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Post-ischemic changes in cellular metabolism alter myocardial and neurological function. Pyruvate dehydrogenase (PDH), the limiting step in mitochondrial glucose oxidation, is inhibited by increased expression of PDH kinase (PDK) during ischemia/reperfusion injury. This results in decreased utilization of glucose to generate cellular ATP. Post-cardiac arrest (CA) hypothermia improves outcomes and alters metabolism, but its influence on PDH and PDK activity following CA are unknown. We hypothesized that therapeutic hypothermia (TH) following CA is associated with the inhibition of PDK activity and increased PDH activity. We further hypothesized that an inhibitor of PDK activity, dichloroacetate (DCA), would improve PDH activity and post-CA outcomes.Anesthetized and ventilated adult female C57BL/6 wild-type mice underwent a 12-minute KCl-induced CA followed by cardiopulmonary resuscitation. Compared to normothermic (37°C) CA controls, administering TH (30°C) improved overall survival (72-hour survival rate: 62.5% vs. 28.6%, P

The Hawkesbury-Nepean valley is one of the largest coastal basins in NSW. It supports the local agriculture industry and is an important environmental asset. Due to its narrow sandstone gorges, which create natural choke points, floodwaters from its major tributaries can rapidly back up, rise and spill out onto the flood plain. Thus, the valley is flood-prone, with a history of disastrous events, aggravated by a constrained road network for evacuation. Two flood events occurred in the Hawkesbury-Nepean valley in 2020 and 2021, however, the impact of each of those events was different in terms of lives lost (2 fatalities compared to none) and economic losses (more than AUD 2 billion compared to less than AUD 1 billion). In this study, reasons for the variation in impacts are explored by determining an inundation likelihood map, derived using a combination of the height above nearest drainage method and streamflow forecasts, and considering antecedent hydrological and climate conditions.

The Australian Bureau of Meteorology has developed a national hydrological projections (NHP) service for Australia. The NHP aimed to provide nationally consistent hydrological projections across jurisdictional boundaries to support planning of water-dependent industries. NHP is complementary to those previously produced by federal and state governments, universities, and other organisations for limited geographical domains. The projections comprise an ensemble of application-ready bias-corrected climate model data, derived hydrological projections at daily temporal and 0.05° × 0.05° spatial resolution for the period 1960–2099, and two emission scenarios (Representative Concentration Pathway (RCP) 4.5 and RCP8.5). The spatial resolution of the projections matches that of gridded historical reference data used to perform the bias correction and the Bureau of Meteorology's operational gridded hydrological model. Three bias correction techniques were applied to four CMIP5 global climate models (GCMs), and one method was applied to a regional climate model (RCM) forced by the same four GCMs, resulting in a 16-member ensemble of bias-corrected GCM data for each emission scenario. The bias correction was applied to fields of precipitation, minimum and maximum temperature, downwelling shortwave radiation, and surface winds. These variables are required inputs to the Bureau of Meteorology's landscape water balance hydrological model (AWRA-L), which was forced using the bias-corrected GCM and RCM data to produce a 16-member ensemble of hydrological output. The hydrological output variables include root zone soil moisture (moisture in the top 1 m soil layer), potential evapotranspiration, and runoff. Here we present an overview of the production of the hydrological projections, including GCM selection, bias correction methods and their evaluation, technical aspects of their implementation, and examples of analysis performed to construct the NHP service. The data are publicly available on the National Computing Infrastructure (https://doi.org/10.25914/6130680dc5a51, Bureau of Meteorology, 2021), and a user interface is accessible at https://awo.bom.gov.au/products/projection/ (last access: 24 November 2023).

Oncolytic viruses (OVs) are being extensively studied for their potential roles in the development of cancer therapy regimens. In addition to their direct lytic effects, OVs can initiate and drive systemic antitumor immunity indirectly via release of tumor antigen, as well as by encoding and delivering immunostimulatory molecules. This combination makes them an effective platform for the development of immunotherapeutic strategies beyond their primary lytic function. Engineering the viruses to also express tumor-associated antigens (TAAs) allows them to simultaneously serve as therapeutic vaccines, targeting and amplifying an immune response to TAAs. Our group and others have shown that vaccinating intratumorally with a poxvirus that encodes TAAs, in addition to immune stimulatory molecules, can modulate the tumor microenvironment, overcome immune inhibitory pathways, and drive both local and systemic tumor specific immune responses.

