LIF and sIL-2R plasma concentrations in IVF patients on the day of embryo transfer: predictive markers of IVF outcome.

Successful implantation is still the limiting step in IVF. We hypothesized that maternal plasma concentrations of certain cytokines at the time of embryo transfer could predict the likelihood of successful implantation and pregnancy. sIL-2R, IL-6, LIF, and MMP2 concentrations were measured in plasma from 160 IVF patients (natural and stimulated IVF cycles) on the morning of the embryo transfer (ET0) and 14days later (ET+14). Patients were ultimately subdivided into four groups depending on the IVF treatment outcome (pregnancy failure, biochemical pregnancy, first-trimester miscarriage and normal term delivery). In natural and stimulated IVF cycles at ET0, sIL-2R concentrations were threefold higher in biochemical pregnancies than in pregnancy failures (P=0.020), and in natural cycles only, 2.5-fold higher in normal term deliveries than in pregnancy failures (P=0.023). Conversely, in natural and stimulated IVF cycles at ET0, LIF concentrations were one third lower in biochemical pregnancies/first-trimester miscarriages compared with pregnancy failures (P=0.042). We suggest that high sIL-2R and low LIF concentrations in maternal plasma on the morning of the embryo transfer might be associated with increased risks of early pregnancy loss, while a basal level of sIL-2R is necessary for normal term delivery outcome. Both cytokine measurements might therefore be useful in the management of IVF patients, and modulation of their concentrations could be investigated as a therapeutic alternative for women with abnormal concentrations at the time of embryo transfer.

MGMT promoter methylation is prognostic but not predictive for outcome to adjuvant PCV chemotherapy in anaplastic oligodendroglial tumors: a report from EORTC Brain Tumor Group Study 26951.

PURPOSE: O6-methylguanine-methyltransferase (MGMT) promoter methylation has been shown to predict survival of patients with glioblastomas if temozolomide is added to radiotherapy (RT). It is unknown if MGMT promoter methylation is also predictive to outcome to RT followed by adjuvant procarbazine, lomustine, and vincristine (PCV) chemotherapy in patients with anaplastic oligodendroglial tumors (AOT). PATIENTS AND METHODS: In the European Organisation for the Research and Treatment of Cancer study 26951, 368 patients with AOT were randomly assigned to either RT alone or to RT followed by adjuvant PCV. From 165 patients of this study, formalin-fixed, paraffin-embedded tumor tissue was available for MGMT promoter methylation analysis. This was investigated with methylation specific multiplex ligation-dependent probe amplification. RESULTS: In 152 cases, an MGMT result was obtained, in 121 (80%) cases MGMT promoter methylation was observed. Methylation strongly correlated with combined loss of chromosome 1p and 19q loss (P = .00043). In multivariate analysis, MGMT promoter methylation, 1p/19q codeletion, tumor necrosis, and extent of resection were independent prognostic factors. The prognostic significance of MGMT promoter methylation was equally strong in the RT arm and the RT/PCV arm for both progression-free survival and overall survival. In tumors diagnosed at central pathology review as glioblastoma, no prognostic effect of MGMT promoter methylation was observed. CONCLUSION: In this study, on patients with AOT MGMT promoter methylation was of prognostic significance and did not have predictive significance for outcome to adjuvant PCV chemotherapy. The biologic effect of MGMT promoter methylation or pathogenetic features associated with MGMT promoter methylation may be different for AOT compared with glioblastoma.

Resurgence of HIV infection among men who have sex with men in Switzerland: mathematical modelling study.

