Lowered microvascular vessel wall oxygen consumption augments tissue pO2 during PgE1-induced vasodilation

Continuous infusion of intravenous prostaglandin E1 (PgE1, 2.5 mug/kg/min) was used to determine how vasodilation affects oxygen consumption of the microvascular wall and tissue pO(2) in the hamster window chamber model. While systemic measurements (mean arterial pressure and heart rate) and central blood gas measurements were not affected, PgE1 treatment caused arteriolar (64.6 +/- 25.1 microm) and venular diameter (71.9 +/- 29.5 microm) to rise to 1.15 +/- 0.21 and 1.06 +/- 0.19, respectively, relative to baseline. Arteriolar (3.2 x 10(-2) +/- 4.3 x 10(-2) nl/s) and venular flow (7.8 x 10(-3) +/- 1.1 x 10(-2)/s) increased to 1.65 +/- 0.93 and 1.32 +/- 0.72 relative to baseline. Interstitial tissue pO(2) was increased significantly from baseline (21 +/- 8 to 28 +/- 7 mmHg; P < 0.001). The arteriolar vessel wall gradient, a measure of oxygen consumption by the microvascular wall decreased from 20 +/- 6 to 16 +/- 3 mmHg (P < 0.001). The arteriolar vessel wall gradient, a measure of oxygen consumption by the vascular wall, decreased from 20 +/- 6 to 16 +/- 3 mmHg (P < 0.001). This reduction reflects a 20% decrease in oxygen consumption by the vessel wall and up to 50% when cylindrical geometry is considered. The venular vessel wall gradient decreased from 12 +/- 4 to 9 +/- 4 mmHg (P < 0.001). Thus PgE1-mediated vasodilation has a positive microvascular effect: enhancement of tissue perfusion by increasing flow and then augmentation of tissue oxygenation by reducing oxygen consumption by the microvascular wall.

Early resuscitation with polymerized bovine hemoglobin reverses acidosis, but not peripheral tissue oxygenation, in a severe hamster shock model

Awake hamsters equipped with the dorsal window chamber preparation were subjected to hemorrhage of 50% of the estimated blood volume. Initial resuscitation (25% of estimated blood volume) with polymerized bovine hemoglobin (PBH) or 10% hydroxyethyl starch (HES) occurred in concert with an equivolumetric bleeding to simulate the early, prehospital setting (exchange transfusion). Resuscitation (25% of estimated blood volume) without bleeding was performed with PBH, HES, or autologous red blood cells (HES-RBCs). Peripheral microcirculation, tissue oxygenation, and systemic hemodynamic and blood gas parameters were assessed. After exchange transfusion, base deficit was -8.6 +/- 3.7 mmol/L (PBH) and -5.1 +/- 5.3 mmol/L (HES) (not significant). Functional capillary density was 17% +/- 6% of baseline (PBH) and 31% +/- 11% (HES) (P < 0.05) and arteriolar diameter 73% +/- 3% of baseline (PBH) and 90% + 5% (HES) (P < 0.01). At the end, hemoglobin levels were 3.7 +/- 0.3 g/dL with HES, 8.2 +/- 0.6 g/dL with PBH, and 10.4 +/- 0.8 g/dL with HES-RBCs (P < 0.01 HES vs. PBH and HES-RBCs, P < 0.05 PBH vs. HES-RBCs). Base excess was restored to baseline with PBH and HES-RBCs, but not with HES (P < 0.05). Functional capillary density was 46% +/- 5% of baseline (PBH), 62% + 20% (HES-RBCs), and 36% +/- 19% (HES) (P < 0.01 HES-RBCs vs. HES). Peripheral oxygen delivery and consumption was highest with HES-RBCs, followed by PBH (P < 0.05 HES-RBCs vs. PBH, P < 0.01 HES-RBCs and PBH vs. HES). In conclusion, the PBH led to a correction of base deficit comparable to blood transfusion. However, oxygenation of the peripheral tissue was inferior with PBH. This was attributed to its negative impact on the peripheral microcirculation caused by arteriolar vasoconstriction.

