Endocardial versus epicardial ventricular radiofrequency ablation: utility of in vivo contact force assessment.

BACKGROUND Contact force (CF) is an important determinant of lesion formation for atrial endocardial radiofrequency ablation. There are minimal published data on CF and ventricular lesion formation. We studied the impact of CF on lesion formation using an ovine model both endocardially and epicardially. METHODS AND RESULTS Twenty sheep received 160 epicardial and 160 endocardial ventricular radiofrequency applications using either a 3.5-mm irrigated-tip catheter (Thermocool, Biosense-Webster, n=160) or a 3.5 irrigated-tip catheter with CF assessment (Tacticath, Endosense, n=160), via percutaneous access. Power was delivered at 30 watts for 60 seconds, when either catheter/tissue contact was felt to be good or when CF>10 g with Tacticath. After completion of all lesions, acute dimensions were taken at pathology. Identifiable lesion formation from radiofrequency application was improved with the aid of CF information, from 78% to 98% on the endocardium (P<0.001) and from 90% to 100% on the epicardium (P=0.02). The mean total force was greater on the endocardium (39±18 g versus 21±14 g for the epicardium; P<0.001) mainly because of axial force. Despite the force-time integral being greater endocardially, epicardial lesions were larger (231±182 mm(3) versus 209±131 mm(3); P=0.02) probably because of the absence of the heat sink effect of the circulating blood and covered a greater area (41±27 mm(2) versus 29±17 mm(2); P=0.03) because of catheter orientation. CONCLUSIONS In the absence of CF feedback, 22% of endocardial radiofrequency applications that are thought to have good contact did not result in lesion formation. Epicardial ablation is associated with larger lesions.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by process-based modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under http://www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws. We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10 m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25 m resolution.

Assessment of the wind-up phenomenon in the equine nociceptive trigeminal system.

Repeated sub-threshold nociceptive electrical stimulation resulting in temporal summation of the limb nociceptive withdrawal reflex is a well-established non-invasive model to investigate the wind-up phenomenon in horses. Due to structural similarities of the trigeminal sensory nucleus to the dorsal horn of the spinal cord, temporal summation should be evoked by repeated transcutaneous electrical stimulation of trigeminal afferents. To evaluate this hypothesis repeated transcutaneous electrical stimulation was applied to the supraorbital and infraorbital nerves of 10 horses. Stimulation intensities varied between 0.5 and 1.3 times the trigemino-cervical reflex threshold defined for single stimulation. Evoked electromyographic activity of the orbicularis oculi, splenius and cleidomastoideus muscles was recorded and the signals analysed in the previously established epochs typical to the early and late component of the blink reflex and to the trigemino-cervical reflex. Behavioural reactions were evaluated with the aid of numerical rating scale. The nociceptive late component and the trigemino-cervical reflex were not elicited by sub-threshold intensity repeated transcutaneous electrical stimulation. Furthermore, the median reflex amplitude for the 10 horses showed a tendency to decline over the stimulation train so temporal summation of afferent trigeminal inputs could not be observed. Therefore, the modulation of trigeminal nociceptive processing attributable to repeated Aδ fibre stimulations seems to differ from spinal processing of similar inputs as it seems to have an inhibitory rather than facilitatory effect. Further evaluation is necessary to highlight the underlying mechanism.

Assessment of detectability of neutral interstellar deuterium by IBEX observations

