestrus and highest in diestrus. These results establish a platform for mapping uterine activity, and show that the question of whether there is an anatomically localized trigger for uterine excitations depends on the estrous cycle phase.

Disentangling Socioeconomic Status and Race in Infant Brain, Birth Weight, and Gestational Age at Birth: A Neural Network Analysis.

Background: Race is commonly used as a proxy for multiple features including socioeconomic status. It is critical to dissociate these factors, to identify mechanisms that affect infant outcomes, such as birth weight, gestational age, and brain development, and to direct appropriate interventions and shape public policy. Methods: Demographic, socioeconomic, and clinical variables were used to model infant outcomes. There were 351 participants included in the analysis for birth weight and gestational age. For the analysis using brain volumes, 280 participants were included after removing participants with missing magnetic resonance imaging scans and those matching our exclusion criteria. We modeled these three different infant outcomes, including infant brain, birth weight, and gestational age, with both linear and nonlinear models. Results: Nonlinear models were better predictors of infant birth weight than linear models (R2 = 0.172 vs. R2 = 0.145, p = .005). In contrast to linear models, nonlinear models ranked income, neighborhood disadvantage, and experiences of discrimination higher in importance than race while modeling birth weight. Race was not an important predictor for either gestational age or structural brain volumes. Conclusions: Consistent with the extant social science literature, the findings related to birth weight suggest that race is a linear proxy for nonlinear factors related to structural racism. Methods that can disentangle factors often correlated with race are important for policy in that they may better identify and rank the modifiable factors that influence outcomes.

Sleep and circadian rhythms during pregnancy, social disadvantage, and alterations in brain development in neonates.

Pregnant women in poverty may be especially likely to experience sleep and circadian rhythm disturbances, which may have downstream effects on fetal neurodevelopment. However, the associations between sleep and circadian rhythm disturbances, social disadvantage during pregnancy, and neonatal brain structure remains poorly understood. The current study explored the association between maternal sleep and circadian rhythm disturbances during pregnancy and neonatal brain outcomes, examining sleep and circadian rhythm disturbances as a mediator of the effect of social disadvantage during pregnancy on infant structural brain outcomes. The study included 148 mother-infant dyads, recruited during early pregnancy, who had both actigraphy and neuroimaging data. Mothers' sleep was assessed throughout their pregnancy using actigraphy, and neonates underwent brain magnetic resonance imaging in the first weeks of life. Neonatal structural brain outcomes included cortical gray matter, subcortical gray matter, and white matter volumes along with a measure of the total surface area of the cortex. Neonates of mothers who experienced greater inter-daily deviations in sleep duration had smaller total cortical gray and white matter volumes and reduced cortical surface areas. Neonates of mothers who had higher levels of circadian misalignment and later sleep timing during pregnancy showed smaller subcortical gray matter volumes. Inter-daily deviations in sleep duration during pregnancy mediated the association between maternal social disadvantage and neonatal structural brain outcomes. Findings highlight the importance of regularity and rhythmicity in sleep schedules during pregnancy and bring to light the role of chronodisruption as a potential mechanism underlying the deleterious neurodevelopmental effects of prenatal adversity. RESEARCH HIGHLIGHTS: Social disadvantage was associated with sleep and circadian rhythm disturbances during pregnancy, including later sleep schedules, increased variability in sleep duration, circadian misalignment, and a higher proportion of the sleep period spent awake. Maternal sleep and circadian rhythm disturbances during pregnancy were associated with decreased brain volume and reduced cortical surface area in neonates. Maternal inter-daily deviations in sleep duration during pregnancy mediated the association between social disadvantage and neonatal brain volume and cortical surface area.

BKCa channels are involved in spontaneous and lipopolysaccharide-stimulated uterine contraction in late gestation mice†.

