The hair tales of women of color in Northern Manhattan: a qualitative analysis.

Introduction: Exposure to endocrine disrupting chemicals (EDCs), such as phthalates, can negatively impact maternal and child health, contributing to impaired fetal growth, preterm birth, and pregnancy complications, as well as increased downstream risks of cardiometabolic disease and breast cancer. Notably, women of color (WOC) are the largest consumers of personal care products, which are a common source of EDC exposure. Methods: The Let's Reclaim Our Ancestral Roots (Let's R.O.A.R) Pilot Study developed an educational intervention delivered during pregnancy to promote reduced use of phthalate-containing hair care products (HCPs). This mixed-methods study included: (1) a quantitative analysis and (2) a qualitative analysis of the educational sessions and the semi-structured focus groups to evaluate the factors that influenced the hair care practices and product choices of WOC at various stages of life, including their current pregnancy (hereafter referred to as the hair journey). During the sessions, participants learned about EDCs (with a focus on phthalates), the unequal burden of exposure for WOC, adverse implications of exposure, and exposure reduction strategies. Focus group sessions provided insight into participants' hair journeys from childhood to the current pregnancy and explored factors during their hair product selection process. All sessions were transcribed and imported into NVivo Version 12 for coding and thematic analysis. Results: A total of 46 individuals were enrolled in the study, and 31 participated in an educational session. This current work synthesizes the qualitative analysis of this study. We identified two important life stages (before and after gaining agency over hair care practices and product choices) and three dominant themes related to HCP use: (1) products that impacted the hair journey, which involved all mentions of hair products, (2) factors that influenced the hair journey, which included individuals or entities that shaped participants' hair experiences, and (3) the relationship between hair and sense of self, where sense of self was defined as the alignment of one's inner and outer beauty. Conclusion: The themes intersected and impacted the participants' hair journey. Cultural integration was a sub-theme that overlapped within the dominant themes and participants discussed the effect of traditions on their hair experiences.

Different mutation rates in the basal core promoter and precore regions between hepatitis B virus subgenotype F1b clusters.

Hepatitis B virus (HBV) is the main etiological agent of hepatocellular carcinoma (HCC) worldwide. It has been classified into nine genotypes and several subgenotypes, with uneven global distribution. There is growing evidence that the viral genotype influences the course and outcome of chronic hepatitis B infection. Two evolutionarily different clusters of the subgenotype F1b, called basal and cosmopolitan, have been described. The two clusters have constrained geographical distribution, with the particular feature that the basal cluster is present in regions of high HCC incidence, while the Cosmopolitan cluster is found in regions of low HCC incidence. The BCP/pC region was sequenced in 68 cases chronically infected with the F1b subgenotype to determine if there was a differential pattern of pathogenic-associated mutations between both clusters. Twenty-two of the 68 cases belonged to the subgenotype F1b basal cluster and 46 to the cosmopolitan cluster. Among the HBeAg-negative patients the A1762T/G1764A and G1896A mutations were more frequently found in the basal samples (85.7 and 92.9%) compared to the cosmopolitan ones (50 and 18.2%). Interestingly, no HBeAg loss-associated mutations were observed in 7.1 and 36.4% of the basal and cosmopolitan cases, respectively. The different rate of mutations associated with a more severe course of chronic hepatitis in the basal cluster would support the difference in the HCC incidence rate in the geographical regions where the basal cluster is restricted.

Identifying optimal vaccination scenarios to reduce varicella zoster virus transmission and reactivation.