Context. The abundance of deuterium in the interstellar gas in front of the Sun gives insight into the processes of filtration of neutral interstellar species through the heliospheric interface and potentially into the chemical evolution of the Galactic gas. Aims: We investigate the possibility of detection of neutral interstellar deuterium at 1 AU from the Sun by direct sampling by the Interstellar Boundary Explorer (IBEX). Methods: Using both previous and the most recent determinations of the flow parameters of neutral gas in the local interstellar cloud (LIC) and an observation-based model of solar radiation pressure and ionization in the heliosphere, we simulated the flux of neutral interstellar D at IBEX for the actual measurement conditions. We assessed the number of interstellar D atom counts expected during the first three years of IBEX operation. We also simulated the observations expected during an epoch of high solar activity. In addition, we calculated the expected counts of D atoms from the thin terrestrial water layer covering the IBEX-Lo conversion surface, sputtered by neutral interstellar He atoms. Results: Most D counts registered by IBEX-Lo are expected to come from the water layer, exceeding the interstellar signal by 2 orders of magnitude. However, the sputtering should stop once the Earth leaves the portion of orbit traversed by interstellar He atoms. We identify seasons during the year when mostly the genuine interstellar D atoms are expected in the signal. During the first 3 years of IBEX operations about 2 detectable interstellar D atoms are expected. This number is comparable to the expected number of sputtered D atoms registered during the same time intervals. Conclusions: The most favorable conditions for the detection occur during low solar activity, in an interval including March and April each year. The detection chances could be improved by extending the instrument duty cycle, say, by making observations in the special deuterium mode of IBEX-Lo.

High resolution quantitative computed tomography-based assessment of trabecular microstructure and strength estimates by finite-element analysis of the spine, but not DXA, reflects vertebral fracture status in men with glucocorticoid-induced osteoporosis

High-resolution quantitative computed tomography (HRQCT)-based analysis of spinal bone density and microstructure, finite element analysis (FEA), and DXA were used to investigate the vertebral bone status of men with glucocorticoid-induced osteoporosis (GIO). DXA of L1–L3 and total hip, QCT of L1–L3, and HRQCT of T12 were available for 73 men (54.6±14.0years) with GIO. Prevalent vertebral fracture status was evaluated on radiographs using a semi-quantitative (SQ) score (normal=0 to severe fracture=3), and the spinal deformity index (SDI) score (sum of SQ scores of T4 to L4 vertebrae). Thirty-one (42.4%) subjects had prevalent vertebral fractures. Cortical BMD (Ct.BMD) and thickness (Ct.Th), trabecular BMD (Tb.BMD), apparent trabecular bone volume fraction (app.BV/TV), and apparent trabecular separation (app.Tb.Sp) were analyzed by HRQCT. Stiffness and strength of T12 were computed by HRQCT-based nonlinear FEA for axial compression, anterior bending and axial torsion. In logistic regressions adjusted for age, glucocorticoid dose and osteoporosis treatment, Tb.BMD was most closely associated with vertebral fracture status (standardized odds ratio [sOR]: Tb.BMD T12: 4.05 [95% CI: 1.8–9.0], Tb.BMD L1–L3: 3.95 [1.8–8.9]). Strength divided by cross-sectional area for axial compression showed the most significant association with spine fracture status among FEA variables (2.56 [1.29–5.07]). SDI was best predicted by a microstructural model using Ct.Th and app.Tb.Sp (r2=0.57, p<0.001). Spinal or hip DXA measurements did not show significant associations with fracture status or severity. In this cross-sectional study of males with GIO, QCT, HRQCT-based measurements and FEA variables were superior to DXA in discriminating between patients of differing prevalent vertebral fracture status. A microstructural model combining aspects of cortical and trabecular bone reflected fracture severity most accurately.

Identifying Distinct Quitting Trajectories after an Unassisted Smoking Cessation Attempt: An Ecological Momentary Assessment Study

Objectives: This study aimed at identifying distinct quitting trajectories over 29 days after an unassisted smoking ces- sation attempt by ecological momentary assessment (EMA). In order to validate these trajectories we tested if they predict smoking frequency up to six months later. Methods: EMA via mobile phones was used to collect real time data on smoking (yes/no) after an unassisted quit attempt over 29 days. Smoking frequency one, three and six months after the quit attempt was assessed with online questionnaires. Latent class growth modeling was used to analyze the data of 230 self-quitters. Results: Four different quitting trajectories emerged: quitter (43.9%), late quitter (11.3%), returner (17%) and persistent smoker (27.8%). The quitting trajectories predicted smoking frequency one, three and six months after the quit attempt (all p < 0.001). Conclusions: Outcome after a smoking cessation attempt is better described by four distinct trajectories instead of a binary variable for abstinence or relapse. In line with the relapse model by Marlatt and Gordon, late quitter may have learned how to cope with lapses during one month after the quitting attempt. This group would have been allocated to the relapse group in traditional outcome studies.

