Decidual-Secreted Factors Alter Invasive Trophoblast Membrane and Secreted Proteins Implying a Role for Decidual Cell Regulation of Placentation

Inadequate or inappropriate implantation and placentation during the establishment of human pregnancy is thought to lead to first trimester miscarriage, placental insufficiency and other obstetric complications. To create the placental blood supply, specialized cells, the ‘extravillous trophoblast’ (EVT) invade through the differentiated uterine endometrium (the decidua) to engraft and remodel uterine spiral arteries. We hypothesized that decidual factors would regulate EVT function by altering the production of EVT membrane and secreted factors. We used a proteomics approach to identify EVT membrane and secreted proteins regulated by decidual cell factors. Human endometrial stromal cells were decidualized in vitro by treatment with estradiol (10−8 M), medroxyprogesterone acetate (10−7 M) and cAMP (0.5 mM) for 14 days. Conditioned media (CM) was collected on day 2 (non-decidualized CM) and 14 (decidualized CM) of treatment. Isolated primary EVT cultured on Matrigel™ were treated with media control, non-decidualized or decidualized CM for 16 h. EVT CM was fractionated for proteins <30 kDa using size-exclusion affinity nanoparticles (SEAN) before trypsin digestion and HPLC-MS/MS. 43 proteins produced by EVT were identified; 14 not previously known to be expressed in the placenta and 12 which had previously been associated with diseases of pregnancy including preeclampsia. Profilin 1, lysosome associated membrane glycoprotein 1 (LAMP1), dipeptidyl peptidase 1 (DPP1/cathepsin C) and annexin A2 expression by interstitial EVT in vivo was validated by immunhistochemistry. Decidual CM regulation in vitro was validated by western blotting: decidualized CM upregulated profilin 1 in EVT CM and non-decidualized CM upregulated annexin A2 in EVT CM and pro-DPP1 in EVT cell lysate. Here, non-decidualized factors induced protease expression by EVT suggesting that non-decidualized factors may induce a pro-inflammatory cascade. Preeclampsia is a pro-inflammatory condition. Overall, we have demonstrated the potential of a proteomics approach to identify novel proteins expressed by EVT and to uncover the mechanisms leading to disease states

Automated Force Volume Image Processing for Biological Samples

Atomic force microscopy (AFM) has now become a powerful technique for investigating on a molecular level, surface forces, nanomechanical properties of deformable particles, biomolecular interactions, kinetics, and dynamic processes. This paper specifically focuses on the analysis of AFM force curves collected on biological systems, in particular, bacteria. The goal is to provide fully automated tools to achieve theoretical interpretation of force curves on the basis of adequate, available physical models. In this respect, we propose two algorithms, one for the processing of approach force curves and another for the quantitative analysis of retraction force curves. In the former, electrostatic interactions prior to contact between AFM probe and bacterium are accounted for and mechanical interactions operating after contact are described in terms of Hertz-Hooke formalism. Retraction force curves are analyzed on the basis of the Freely Jointed Chain model. For both algorithms, the quantitative reconstruction of force curves is based on the robust detection of critical points (jumps, changes of slope or changes of curvature) which mark the transitions between the various relevant interactions taking place between the AFM tip and the studied sample during approach and retraction. Once the key regions of separation distance and indentation are detected, the physical parameters describing the relevant interactions operating in these regions are extracted making use of regression procedure for fitting experiments to theory. The flexibility, accuracy and strength of the algorithms are illustrated with the processing of two force-volume images, which collect a large set of approach and retraction curves measured on a single biological surface. For each force-volume image, several maps are generated, representing the spatial distribution of the searched physical parameters as estimated for each pixel of the force-volume image

Effects of perceived cost, service quality, and customer satisfaction on health insurance service continuance

This paper aims to contribute to the universal discourse on financial services continuance behavior by examining the impact of service cost on customers\u27 service-quality perception and service continuance intention. It presents the results of an empirical study that has explored the impacts of service cost, service quality, and customer satisfaction on health insurance customers\u27 behavioral intention toward continuing or discontinuing with their service providers. Very few studies had examined the impact of service cost on service-quality perception. Our study attempts to fill that gap. A sample of 820 customers was surveyed, and 624 usable responses were analyzed with ANOVA, standard multiple regression, and logistic regression. Our findings indicate that, although highly satisfied health insurance customers will most likely retain their current service providers, customer dissatisfaction does not necessarily lead to discontinuance. Our results also provide some operational implications for health insurance managers, with strategies for reducing attrition and improving customer retention

Coal-mine fire-related fine particulate matter and medical-service utilization in Australia: a time-series analysis from the Hazelwood Health Study

BackgroundThis study assessed the association between coal-mine-fire-related fine particulate matter (PM2.5) and medical-service utilization, following a 6-week coal-mine fire in Australia, in 2014. Areas in the immediate vicinity of the mine experienced hourly mine-fire-related PM2.5 concentrations of up to 3700 μg/m3.MethodsData on medical-service utilization were collected from the Medicare Benefits Schedule—a national database of payment for medical services. PM2.5 concentrations were modelled using atmospheric chemical transport modelling. Quasi-Poisson interrupted distributed lag time-series analysis examined the association between daily mine-fire-related PM2.5 concentrations and medical-service utilization, including General Practitioner (GP) consultations and respiratory, cardiovascular and mental health services. Confounders included seasonality, long-term trend, day of the week, maximum daily temperature and public holidays. Gender and age stratification were conducted.ResultsA 10-μg/m3 increase in PM2.5 was associated with an increased relative risk of service usage for all long and short GP consultations [11% (95% confidence interval: 7 to 15%)] and respiratory services [22% (4 to 43%)] in both men and women. Sex stratification found an increased relative risk in mental health consultations in men [32% (2 to 72%)] but not women. No associations were found for cardiovascular services in men or women.ConclusionsCoal-mine-fire-related PM2.5 exposure was associated with increased use of medical services for GP consultations and respiratory services in men and women and mental health consultations in men. These findings can inform the development of future public-health-policy responses in the event of major air-pollution episodes

Fine particulate matter exposure and medication dispensing during and after a coal mine fire: A time series analysis from the Hazelwood Health Study

Limited research has examined the impacts of coal mine fire smoke on human health. The aim of this study was to assess the association between prolonged smoke PM2.5 exposure from a brown coal mine fire that burned over a seven week period in 2014 and medications dispensed across five localities in South-eastern Victoria, Australia. Spatially resolved PM2.5 concentrations were retrospectively estimated using a dispersion model coupled with a chemical transport model. Data on medications dispensed were collected from the national Pharmaceutical Benefits Schedule database for 2013-2016. Poisson distributed lag time series analysis was used to examine associations between daily mine fire-related PM2.5 concentrations and daily counts of medications dispensed for respiratory, cardiovascular or psychiatric conditions. Factors controlled for included: seasonality, long-term trend, day of the week, maximum 2.5 and increased risks of medications dispensed for respiratory, cardiovascular and psychiatric conditions, over a lag range of 3-7 days. A 10 μg/m3 increase in coal mine fire-related PM2.5 was associated with a 25% (95%CI 19-32%) increase in respiratory medications, a 10% (95%CI 7-13%) increase in cardiovascular medications and a 12% (95%CI 8-16%) increase in psychiatric medications dispensed. These findings have the potential to better prepare for and develop more appropriate public health responses in the event of future coal mine fires