High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, many of the existing global- to continental-scale hydrological models are applied at coarse resolution and neglect more complex processes such as lateral surface and groundwater flow, thereby not capturing smaller-scale hydrologic processes. Applications of high-resolution and physically based integrated hydrological models are often limited to watershed scales, neglecting the mesoscale climate effects on the water cycle. We implemented an integrated, physically based coupled land surface groundwater model, ParFlow-CLM version 3.6.0, over a pan-European model domain at 0.0275∘ (∼3 km) resolution. The model simulates a three-dimensional variably saturated groundwater-flow-solving Richards equation and overland flow with a two-dimensional kinematic wave approximation, which is fully integrated with land surface exchange processes. A comprehensive evaluation of multiple hydrologic variables including discharge, surface soil moisture (SM), evapotranspiration (ET), snow water equivalent (SWE), total water storage (TWS), and water table depth (WTD) resulting from a 10-year (1997–2006) model simulation was performed using in situ and remote sensing (RS) observations. Overall, the uncalibrated ParFlow-CLM model showed good agreement in simulating river discharge for 176 gauging stations across Europe (average Spearman's rank correlation (R) of 0.77). At the local scale, ParFlow-CLM model performed well for ET (R>0.94) against eddy covariance observations but showed relatively large differences for SM and WTD (median R values of 0.7 and 0.50, respectively) when compared with soil moisture networks and groundwater-monitoring-well data. However, model performance varied between hydroclimate regions, with the best agreement to RS datasets being shown in semi-arid and arid regions for most variables. Conversely, the largest differences between modeled and RS datasets (e.g., for SM, SWE, and TWS) are shown in humid and cold regions. Our findings highlight the importance of including multiple variables using both local-scale and large-scale RS datasets in model evaluations for a better understanding of physically based fully distributed hydrologic model performance and uncertainties in water and energy fluxes over continental scales and across different hydroclimate regions. The large-scale, high-resolution setup also forms a basis for future studies and provides an evaluation reference for climate change impact projections and a climatology for hydrological forecasting considering the effects of lateral surface and groundwater flows.

A simple and effective two-step data assimilation framework was developed to improve soil moisture representation in an operational large-scale water balance model. The first step is a Kalman-filter-type sequential state updating process that exploits temporal covariance statistics between modelled and satellite-derived soil moisture to produce analysed estimates. The second step is to use analysed surface moisture estimates to impart mass conservation constraints (mass redistribution) on related states and fluxes of the model using tangent linear modelling theory in a post-analysis adjustment after the state updating at each time step. In this study, we assimilate satellite soil moisture retrievals from both Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) missions simultaneously into the Australian Water Resources Assessment Landscape model (AWRA-L) using the proposed framework and evaluate its impact on the model's accuracy against in situ observations across water balance components. We show that the correlation between simulated surface soil moisture and in situ observation increases from 0.54 (open loop) to 0.77 (data assimilation). Furthermore, indirect verification of root-zone soil moisture using remotely sensed Enhanced Vegetation Index (EVI) time series across cropland areas results in significant improvements from 0.52 to 0.64 in correlation. The improvements gained from data assimilation can persist for more than 1 week in surface soil moisture estimates and 1 month in root-zone soil moisture estimates, thus demonstrating the efficacy of this data assimilation framework.

Accurate and reliable hydrologic simulations are important for many applications such as water resources management, future water availability projections and predictions of extreme events. However, the accuracy of water balance estimates is limited by the lack of large-scale observations, model simulation uncertainties and biases related to errors in model structure and uncertain inputs (e.g., hydrologic parameters and atmospheric forcings). The availability of long-term and global remotely sensed soil moisture offers the opportunity to improve model estimates through data assimilation with complete spatiotemporal coverage. In this study, we assimilated the European Space Agency (ESA) Climate Change Initiative (CCI) derived soil moisture (SM) information to improve the estimation of continental-scale soil moisture and runoff. The assimilation experiment was conducted over a time period 2000–2006 with the Community Land Model, version 3.5 (CLM3.5), integrated with the Parallel Data Assimilation Framework (PDAF) at a spatial resolution of 0.0275∘ (∼3 km) over Europe. The model was forced with the high-resolution reanalysis COSMO-REA6 from the Hans Ertel Centre for Weather Research (HErZ). The performance of assimilation was assessed against open-loop model simulations and cross-validated with independent ESA CCI-derived soil moisture (CCI-SM) and gridded runoff observations. Our results showed improved estimates of soil moisture, particularly in the summer and autumn seasons when cross-validated with independent CCI-SM observations. The assimilation experiment results also showed overall improvements in runoff, although some regions were degraded, especially in central Europe. The results demonstrated the potential of assimilating satellite soil moisture observations to produce downscaled and improved high-resolution soil moisture and runoff simulations at the continental scale, which is useful for water resources assessment and monitoring.

