Pharmacological and non-pharmacological therapy for arrhythmias in the pediatric population: EHRA and AEPC-Arrhythmia Working Group joint consensus statement

In children with structurally normal hearts, the mechanisms of arrhythmias are usually the same as in the adult patient. Some arrhythmias are particularly associated with young age and very rarely seen in adult patients. Arrhythmias in structural heart disease may be associated either with the underlying abnormality or result from surgical intervention. Chronic haemodynamic stress of congenital heart disease (CHD) might create an electrophysiological and anatomic substrate highly favourable for re-entrant arrhythmias. As a general rule, prescription of antiarrhythmic drugs requires a clear diagnosis with electrocardiographic documentation of a given arrhythmia. Risk-benefit analysis of drug therapy should be considered when facing an arrhythmia in a child. Prophylactic antiarrhythmic drug therapy is given only to protect the child from recurrent supraventricular tachycardia during this time span until the disease will eventually cease spontaneously. In the last decades, radiofrequency catheter ablation is progressively used as curative therapy for tachyarrhythmias in children and patients with or without CHD. Even in young children, procedures can be performed with high success rates and low complication rates as shown by several retrospective and prospective paediatric multi-centre studies. Three-dimensional mapping and non-fluoroscopic navigation techniques and enhanced catheter technology have further improved safety and efficacy even in CHD patients with complex arrhythmias. During last decades, cardiac devices (pacemakers and implantable cardiac defibrillator) have developed rapidly. The pacing generator size has diminished and the pacing leads have become progressively thinner. These developments have made application of cardiac pacing in children easier although no dedicated paediatric pacing systems exist.

Treatment of aortic stenosis with a self-expanding transcatheter valve: the International Multi-centre ADVANCE Study.

AIM Transcatheter aortic valve implantation has become an alternative to surgery in higher risk patients with symptomatic aortic stenosis. The aim of the ADVANCE study was to evaluate outcomes following implantation of a self-expanding transcatheter aortic valve system in a fully monitored, multi-centre 'real-world' patient population in highly experienced centres. METHODS AND RESULTS Patients with severe aortic stenosis at a higher surgical risk in whom implantation of the CoreValve System was decided by the Heart Team were included. Endpoints were a composite of major adverse cardiovascular and cerebrovascular events (MACCE; all-cause mortality, myocardial infarction, stroke, or reintervention) and mortality at 30 days and 1 year. Endpoint-related events were independently adjudicated based on Valve Academic Research Consortium definitions. A total of 1015 patients [mean logistic EuroSCORE 19.4 ± 12.3% [median (Q1,Q3), 16.0% (10.3, 25.3%)], age 81 ± 6 years] were enrolled. Implantation of the CoreValve System led to a significant improvement in haemodynamics and an increase in the effective aortic valve orifice area. At 30 days, the MACCE rate was 8.0% (95% CI: 6.3-9.7%), all-cause mortality was 4.5% (3.2-5.8%), cardiovascular mortality was 3.4% (2.3-4.6%), and the rate of stroke was 3.0% (2.0-4.1%). The life-threatening or disabling bleeding rate was 4.0% (2.8-6.3%). The 12-month rates of MACCE, all-cause mortality, cardiovascular mortality, and stroke were 21.2% (18.4-24.1%), 17.9% (15.2-20.5%), 11.7% (9.4-14.1%), and 4.5% (2.9-6.1%), respectively. The 12-month rates of all-cause mortality were 11.1, 16.5, and 23.6% among patients with a logistic EuroSCORE ≤10%, EuroSCORE 10-20%, and EuroSCORE >20% (P< 0.05), respectively. CONCLUSION The ADVANCE study demonstrates the safety and effectiveness of the CoreValve System with low mortality and stroke rates in higher risk real-world patients with severe aortic stenosis.