The large-conductance, voltage-gated, calcium (Ca2+)-activated potassium channel (BKCa) is one of the most abundant potassium channels in the myometrium. Previous work conducted by our group has identified a link between inflammation, BKCa channels and excitability of myometrial smooth muscle cells. Here, we investigate the role of BKCa channels in spontaneous and lipopolysaccharide (LPS)-stimulated uterine contraction to gain a better understanding of the relationship between the BKCa channel and uterine contraction in basal and inflammatory states. Uteri of C57BL/6 J mice on gestational day 18.5 (GD18.5) were obtained and either fixed in formalin or used immediately for tension recording or isolation of primary myocytes for patch-clamp. Paraffin sections were used for immunofluorescenctdetection of BKCa and Toll-like receptor (TLR4). For tension recordings, LPS was administered to determine its effect on uterine contractions. Paxilline, a BKCa inhibitor, was used to dissect the role of BKCa in uterine contraction in basal and inflammatory states. Finally, patch-clamp recordings were performed to investigate the relationship between LPS, the BKCa channel and membrane currents in mouse myometrial smooth muscle cells (mMSMCs). We confirmed the expression of BKCa and TLR4 in the myometrium of GD18.5 mice and found that inhibiting BKCa channels with paxilline suppressed both spontaneous and LPS-stimulated uterine contractions. Furthermore, application of BKCa inhibitors (paxilline or iberiotoxin) after LPS inhibited BKCa channel activity in mMSMCs. Moreover, pretreatment with BKCa inhibitor or the TLR4 inhibitor suppressed LPS-activated BKCa currents. Our study demonstrates that BKCa channels are involved in both basal and LPS-stimulated uterine contraction in pregnant mice.

The Association between Mode of Transportation Support and Research Study Visit Attendance among Pregnant Patients.

OBJECTIVE: This study aimed to examine the association between transportation assistance and study visits, and explore differences by transportation modality. STUDY DESIGN: This was a secondary analysis of prospective cohort study. We identified patients requesting transportation support for research ultrasound visits and identified controls (1:2 ratio) who did not request support matched for age, race, and insurance type. Conditional logistic regression examined the association between transportation support and mode of transportation with study visit attendance. RESULTS: Transportation support was requested by 57/1,184 (4.8%) participants. Participants that requested transportation support were three times more likely to attend visits than their matched controls (adjusted odds ratio [aOR] 3.16, 95% confidence interval [CI]: 1.76-5.68). Among visits with transportation support, those supported by a ridesharing service had five-fold higher odds of attendance than visits supported with taxi service (aOR 5.06, 95% CI: 1.50-16.98). CONCLUSION: Transportation support, especially a ridesharing service, is associated with improved attendance at research study visits in a sample of predominantly low-income, Black, pregnant participants. Implementing transportation support may be a promising strategy to improve engagement in research studies. KEY POINTS: · Participants utilizing transportation assistance were more likely to attend study appointments.. · Participants using ridesharing had higher likelihood of attendance than those using taxi service.. · Transportation assistance may improve research engagement for historically marginalized people..

Risk of pre-term birth as a function of sleep quality and obesity: prospective analysis in a large Prematurity Research Cohort.

Study Objective: To investigate whether poor sleep quality is associated with pre-term birth (PTB) risk, overall and independent of sleep apnea and habitual snoring. Methods: We used longitudinal data from the Washington University Prematurity Research Cohort to investigate the association between poor sleep quality (defined as a Pittsburgh Sleep Quality Index > 5) and PTB, overall and independent of sleep apnea and snoring (defined by the Berlin questionnaire and prior sleep clinic attendance). Associations were investigated for sleep quality early and throughout pregnancy. Stratified analyses were performed by factors previously shown to modify associations between sleep and PTB (race, pre-pregnancy obesity). Results: Of the 976 eligible participants, 50.1% experienced poor sleep quality early in pregnancy (<20 completed weeks) and 14.2% delivered pre-term (n = 50 without and 89 with poor sleep quality). In multivariable-adjusted analyses, poor sleep quality early in pregnancy was associated with increased PTB risk (hazard ratio [HR] = 1.48, 95% confidence interval [CI] = 1.02-2.14). This association persisted after further adjustment for sleep apnea and snoring (HR = 1.50, 95% CI = 1.02-2.20) and in analyses stratified by race. It varied, however, by pre-pregnancy obesity. Among individuals without obesity, no association was observed between poor sleep and PTB (HR = 1.08, 95% CI = 0.65-1.79), whereas among those with obesity, a positive association was observed (HR = 2.94, 95% CI = 1.52-5.69, p-interaction = .05). This association was limited to individuals with obesity who experienced poor sleep both earlier and later in pregnancy (HR = 3.94, 95% CI = 1.56-9.99). Conclusion: Our findings suggest that improving sleep quality early in pregnancy may be important for PTB prevention, particularly among individuals with obesity.