BACKGROUND: New HIV infections in men who have sex with men (MSM) have increased in Switzerland since 2000 despite combination antiretroviral therapy (cART). The objectives of this mathematical modelling study were: to describe the dynamics of the HIV epidemic in MSM in Switzerland using national data; to explore the effects of hypothetical prevention scenarios; and to conduct a multivariate sensitivity analysis. METHODOLOGY/PRINCIPAL FINDINGS: The model describes HIV transmission, progression and the effects of cART using differential equations. The model was fitted to Swiss HIV and AIDS surveillance data and twelve unknown parameters were estimated. Predicted numbers of diagnosed HIV infections and AIDS cases fitted the observed data well. By the end of 2010, an estimated 13.5% (95% CI 12.5, 14.6%) of all HIV-infected MSM were undiagnosed and accounted for 81.8% (95% CI 81.1, 82.4%) of new HIV infections. The transmission rate was at its lowest from 1995-1999, with a nadir of 46 incident HIV infections in 1999, but increased from 2000. The estimated number of new infections continued to increase to more than 250 in 2010, although the reproduction number was still below the epidemic threshold. Prevention scenarios included temporary reductions in risk behaviour, annual test and treat, and reduction in risk behaviour to levels observed earlier in the epidemic. These led to predicted reductions in new infections from 2 to 26% by 2020. Parameters related to disease progression and relative infectiousness at different HIV stages had the greatest influence on estimates of the net transmission rate. CONCLUSIONS/SIGNIFICANCE: The model outputs suggest that the increase in HIV transmission amongst MSM in Switzerland is the result of continuing risky sexual behaviour, particularly by those unaware of their infection status. Long term reductions in the incidence of HIV infection in MSM in Switzerland will require increased and sustained uptake of effective interventions.

The predictive value of trabecular bone score (TBS) on whole lumbar vertebrae mechanics: an ex vivo study.

We investigated the association of trabecular bone score (TBS) with microarchitecture and mechanical behavior of human lumbar vertebrae. We found that TBS reflects vertebral trabecular microarchitecture and is an independent predictor of vertebral mechanics. However, the addition of TBS to areal BMD (aBMD) did not significantly improve prediction of vertebral strength. INTRODUCTION: The trabecular bone score (TBS) is a gray-level measure of texture using a modified experimental variogram which can be extracted from dual-energy X-ray absorptiometry (DXA) images. The current study aimed to confirm whether TBS is associated with trabecular microarchitecture and mechanics of human lumbar vertebrae, and if its combination with BMD improves prediction of fracture risk. METHODS: Lumbar vertebrae (L3) were harvested fresh from 16 donors. The anteroposterior and lateral bone mineral content (BMC) and areal BMD (aBMD) of the vertebral body were measured using DXA; then, the TBS was extracted using TBS iNsight software (Medimaps SA, France). The trabecular bone volume (Tb.BV/tissue volume, TV), trabecular thickness (Tb.Th), degree of anisotropy, and structure model index (SMI) were measured using microcomputed tomography. Quasi-static uniaxial compressive testing was performed on L3 vertebral bodies to assess failure load and stiffness. RESULTS: The TBS was significantly correlated to Tb.BV/TV and SMI (râeuro0/00=âeuro0/000.58 and -0.62; pâeuro0/00=âeuro0/000.02, 0.01), but not related to BMC and BMD. TBS was significantly correlated with stiffness (râeuro0/00=âeuro0/000.64; pâeuro0/00=âeuro0/000.007), independently of bone mass. Using stepwise multiple regression models, we failed to demonstrate that the combination of BMD and TBS was better at explaining mechanical behavior than either variable alone. However, the combination TBS, Tb.Th, and BMC did perform better than each parameter alone, explaining 79 % of the variability in stiffness. CONCLUSIONS: In our study, TBS was associated with microarchitecture parameters and with vertebral mechanical behavior, but TBS did not improve prediction of vertebral biomechanical properties in addition to aBMD.

The predictive value of preoperative B-type natriuretic peptide in children undergooing heart surgery.

Introduction: Low cardiac output syndrome is frequent in childrenafter heart surgery for congenital heart disease and may result in pooroutcome and increased morbidity. In the adult population, preoperativebrain natriuretic peptide (BNP) was shown to be predictive of postoperative complications. In children, the value of preoperative BNP onpostoperative outcome is not so clear. The aim of this study was todetermine the predictive value of preoperative BNP on postoperativeoutcome and low cardiac output syndrome in children after heartsurgery for congenital heart disease.Methods: We examined, retrospectively, the postoperative course of97 pediatric patients (mean age 3.7 years, range 0-14 years old) whounderwent heart surgery in a tertiary care pediatric intensive caresetting. NTproBNP was measured preoperatively in all patients(median 412 pg/ml, range 12-35'000 pg/ml). Patients were divided intothree groups according to their NTproBNP levels (group 1: 0-300 pg/ml, group 2: 300-600 pg/ml, group 3: >600 pg/ml) and then,correlations with postoperative outcomes were examined.Results: We found that patients with a high preoperative BNP requiredmore frequently prolonged (>2 days) mechanical ventilation (33%vs 40% vs 61%, p = 0.045) and stayed more frequently longer than6 days in the intensive care unit (42% vs 50% vs 71%, p = 0.03).However, high preoperative BNP was not correlated with occurrenceof low cardiac output syndrome.Conclusion: Preoperative BNP cannot be used, in children, as areliable and sole predictor of postoperative low cardiac outputsyndrome. However it may help identify, before surgery, those patientsat risk of having a difficult postoperative course.