Predicting the population impact of chlamydia screening programmes: comparative mathematical modelling study

BACKGROUND: Published individual-based, dynamic sexual network modelling studies reach different conclusions about the population impact of screening for Chlamydia trachomatis. The objective of this study was to conduct a direct comparison of the effect of organised chlamydia screening in different models. METHODS: Three models simulating population-level sexual behaviour, chlamydia transmission, screening and partner notification were used. Parameters describing a hypothetical annual opportunistic screening program in 16-24 year olds were standardised, whereas other parameters from the three original studies were retained. Model predictions of the change in chlamydia prevalence were compared under a range of scenarios. RESULTS: Initial overall chlamydia prevalence rates were similar in women but not men and there were age and sex-specific differences between models. The number of screening tests carried out was comparable in all models but there were large differences in the predicted impact of screening. After 10 years of screening, the predicted reduction in chlamydia prevalence in women aged 16-44 years ranged from 4% to 85%. Screening men and women had a greater impact than screening women alone in all models. There were marked differences between models in assumptions about treatment seeking and sexual behaviour before the start of the screening intervention. CONCLUSIONS: Future models of chlamydia transmission should be fitted to both incidence and prevalence data. This meta-modelling study provides essential information for explaining differences between published studies and increasing the utility of individual-based chlamydia transmission models for policy making.

NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.

Prediction of residential radon exposure of the whole Swiss population: comparison of model-based predictions with measurement-based predictions

Radon plays an important role for human exposure to natural sources of ionizing radiation. The aim of this article is to compare two approaches to estimate mean radon exposure in the Swiss population: model-based predictions at individual level and measurement-based predictions based on measurements aggregated at municipality level. A nationwide model was used to predict radon levels in each household and for each individual based on the corresponding tectonic unit, building age, building type, soil texture, degree of urbanization, and floor. Measurement-based predictions were carried out within a health impact assessment on residential radon and lung cancer. Mean measured radon levels were corrected for the average floor distribution and weighted with population size of each municipality. Model-based predictions yielded a mean radon exposure of the Swiss population of 84.1 Bq/m(3) . Measurement-based predictions yielded an average exposure of 78 Bq/m(3) . This study demonstrates that the model- and the measurement-based predictions provided similar results. The advantage of the measurement-based approach is its simplicity, which is sufficient for assessing exposure distribution in a population. The model-based approach allows predicting radon levels at specific sites, which is needed in an epidemiological study, and the results do not depend on how the measurement sites have been selected.

Predicting daily smoking around a quit date : Volitional processes at the inter- and intraindividual level

Background: The health action process approach (hapa) is a well-established model in predicting health behavior and assumes that volitional processes are important for effective behavioral change. however, only few studies have so far tested associations on the intraindividual level. thus, this study examined the inter- and intraindividual associations between volitional predictors and daily smoking around a quit attempt. method: overall, 105 smokers completed daily electronic questionnaires 10 days before and 21 days after a self-set quit date, including measures of intentions, self-efficacy, planning, action control and numbers of cigarettes smoked. multilevel analysis was applied. findings: at the interindividual level, higher mean levels of volitional predictors across the 32 days were associated with less numbers of cigarettes smoked. negative associations emerged also at the intraindividual level, indicating that on days with higher intentions, self-efficacy, planning and action control than usual, less cigarettes were smoked. moreover, these effects were stronger after the quit date than before the quit date. intentions and action control emerged as most powerful predictors at the intraindividual level. discussion: findings confirm assumptions of the hapa and emphasize the importance of volitional processes at the inter- and intraindividual level in the context of quitting smoking.