The Association Between Maternal Cortisol and Infant Amygdala Volume Is Moderated by Socioeconomic Status.

Background: It has been well established that socioeconomic status is associated with mental and physical health as well as brain development, with emerging data suggesting that these relationships begin in utero. However, less is known about how prenatal socioeconomic environments interact with the gestational environment to affect neonatal brain volume. Methods: Maternal cortisol output measured at each trimester of pregnancy and neonatal brain structure were assessed in 241 mother-infant dyads. We examined associations between the trajectory of maternal cortisol output across pregnancy and volumes of cortisol receptor-rich regions of the brain, including the amygdala, hippocampus, medial prefrontal cortex, and caudate. Given the known effects of poverty on infant brain structure, socioeconomic disadvantage was included as a moderating variable. Results: Neonatal amygdala volume was predicted by an interaction between maternal cortisol output across pregnancy and socioeconomic disadvantage (standardized ß = -0.31, p < .001), controlling for postmenstrual age at scan, infant sex, and total gray matter volume. Notably, amygdala volumes were positively associated with maternal cortisol for infants with maternal disadvantage scores 1 standard deviation below the mean (i.e., less disadvantage) (simple slope = 123.36, p < .01), while the association was negative in infants with maternal disadvantage 1 standard deviation above the mean (i.e., more disadvantage) (simple slope = -82.70, p = .02). Individuals with disadvantage scores at the mean showed no association, and there were no significant interactions in the other brain regions examined. Conclusions: These data suggest that fetal development of the amygdala is differentially affected by maternal cortisol production at varying levels of socioeconomic advantage.

Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity.

Preterm birth (PTB) is the leading cause of infant mortality globally. Research has focused on developing predictive models for PTB without prioritizing cost-effective interventions. Physical activity and sleep present unique opportunities for interventions in low- and middle-income populations (LMICs). However, objective measurement of physical activity and sleep remains challenging and self-reported metrics suffer from low-resolution and accuracy. In this study, we use physical activity data collected using a wearable device comprising over 181,944 h of data across N = 1083 patients. Using a new state-of-the art deep learning time-series classification architecture, we develop a 'clock' of healthy dynamics during pregnancy by using gestational age (GA) as a surrogate for progression of pregnancy. We also develop novel interpretability algorithms that integrate unsupervised clustering, model error analysis, feature attribution, and automated actigraphy analysis, allowing for model interpretation with respect to sleep, activity, and clinical variables. Our model performs significantly better than 7 other machine learning and AI methods for modeling the progression of pregnancy. We found that deviations from a normal 'clock' of physical activity and sleep changes during pregnancy are strongly associated with pregnancy outcomes. When our model underestimates GA, there are 0.52 fewer preterm births than expected (P = 1.01e - 67, permutation test) and when our model overestimates GA, there are 1.44 times (P = 2.82e - 39, permutation test) more preterm births than expected. Model error is negatively correlated with interdaily stability (P = 0.043, Spearman's), indicating that our model assigns a more advanced GA when an individual's daily rhythms are less precise. Supporting this, our model attributes higher importance to sleep periods in predicting higher-than-actual GA, relative to lower-than-actual GA (P = 1.01e - 21, Mann-Whitney U). Combining prediction and interpretability allows us to signal when activity behaviors alter the likelihood of preterm birth and advocates for the development of clinical decision support through passive monitoring and exercise habit and sleep recommendations, which can be easily implemented in LMICs.

