Cyclooxygenase-2 inhibition selectively attenuates bone morphogenetic protein-6 synthesis and bone formation during guided tissue regeneration in a rat model

OBJECTIVES: Bone formation during guided tissue regeneration is a tightly regulated process involving cells, extracellular matrix and growth factors. The aims of this study were (i) to examine the expression of cyclooxygenase-2 (COX-2) during bone regeneration and (ii) the effects of selective COX-2 inhibition on osseous regeneration and growth factor expression in the rodent femur model. MATERIAL AND METHODS: A standardized transcortical defect of 5 x 1.5 mm was prepared in the femur of 12 male rats and a closed half-cylindrical titanium chamber was placed over the defect. The expression of COX-2 and of platelet-derived growth factor-B (PDGF-B), bone morphogenetic protein-6 (BMP-6) and insulin-like growth factor-I/II (IGF-I/II) was analyzed at Days 3, 7, 21 and 28 semiquantitatively by reverse transcriptase-polymerase chain reaction and immunohistochemistry. The effects of COX-2 inhibition by intraperitoneal injection of NS-398 (3 mg/kg/day) were analyzed in five additional animals sacrificed at Day 14. RESULTS: Histomorphometry revealed that new bone formation occurred in the cortical defect area as well as in the supracortical region, i.e. region within the chamber by Day 7 and increased through Day 28. Immunohistochemical evidence of COX-2 and PDGF-B levels were observed early (i.e. Day 3) and decreased rapidly by Day 7. BMP-6 expression was maximal at Day 3 and slowly declined by Day 28. In contrast, IGF-I/II expression gradually increased during the 28-day period. Systemic administration NS-398 caused a statistically significant reduction (P<0.05) in new bone formation (25-30%) and was associated with a statistically significant reduction in BMP-6 protein and mRNA expression (50% and 65% at P<0.05 and P<0.01, respectively). PDGF-B mRNA or protein expression was not affected by NS-398 treatment. CONCLUSION: COX-2 inhibition resulted in reduced BMP-6 expression and impaired osseous regeneration suggesting an important role for COX-2-induced signaling in BMP synthesis and new bone formation.

A Mechanistic Latent Variable Model for Estimating Drug Concentrations in the Male Genital Tract

The purpose of this study is to develop statistical methodology to facilitate indirect estimation of the concentration of antiretroviral drugs and viral loads in the prostate gland and the seminal vesicle. The differences in antiretroviral drug concentrations in these organs may lead to suboptimal concentrations in one gland compared to the other. Suboptimal levels of the antiretroviral drugs will not be able to fully suppress the virus in that gland, lead to a source of sexually transmissible virus and increase the chance of selecting for drug resistant virus. This information may be useful selecting antiretroviral drug regimen that will achieve optimal concentrations in most of male genital tract glands. Using fractionally collected semen ejaculates, Lundquist (1949) measured levels of surrogate markers in each fraction that are uniquely produced by specific male accessory glands. To determine the original glandular concentrations of the surrogate markers, Lundquist solved a simultaneous series of linear equations. This method has several limitations. In particular, it does not yield a unique solution, it does not address measurement error, and it disregards inter-subject variability in the parameters. To cope with these limitations, we developed a mechanistic latent variable model based on the physiology of the male genital tract and surrogate markers. We employ a Bayesian approach and perform a sensitivity analysis with regard to the distributional assumptions on the random effects and priors. The model and Bayesian approach is validated on experimental data where the concentration of a drug should be (biologically) differentially distributed between the two glands. In this example, the Bayesian model-based conclusions are found to be robust to model specification and this hierarchical approach leads to more scientifically valid conclusions than the original methodology. In particular, unlike existing methods, the proposed model based approach was not affected by a common form of outliers.

Modelling the results of health promotion activities in Switzerland: development of the Swiss Model for Outcome Classification in Health Promotion and Prevention

This paper describes the Model for Outcome Classification in Health Promotion and Prevention adopted by Health Promotion Switzerland (SMOC, Swiss Model for Outcome Classification) and the process of its development. The context and method of model development, and the aim and objectives of the model are outlined. Preliminary experience with application of the model in evaluation planning and situation analysis is reported. On the basis of an extensive literature search, the model is situated within the wider international context of similar efforts to meet the challenge of developing tools to assess systematically the activities of health promotion and prevention.