BACKGROUND: Varicella zoster virus (VZV) is one of the eight known human herpesviruses. Initial VZV infection results in chickenpox, while viral reactivation following a period of latency manifests as shingles. Separate vaccines exist to protect against both initial infection and subsequent reactivation. Controversy regarding chickenpox vaccination is contentious with most countries not including the vaccine in their childhood immunization schedule due to the hypothesized negative impact on immune-boosting, where VZV reactivation is suppressed through exogenous boosting of VZV antibodies from exposure to natural chickenpox infections. METHODS: Population-level chickenpox and shingles notifications from Thailand, a country that does not vaccinate against either disease, were previously fitted with mathematical models to estimate rates of VZV transmission and reactivation. Here, multiple chickenpox and shingles vaccination scenarios were simulated and compared to a model lacking any vaccination to analyze the long-term impacts of VZV vaccination. RESULTS: As expected, simulations suggested that an introduction of the chickenpox vaccine, at any coverage level, would reduce chickenpox incidence. However, chickenpox vaccine coverage levels above 35% would increase shingles incidence under realistic estimates of shingles coverage with the current length of protective immunity from the vaccine. A trade-off between chickenpox and shingles vaccination coverage was discovered, where mid-level chickenpox coverage levels were identified as the optimal target to minimize total zoster burden. Only in scenarios where shingles vaccine provided lifelong immunity or coverage exceeded current levels could large reductions in both chickenpox and shingles be achieved. CONCLUSIONS: The complicated nature of VZV makes it impossible to select a single vaccination scenario as universal policy. Strategies focused on reducing both chickenpox and shingles incidence, but prioritizing the latter should maximize efforts towards shingles vaccination, while slowly incorporating chickenpox vaccination. Alternatively, countries may wish to minimize VZV complications of both chickenpox and shingles, which would lead to maximizing vaccine coverage levels across both diseases. Balancing the consequences of vaccination to overall health impacts, including understanding the impact of an altered mean age of infection for both chickenpox and shingles, would need to be considered prior to any vaccine introduction.

Cellular and transcriptional diversity over the course of human lactation.

Human breast milk (hBM) is a dynamic fluid that contains millions of cells, but their identities and phenotypic properties are poorly understood. We generated and analyzed single-cell RNA-sequencing (scRNA-seq) data to characterize the transcriptomes of cells from hBM across lactational time from 3 to 632 d postpartum in 15 donors. We found that the majority of cells in hBM are lactocytes, a specialized epithelial subset, and that cell-type frequencies shift over the course of lactation, yielding greater epithelial diversity at later points. Analysis of lactocytes reveals a continuum of cell states characterized by transcriptional changes in hormone-, growth factor-, and milk production-related pathways. Generalized additive models suggest that one subcluster, LC1 epithelial cells, increases as a function of time postpartum, daycare attendance, and the use of hormonal birth control. We identify several subclusters of macrophages in hBM that are enriched for tolerogenic functions, possibly playing a role in protecting the mammary gland during lactation. Our description of the cellular components of breast milk, their association with maternal­infant dyad metadata, and our quantification of alterations at the gene and pathway levels provide a detailed longitudinal picture of hBM cells across lactational time. This work paves the way for future investigations of how a potential division of cellular labor and differential hormone regulation might be leveraged therapeutically to support healthy lactation and potentially aid in milk production.

Characterizing the modern light environment and its influence on circadian rhythms.

Humans have largely supplanted natural light cycles with a variety of electric light sources and schedules misaligned with day-night cycles. Circadian disruption has been linked to a number of disease processes, but the extent of circadian disruption among the population is unknown. In this study, we measured light exposure and wrist temperature among residents of an urban area during each of the four seasons, as well as light illuminance in nearby outdoor locations. Daily light exposure was significantly lower for individuals, compared to outdoor light sensors, across all four seasons. There was also little seasonal variation in the realized photoperiod experienced by individuals, with the only significant difference occurring between winter and summer. We tested the hypothesis that differential light exposure impacts circadian phase timing, detected via the wrist temperature rhythm. To determine the influence of light exposure on circadian rhythms, we modelled the impact of morning and night-time light exposure on the timing of the maximum wrist temperature. We found that morning and night-time light exposure had significant but opposing impacts on maximum wrist temperature timing. Our results demonstrate that, within the range of exposure seen in everyday life, night-time light can delay the onset of the maximum wrist temperature, while morning light can lead to earlier onset. Our results demonstrate that humans are minimizing natural seasonal differences in light exposure, and that circadian shifts and disruptions may be a more regular occurrence in the general population than is currently recognized.

Social-distancing fatigue: Evidence from real-time crowd-sourced traffic data.