Geoscientific modeling is constantly evolving, with next-generation geoscientific models and applications placing large demands on high-performance computing (HPC) resources. These demands are being met by new developments in HPC architectures, software libraries, and infrastructures. In addition to the challenge of new massively parallel HPC systems, reproducibility of simulation and analysis results is of great concern. This is due to the fact that next-generation geoscientific models are based on complex model implementations and profiling, modeling, and data processing workflows. Thus, in order to reduce both the duration and the cost of code migration, aid in the development of new models or model components, while ensuring reproducibility and sustainability over the complete data life cycle, an automated approach to profiling, porting, and provenance tracking is necessary. We propose a run control framework (RCF) integrated with a workflow engine as a best practice approach to automate profiling, porting, provenance tracking, and simulation runs. Our RCF encompasses all stages of the modeling chain: (1) preprocess input, (2) compilation of code (including code instrumentation with performance analysis tools), (3) simulation run, and (4) postprocessing and analysis, to address these issues. Within this RCF, the workflow engine is used to create and manage benchmark or simulation parameter combinations and performs the documentation and data organization for reproducibility. In this study, we outline this approach and highlight the subsequent developments scheduled for implementation born out of the extensive profiling of ParFlow. We show that in using our run control framework, testing, benchmarking, profiling, and running models is less time consuming and more robust than running geoscientific applications in an ad hoc fashion, resulting in more efficient use of HPC resources, more strategic code development, and enhanced data integrity and reproducibility.

Introduction Laboratory testing is a fundamental diagnostic and prognostic tool to ensure the quality of healthcare, treatment, and responses. This study aimed to evaluate the cost of laboratory tests performed for patients undergoing chemotherapy treatment in the oncology treatment center at Johns Hopkins Aramco Healthcare in Saudi Arabia. Additionally, we aimed to reduce the cost of unnecessary laboratory tests in a 1-year period. Methods This was a quality improvement study with a quasi-experimental design using DMAIC methodology. The intervention strategy involved educating staff about adhering to the British Columbia Cancer Agency (BCCA) guidelines when ordering laboratory tests for chemotherapy patients, then integrating those guidelines into the electronic health record system. Data were collected for 200 randomly selected cases with 10 different chemotherapy protocols before and after the intervention. A paired t test was used to analyze differences in mean cost for all laboratory tests and unnecessary testing before and after the intervention. Results A significant cost reduction was achieved for unnecessary laboratory tests (77%, p < 0.01) when following the BCCA guidelines. In addition, the mean cost of all laboratory tests (including necessary and unnecessary) was significantly reduced by 45.5% (p = 0.023). Conclusion Lean thinking in clinical practice, realized by integrating a standardized laboratory test guided by BCCA guidelines into the electronic health record, significantly reduced financial costs within 1 year, thereby enhancing efficient resource utilization in the organization. This quality improvement project may serve to increase awareness of further efforts to improve resource utilization for other oncology treatment protocols.