Translocation of particles and inflammatory responses after exposure to fine particles and nanoparticles in an epithelial airway model

ABSTRACT: BACKGROUND: Experimental studies provide evidence that inhaled nanoparticles may translocate over the airspace epithelium and cause increased cellular inflammation. Little is known, however, about the dependence of particle size or material on translocation characteristics, inflammatory response and intracellular localization. RESULTS: Using a triple cell co-culture model of the human airway wall composed of epithelial cells, macrophages and dendritic cells we quantified the entering of fine (1 mum) and nano-sized (0.078 mum) polystyrene particles by laser scanning microscopy. The number distribution of particles within the cell types was significantly different between fine and nano-sized particles suggesting different translocation characteristics. Analysis of the intracellular localization of gold (0.025 mum) and titanium dioxide (0.02-0.03 mum) nanoparticles by energy filtering transmission electron microscopy showed differences in intracellular localization depending on particle composition. Titanium dioxide nanoparticles were detected as single particles without membranes as well as in membrane-bound agglomerations. Gold nanoparticles were found inside the cells as free particles only. The potential of the different particle types (different sizes and different materials) to induce a cellular response was determined by measurements of the tumour necrosis factor-alpha in the supernatants. We measured a 2-3 fold increase of tumour necrosis factor-alpha in the supernatants after applying 1 mum polystyrene particles, gold nanoparticles, but not with polystyrene and titanium dioxide nanoparticles. CONCLUSION: Quantitative laser scanning microscopy provided evidence that the translocation and entering characteristics of particles are size-dependent. Energy filtering transmission electron microscopy showed that the intracellular localization of nanoparticles depends on the particle material. Both particle size and material affect the cellular responses to particle exposure as measured by the generation of tumour necrosis factor-alpha.

Methylprednisolone Fails to Preserve Pulmonary Surfactant and Blood-Air Barrier Integrity in a Porcine Cardiopulmonary Bypass Model

BACKGROUND: Pulmonary inflammation after cardiac surgery with cardiopulmonary bypass (CPB) has been linked to respiratory dysfunction and ultrastructural injury. Whether pretreatment with methylprednisolone (MP) can preserve pulmonary surfactant and blood-air barrier, thereby improving pulmonary function, was tested in a porcine CPB-model. MATERIALS AND METHODS: After randomizing pigs to placebo (PLA; n = 5) or MP (30 mg/kg, MP; n = 5), animals were subjected to 3 h of CPB with 1 h of cardioplegic cardiac arrest. Hemodynamic data, plasma tumor necrosis factor-alpha (TNF-alpha, ELISA), and pulmonary function parameters were assessed before, 15 min after CPB, and 8 h after CPB. Lung biopsies were analyzed for TNF-alpha (Western blot) or blood-air barrier and surfactant morphology (electron microscopy, stereology). RESULTS: Systemic TNF-alpha increased and cardiac index decreased at 8 h after CPB in PLA (P < 0.05 versus pre-CPB), but not in MP (P < 0.05 versus PLA). In both groups, at 8 h after CPB, PaO(2) and PaO(2)/FiO(2) were decreased and arterio-alveolar oxygen difference and pulmonary vascular resistance were increased (P < 0.05 versus baseline). Postoperative pulmonary TNF-alpha remained unchanged in both groups, but tended to be higher in PLA (P = 0.06 versus MP). The volume fraction of inactivated intra-alveolar surfactant was increased in PLA (58 +/- 17% versus 83 +/- 6%) and MP (55 +/- 18% versus 80 +/- 17%) after CPB (P < 0.05 versus baseline for both groups). Profound blood-air barrier injury was present in both groups at 8 h as indicated by an increased blood-air barrier integrity score (PLA: 1.28 +/- 0.03 versus 1.70 +/- 0.1; MP: 1.27 +/- 0.08 versus 1.81 +/- 0.1; P < 0.05). CONCLUSION: Despite reduction of the systemic inflammatory response and pulmonary TNF-alpha generation, methylprednisolone fails to decrease pulmonary TNF-alpha and to preserve pulmonary surfactant morphology, blood-air barrier integrity, and pulmonary function after CPB.