INTRODUCTION: To mitigate the COVID-19 pandemic and prevent overwhelming the healthcare system, social-distancing policies such as school closure, stay-at-home orders, and indoor dining closure have been utilized worldwide. These policies function by reducing the rate of close contact within populations and result in decreased human mobility. Adherence to social distancing can substantially reduce disease spread. Thus, quantifying human mobility and social-distancing compliance, especially at high temporal resolution, can provide great insight into the impact of social distancing policies. METHODS: We used the movement of individuals around New York City (NYC), measured via traffic levels, as a proxy for human mobility and the impact of social-distancing policies (i.e., work from home policies, school closure, indoor dining closure etc.). By data mining Google traffic in real-time, and applying image processing, we derived high resolution time series of traffic in NYC. We used time series decomposition and generalized additive models to quantify changes in rush hour/non-rush hour, and weekday/weekend traffic, pre-pandemic and following the roll-out of multiple social distancing interventions. RESULTS: Mobility decreased sharply on March 14, 2020 following declaration of the pandemic. However, levels began rebounding by approximately April 13, almost 2 months before stay-at-home orders were lifted, indicating premature increase in mobility, which we term social-distancing fatigue. We also observed large impacts on diurnal traffic congestion, such that the pre-pandemic bi-modal weekday congestion representing morning and evening rush hour was dramatically altered. By September, traffic congestion rebounded to approximately 75% of pre-pandemic levels. CONCLUSION: Using crowd-sourced traffic congestion data, we described changes in mobility in Manhattan, NYC, during the COVID-19 pandemic. These data can be used to inform human mobility changes during the current pandemic, in planning for responses to future pandemics, and in understanding the potential impact of large-scale traffic interventions such as congestion pricing policies.

Social-distancing Fatigue: Evidence from Real-time Crowd-sourced Traffic Data.

INTRODUCTION: To mitigate the COVID-19 pandemic and prevent overwhelming the healthcare system, social-distancing policies such as school closure, stay-at-home orders, and indoor dining closure have been utilized worldwide. These policies function by reducing the rate of close contact within populations and results in decreased human mobility. Adherence to social distancing can substantially reduce disease spread. Thus, quantifying human mobility and social-distancing compliance, especially at high temporal resolution, can provide great insight into the impact of social distancing policies. METHODS: We used the movement of individuals around New York City (NYC), measured via traffic levels, as a proxy for human mobility and the impact of social-distancing policies (i.e., work from home policies, school closure, indoor dining closure etc.). By data mining Google traffic in real-time, and applying image processing, we derived high resolution time series of traffic in NYC. We used time series decomposition and generalized additive models to quantify changes in rush hour/non-rush hour, and weekday/weekend traffic, pre-pandemic and following the roll-out of multiple social distancing interventions. RESULTS: Mobility decreased sharply on March 14, 2020 following declaration of the pandemic. However, levels began rebounding by approximately April 13, almost 2 months before stay-at-home orders were lifted, indicating premature increase in mobility, which we term social-distancing fatigue. We also observed large impacts on diurnal traffic congestion, such that the pre-pandemic bi-modal weekday congestion representing morning and evening rush hour was dramatically altered. By September, traffic congestion rebounded to approximately 75% of pre-pandemic levels. CONCLUSION: Using crowd-sourced traffic congestion data, we described changes in mobility in Manhattan, NYC, during the COVID-19 pandemic. These data can be used to inform human mobility changes during the current pandemic, in planning for responses to future pandemics, and in understanding the potential impact of large-scale traffic interventions such as congestion pricing policies.

Exploring the Seasonal Drivers of Varicella Zoster Virus Transmission and Reactivation.

Varicella zoster virus (VZV) is a herpesvirus that causes chickenpox and shingles. The biological mechanisms underpinning the multidecadal latency of VZV in the body and subsequent viral reactivation-which occurs in approximately 30% of individuals-are largely unknown. Because chickenpox and shingles are endemic worldwide, understanding the relationship between VZV transmission and reactivation is important for informing disease treatment and control. While chickenpox is a vaccine-preventable childhood disease with a rich legacy of research, shingles is not a notifiable disease in most countries. To date, population-level studies of shingles have had to rely on small-scale hospital or community-level data sets. Here, we examined chickenpox and shingles notifications from Thailand and found strong seasonal incidence in both diseases, with a 3-month lag between peak chickenpox transmission season and peak shingles reactivation. We tested and fitted 14 mathematical models examining the biological drivers of chickenpox and shingles over an 8-year period to estimate rates of VZV transmission, reactivation, and immunity-boosting, wherein reexposure to VZV boosts VZV-specific immunity to reinforce protection against shingles. The models suggested that the seasonal cycles of chickenpox and shingles have different underlying mechanisms, with ambient levels of ultraviolet radiation being correlated with shingles reactivation.