Immunologic response to the survivin-derived multi-epitope vaccine EMD640744 in patients with advanced solid tumors

PURPOSE Survivin is a member of the inhibitor-of-apoptosis family. Essential for tumor cell survival and overexpressed in most cancers, survivin is a promising target for anti-cancer immunotherapy. Immunogenicity has been demonstrated in multiple cancers. Nonetheless, few clinical trials have demonstrated survivin-vaccine-induced immune responses. EXPERIMENTAL DESIGN This phase I trial was conducted to test whether vaccine EMD640744, a cocktail of five HLA class I-binding survivin peptides in Montanide(®) ISA 51 VG, promotes anti-survivin T-cell responses in patients with solid cancers. The primary objective was to compare immunologic efficacy of EMD640744 at doses of 30, 100, and 300 μg. Secondary objectives included safety, tolerability, and clinical efficacy. RESULTS In total, 49 patients who received ≥2 EMD640744 injections with available baseline- and ≥1 post-vaccination samples [immunologic-diagnostic (ID)-intention-to-treat] were analyzed by ELISpot- and peptide/MHC-multimer staining, revealing vaccine-activated peptide-specific T-cell responses in 31 patients (63 %). This cohort included the per study protocol relevant ID population for the primary objective, i.e., T-cell responses by ELISpot in 17 weeks following first vaccination, as well as subjects who discontinued the study before week 17 but showed responses to the treatment. No dose-dependent effects were observed. In the majority of patients (61 %), anti-survivin responses were detected only after vaccination, providing evidence for de novo induction. Best overall tumor response was stable disease (28 %). EMD640744 was well tolerated; local injection-site reactions constituted the most frequent adverse event. CONCLUSIONS Vaccination with EMD640744 elicited T-cell responses against survivin peptides in the majority of patients, demonstrating the immunologic efficacy of EMD640744.

Risk factors for depressed mood amongst a community dwelling older age population in England: cross-sectional survey data from the PRO-AGE study.

BACKGROUND The Quality and Outcomes Framework in the United Kingdom (UK) National Health Service previously highlighted case finding of depression amongst patients with diabetes or coronary heart disease. However, depression in older people remains under-recognized. Comprehensive data for analyses of the association of depression in older age with other health and functional measures, and demographic factors from community populations within England, are lacking. METHODS Secondary analyses of cross-sectional baseline survey data from the England arm of a randomised controlled trial of health risk appraisal for older people in Europe; PRO-AGE study. Data from 1085 community-dwelling non-disabled people aged 65 years or more from three group practices in suburban London contributed to this study. Depressed mood was ascertained from the 5-item Mental Health Inventory Screening test. Exploratory multivariable logistic regression was used to identify the strongest associations of depressed mood with a previous diagnosis of a specified physical/mental health condition, health and functional measures, and demographic factors. RESULTS Depressed mood occurred in 14% (155/1085) of participants. A previous diagnoses of depression (OR 3.39; P < 0.001) and poor vision as determined from a Visual Function Questionnaire (OR 2.37; P = 0.001) were amongst the strongest factors associated with depressed mood that were independent of functional impairment, other co-morbidities, and demographic factors. A subgroup analyses on those without a previous diagnosis of depression also indicated that within this group, poor vision (OR 2.51; P = 0.002) was amongst the strongest independent factors associated with depressed mood. CONCLUSIONS Previous case-finding strategies in primary care focussed on heart disease and diabetes but health-related conditions other than coronary heart disease and diabetes are also associated with an increased risk for depression. Complex issues of multi-morbidity occur within aging populations. 'Risk' factors that appeared stronger than those, such as, diabetes and coronary heart disease that until recently prompted for screening in the UK due to the QOF, were identified, and independent of other morbidities associated with depressed mood. From the health and functional factors investigated, amongst the strongest factors associated with depressed mood was poor vision. Consideration to case finding for depressed mood among older people with visual impairment might be justified.

In-vitro activity of taurolidine on single species and a multispecies population associated with periodontitis.