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

Golden-winged Warbler habitat model validation for northern Wisconsin and central Minnesota

Between 1966 and 2003, the Golden-winged Warbler (Vermivora chrysoptera) experienced declines of 3.4% per year in large parts of the breeding range and has been identified by Partners in Flight as one of 28 land birds requiring expedient action to prevent its continued decline. It is currently being considered for listing under the Endangered Species Act. A major step in advancing our understanding of the status and habitat preferences of Golden-winged Warbler populations in the Upper Midwest was initiated by the publication of new predictive spatially explicit Golden-winged Warbler habitat models for the northern Midwest. Here, I use original data on observed Golden-winged Warbler abundances in Wisconsin and Minnesota to compare two population models: the hierarchical spatial count (HSC) model with the Habitat Suitability Index (HSI) model. I assessed how well the field data compared to the model predictions and found that within Wisconsin, the HSC model performed slightly better than the HSI model whereas both models performed relatively equally in Minnesota. For the HSC model, I found a 10% error of commission in Wisconsin and a 24.2% error of commission for Minnesota. Similarly, the HSI model has a 23% error of commission in Minnesota; in Wisconsin due to limited areas where the HSI model predicted absences, there was incomplete data and I was unable to determine the error of commission for the HSI model. These are sites where the model predicted presences and the Golden-winged Warbler did not occur. To compare predicted abundance from the two models, a 3x3 contingency table was used. I found that when overlapped, the models do not complement one another in identifying Golden-winged Warbler presences. To calculate discrepancy between the models, the error of commission shows that the HSI model has only a 6.8% chance of correctly classifying absences in the HSC model. The HSC model has only 3.3% chance of correctly classifying absences in the HSI model. These findings highlight the importance of grasses for nesting, shrubs used for cover and foraging, and trees for song perches and foraging as key habitat characteristics for breeding territory occupancy by singing males.

Discrete element methods for asphalt concrete : development and application of user-defined microstructural models and a viscoelastic micromechanical model

As an important Civil Engineering material, asphalt concrete (AC) is commonly used to build road surfaces, airports, and parking lots. With traditional laboratory tests and theoretical equations, it is a challenge to fully understand such a random composite material. Based on the discrete element method (DEM), this research seeks to develop and implement computer models as research approaches for improving understandings of AC microstructure-based mechanics. In this research, three categories of approaches were developed or employed to simulate microstructures of AC materials, namely the randomly-generated models, the idealized models, and image-based models. The image-based models were recommended for accurately predicting AC performance, while the other models were recommended as research tools to obtain deep insight into the AC microstructure-based mechanics. A viscoelastic micromechanical model was developed to capture viscoelastic interactions within the AC microstructure. Four types of constitutive models were built to address the four categories of interactions within an AC specimen. Each of the constitutive models consists of three parts which represent three different interaction behaviors: a stiffness model (force-displace relation), a bonding model (shear and tensile strengths), and a slip model (frictional property). Three techniques were developed to reduce the computational time for AC viscoelastic simulations. It was found that the computational time was significantly reduced to days or hours from years or months for typical three-dimensional models. Dynamic modulus and creep stiffness tests were simulated and methodologies were developed to determine the viscoelastic parameters. It was found that the DE models could successfully predict dynamic modulus, phase angles, and creep stiffness in a wide range of frequencies, temperatures, and time spans. Mineral aggregate morphology characteristics (sphericity, orientation, and angularity) were studied to investigate their impacts on AC creep stiffness. It was found that aggregate characteristics significantly impact creep stiffness. Pavement responses and pavement-vehicle interactions were investigated by simulating pavement sections under a rolling wheel. It was found that wheel acceleration, steadily moving, and deceleration significantly impact contact forces. Additionally, summary and recommendations were provided in the last chapter and part of computer programming codes wree provided in the appendixes.