How quickly should we titrate antihypertensive medication? Systematic review modelling blood pressure response from trial data.

Context There are no evidence syntheses available to guide clinicians on when to titrate antihypertensive medication after initiation. Objective To model the blood pressure (BP) response after initiating antihypertensive medication. Data sources electronic databases including Medline, Embase, Cochrane Register and reference lists up to December 2009. Study selection Trials that initiated antihypertensive medication as single therapy in hypertensive patients who were either drug naive or had a placebo washout from previous drugs. Data extraction Office BP measurements at a minimum of two weekly intervals for a minimum of 4 weeks. An asymptotic approach model of BP response was assumed and non-linear mixed effects modelling used to calculate model parameters. Results and conclusions Eighteen trials that recruited 4168 patients met inclusion criteria. The time to reach 50% of the maximum estimated BP lowering effect was 1 week (systolic 0.91 weeks, 95% CI 0.74 to 1.10; diastolic 0.95, 0.75 to 1.15). Models incorporating drug class as a source of variability did not improve fit of the data. Incorporating the presence of a titration schedule improved model fit for both systolic and diastolic pressure. Titration increased both the predicted maximum effect and the time taken to reach 50% of the maximum (systolic 1.2 vs 0.7 weeks; diastolic 1.4 vs 0.7 weeks). Conclusions Estimates of the maximum efficacy of antihypertensive agents can be made early after starting therapy. This knowledge will guide clinicians in deciding when a newly started antihypertensive agent is likely to be effective or not at controlling BP.

Predictive value of the MGMT promoter methylation status in metastatic melanoma patients receiving first-line temozolomide plus bevacizumab in the trial SAKK 50/07.

The O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status is a predictive parameter for the response of malignant gliomas to alkylating agents such as temozolomide. First clinical trials with temozolomide plus bevacizumab therapy in metastatic melanoma patients are ongoing, although the predictive value of the MGMT promoter methylation status in this setting remains unclear. We assessed MGMT promoter methylation in formalin-fixed, primary tumor tissue of metastatic melanoma patients treated with first-line temozolomide and bevacizumab from the trial SAKK 50/07 by methylation-specific polymerase chain reaction. In addition, the MGMT expression levels were also analyzed by MGMT immunohistochemistry. Eleven of 42 primary melanomas (26%) revealed a methylated MGMT promoter. Promoter methylation was significantly associated with response rates CR + PR versus SD + PD according to RECIST (response evaluation criteria in solid tumors) (p<0.05) with a trend to prolonged median progression-free survival (8.1 versus 3.4 months, p>0.05). Immunohistochemically different protein expression patterns with heterogeneous and homogeneous nuclear MGMT expression were identified. Negative MGMT expression levels were associated with overall disease stabilization CR+PR+SD versus PD (p=0.05). There was only a poor correlation between MGMT methylation and lack of MGMT expression. A significant proportion of melanomas have a methylated MGMT promoter. The MGMT promoter methylation status may be a promising predictive marker for temozolomide therapy in metastatic melanoma patients. Larger sample sizes may help to validate significant differences in survival type endpoints.

Which is the optimal sampling strategy for habitat suitability modelling

Designing an efficient sampling strategy is of crucial importance for habitat suitability modelling. This paper compares four such strategies, namely, 'random', 'regular', 'proportional-stratified' and 'equal -stratified'- to investigate (1) how they affect prediction accuracy and (2) how sensitive they are to sample size. In order to compare them, a virtual species approach (Ecol. Model. 145 (2001) 111) in a real landscape, based on reliable data, was chosen. The distribution of the virtual species was sampled 300 times using each of the four strategies in four sample sizes. The sampled data were then fed into a GLM to make two types of prediction: (1) habitat suitability and (2) presence/ absence. Comparing the predictions to the known distribution of the virtual species allows model accuracy to be assessed. Habitat suitability predictions were assessed by Pearson's correlation coefficient and presence/absence predictions by Cohen's K agreement coefficient. The results show the 'regular' and 'equal-stratified' sampling strategies to be the most accurate and most robust. We propose the following characteristics to improve sample design: (1) increase sample size, (2) prefer systematic to random sampling and (3) include environmental information in the design'

Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables

Questions Soil properties have been widely shown to influence plant growth and distribution. However, the degree to which edaphic variables can improve models based on topo-climatic variables is still unclear. In this study, we tested the roles of seven edaphic variables, namely (1) pH; (2) the content of nitrogen and of (3) phosphorus; (4) silt; (5) sand; (6) clay and (7) carbon-to-nitrogen ratio, as predictors of species distribution models in an edaphically heterogeneous landscape. We also tested how the respective influence of these variables in the models is linked to different ecological and functional species characteristics. Location The Western Alps, Switzerland. Methods With four different modelling techniques, we built models for 115 plant species using topo-climatic variables alone and then topo-climatic variables plus each of the seven edaphic variables, one at a time. We evaluated the contribution of each edaphic variable by assessing the change in predictive power of the model. In a second step, we evaluated the importance of the two edaphic variables that yielded the largest increase in predictive power in one final set of models for each species. Third, we explored the change in predictive power and the importance of variables across plant functional groups. Finally, we assessed the influence of the edaphic predictors on the prediction of community composition by stacking the models for all species and comparing the predicted communities with the observed community. Results Among the set of edaphic variables studied, pH and nitrogen content showed the highest contributions to improvement of the predictive power of the models, as well as the predictions of community composition. When considering all topo-climatic and edaphic variables together, pH was the second most important variable after degree-days. The changes in model results caused by edaphic predictors were dependent on species characteristics. The predictions for the species that have a low specific leaf area, and acidophilic preferences, tolerating low soil pH and high humus content, showed the largest improvement by the addition of pH and nitrogen in the model. Conclusions pH was an important predictor variable for explaining species distribution and community composition of the mountain plants considered in our study. pH allowed more precise predictions for acidophilic species. This variable should not be neglected in the construction of species distribution models in areas with contrasting edaphic conditions.

Stochastic Population Projection for Germany - based on the Quadratic Spline approach to modelling age specific fertility rates

This contribution builds upon a former paper by the authors (Lipps and Betz 2004), in which a stochastic population projection for East- and West Germany is performed. Aim was to forecast relevant population parameters and their distribution in a consistent way. We now present some modifications, which have been modelled since. First, population parameters for the entire German population are modelled. In order to overcome the modelling problem of the structural break in the East during reunification, we show that the adaptation process of the relevant figures by the East can be considered to be completed by now. As a consequence, German parameters can be modelled just by using the West German historic patterns, with the start-off population of entire Germany. Second, a new model to simulate age specific fertility rates is presented, based on a quadratic spline approach. This offers a higher flexibility to model various age specific fertility curves. The simulation results are compared with the scenario based official forecasts for Germany in 2050. Exemplary for some population parameters (e.g. dependency ratio), it can be shown that the range spanned by the medium and extreme variants correspond to the s-intervals in the stochastic framework. It seems therefore more appropriate to treat this range as a s-interval covering about two thirds of the true distribution.

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

There and back again? Combining habitat suitability modelling and connectivity analyses to assess a potential return of the otter to Switzerland

After a steady decline in the early 20th century, several terrestrial carnivore species have recently recovered in Western Europe, either through reintroductions or natural recolonization. Because of the large space requirements of these species and potential conflicts with human activities, ensuring their recovery requires the implementation of conservation and management measures that address the environmental, landscape and social dimensions of the problem. Few examples exist of such integrated management. Taking the case of the otter (Lutra lutra) in Switzerland, we propose a multi-step approach that allows to (1) identify areas with potentially suitable habitat, (2) evaluate their connectivity, (3) verify the potentiality of the species recolonization from populations in neighbouring countries. We showed that even though suitable habitat is available for the species and the level of structural connectivity within Switzerland is satisfactory, the level of connectivity with neighbouring populations is crucial to prioritize strategies that favour the species recovery in the field. This research is the first example integrating habitat suitability and connectivity assessment at different scales with other factors in a multi-step assessment for species recovery.