A nonlinear QCT-based finite element model validation study for the human femur tested in two configurations in vitro

Purpose Femoral fracture is a common medical problem in osteoporotic individuals. Bone mineral density (BMD) is the gold standard measure to evaluate fracture risk in vivo. Quantitative computed tomography (QCT)-based homogenized voxel finite element (hvFE) models have been proved to be more accurate predictors of femoral strength than BMD by adding geometrical and material properties. The aim of this study was to evaluate the ability of hvFE models in predicting femoral stiffness, strength and failure location for a large number of pairs of human femora tested in two different loading scenarios. Methods Thirty-six pairs of femora were scanned with QCT and total proximal BMD and BMC were evaluated. For each pair, one femur was positioned in one-legged stance configuration (STANCE) and the other in a sideways configuration (SIDE). Nonlinear hvFE models were generated from QCT images by reproducing the same loading configurations imposed in the experiments. For experiments and models, the structural properties (stiffness and ultimate load), the failure location and the motion of the femoral head were computed and compared. Results In both configurations, hvFE models predicted both stiffness (R2=0.82 for STANCE and R2=0.74 for SIDE) and femoral ultimate load (R2=0.80 for STANCE and R2=0.85 for SIDE) better than BMD and BMC. Moreover, the models predicted qualitatively well the failure location (66% of cases) and the motion of the femoral head. Conclusions The subject specific QCT-based nonlinear hvFE model cannot only predict femoral apparent mechanical properties better than densitometric measures, but can additionally provide useful qualitative information about failure location.

Evaluation of 9 biomarkers for predicting 10-year cardiovascular risk in patients undergoing coronary angiography: findings from the LUdwigshafen RIsk and Cardiovascular Health (LURIC) study.

BACKGROUND Conventional factors do not fully explain the distribution of cardiovascular outcomes. Biomarkers are known to participate in well-established pathways associated with cardiovascular disease, and may therefore provide further information over and above conventional risk factors. This study sought to determine whether individual and/or combined assessment of 9 biomarkers improved discrimination, calibration and reclassification of cardiovascular mortality. METHODS 3267 patients (2283 men), aged 18-95 years, at intermediate-to-high-risk of cardiovascular disease were followed in this prospective cohort study. Conventional risk factors and biomarkers were included based on forward and backward Cox proportional stepwise selection models. RESULTS During 10-years of follow-up, 546 fatal cardiovascular events occurred. Four biomarkers (interleukin-6, neutrophils, von Willebrand factor, and 25-hydroxyvitamin D) were retained during stepwise selection procedures for subsequent analyses. Simultaneous inclusion of these biomarkers significantly improved discrimination as measured by the C-index (0.78, P = 0.0001), and integrated discrimination improvement (0.0219, P<0.0001). Collectively, these biomarkers improved net reclassification for cardiovascular death by 10.6% (P<0.0001) when added to the conventional risk model. CONCLUSIONS In terms of adverse cardiovascular prognosis, a biomarker panel consisting of interleukin-6, neutrophils, von Willebrand factor, and 25-hydroxyvitamin D offered significant incremental value beyond that conveyed by simple conventional risk factors.

Predicting smoking cessation and its relapse in HIV-infected patients: the Swiss HIV Cohort Study

OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.

Impact of epinephrine and norepinephrine on two dynamic indices in a porcine hemorrhagic shock model

Abstract BACKGROUND: Pulse pressure variations (PPVs) and stroke volume variations (SVVs) are dynamic indices for predicting fluid responsiveness in intensive care unit patients. These hemodynamic markers underscore Frank-Starling law by which volume expansion increases cardiac output (CO). The aim of the present study was to evaluate the impact of the administration of catecholamines on PPV, SVV, and inferior vena cava flow (IVCF). METHODS: In this prospective, physiologic, animal study, hemodynamic parameters were measured in deeply sedated and mechanically ventilated pigs. Systemic hemodynamic and pressure-volume loops obtained by inferior vena cava occlusion were recorded. Measurements were collected during two conditions, that is, normovolemia and hypovolemia, generated by blood removal to obtain a mean arterial pressure value lower than 60 mm Hg. At each condition, CO, IVCF, SVV, and PPV were assessed by catheters and flow meters. Data were compared between the conditions normovolemia and hypovolemia before and after intravenous administrations of norepinephrine and epinephrine using a nonparametric Wilcoxon test. RESULTS: Eight pigs were anesthetized, mechanically ventilated, and equipped. Both norepinephrine and epinephrine significantly increased IVCF and decreased PPV and SVV, regardless of volemic conditions (p < 0.05). However, epinephrine was also able to significantly increase CO regardless of volemic conditions. CONCLUSION: The present study demonstrates that intravenous administrations of norepinephrine and epinephrine increase IVCF, whatever the volemic conditions are. The concomitant decreases in PPV and SVV corroborate the fact that catecholamine administration recruits unstressed blood volume. In this regard, understanding a decrease in PPV and SVV values, after catecholamine administration, as an obvious indication of a restored volemia could be an outright misinterpretation.