Parameter estimation for transformer modeling

Large Power transformers, an aging and vulnerable part of our energy infrastructure, are at choke points in the grid and are key to reliability and security. Damage or destruction due to vandalism, misoperation, or other unexpected events is of great concern, given replacement costs upward of $2M and lead time of 12 months. Transient overvoltages can cause great damage and there is much interest in improving computer simulation models to correctly predict and avoid the consequences. EMTP (the Electromagnetic Transients Program) has been developed for computer simulation of power system transients. Component models for most equipment have been developed and benchmarked. Power transformers would appear to be simple. However, due to their nonlinear and frequency-dependent behaviors, they can be one of the most complex system components to model. It is imperative that the applied models be appropriate for the range of frequencies and excitation levels that the system experiences. Thus, transformer modeling is not a mature field and newer improved models must be made available. In this work, improved topologically-correct duality-based models are developed for three-phase autotransformers having five-legged, three-legged, and shell-form cores. The main problem in the implementation of detailed models is the lack of complete and reliable data, as no international standard suggests how to measure and calculate parameters. Therefore, parameter estimation methods are developed here to determine the parameters of a given model in cases where available information is incomplete. The transformer nameplate data is required and relative physical dimensions of the core are estimated. The models include a separate representation of each segment of the core, including hysteresis of the core, λ-i saturation characteristic, capacitive effects, and frequency dependency of winding resistance and core loss. Steady-state excitation, and de-energization and re-energization transients are simulated and compared with an earlier-developed BCTRAN-based model. Black start energization cases are also simulated as a means of model evaluation and compared with actual event records. The simulated results using the model developed here are reasonable and more correct than those of the BCTRAN-based model. Simulation accuracy is dependent on the accuracy of the equipment model and its parameters. This work is significant in that it advances existing parameter estimation methods in cases where the available data and measurements are incomplete. The accuracy of EMTP simulation for power systems including three-phase autotransformers is thus enhanced. Theoretical results obtained from this work provide a sound foundation for development of transformer parameter estimation methods using engineering optimization. In addition, it should be possible to refine which information and measurement data are necessary for complete duality-based transformer models. To further refine and develop the models and transformer parameter estimation methods developed here, iterative full-scale laboratory tests using high-voltage and high-power three-phase transformer would be helpful.

MODELING DYNAMICS OF OZONE AND NITROGEN OXIDES AT SUMMIT, GREENLAND WITH A 1-D PROCESS-SCALE MODEL

This work presents a 1-D process scale model used to investigate the chemical dynamics and temporal variability of nitrogen oxides (NOx) and ozone (O3) within and above snowpack at Summit, Greenland for March-May 2009 and estimates surface exchange of NOx between the snowpack and surface layer in April-May 2009. The model assumes the surface of snowflakes have a Liquid Like Layer (LLL) where aqueous chemistry occurs and interacts with the interstitial air of the snowpack. Model parameters and initialization are physically and chemically representative of snowpack at Summit, Greenland and model results are compared to measurements of NOx and O3 collected by our group at Summit, Greenland from 2008-2010. The model paired with measurements confirmed the main hypothesis in literature that photolysis of nitrate on the surface of snowflakes is responsible for nitrogen dioxide (NO2) production in the top ~50 cm of the snowpack at solar noon for March – May time periods in 2009. Nighttime peaks of NO2 in the snowpack for April and May were reproduced with aqueous formation of peroxynitric acid (HNO4) in the top ~50 cm of the snowpack with subsequent mass transfer to the gas phase, decomposition to form NO2 at nighttime, and transportation of the NO2 to depths of 2 meters. Modeled production of HNO4 was hindered in March 2009 due to the low production of its precursor, hydroperoxy radical, resulting in underestimation of nighttime NO2 in the snowpack for March 2009. The aqueous reaction of O3 with formic acid was the major sync of O3 in the snowpack for March-May, 2009. Nitrogen monoxide (NO) production in the top ~50 cm of the snowpack is related to the photolysis of NO2, which underrepresents NO in May of 2009. Modeled surface exchange of NOx in April and May are on the order of 1011 molecules m-2 s-1. Removal of measured downward fluxes of NO and NO2 in measured fluxes resulted in agreement between measured NOx fluxes and modeled surface exchange in April and an order of magnitude deviation in May. Modeled transport of NOx above the snowpack in May shows an order of magnitude increase of NOx fluxes in the first 50 cm of the snowpack and is attributed to the production of NO2 during the day from the thermal decomposition and photolysis of peroxynitric acid with minor contributions of NO from HONO photolysis in the early morning.