Microalgae are multi-purpose microbial agents due to their capability to efficiently sequester carbon dioxide and produce valuable biomass such as protein and single-cell oils. Formulation and tuning of microalgae kinetics models can significantly contribute to the successful design and operation of microalgae reactors. This work aimed to demonstrate the capability of self-organizing map (SOM) algorithm to elucidate the patterns of parameter rankings in microalgae models subject to stochastic variations of input forcing functions–bioprocess influent component concentration levels. These stochastic variations were implemented on a modeled chemostat with a deterministic microalgae kinetic model consists of ten time-dependent variables and eighteen model parameters. The methodology consists of two major stages: (1) global sensitivity analysis (GSA) on the importance of model parameters with stochastic sampling of bioreactor influent component concentrations, and (2) training of self-organizing maps on the datasets of model parameter rankings derived from the GSA indices. Results reveal that functional principal components analysis can project at least 99% of the time-dependent dynamic patterns of the model variables on B-splines basis functions. The component planes for hexagonal lattice SOMs reveal that the sensitivity rankings some parameters in the algae model tested can be stable over a wide range of variations in the levels of influent component concentrations. Therefore, SOM can be used to reveal the trends in multi-dimensional data arrays arising from the implementation of GSA of kinetic models under stochastic perturbation of input forcing functions.

We present a velocity-resolved reverberation mapping analysis of the hypervariable quasar RM160 (SDSS J141041.25+531849.0) at z = 0.359 with 153 spectroscopic epochs of data representing a 10 yr baseline (2013–2023). We split the baseline into two regimes based on the 3× flux increase in the light curve: a “low state” phase during the years 2013–2019 and a “high state” phase during the years 2022–2023. The velocity-resolved lag profiles (VRLPs) indicate that gas with different kinematics dominates the line emission in different states. The H β VRLP begins with a signature of inflow onto the broad-line region (BLR) in the low state, while in the high state it is flatter with less signature of inflow. The H α VRLP begins consistent with a virialized BLR in the low state, while in the high state shows a signature of inflow. The differences in the kinematics between the Balmer lines and between the low state and the high state suggests complex BLR dynamics. We find that the BLR radius and velocity (both FWHM and σ ) do not obey a constant virial product throughout the monitoring period. We find that the BLR lags and continuum luminosity are correlated, consistent with rapid response of the BLR gas to the illuminating continuum. The BLR kinematic profile changes in unpredictable ways that are not related to continuum changes and reverberation lag. Our observations indicate that nonvirial kinematics can significantly contribute to observed line profiles, suggesting caution for black hole mass estimation in luminous and highly varying quasars like RM160.

This work studies the relationship between accretion-disk size and quasar properties, using a sample of 95 quasars from the Sloan Digital Sky Survey Reverberation Mapping Project with measured lags between the g and i photometric bands. Our sample includes disk lags that are both longer and shorter than predicted by the Shakura and Sunyaev model, requiring explanations that satisfy both cases. Although our quasars each have one lag measurement, we explore the wavelength-dependent effects of diffuse broad-line region (BLR) contamination through our sample’s broad redshift range, 0.1 < z < 1.2. We do not find significant evidence of variable diffuse Fe ii and Balmer nebular emission in the rms spectra, nor from Anderson–Darling tests of quasars in redshift ranges with and without diffuse nebular emission falling in the observed-frame filters. Contrary to previous work, we do not detect a significant correlation between the measured continuum and BLR lags in our luminous quasar sample, similarly suggesting that our continuum lags are not dominated by diffuse nebular emission. Similar to other studies, we find that quasars with larger-than-expected continuum lags have lower 3000 Å luminosities, and we additionally find longer continuum lags with lower X-ray luminosities and black hole masses. Our lack of evidence for diffuse BLR contribution to the lags indicates that the anticorrelation between continuum lag and luminosity is not likely to be due to the Baldwin effect. Instead, these anticorrelations favor models in which the continuum lag increases in lower-luminosity active galactic nuclei, including scenarios featuring magnetic coupling between the accretion disk and X-ray corona, and/or ripples or rims in the disk.

Cellular metabolism is a critical regulator of macrophage effector function. Tissue-resident alveolar macrophages (TR-AMs) inhabit a unique niche marked by high oxygen and low glucose. We have recently shown that in contrast to bone marrow-derived macrophages (BMDMs), TR-AMs do not utilize glycolysis and instead predominantly rely on mitochondrial function for their effector response. It is not known how changes in local oxygen concentration that occur during conditions such as acute respiratory distress syndrome (ARDS) might affect TR-AM metabolism and function; however, ARDS is associated with progressive loss of TR-AMs, which correlates with the severity of disease and mortality. Here, we demonstrate that hypoxia robustly stabilizes HIF-1α in TR-AMs to promote a glycolytic phenotype. Hypoxia altered TR-AM metabolite signatures, cytokine production, and decreased their sensitivity to the inhibition of mitochondrial function. By contrast, hypoxia had minimal effects on BMDM metabolism. The effects of hypoxia on TR-AMs were mimicked by FG-4592, a HIF-1α stabilizer. Treatment with FG-4592 decreased TR-AM death and attenuated acute lung injury in mice. These findings reveal the importance of microenvironment in determining macrophage metabolic phenotype and highlight the therapeutic potential in targeting cellular metabolism to improve outcomes in diseases characterized by acute inflammation.