Predicting 3-year mortality after percutaneous coronary intervention: updated logistic clinical SYNTAX score based on patient-level data from 7 contemporary stent trials

OBJECTIVES This study aimed to update the Logistic Clinical SYNTAX score to predict 3-year survival after percutaneous coronary intervention (PCI) and compare the performance with the SYNTAX score alone. BACKGROUND The SYNTAX score is a well-established angiographic tool to predict long-term outcomes after PCI. The Logistic Clinical SYNTAX score, developed by combining clinical variables with the anatomic SYNTAX score, has been shown to perform better than the SYNTAX score alone in predicting 1-year outcomes after PCI. However, the ability of this score to predict long-term survival is unknown. METHODS Patient-level data (N = 6,304, 399 deaths within 3 years) from 7 contemporary PCI trials were analyzed. We revised the overall risk and the predictor effects in the core model (SYNTAX score, age, creatinine clearance, and left ventricular ejection fraction) using Cox regression analysis to predict mortality at 3 years. We also updated the extended model by combining the core model with additional independent predictors of 3-year mortality (i.e., diabetes mellitus, peripheral vascular disease, and body mass index). RESULTS The revised Logistic Clinical SYNTAX models showed better discriminative ability than the anatomic SYNTAX score for the prediction of 3-year mortality after PCI (c-index: SYNTAX score, 0.61; core model, 0.71; and extended model, 0.73 in a cross-validation procedure). The extended model in particular performed better in differentiating low- and intermediate-risk groups. CONCLUSIONS Risk scores combining clinical characteristics with the anatomic SYNTAX score substantially better predict 3-year mortality than the SYNTAX score alone and should be used for long-term risk stratification of patients undergoing PCI.

Pretreatment Tables Predicting Pathologic Stage of Locally Advanced Prostate Cancer

BACKGROUND Pretreatment tables for the prediction of pathologic stage have been published and validated for localized prostate cancer (PCa). No such tables are available for locally advanced (cT3a) PCa. OBJECTIVE To construct tables predicting pathologic outcome after radical prostatectomy (RP) for patients with cT3a PCa with the aim to help guide treatment decisions in clinical practice. DESIGN, SETTING, AND PARTICIPANTS This was a multicenter retrospective cohort study including 759 consecutive patients with cT3a PCa treated with RP between 1987 and 2010. INTERVENTION Retropubic RP and pelvic lymphadenectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Patients were divided into pretreatment prostate-specific antigen (PSA) and biopsy Gleason score (GS) subgroups. These parameters were used to construct tables predicting pathologic outcome and the presence of positive lymph nodes (LNs) after RP for cT3a PCa using ordinal logistic regression. RESULTS AND LIMITATIONS In the model predicting pathologic outcome, the main effects of biopsy GS and pretreatment PSA were significant. A higher GS and/or higher PSA level was associated with a more unfavorable pathologic outcome. The validation procedure, using a repeated split-sample method, showed good predictive ability. Regression analysis also showed an increasing probability of positive LNs with increasing PSA levels and/or higher GS. Limitations of the study are the retrospective design and the long study period. CONCLUSIONS These novel tables predict pathologic stage after RP for patients with cT3a PCa based on pretreatment PSA level and biopsy GS. They can be used to guide decision making in men with locally advanced PCa. PATIENT SUMMARY Our study might provide physicians with a useful tool to predict pathologic stage in locally advanced prostate cancer that might help select patients who may need multimodal treatment.