A Stratified Model for Psychosis Prediction in Clinical Practice

Objective: Impaired cognition is an important dimension in psychosis and its at-risk states. Research on the value of impaired cognition for psychosis prediction in at-risk samples, however, mainly relies on study-specific sample means of neurocognitive tests, which unlike widely available general test norms are difficult to translate into clinical practice. The aim of this study was to explore the combined predictive value of at-risk criteria and neurocognitive deficits according to test norms with a risk stratification approach. Method: Potential predictors of psychosis (neurocognitive deficits and at-risk criteria) over 24 months were investigated in 97 at-risk patients. Results: The final prediction model included (1) at-risk criteria (attenuated psychotic symptoms plus subjective cognitive disturbances) and (2) a processing speed deficit (digit symbol test). The model was stratified into 4 risk classes with hazard rates between 0.0 (both predictors absent) and 1.29 (both predictors present). Conclusions: The combination of a processing speed deficit and at-risk criteria provides an optimized stratified risk assessment. Based on neurocognitive test norms, the validity of our proposed 3 risk classes could easily be examined in independent at-risk samples and, pending positive validation results, our approach could easily be applied in clinical practice in the future.

Characterization of the 9L gliosarcoma implanted in the Fischer rat: an orthotopic model for a grade IV brain tumor.

Among rodent models for brain tumors, the 9L gliosarcoma is one of the most widely used. Our 9L-European Synchrotron Radiation Facility (ESRF) model was developed from cells acquired at the Brookhaven National Laboratory (NY, USA) in 1997 and implanted in the right caudate nucleus of syngeneic Fisher rats. It has been largely used by the user community of the ESRF during the last decade, for imaging, radiotherapy, and chemotherapy, including innovative treatments based on particular irradiation techniques and/or use of new drugs. This work presents a detailed study of its characteristics, assessed by magnetic resonance imaging (MRI), histology, immunohistochemistry, and cytogenetic analysis. The data used for this work were from rats sampled in six experiments carried out over a 3-year period in our lab (total number of rats = 142). The 9L-ESRF tumors were induced by a stereotactic inoculation of 10(4) 9L cells in the right caudate nucleus of the brain. The assessment of vascular parameters was performed by MRI (blood volume fraction and vascular size index) and by immunostaining of vessels (rat endothelial cell antigen-1 and type IV collagen). Immunohistochemistry and regular histology were used to describe features such as tumor cell infiltration, necrosis area, nuclear pleomorphism, cellularity, mitotic characteristics, leukocytic infiltration, proliferation, and inflammation. Moreover, for each of the six experiments, the survival of the animals was assessed and related to the tumor growth observed by MRI or histology. Additionally, the cytogenetic status of the 9L cells used at ESRF lab was investigated by comparative genomics hybridization analysis. Finally, the response of the 9L-ESRF tumor to radiotherapy was estimated by plotting the survival curves after irradiation. The median survival time of 9L-ESRF tumor-bearing rats was highly reproducible (19-20 days). The 9L-ESRF tumors presented a quasi-exponential growth, were highly vascularized with a high cellular density and a high proliferative index, accompanied by signs of inflammatory responses. We also report an infiltrative pattern which is poorly observed on conventional 9 L tumor. The 9L-ESRF cells presented some cytogenetic specificities such as altered regions including CDK4, CDKN2A, CDKN2B, and MDM2 genes. Finally, the lifespan of 9L-ESRF tumor-bearing rats was enhanced up to 28, 35, and 45 days for single doses of 10, 20, and 2 × 20 Gy, respectively. First, this report describes an animal model that is used worldwide. Second, we describe few features typical of our model if compared to other 9L models worldwide. Altogether, the 9L-ESRF tumor model presents characteristics close to the human high-grade gliomas such as high proliferative capability, high vascularization and a high infiltrative pattern. Its response to radiotherapy demonstrates its potential as a tool for innovative radiotherapy protocols.