Post-activation potentiation has proven to be an effective strategy to enhance performance for many tasks, but little research has been conducted specifically concerning endurance sport performance. This study examined whether 5-km run performance could be improved by completing pre-run strides while wearing a 6.8 kg weighted compression garment (LOAD). A counter-balanced crossover field study design was incorporated with NCAA Division I Cross Country runners (n = 10) during coach-led, official team pre-season “speed day” practices. On Monday of Week 1, testing participants completed a course preview run and strategy session with their coach as they would do in preparation for a meet. The following two Mondays, participants completed the 5-km run as quickly as possible while blinded to pace. The team’s habitual warmup routine was used, which included a 3.22-km run followed by a series of dynamic warm-up movements before four, 80-m strides were completed with LOAD or without load (CON). Average wet-bulb globe temperature for both sessions was 22.3 °C. CON did not differ (p>0.05) from LOAD in split times for kilometres 0.00-1.61 (339±13 vs 341±13 s), 1.61-3.22 (312±15 vs 312±16 s), 3.22-4.83 (339±21 vs 338±22 s), or the 0.17 km distance kick at the end of the run (71±16 vs 69±14 s). Overall time was also not improved for LOAD (1060±49 s) versus CON (1062±55 s). The ~10% body mass LOAD warm-up strategy failed to improve early, mid-, or finishing kick performance in a 5-km time-trial with well-trained runners.

We present a high-cadence multiepoch analysis of dramatic variability of three broad emission lines (Mg ii , H β , and H α ) in the spectra of the luminous quasar ( λ L _λ (5100 Å) = 4.7 × 10 ^44 erg s ^−1 ) SDSS J141041.25+531849.0 at z = 0.359 with 127 spectroscopic epochs over nine years of monitoring (2013–2022). We observe anticorrelations between the broad emission-line widths and flux in all three emission lines, indicating that all three broad emission lines “breathe” in response to stochastic continuum variations. We also observe dramatic radial velocity shifts in all three broad emission lines, ranging from Δ v ∼ 400 km s ^−1 to ∼800 km s ^−1 , that vary over the course of the monitoring period. Our preferred explanation for the broad-line variability is complex kinematics in the gas in the broad-line region. We suggest a model for the broad-line variability that includes a combination of gas inflow with a radial gradient, an azimuthal asymmetry (e.g., a hot spot), superimposed on the stochastic flux-driven changes to the optimal emission region (“line breathing”). Similar instances of line-profile variability due to complex gas kinematics around quasars are likely to represent an important source of false positives in radial velocity searches for binary black holes, which typically lack the kind of high-cadence data we analyze here. The long-duration, wide-field, and many-epoch spectroscopic monitoring of SDSS-V BHM-RM provides an excellent opportunity for identifying and characterizing broad emission-line variability, and the inferred nature of the inner gas environment, of luminous quasars.

Introduction: Patients with coronavirus disease 2019 (COVID-19) can develop rapidly progressive respiratory failure. Ventilation strategies during the COVID-19 pandemic seek to minimize patient mortality. In this study we examine associations between the availability of emergency department (ED)-initiated high-flow nasal cannula (HFNC) for patients presenting with COVID-19 respiratory distress and outcomes, including rates of endotracheal intubation (ETT), mortality, and hospital length of stay. Methods: We performed a retrospective, non-concurrent cohort study of patients with COVID-19 respiratory distress presenting to the ED who required HFNC or ETT in the ED or within 24 hours following ED departure. Comparisons were made between patients presenting before and after the introduction of an ED-HFNC protocol. Results: Use of HFNC was associated with a reduced rate of ETT in the ED (46.4% vs 26.3%, P