Assessing vegetation cover and biomass in restored erosion areas in Iceland using SPOT satellite data

Due to highly erodible volcanic soils and a harsh climate, livestock grazing in Iceland has led to serious soil erosion on about 40% of the country's surface. Over the last 100 years, various revegetation and restoration measures were taken on large areas distributed all over Iceland in an attempt to counteract this problem. The present research aimed to develop models for estimating percent vegetation cover (VC) and aboveground biomass (AGB) based on satellite data, as this would make it possible to assess and monitor the effectiveness of restoration measures over large areas at a fairly low cost. Models were developed based on 203 vegetation cover samples and 114 aboveground biomass samples distributed over five SPOT satellite datasets. All satellite datasets were atmospherically corrected, and digital numbers were converted into ground reflectance. Then a selection of vegetation indices (VIs) was calculated, followed by simple and multiple linear regression analysis of the relations between the field data and the calculated VIs. Best results were achieved using multiple linear regression models for both %VC and AGB. The model calibration and validation results showed that R2 and RMSE values for most VIs do not vary very much. For percent VC, R2 values range between 0.789 and 0.822, leading to RMSEs ranging between 15.89% and 16.72%. For AGB, R2 values for low-biomass areas (AGB < 800 g/m2) range between 0.607 and 0.650, leading to RMSEs ranging between 126.08 g/m2 and 136.38 g/m2. The AGB model developed for all areas, including those with high biomass coverage (AGB > 800 g/m2), achieved R2 values between 0.487 and 0.510, resulting in RMSEs ranging from 234 g/m2 to 259.20 g/m2. The models predicting percent VC generally overestimate observed low percent VC and slightly underestimate observed high percent VC. The estimation models for AGB behave in a similar way, but over- and underestimation are much more pronounced. These results show that it is possible to estimate percent VC with high accuracy based on various VIs derived from SPOT satellite data. AGB of restoration areas with low-biomass values of up to 800 g/m2 can likewise be estimated with high accuracy based on various VIs derived from SPOT satellite data, whereas in the case of high biomass coverage, estimation accuracy decreases with increasing biomass values. Accordingly, percent VC can be estimated with high accuracy anywhere in Iceland, whereas AGB is much more difficult to estimate, particularly for areas with high-AGB variability.

Effect of pressure-controlled intermittent coronary sinus occlusion (PICSO) on myocardial ischaemia and reperfusion in a closed-chest porcine model

AIMS To investigate a pressure-controlled intermittent coronary sinus occlusion (PICSO) system in an ischaemia/reperfusion model. METHODS AND RESULTS We randomly assigned 18 pigs subjected to 60 minutes ischaemia by left anterior descending (LAD) coronary artery balloon occlusion to PICSO (n=12, groups A and B) or to controls (n=6, group C). PICSO started 10 minutes before (group A), or 10 minutes after (group B) reperfusion and was maintained for 180 minutes. A continuous drop of distal LAD pressure was observed in group C. At 180 minutes of reperfusion, LAD diastolic pressure was significantly lower in group C compared to groups A and B (p=0.02). LAD mean pressure was significantly less than the systemic arterial mean pressure in group C (p=0.02), and the diastolic flow slope was flat, compared to groups A and B (p=0.03). IgG and IgM antibody deposition was significantly higher in ischaemic compared to non-ischaemic tissue in group C (p<0.05). Significantly more haemorrhagic lesions were seen in the ischaemic myocardium of group C, compared to groups A and B (p=0.002). The necrotic area differed non-significantly among groups. CONCLUSIONS PICSO was safe and effective in improving coronary perfusion pressure and reducing antibody deposition consistent with reduced microvascular obstruction and ischaemia/reperfusion injury.