Assessment of anastomotic leakage: A Novel System for the Training of Surgeons to Perform a Tubular Anastomosis and Objectively Evaluate Anastomotic Leak

Introduction: Dehiscence of the suture line of an anastomosis can lead to reoperation, temporary or permanent stoma, and even sepsis or death. Few techniques for the laboratory training of tubular anastomosis use ex-vivo animal tissues. We describe a novel model that can be used in the laboratory for the training of anastomosis in tubular tissues and objectively assess any anastomotic leak. [See PDF for complete abstract]

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

Historical and idealized climate model experiments: an intercomparison of Earth system models of intermediate complexity

Both historical and idealized climate model experiments are performed with a variety of Earth system models of intermediate complexity (EMICs) as part of a community contribution to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Historical simulations start at 850 CE and continue through to 2005. The standard simulations include changes in forcing from solar luminosity, Earth's orbital configuration, CO2, additional greenhouse gases, land use, and sulphate and volcanic aerosols. In spite of very different modelled pre-industrial global surface air temperatures, overall 20th century trends in surface air temperature and carbon uptake are reasonably well simulated when compared to observed trends. Land carbon fluxes show much more variation between models than ocean carbon fluxes, and recent land fluxes appear to be slightly underestimated. It is possible that recent modelled climate trends or climate–carbon feedbacks are overestimated resulting in too much land carbon loss or that carbon uptake due to CO2 and/or nitrogen fertilization is underestimated. Several one thousand year long, idealized, 2 × and 4 × CO2 experiments are used to quantify standard model characteristics, including transient and equilibrium climate sensitivities, and climate–carbon feedbacks. The values from EMICs generally fall within the range given by general circulation models. Seven additional historical simulations, each including a single specified forcing, are used to assess the contributions of different climate forcings to the overall climate and carbon cycle response. The response of surface air temperature is the linear sum of the individual forcings, while the carbon cycle response shows a non-linear interaction between land-use change and CO2 forcings for some models. Finally, the preindustrial portions of the last millennium simulations are used to assess historical model carbon-climate feedbacks. Given the specified forcing, there is a tendency for the EMICs to underestimate the drop in surface air temperature and CO2 between the Medieval Climate Anomaly and the Little Ice Age estimated from palaeoclimate reconstructions. This in turn could be a result of unforced variability within the climate system, uncertainty in the reconstructions of temperature and CO2, errors in the reconstructions of forcing used to drive the models, or the incomplete representation of certain processes within the models. Given the forcing datasets used in this study, the models calculate significant land-use emissions over the pre-industrial period. This implies that land-use emissions might need to be taken into account, when making estimates of climate–carbon feedbacks from palaeoclimate reconstructions.

Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis

The responses of carbon dioxide (CO2) and other climate variables to an emission pulse of CO2 into the atmosphere are often used to compute the Global Warming Potential (GWP) and Global Temperature change Potential (GTP), to characterize the response timescales of Earth System models, and to build reduced-form models. In this carbon cycle-climate model intercomparison project, which spans the full model hierarchy, we quantify responses to emission pulses of different magnitudes injected under different conditions. The CO2 response shows the known rapid decline in the first few decades followed by a millennium-scale tail. For a 100 Gt-C emission pulse added to a constant CO2 concentration of 389 ppm, 25 ± 9% is still found in the atmosphere after 1000 yr; the ocean has absorbed 59 ± 12% and the land the remainder (16 ± 14%). The response in global mean surface air temperature is an increase by 0.20 ± 0.12 °C within the first twenty years; thereafter and until year 1000, temperature decreases only slightly, whereas ocean heat content and sea level continue to rise. Our best estimate for the Absolute Global Warming Potential, given by the time-integrated response in CO2 at year 100 multiplied by its radiative efficiency, is 92.5 × 10−15 yr W m−2 per kg-CO2. This value very likely (5 to 95% confidence) lies within the range of (68 to 117) × 10−15 yr W m−2 per kg-CO2. Estimates for time-integrated response in CO2 published in the IPCC First, Second, and Fourth Assessment and our multi-model best estimate all agree within 15% during the first 100 yr. The integrated CO2 response, normalized by the pulse size, is lower for pre-industrial conditions, compared to present day, and lower for smaller pulses than larger pulses. In contrast, the response in temperature, sea level and ocean heat content is less sensitive to these choices. Although, choices in pulse size, background concentration, and model lead to uncertainties, the most important and subjective choice to determine AGWP of CO2 and GWP is the time horizon.