Social and psychological adversity are associated with distinct mother and infant gut microbiome variations.

Health disparities are driven by underlying social disadvantage and psychosocial stressors. However, how social disadvantage and psychosocial stressors lead to adverse health outcomes is unclear, particularly when exposure begins prenatally. Variations in the gut microbiome and circulating proinflammatory cytokines offer potential mechanistic pathways. Here, we interrogate the gut microbiome of mother-child dyads to compare high-versus-low prenatal social disadvantage, psychosocial stressors and maternal circulating cytokine cohorts (prospective case-control study design using gut microbiomes from 121 dyads profiled with 16 S rRNA sequencing and 89 dyads with shotgun metagenomic sequencing). Gut microbiome characteristics significantly predictive of social disadvantage and psychosocial stressors in the mothers and children indicate that different discriminatory taxa and related pathways are involved, including many species of Bifidobacterium and related pathways across several comparisons. The lowest inter-individual gut microbiome similarity was observed among high-social disadvantage/high-psychosocial stressors mothers, suggesting distinct environmental exposures driving a diverging gut microbiome assembly compared to low-social disadvantage/low-psychosocial stressors controls (P = 3.5 × 10-5 for social disadvantage, P = 2.7 × 10-15 for psychosocial stressors). Children's gut metagenome profiles at 4 months also significantly predicted high/low maternal prenatal IL-6 (P = 0.029), with many bacterial species overlapping those identified by social disadvantage and psychosocial stressors. These differences, based on maternal social and psychological status during a critical developmental window early in life, offer potentially modifiable targets to mitigate health inequities.

Social disadvantage during pregnancy: effects on gestational age and birthweight.

OBJECTIVE: Whether psychosocial adversity during pregnancy impacts fetal health outcomes at birth remains underexplored. This is a critical issue given significant social disadvantage and psychosocial stress faced by pregnant women worldwide. STUDY DESIGN: Measures of social disadvantage and psychological factors, and medical/reproductive and nutritional health status in pregnant women were obtained at each trimester. Using Structural Equation Modeling (SEM), we investigated the relationship of forms of adversity to each other and to infant gestational age, and birthweight. RESULTS: Among 399 singletons, Social Disadvantage significantly predicted gestational age (p = 0.003), and residual birthweight (p = 0.006). There was a 0.4 week decrease in gestational age and a 3% decrease in birthweight for each standard deviation increase in Social Disadvantage. CONCLUSION: Significant negative effects of social adversity on the developing fetus were found. Notably, these effects emerged despite good prenatal care and after accounting for maternal age and medical reproductive risk factors.

Association between Maternal Serum Lipids and Intrapartum Oxytocin Requirements during Labor Induction and Augmentation.