Choosing and Maintaining Programs for Sex Education in Schools: The CHAMPSS Model

Background: Despite effective solutions to reduce teen birth rates, Texas teen birth rates are among the highest in the nation. School districts can impact youth sexual behavior through implementation of evidence-based programs (EBPs); however, teen pregnancy prevention is a complex and controversial issue for school districts. Subsequently, very few districts in Texas implement EBPs for pregnancy prevention. Additionally, school districts receive little guidance on the process for finding, adopting, and implementing EBPs. Purpose: The purpose of this report is to present the CHoosing And Maintaining Programs for Sex education in Schools (CHAMPSS) Model, a practical and realistic framework to help districts find, adopt, and implement EBPs. Methods: Model development occurred in four phases using the core processes of Intervention Mapping: 1) knowledge acquisition, 2) knowledge engineering, 3) model representation, and 4) knowledge development. Results: The CHAMPSS Model provides seven steps, tailored for school-based settings, which encompass phases of assessment, preparation, implementation, and maintenance: Prioritize, Asses, Select, Approve, Prepare, Implement, and Maintain. Advocacy and eliciting support for adolescent sexual health are also core elements of the model. Conclusion: This systematic framework may help schools increase adoption, implementation, and maintenance for EBPs.

Regulation of androgen biosynthesis - A short review and preliminary results from the hyperandrogenic starvation NCI-H295R cell model

Regulation of androgen production is poorly understood. Adrenarche is the physiologic event in mid-childhood when the adrenal zona reticularis starts to produce androgens through specific expression of genes for enzymes and cofactors necessary for androgen synthesis. Similarly, expression and activities of same genes and products are deregulated in hyperandrogenic disorders such as the polycystic ovary syndrome (PCOS). Numerous studies revealed involvement of several signaling pathways stimulated through G-protein coupled receptors or growth factors transmitting their effects through cAMP- or non-cAMP-dependent signaling. Overall a complex network regulates androgen synthesis targeting involved genes and proteins at the transcriptional and post-translational levels. Newest players in the field are the DENND1A gene identified in PCOS patients and the MAPK14 which is the kinase phosphorylating CYP17 for enhanced lyase activity. Next generation sequencing studies of PCOS patients and transcriptome analysis of androgen producing tissues or cell models provide newer tools to identify modulators of androgen synthesis.

Virulence of broad- and narrow-host-range Salmonella enterica serovars in the streptomycin-pretreated mouse model.

Salmonella enterica subspecies I serovars are common bacterial pathogens causing diseases ranging from enterocolitis to systemic infections. Some serovars are adapted to specific hosts, whereas others have a broad host range. The molecular mechanisms defining the virulence characteristics and the host range of a given S. enterica serovar are unknown. Streptomycin pretreated mice provide a surrogate host model for studying molecular aspects of the intestinal inflammation (colitis) caused by serovar Typhimurium (S. Hapfelmeier and W. D. Hardt, Trends Microbiol. 13:497-503, 2005). Here, we studied whether this animal model is also useful for studying other S. enterica subspecies I serovars. All three tested strains of the broad-host-range serovar Enteritidis (125109, 5496/98, and 832/99) caused pronounced colitis and systemic infection in streptomycin pretreated mice. Different levels of virulence were observed among three tested strains of the host-adapted serovar Dublin (SARB13, SD2229, and SD3246). Several strains of host restricted serovars were also studied. Two serovar Pullorum strains (X3543 and 449/87) caused intermediate levels of colitis. No intestinal inflammation was observed upon infection with three different serovar Paratyphi A strains (SARB42, 2804/96, and 5314/98) and one serovar Gallinarum strain (X3796). A second serovar Gallinarum strain (287/91) was highly virulent and caused severe colitis. This strain awaits future analysis. In conclusion, the streptomycin pretreated mouse model can provide an additional tool to study virulence factors (i.e., those involved in enteropathogenesis) of various S. enterica subspecies I serovars. Five of these strains (125109, 2229, 287/91, 449/87, and SARB42) are subject of Salmonella genome sequencing projects. The streptomycin pretreated mouse model may be useful for testing hypotheses derived from this genomic data.