The antimicrobial activity of taurolidine was compared with minocycline against microbial species associated with periodontitis (four single strains and a 12-species mixture). Minimal inhibitory concentrations (MICs) and minimal bactericidal concentrations (MBCs), killing as well as activities on established and forming single-species biofilms and a 12-species biofilm were determined. The MICs of taurolidine against single species were always 0.31 mg/ml, the MBCs were 0.64 mg/ml. The used mixed microbiota was less sensitive to taurolidine, MIC and the MBC was 2.5 mg/ml. The strains and the mixture were completely killed by 2.5 mg/ml taurolidine, whereas 256 μg/ml minocycline reduced the bacterial counts of the mixture by 5 log10 colony forming units (cfu). Coating the surface with 10 mg/ml taurolidine or 256 μg/ml minocycline prevented completely biofilm formation of Porphyromonas gingivalis ATCC 33277 but not of Aggregatibacter actinomycetemcomitans Y4 and the mixture. On 4.5 d old biofilms, taurolidine acted concentration dependent with a reduction by 5 log10 cfu (P. gingivalis ATCC 33277) and 7 log10 cfu (A. actinomycetemcomitans Y4) when applying 10 mg/ml. Minocycline decreased the cfu counts by 1-2 log10 cfu independent of the used concentration. The reduction of the cfu counts in the 4.5 d old multi-species biofilms was about 3 log10 cfu after application of any minocycline concentration and after using 10 mg/ml taurolidine. Taurolidine is active against species associated with periodontitis, even within biofilms. Nevertheless a complete elimination of complex biofilms by taurolidine seems to be impossible and underlines the importance of a mechanical removal of biofilms prior to application of taurolidine.

Automatic multi-resolution shape modeling of multi-organ structures.

Point Distribution Models (PDM) are among the most popular shape description techniques and their usefulness has been demonstrated in a wide variety of medical imaging applications. However, to adequately characterize the underlying modeled population it is essential to have a representative number of training samples, which is not always possible. This problem is especially relevant as the complexity of the modeled structure increases, being the modeling of ensembles of multiple 3D organs one of the most challenging cases. In this paper, we introduce a new GEneralized Multi-resolution PDM (GEM-PDM) in the context of multi-organ analysis able to efficiently characterize the different inter-object relations, as well as the particular locality of each object separately. Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller anatomically significant regions within organs. The significant advantage of the GEM-PDM method over two previous approaches (PDM and hierarchical PDM) in terms of shape modeling accuracy and robustness to noise, has been successfully verified for two different databases of sets of multiple organs: six subcortical brain structures, and seven abdominal organs. Finally, we propose the integration of the new shape modeling framework into an active shape-model-based segmentation algorithm. The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.

1D.03: Inactive Matrix Gla Protein is Assocated with Renal Resistive Index in a Population-Based Study

OBJECTIVE Renal resistive index (RRI) varies directly with renal vascular stiffness and pulse pressure. RRI correlates positively with arteriolosclerosis in damaged kidneys and predicts progressive renal dysfunction. Matrix Gla-protein (MGP) is a vascular calcification inhibitor that needs vitamin K to be activated. Inactive MGP, known as desphospho-uncarboxylated MGP (dp-ucMGP), can be measured in plasma and has been associated with various cardiovascular (CV) markers, CV outcomes and mortality. In this study we hypothesize that increased RRI is associated with high levels of dp-ucMGP. DESIGN AND METHOD We recruited participants via a multi-center family-based cross-sectional study in Switzerland exploring the role of genes and kidney hemodynamics in blood pressure regulation. Dp-ucMGP was quantified in plasma samples by sandwich ELISA. Renal doppler sonography was performed using a standardized protocol to measure RRIs on 3 segmental arteries in each kidney. The mean of the 6 measures was reported. Multiple regression analysis was performed to estimate associations between RRI and dp-ucMGP adjusting for sex, age, pulse pressure, mean pressure, renal function and other CV risk factors. RESULTS We included 1035 participants in our analyses. Mean values were 0.64 ± 0.06 for RRI and 0.44 ± 0.21 (nmol/L) for dp-ucMGP. RRI was positively associated with dp-ucMGP both before and after adjustment for sex, age, body mass index, pulse pressure, mean pressure, heart rate, renal function, low and high density lipoprotein, smoking status, diabetes, blood pressure and cholesterol lowering drugs, and history of CV disease (P < 0.001). CONCLUSIONS RRI is independently and positively associated with high levels of dp-ucMGP after adjustment for pulse pressure and common CV risk factors. Further studies are needed to determine if vitamin K supplementation can have a positive effect on renal vascular stiffness and kidney function.