Socioeconomic Disparities in Subway Use and COVID-19 Outcomes in New York City.

Using data from New York City from January 2020 to April 2020, we found an estimated 28-day lag between the onset of reduced subway use and the end of the exponential growth period of severe acute respiratory syndrome coronavirus 2 within New York City boroughs. We also conducted a cross-sectional analysis of the associations between human mobility (i.e., subway ridership) on the week of April 11, 2020, sociodemographic factors, and coronavirus disease 2019 (COVID-19) incidence as of April 26, 2020. Areas with lower median income, a greater percentage of individuals who identify as non-White and/or Hispanic/Latino, a greater percentage of essential workers, and a greater percentage of health-care essential workers had more mobility during the pandemic. When adjusted for the percentage of essential workers, these associations did not remain, suggesting essential work drives human movement in these areas. Increased mobility and all sociodemographic variables (except percentage of people older than 75 years old and percentage of health-care essential workers) were associated with a higher rate of COVID-19 cases per 100,000 people, when adjusted for testing effort. Our study demonstrates that the most socially disadvantaged not only are at an increased risk for COVID-19 infection, they lack the privilege to fully engage in social distancing interventions.

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions.

BACKGROUND: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745.

Circadian Rhythms in Environmental Health Sciences.

PURPOSE OF REVIEW: This review aims to explore how circadian rhythms influence disease susceptibility and potentially modify the effect of environmental exposures. We aimed to identify biomarkers commonly used in environmental health research that have also been the subject of chronobiology studies, in order to review circadian rhythms of relevance to environmental health and determine if time-of-day is an important factor to consider in environmental health studies. Moreover, we discuss opportunities for studying how environmental exposures may interact with circadian rhythms to structure disease pathology and etiology. RECENT FINDINGS: In recent years, the study of circadian rhythms in mammals has flourished. Animal models revealed that all body tissues have circadian rhythms. In humans, circadian rhythms were also shown to exist at multiple levels of organization: molecular, cellular, and physiological processes, including responding to oxidative stress, cell trafficking, and sex hormone production, respectively. Together, these rhythms are an essential component of human physiology and can shape an individual's susceptibility and response to disease. Circadian rhythms are relatively unexplored in environmental health research. However, circadian clocks control many physiological and behavioral processes that impact exposure pathways and disease systems. We believe this review will motivate new studies of (i) the impact of exposures on circadian rhythms, (ii) how circadian rhythms modify the effect of environmental exposures, and (iii) how time-of-day impacts our ability to observe the body's response to exposure.

Socioeconomic disparities in subway use and COVID-19 outcomes in New York City.