OBJECTIVE: This study aimed to investigate the relationship between maternal serum lipid parameters and oxytocin requirements among women with term vaginal deliveries. STUDY DESIGN: In this secondary analysis of a prospective cohort study, women who presented for delivery at ≥37 weeks' gestation and received oxytocin during their labor were included. Maternal serum was collected intrapartum. The cohort was stratified into two groups based on maximum oxytocin infusion dose during labor. Primary outcomes were maternal total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride levels. Generalized linear regression models were used to assess the association between lipid parameters and maximum oxytocin dose requirements while controlling for potential confounders. For secondary analyses, the cohort was stratified by HDL-C into two groups. Multivariable logistic regression was used to evaluate the relationship between low maternal HDL-C and additional intrapartum oxytocin parameters. RESULTS: There were no differences in maternal total cholesterol, LDL-C, or triglyceride values between high and low maximum oxytocin groups. Median serum HDL-C was significantly lower among women in the high oxytocin group compared with those in the low oxytocin group (56 vs. 62 mg/dL, p < 0.01). For every 0.26 mg/dL lower HDL-C, women had 1 mU/min higher maximum oxytocin infusion dose during labor. Women with low serum HDL-C were also more likely to require maximum oxytocin doses above the 75th percentile (adjusted odds ratio [aOR]: 1.99, 95% confidence interval [CI]: 1.06-3.75) and above the 90th percentile (aOR: 2.47, 95% CI: 1.10-5.54). Among women undergoing induction of labor, low serum HDL-C was also associated with longer duration of oxytocin infusion (aOR: 2.07, 95% CI: 1.02-4.20). CONCLUSION: Low maternal HDL-C levels at term are associated with higher maximum oxytocin infusion doses among women undergoing labor induction or augmentation. Given the growing prevalence of metabolic syndrome in the United States and persistently high rates of cesarean delivery, HDL-C or its components may present a new target for predicting and improving labor outcomes. KEY POINTS: · Serum HDL-C at term is inversely correlated with oxytocin infusion doses at term.. · Low maternal serum HDL-C is associated with higher oxytocin requirements during labor induction or augmentation.. · No association between maternal serum total cholesterol, LDL-C, or triglyceride levels and oxytocin requirements in labor..

A multidisciplinary Prematurity Research Cohort Study.

BACKGROUND: Worldwide, 10% of babies are born preterm, defined as a live birth before 37 weeks of gestation. Preterm birth is the leading cause of neonatal death, and survivors face lifelong risks of adverse outcomes. New approaches with large sample sizes are needed to identify strategies to predict and prevent preterm birth. The primary aims of the Washington University Prematurity Research Cohort Study were to conduct three prospective projects addressing possible causes of preterm birth and provide data and samples for future research. STUDY DESIGN: Pregnant patients were recruited into the cohort between January 2017 and January 2020. Consenting patients were enrolled into the study before 20 weeks' gestation and followed through delivery. Participants completed demographic and lifestyle surveys; provided maternal blood, placenta samples, and cord blood; and participated in up to three projects focused on underlying physiology of preterm birth: cervical imaging (Project 1), circadian rhythms (Project 2), and uterine magnetic resonance imaging and electromyometrial imaging (Project 3). RESULTS: A total of 1260 participants were enrolled and delivered during the study period. Of the participants, 706 (56%) were Black/African American, 494 (39%) were nulliparous, and 185 (15%) had a previous preterm birth. Of the 1260 participants, 1220 (97%) delivered a live infant. Of the 1220 with a live birth, 163 (14.1%) had preterm birth, of which 74 (6.1%) were spontaneous preterm birth. Of the 1220 participants with a live birth, 841 participated in cervical imaging, 1047 contributed data and/or samples on circadian rhythms, and 39 underwent uterine magnetic resonance imaging. Of the 39, 25 underwent electromyometrial imaging. CONCLUSION: We demonstrate feasibility of recruiting and retaining a diverse cohort in a complex prospective, longitudinal study throughout pregnancy. The extensive clinical, imaging, survey, and biologic data obtained will be used to explore cervical, uterine, and endocrine physiology of preterm birth and can be used to develop novel approaches to predict and prevent preterm birth.

Absolute Quantification of Plasma Membrane Receptors Via Quantitative Flow Cytometry.

Plasma membrane receptors are transmembrane proteins that initiate cellular response following the binding of specific ligands (e.g., growth factors, hormones, and cytokines). The abundance of plasma membrane receptors can be a diagnostic or prognostic biomarker in many human diseases. One of the best techniques for measuring plasma membrane receptors is quantitative flow cytometry (qFlow). qFlow employs fluorophore-conjugated antibodies against the receptors of interest and corresponding fluorophore-loaded calibration beads offers standardized and reproducible measurements of plasma membrane receptors. More importantly, qFlow can achieve absolute quantification of plasma membrane receptors when phycoerythrin (PE) is the fluorophore of choice. Here we describe a detailed qFlow protocol to obtain absolute receptor quantities on the basis of PE calibration. This protocol is foundational for many previous and ongoing studies in quantifying tyrosine kinase receptors and G-protein-coupled receptors with in vitro cell models and ex vivo cell samples.