Genetic diversity and differentiation follow secondary succession in a multi-species study on woody plants from subtropical China

Aims: Species diversity and genetic diversity may be affected in parallel by similar environmental drivers. However, genetic diversity may also be affected independently by habitat characteristics. We aim at disentangling relationships between genetic diversity, species diversity and habitat characteristics of woody species in subtropical forest. Methods: We studied 11 dominant tree and shrub species in 27 plots in Gutianshan, China, and assessed their genetic diversity (Ar) and population differentiation (F’ST) with microsatellite markers. We tested if Ar and population specific F’ST were correlated to local species diversity and plot characteristics. Multi-model inference and model averaging were used to determine the relative importance of each predictor. Additionally we tested for isolation-by-distance and isolation-by-elevation by regressing pairwise F’ST against pairwise spatial and elevational distances. Important findings: Genetic diversity was not related to species diversity for any of the study species. Thus, our results do not support joint effects of habitat characteristics on these two levels of biodiversity. Instead, genetic diversity in two understory shrubs, Rhododendron simsii and Vaccinium carlesii, was affected by plot age with decreasing genetic diversity in successionally older plots. Population differentiation increased with plot age in Rhododendron simsii and Lithocarpus glaber. This shows that succession can reduce genetic diversity within, and increase genetic diversity between populations. Furthermore, we found four cases of isolation-by-distance and two cases of isolation-by-elevation. The former indicates inefficient pollen and seed dispersal by animals whereas the latter might be due to phenological asynchronies. These patterns indicate that succession can affect genetic diversity without parallel effects on species diversity and that gene flow in a continuous subtropical forest can be restricted even at a local scale.

Dynamic population coding in primary visual cortex

More than a century ago Ramon y Cajal pioneered the description of neural circuits. Currently, new techniques are being developed to streamline the characterization of entire neural circuits. Even if this 'connectome' approach is successful, it will represent only a static description of neural circuits. Thus, a fundamental question in neuroscience is to understand how information is dynamically represented by neural populations. In this thesis, I studied two main aspects of dynamical population codes. ^ First, I studied how the exposure or adaptation, for a fraction of a second to oriented gratings dynamically changes the population response of primary visual cortex neurons. The effects of adaptation to oriented gratings have been extensively explored in psychophysical and electrophysiological experiments. However, whether rapid adaptation might induce a change in the primary visual cortex's functional connectivity to dynamically impact the population coding accuracy is currently unknown. To address this issue, we performed multi-electrode recordings in primary visual cortex, where adaptation has been previously shown to induce changes in the selectivity and response amplitude of individual neurons. We found that adaptation improves the population coding accuracy. The improvement was more prominent for iso- and orthogonal orientation adaptation, consistent with previously reported psychophysical experiments. We propose that selective decorrelation is a metabolically inexpensive mechanism that the visual system employs to dynamically adapt the neural responses to the statistics of the input stimuli to improve coding efficiency. ^ Second, I investigated how ongoing activity modulates orientation coding in single neurons, neural populations and behavior. Cortical networks are never silent even in the absence of external stimulation. The ongoing activity can account for up to 80% of the metabolic energy consumed by the brain. Thus, a fundamental question is to understand the functional role of ongoing activity and its impact on neural computations. I studied how the orientation coding by individual neurons and cell populations in primary visual cortex depend on the spontaneous activity before stimulus presentation. We hypothesized that since the ongoing activity of nearby neurons is strongly correlated, it would influence the ability of the entire population of orientation-selective cells to process orientation depending on the prestimulus spontaneous state. Our findings demonstrate that ongoing activity dynamically filters incoming stimuli to shape the accuracy of orientation coding by individual neurons and cell populations and this interaction affects behavioral performance. In summary, this thesis is a contribution to the study of how dynamic internal states such as rapid adaptation and ongoing activity modulate the population code accuracy. ^

Ethnicity as a risk factor for diabetes incidence in a population of diagnosed hypertensives