BACKGROUND: The United States CDC has reported that racial and ethnic disparities in the COVID-19 pandemic may in part be due to socioeconomic disadvantages that require individuals to continue to work outside their home and a lack of paid sick leave. However, data-driven analyses of the socioeconomic determinants of COVID-19 burden are still needed. Using data from New York City (NYC), we aimed to determine how socioeconomic factors impact human mobility and COVID-19 burden. Methods/Summary: New York City has a large amount of heterogeneity in socioeconomic status (SES) and demographics among neighborhoods. We used this heterogeneity to conduct a cross-sectional spatial analysis of the associations between human mobility (i.e., subway ridership), sociodemographic factors, and COVID-19 incidence as of April 26, 2020. We also conducted a secondary analysis of NYC boroughs (which are equivalent to counties in the city) to assess the relationship between the decline in subway use and the time it took for each borough to end the exponential growth period of COVID-19 cases. FINDINGS: Areas with the lower median income, a greater percentage of individuals who identify as non-white and/or Hispanic/Latino, a greater percentage of essential workers, and a greater percentage of healthcare workers had more subway use during the pandemic. The positive associations between subway use and median income, and between subway use and percent non-white and/or Hispanic/Latino do not remain when adjusted for the percent of essential workers. This suggests essential work is what drives subway use in lower SES zip codes and communities of color. Increased subway use was associated with a higher rate of COVID-19 cases per 100,000 population when adjusted for testing effort (aRR=1.11; 95% CI: 1.03 - 1.19), but this association was weaker once we adjusted for median income (aRR=1.06; 95% CI: 1.00 - 1.12). All sociodemographic variables were significantly associated with the rate of positive cases per 100,000 population when adjusting for testing effort (except percent uninsured) and adjusting for both income and testing effort. The risk factor with the strongest association with COVID-19 was the percent of individuals in essential work (aRR = 1.59, 95% CI: 1.36 - 1.86). We found that subway use declined prior to any executive order, and there was an estimated 28-day lag between the onset of reduced subway use and the end of the exponential growth period of SARS-CoV-2 within New York City boroughs. INTERPRETATION: Our results suggest that the ability to stay home during the pandemic has been constrained by SES and work circumstances. Poorer neighborhoods are not afforded the same reductions in mobility as their richer counterparts. Furthermore, lower SES neighborhoods have higher disease burdens, which may be due to inequities in ability to shelter-in-place, and/or due to the plethora of other existing health disparities that increase vulnerability to COVID-19. Furthermore, the extended lag time between the dramatic fall in subway ridership and the end of the exponential growth phase for COVID-19 cases is important for future policy, because it demonstrates that if there is a resurgence, and stay-at-home orders are re-issued, then cities can expect to wait a month before reported cases will plateau.

Rescuing Troves of Hidden Ecological Data to Tackle Emerging Mosquito-Borne Diseases.

Despite the major impact of mosquitoes on human health, knowledge gaps exist regarding their natural population dynamics. Even the most basic information-such as spatiotemporal abundance-is mostly unavailable. In the USA, municipalities have created agencies for mosquito control and monitoring, yet no national open-access repository for mosquito surveillance data exists. Vectors, and the pathogens they transmit, know no jurisdictions. We identify >1,000 mosquito control agencies and identify those which make their population abundance surveillance data publicly available. We directly survey Floridian mosquito districts to estimate, from one state alone, the potential amount of hidden data. We generate a large, standardized data set from publicly available online data and demonstrate that spatiotemporal population abundance can be reconstructed and analyzed across data generators. We propose that the ensemble of US mosquito control agencies can, and should, be used to develop a national-and potentially international-open-access repository of mosquito surveillance data, generating the data capital needed to gain a mechanistic understanding of vector population dynamics, and identify existing digital infrastructure that could be leveraged for digitizing and collating extant and future surveillance data for such a repository.

Benefits and Challenges in Using Seroprevalence Data to Inform Models for Measles and Rubella Elimination.

Background: Control efforts for measles and rubella are intensifying globally. It becomes increasingly important to identify and reach remaining susceptible populations as elimination is approached. Methods: Serological surveys for measles and rubella can potentially measure susceptibility directly, but their use remains rare. In this study, using simulations, we outline key subtleties in interpretation associated with the dynamic context of age-specific immunity, highlighting how the patterns of immunity predicted from disease surveillance and vaccination coverage data may be misleading. Results: High-quality representative serosurveys could provide a more accurate assessment of immunity if challenges of conducting, analyzing, and interpreting them are overcome. We frame the core disease control and elimination questions that could be addressed by improved serological tools, discussing challenges and suggesting approaches to increase the feasibility and sustainability of the tool. Conclusions: Accounting for the dynamical context, serosurveys could play a key role in efforts to achieve and sustain elimination.

Preventing Zika Virus Infection during Pregnancy Using a Seasonal Window of Opportunity for Conception.