Estrogen metabolites increase nociceptor hyperactivity in a mouse model of uterine pain.

Pain emanating from the female reproductive tract is notoriously difficult to treat, and the prevalence of transient pelvic pain has been placed as high as 70%-80% in women surveyed. Although sex hormones, especially estrogen, are thought to underlie enhanced pain perception in females, the underlying molecular and cellular mechanisms are not completely understood. Here, we showed that the pain-initiating TRPA1 channel was required for pain-related behaviors in a mouse model of estrogen-induced uterine pain in ovariectomized female mice. Surprisingly, 2- and 4-hydroxylated estrogen metabolites (2- and 4-HEMs) in the estrogen hydroxylation pathway, but not estrone, estradiol, or 16-HEMs, directly increased nociceptor hyperactivity through TRPA1 and TRPV1 channels, and picomolar concentrations of 2- and 4-hydroxylation estrone (2- or 4-OHE1) could sensitize TRPA1 channel function. Moreover, both TRPA1 and TRPV1 were expressed in uterine-innervating primary nociceptors, and their expression was increased in the estrogen-induced uterine pain model. Importantly, pretreatment with 2- or 4-OHE1 recapitulated estrogen-induced uterine pain-like behaviors, and intraplantar injections of 2- and 4-OHE1 directly produced a TRPA1-dependent mechanical hypersensitivity. Our findings demonstrated that TRPA1 is critically involved in estrogen-induced uterine pain-like behaviors, which may provide a potential drug target for treating female reproductive tract pain.

Sleep behavior and chronotype before and throughout pregnancy.

STUDY OBJECTIVE: To compare sleep behavior before and during pregnancy. METHODS: In this prospective cohort study, healthy women were followed from pre-pregnancy until delivery. At pre-pregnancy and each trimester, participants completed validated questionnaires of chronotype and sleep quality and timing, including the Munich ChronoType Questionnaire, Epworth Sleepiness Scale, and Pittsburgh Sleep Quality Index. The primary outcomes were sleep period start and end times, sleep duration, sleep midpoint, and social jetlag, compared between pre-pregnancy and each trimester. Wrist actigraphy was used to measure the same outcomes in a subset of participants. RESULTS: Eighty-six women were included in analysis of questionnaires. Of these, 37 provided complete actigraphy data. Questionnaire and actigraphy data indicate that participants had less social jetlag during pregnancy than before pregnancy. Sleep period start times were earlier on both work and free days in the first and second trimesters than pre-pregnancy, and returned to pre-pregnancy times by the third trimester. Actigraphy data revealed that, compared to pre-pregnancy, participants had longer sleep periods in all trimesters on work days and in the first trimester on free days. Sleep surveys revealed that participants had poorer sleep quality in the first and third trimesters and more sleepiness in the first trimester than pre-pregnancy. CONCLUSION: The first trimester of pregnancy is characterized by earlier sleep period start time, longer sleep duration, and poorer sleep quality than pre-pregnancy. Sleep quality temporarily improves in the second trimester, and sleep period start time returns to pre-pregnancy time by the third trimester. STUDY RATIONALE: Multiple parameters of sleep have been studied in the context of pregnancy and pregnancy outcomes, but rarely in comparison to pre-pregnancy or longitudinally through pregnancy. STUDY IMPACT: Actigraphy and questionnaire data reveal sleep timing and quality change throughout pregnancy. These data on sleep changes in healthy pregnancy can be used as a baseline to identify sleep-related risk factors throughout pregnancy.