Validity assessment of the Breast Cancer Risk Reduction Health Belief scale.

BACKGROUND: : Women at increased risk of breast cancer (BC) are not widely accepting of chemopreventive interventions, and ethnic minorities are underrepresented in related trials. Furthermore, there is no validated instrument to assess the health-seeking behavior of these women with respect to these interventions. METHODS: : By using constructs from the Health Belief Model, the authors developed and refined, based on pilot data, the Breast Cancer Risk Reduction Health Belief (BCRRHB) scale using a population of 265 women at increased risk of BC who were largely medically underserved, of low socioeconomic status (SES), and ethnic minorities. Construct validity was assessed using principal components analysis with oblique rotation to extract factors, and generate and interpret summary scales. Internal consistency was determined using Cronbach alpha coefficients. RESULTS: : Test-retest reliability for the pilot and final data was calculated to be r = 0.85. Principal components analysis yielded 16 components that explained 64% of the total variance, with communalities ranging from 0.50-0.75. Cronbach alpha coefficients for the extracted factors ranged from 0.45-0.77. CONCLUSIONS: : Evidence suggests that the BCRRHB yields reliable and valid data that allows for the identification of barriers and enhancing factors associated with use of breast cancer chemoprevention in the study population. These findings allow for tailoring treatment plans and intervention strategies to the individual. Future research is needed to validate the scale for use in other female populations. Cancer 2009. (c) 2009 American Cancer Society.

Assessment of Collimator Jaw Optimization in Reducing Normal Tissue Irradiation with Intensity Modulated Radiation Therapy

Purpose: To evaluate normal tissue dose reduction in step-and-shoot intensity-modulated radiation therapy (IMRT) on the Varian 2100 platform by tracking the multileaf collimator (MLC) apertures with the accelerator jaws. Methods: Clinical radiation treatment plans for 10 thoracic, 3 pediatric and 3 head and neck patients were converted to plans with the jaws tracking each segment’s MLC apertures. Each segment was then renormalized to account for the change in collimator scatter to obtain target coverage within 1% of that in the original plan. The new plans were compared to the original plans in a commercial radiation treatment planning system (TPS). Reduction in normal tissue dose was evaluated in the new plan by using the parameters V5, V10, and V20 in the cumulative dose-volume histogram for the following structures: total lung minus GTV (gross target volume), heart, esophagus, spinal cord, liver, parotids, and brainstem. In order to validate the accuracy of our beam model, MLC transmission measurements were made and compared to those predicted by the TPS. Results: The greatest change between the original plan and new plan occurred at lower dose levels. The reduction in V20 was never more than 6.3% and was typically less than 1% for all patients. The reduction in V5 was 16.7% maximum and was typically less than 3% for all patients. The variation in normal tissue dose reduction was not predictable, and we found no clear parameters that indicated which patients would benefit most from jaw tracking. Our TPS model of MLC transmission agreed with measurements with absolute transmission differences of less than 0.1 % and thus uncertainties in the model did not contribute significantly to the uncertainty in the dose determination. Conclusion: The amount of dose reduction achieved by collimating the jaws around each MLC aperture in step-and-shoot IMRT does not appear to be clinically significant.

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.