Significant racial/ethnic differences exist in prevalence of hypertension (HTN) and non-insulin dependent diabetes mellitus (NIDDM). Hypertension is more common in diabetics than in non-diabetics, and an etiologic link between the two conditions has been proposed. Since there are few longitudinal studies of persons with both HTN and NIDDM, a retrospective cohort study was conducted to determine if ethnicity (Black, Hispanic (Mexican-American), and non-Hispanic White) was related to NIDDM incidence in a low-SES, multi-ethnic clinic population of diagnosed hypertensives. Two thousand nine hundred forty-one hypertensives free of NIDDM at baseline were followed for up to 10 years. Mean baseline age was 56 $\pm$ 12 years, M:F percent was 33:67, and Black:Hispanic:White percent was 63:17:20. There were 236 incident cases of NIDDM. In Cox proportional hazards analysis, the risk of developing NIDDM over 10 years was not related to ethnicity after controlling for significant covariates, including age, baseline blood glucose and body mass index (adjusted RR for Blacks compared to Whites =.82, 95 percent CI =.57-1.18; adjusted RR for Hispanics compared to Whites =.84, 95 percent CI =.51-1.38). This result contrasts with the increased risk of NIDDM among Blacks and Hispanics compared to Whites found in the general population. The study suggests that a diagnosis of hypertension equalizes the risk of developing NIDDM among the three ethnic groups. ^

THE RELATIONSHIP BETWEEN SERUM CHOLESTEROL AND CANCER INCIDENCE IN THE POPULATION OF THE HYPERTENSION DETECTION AND FOLLOW-UP PROGRAM

The relationship between serum cholesterol and cancer incidence was investigated in the population of the Hypertension Detection and Follow-up Program (HDFP). The HDFP was a multi-center trial designed to test the effectiveness of a stepped program of medication in reducing mortality associated with hypertension. Over 10,000 participants, ages 30-69, were followed with clinic and home visits for a minimum of five years. Cancer incidence was ascertained from existing study documents, which included hospitalization records, autopsy reports and death certificates. During the five years of follow-up, 286 new cancer cases were documented. The distribution of sites and total number of cases were similar to those predicted using rates from the Third National Cancer Survey. A non-fasting baseline serum cholesterol level was available for most participants. Age, sex, and race specific five-year cancer incidence rates were computed for each cholesterol quartile. Rates were also computed by smoking status, education status, and percent ideal weight quartiles. In addition, these and other factors were investigated with the use of the multiple logistic model.^ For all cancers combined, a significant inverse relationship existed between baseline serum cholesterol levels and cancer incidence. Previously documented associations between smoking, education and cancer were also demonstrated but did not account for the relationship between serum cholesterol and cancer. The relationship was more evident in males than females but this was felt to represent the different distribution of occurrence of specific cancer sites in the two sexes. The inverse relationship existed for all specific sites investigated (except breast) although a level of statistical significance was reached only for prostate carcinoma. Analyses after exclusion of cases diagnosed during the first two years of follow-up still yielded an inverse relationship. Life table analysis indicated that competing risks during the period of follow-up did not account for the existence of an inverse relationship. It is concluded that a weak inverse relationship does exist between serum cholesterol for many but not all cancer sites. This relationship is not due to confounding by other known cancer risk factors, competing risks or persons entering the study with undiagnosed cancer. Not enough information is available at the present time to determine whether this relationship is causal and further research is suggested. ^

An outbreak of Multi-Drug Resistant Acinetobacter in the burn intensive care unit of a large tertiary care center

Risk factors for Multi-Drug Resistant Acinetobacter (MDRA) acquisition were studied in patients in a burn intensive care unit (ICU) where there was an outbreak of MDRA. Forty cases were matched with eighty controls based on length of stay in the Burn ICU and statistical analysis was performed on data for several different variables. Matched analysis showed that mechanical ventilation, transport ventilation, number of intubations, number of bronchoscopy procedures, total body surface area burn, and prior Methicillin Resistant Staphylococcus aureus colonization were all significant risk factors for MDRA acquisition. ^ MDRA remains a significant threat to the burn population. Treatment for burn patients with MDRA is challenging as resistance to antibiotics continues to increase. This study underlined the need to closely monitor the most critically ill ventilated patients during an outbreak of MDRA as they are the most at risk for MDRA acquisition.^

Impact of traffic pollution on telomere length and chronic diseases: Results from the multi-ethnic study of atherosclerosis and the Mexican-American cohort study