It has come to light that Zika virus (ZIKV) infection during pregnancy can result in trans-placental transmission to the fetus along with fetal death, congenital microcephaly, and/or Central Nervous System (CNS) malformations. There are projected to be >9,200,000 births annually in countries with ongoing ZIKV transmission. In response to the ZIKV threat, the World Health Organization (WHO) is strategically targeting prevention of infection in pregnant women and funding contraception in epidemic regions. I propose that the damaging effects of ZIKV can be reduced using a seasonal window of opportunity for conception that may minimize maternal exposure. Like other acute viral infections-including the related flavivirus, dengue virus (DENV)-the transmission of ZIKV is anticipated to be seasonal. By seasonally planning pregnancy, this aspect of pathogen ecology can be leveraged to align sensitive periods of gestation with the low-transmission season.

Effects of a grape-supplemented diet on proliferation and Wnt signaling in the colonic mucosa are greatest for those over age 50 and with high arginine consumption.

A diet rich in fruits and vegetables, and a grape-derived compound, resveratrol, have been linked to a reduced incidence of colon cancer. In vitro and in vivo, resveratrol suppresses Wnt signaling, a pathway constitutively activated in over 85 % of colon cancers.Thirty participants were placed on a low resveratrol diet and subsequently allocated to one of three groups ingesting 1/3-to-1 lb (0.15-0.45 kg) of grapes per day for 2 weeks. Dietary information was collected via 24-h recall. Colon biopsies for biomarker analysis were obtained pre- and post-grape and evaluated for the expression of Wnt pathway target genes and for markers of proliferation by RT-PCR and immunohistochemistry.Participants lost an average of 2 · 6 lb (1.2 kg, p = 0 · 0018) during the period of grape ingestion. The expression of CyclinD1 (p < 0 · 01), AXIN2, CD133 (p = 0 · 02) and Ki67 (p = 0 · 002) were all reduced after grape ingestion. Individuals over 50 years of age and those with high dietary arginine consumption had increased basal expression of CyclinD1, AXIN2, cMYC and CD133 (p value range 0 · 04 to <0 · 001) that, following grape ingestion, were reduced to levels seen in younger participants.The reduction in Wnt signaling and mucosal proliferation seen following short-term ingestion of 1/3-1 lb (0.15-0.45 kg) of grapes per day may reduce the risk of mutational events that can facilitate colon carcinogenesis. The potential benefit is most marked for high-risk older individuals and individuals whose diet is high in arginine intake. Dietary grape supplementation may play a role in colon cancer prevention for high-risk individuals.

Expression of the Wnt antagonist Dickkopf-3 is associated with prognostic clinicopathologic characteristics and impairs proliferation and invasion in endometrial cancer.

OBJECTIVE: Emerging evidence implicates the Wnt antagonist Dickkopf-3 (Dkk3) as a tumor suppressor and potential biomarker in solid tumors. We investigated whether Dkk3 plays an important role in the carcinogenesis of endometrial cancer (EC). METHODS: We analyzed Dkk3 mRNA expression via real-time RT-PCR in twenty-seven human primary EC tissues, and six matched normal endometrial controls. Dkk3 levels were correlated with various clinicopathologic characteristics. Additionally, enforced Dkk3 expression was examined in proliferation and tumorigenesis in vitro and in vivo, using MTT, soft agar assay, invasion assay, a xenograft mouse model, and a ß-catenin-responsive SuperTopFlash luciferase assay. RESULTS: Compared with matched normal endometrial cases, Dkk3 was down-regulated in EC (p<0.0001). Among cancer cases, Dkk3 expression was significantly reduced in patients with higher stage (p=0.002), positive pelvic lymph nodes (p=0.0004), non-endometrioid histology (p=0.02), and cytology-positive ECs (p=0.02). Enforced expression of Dkk3 in EC cell lines showed reduced proliferation (p<0.0001), anchorage-independent growth (p=0.005), invasion (p=0.02), and reduced TCF activity (p=0.04), confirming Dkk3 as a negative regulator of the ß-catenin/Wnt signaling pathway. Tumor growth in Dkk3-injected mice was not statistically different, though did plateau towards the end, and was associated with increased lymphoid infiltration and tumor necrosis. CONCLUSION: Dkk3 gene expression is frequently downregulated in endometrial cancer, and is associated with poor prognostic clinicopathologic markers. The results also identify a role for Dkk3 as a tumor suppressor in EC, affecting both proliferation and invasiveness. These findings may prove to be important in the design of novel biomarkers and treatment modalities for advanced EC.