Background: Cardiopulmonary resuscitation (CPR) in adults following non-traumatic out of hospital cardiac arrest (OHCA) can cause thoracic complications including rib fractures, sternal fractures, and pneumothorax. Post-CPR complication rates are poorly studied and the optimum imaging modality to detect these complications post-resuscitation has not been established. Methods: We performed a retrospective review of adult patients transported to a single, urban, academic hospital following atraumatic OHCA between September 2015 and January 2020. Patients who achieved sustained return of spontaneous circulation (ROSC) and who underwent computed tomography (CT) imaging of the chest following radiographic chest x-ray were included in the analyses. Patient demographics and prehospital data were collected. Descriptive statistics and multivariate logistic regression analysis were performed. Sensitivity and specificity of chest x-ray for the detection of thoracic injury in this population were estimated. Results: 786 non-traumatic OHCA patients were transported to the ED, 417 of whom obtained sustained ROSC and were admitted to the hospital (53%). 137 (32.9%) admitted patients underwent CT imaging of the chest in the ED. Of these imaged patients median age was 62 years old (IQR 53–70) with 54.0% female and 38.0% of patients having received bystander CPR. 40/137 (29.2%) patients had skeletal fractures noted on CT imaging and 12/137 (8.8%) had pneumothorax present on CT imaging. X-ray yielded a sensitivity of 7.5% for rib fracture and 50% for pneumothorax with a specificity of 100% for both. Logistic regression analysis revealed no significant association between age, sex, bystander CPR, or resuscitation length with thoracic fractures or pneumothorax. Conclusions: Complications from OHCA CPR were high with 29.2% of CT imaged patients having rib fractures and 8.8% having pneumothoraces. X-ray had poor sensitivity for these post-resuscitation complications. Post-CPR CT imaging of the chest should be considered for detecting post-CPR complications.

United States and European Union trademark laws have common foundations in the Paris Convention for the Protection of Industrial Property and also in the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS Agreement). As parties to these international agreements, both jurisdictions are obligated to adhere to certain fundamental parameters regarding trademark law and its enforcement. Despite these shared roots, a comparison of the European Court of Justice’s ruling in L’Oréal v. Bellure with the factually similar US Ninth Circuit Court of Appeals case Smith v. Chanel reveals a divergence between the US and the EU in these two jurisdictions’ construal of the interaction between trademark law and comparative advertising law. This variance reflects differences in the cultural and policy considerations behind these jurisdictions’ creation of the laws. Ultimately, however, it is due to fundamental differences in subsequent interpretations of those laws, as illustrated by diverging developments in the relevant case law. An understanding of these differences and developments can help clarify not only the reasons for their emergence, but may also help predict future directions the laws may take. This paper is divided into four main sections. Section 1 presents an overview of comparative advertising laws in the EU and the US, providing background for the case law discussion that follows. Section 2 delves further into these jurisdictions’ respective trademark and comparative advertising laws to reveal their interrelationship, the foundations upon which they are based, and the values they are intended to protect. Section 3 reviews the cases at issue in light of those laws and proposes that the divergence in laws between the EU and US stems primarily from opposing interpretations of anti-dilution laws. This divergence then triggers different interpretations regarding the way in which trademark law should intersect with comparative advertising law. Section 4 suggests that the Max Planck Institute’s Study on the Overall Functioning of the European Trade Mark System indicates that in the future, the EU laws are likely to align more closely with their US counterparts, if certain proposals made by the Institute are implemented by the European Commission.

Most women with breast cancer in sub-Saharan Africa (SSA) are diagnosed with late-staged disease. The current study assesses patient-related barriers among women from a general SSA population to better understand how patient-related barriers contribute to diagnostic delays. Using convenience-based sampling, 401 Ugandan women without breast cancer were surveyed to determine how prior participation in cancer detection practices correlate with patient-related barriers to prompt diagnosis. In a predominantly poor (76%) and rural population (75%), the median age of the participants was 38. Of the women surveyed, 155 (46%) had prior exposure to breast cancer education, 92 (27%) performed breast self-examination (BSE) and 68 (20%) had undergone a recent clinical breast examination (CBE), breast ultrasound or breast biopsy. The most commonly identified barriers to prompt diagnosis were knowledge deficits regarding early diagnosis (79%), economic barriers to accessing care (68%), fear (37%) and poor social support (24%). However, only women who reported knowledge deficits-a modifiable barrier-were less likely to participate in cancer detection practices (p