Exposure to air pollutants in urban locales has been associated with increased risk for chronic diseases including cardiovascular disease (CVD) and pulmonary diseases in epidemiological studies. The exact mechanism explaining how air pollution affects chronic disease is still unknown. However, oxidative stress and inflammatory pathways have been posited as likely mechanisms. ^ Data from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Mexican-American Cohort Study (2003-2009) were used to examine the following aims, respectively: 1) to evaluate the association between long-term exposure to ambient particulate matter (PM) (PM10 and PM2.5) and nitrogen oxides (NO x) and telomere length (TL) among approximately 1,000 participants within MESA; and 2) to evaluate the association between traffic-related air pollution with self-reported asthma, diabetes, and hypertension among Mexican-Americans in Houston, Texas. ^ Our results from MESA were inconsistent regarding associations between long-term exposure to air pollution and shorter telomere length based on whether the participants came from New York (NY) or Los Angeles (LA). Although not statistically significant, we observed a negative association between long-term air pollution exposure and mean telomere length for NY participants, which was consistent with our hypothesis. Positive (statistically insignificant) associations were observed for LA participants. It is possible that our findings were more influenced by both outcome and exposure misclassification than by the absence of a relationship between pollution and TL. Future studies are needed that include longitudinal measures of telomere length as well as focus on effects of specific constituents of PM and other pollutant exposures on changes in telomere length over time. ^ This research provides support that Mexican-American adults who live near a major roadway or in close proximity to a dense street network have a higher prevalence of asthma. There was a non-significant trend towards an increased prevalence of adult asthma with increasing residential traffic exposure especially for residents who lived three or more years at their baseline address. Even though the prevalence of asthma is low in the Mexican-origin population, it is the fastest growing minority group in the U.S. and we would expect a growing number of Mexican-Americans who suffer from asthma in the future. Future studies are needed to better characterize risks for asthma associated with air pollution in this population.^

Multi-temporal mapping of seagrass cover, species and biomass of the Eastern Banks, Moreton Bay, Australia, with links to shapefiles

The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.

Regularized model learning in EDAs for continuous and multi-objective optimization

Probabilistic modeling is the de�ning characteristic of estimation of distribution algorithms (EDAs) which determines their behavior and performance in optimization. Regularization is a well-known statistical technique used for obtaining an improved model by reducing the generalization error of estimation, especially in high-dimensional problems. `1-regularization is a type of this technique with the appealing variable selection property which results in sparse model estimations. In this thesis, we study the use of regularization techniques for model learning in EDAs. Several methods for regularized model estimation in continuous domains based on a Gaussian distribution assumption are presented, and analyzed from di�erent aspects when used for optimization in a high-dimensional setting, where the population size of EDA has a logarithmic scale with respect to the number of variables. The optimization results obtained for a number of continuous problems with an increasing number of variables show that the proposed EDA based on regularized model estimation performs a more robust optimization, and is able to achieve signi�cantly better results for larger dimensions than other Gaussian-based EDAs. We also propose a method for learning a marginally factorized Gaussian Markov random �eld model using regularization techniques and a clustering algorithm. The experimental results show notable optimization performance on continuous additively decomposable problems when using this model estimation method. Our study also covers multi-objective optimization and we propose joint probabilistic modeling of variables and objectives in EDAs based on Bayesian networks, speci�cally models inspired from multi-dimensional Bayesian network classi�ers. It is shown that with this approach to modeling, two new types of relationships are encoded in the estimated models in addition to the variable relationships captured in other EDAs: objectivevariable and objective-objective relationships. An extensive experimental study shows the e�ectiveness of this approach for multi- and many-objective optimization. With the proposed joint variable-objective modeling, in addition to the Pareto set approximation, the algorithm is also able to obtain an estimation of the multi-objective problem structure. Finally, the study of multi-objective optimization based on joint probabilistic modeling is extended to noisy domains, where the noise in objective values is represented by intervals. A new version of the Pareto dominance relation for ordering the solutions in these problems, namely �-degree Pareto dominance, is introduced and its properties are analyzed. We show that the ranking methods based on this dominance relation can result in competitive performance of EDAs with respect to the quality of the approximated Pareto sets. This dominance relation is then used together with a method for joint probabilistic modeling based on `1-regularization for multi-objective feature subset selection in classi�cation, where six di�erent measures of accuracy are considered as objectives with interval values. The individual assessment of the proposed joint probabilistic modeling and solution ranking methods on datasets with small-medium dimensionality, when using two di�erent Bayesian classi�ers, shows that comparable or better Pareto sets of feature subsets are approximated in comparison to standard methods.