Visible near infra-red (VisNIR) spectroscopy for predicting soil organic carbon in Ethiopia

Over the past few decades, the advantages of the visible-near infra-red (VisNIR) diffuse reflectance spectrometer (DRS) method have enabled prediction of soil organic carbon (SOC). In this study, SOC was predicted using regression models for samples taken from three sites (Gununo, Maybar and Anjeni) in Ethiopia. SOC was characterized in laboratory using conventional wet chemistry and VisNIR-DRS methods. Principal component analysis (PCA), principal component regression (PCR) and partial least square regression (PLS) models were developed using Unscrambler X 10.2. PCA results show that the first two components accounted for a minimum of 96% variation which increased for individual sites and with data treatments. Correlation (r), coefficient of determination (R2) and residual prediction deviation (RPD) were used to rate four models built. PLS model (r, R2, RPD) values for Anjeni were 0.9, 0.9 and 3.6; for Gununo values 0.6, 0.3 and 1.2; for Maybar values 0.6, 0.3 and 0.9, and for the three sites values 0.7, 0.6 and 1.5, respectively. PCR model values (r, R2, RPD) for Anjeni were 0.9, 0.8 and 2.7; for Gununo values 0.5, 0.3 and 1; for Maybar values 0.5, 0.1 and 0.7, and for the three sites values 0.7, 0.5 and 1.2, respectively. Comparison and testing of models shows superior performance of PLS to PCR. Models were rated as very poor (Maybar), poor (Gununo and three sites) and excellent (Anjeni). A robust model, Anjeni, is recommended for prediction of SOC in Ethiopia.

A mouse model of HIES reveals pro- and anti-inflammatory functions of STAT3.

Mutations of STAT3 underlie the autosomal dominant form of hyperimmunoglobulin E syndrome (HIES). STAT3 has critical roles in immune cells and thus, hematopoietic stem cell transplantation (HSCT), might be a reasonable therapeutic strategy in this disease. However, STAT3 also has critical functions in nonhematopoietic cells and dissecting the protean roles of STAT3 is limited by the lethality associated with germline deletion of Stat3. Thus, predicting the efficacy of HSCT for HIES is difficult. To begin to dissect the importance of STAT3 in hematopoietic and nonhematopoietic cells as it relates to HIES, we generated a mouse model of this disease. We found that these transgenic mice recapitulate multiple aspects of HIES, including elevated serum IgE and failure to generate Th17 cells. We found that these mice were susceptible to bacterial infection that was partially corrected by HSCT using wild-type bone marrow, emphasizing the role played by the epithelium in the pathophysiology of HIES.

Predicting Physical Activity in Adolescents: The Role of Compensatory Health Beliefs within the Health Action Process Approach

Objective: Compensatory health beliefs (CHBs), defined as beliefs that healthy behaviours can compensate for unhealthy behaviours, may be one possible factor hindering people in adopting a healthier lifestyle. This study examined the contribution of CHBs to the prediction of adolescents’ physical activity within the theoretical framework of the Health Action Process Approach (HAPA). Design: The study followed a prospective survey design with assessments at baseline (T1) and two weeks later (T2). Method: Questionnaire data on physical activity, HAPA variables and CHBs were obtained twice from 430 adolescents of four different Swiss schools. Multilevel modelling was applied. Results: CHBs added significantly to the prediction of intentions and change in intentions, in that higher CHBs were associated with lower intentions to be physically active at T2 and a reduction in intentions from T1 to T2. No effect of CHBs emerged for the prediction of self-reported levels of physical activity at T2 and change in physical activity from T1 to T2. Conclusion: Findings emphasise the relevance of examining CHBs in the context of an established health behaviour change model and suggest that CHBs are of particular importance in the process of intention formation.