A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.

Simulation-based cost-utility analysis of population screening-based alendronate use in Switzerland

A simulation model adopting a health system perspective showed population-based screening with DXA, followed by alendronate treatment of persons with osteoporosis, or with anamnestic fracture and osteopenia, to be cost-effective in Swiss postmenopausal women from age 70, but not in men. INTRODUCTION: We assessed the cost-effectiveness of a population-based screen-and-treat strategy for osteoporosis (DXA followed by alendronate treatment if osteoporotic, or osteopenic in the presence of fracture), compared to no intervention, from the perspective of the Swiss health care system. METHODS: A published Markov model assessed by first-order Monte Carlo simulation was refined to reflect the diagnostic process and treatment effects. Women and men entered the model at age 50. Main screening ages were 65, 75, and 85 years. Age at bone densitometry was flexible for persons fracturing before the main screening age. Realistic assumptions were made with respect to persistence with intended 5 years of alendronate treatment. The main outcome was cost per quality-adjusted life year (QALY) gained. RESULTS: In women, costs per QALY were Swiss francs (CHF) 71,000, CHF 35,000, and CHF 28,000 for the main screening ages of 65, 75, and 85 years. The threshold of CHF 50,000 per QALY was reached between main screening ages 65 and 75 years. Population-based screening was not cost-effective in men. CONCLUSION: Population-based DXA screening, followed by alendronate treatment in the presence of osteoporosis, or of fracture and osteopenia, is a cost-effective option in Swiss postmenopausal women after age 70.

The performance of conventional and fluorescence-based methods for occlusal caries detection: an in vivo study with histologic validation

The authors conducted an in vivo study to determine clinical cutoffs for a laser fluorescence (LF) device, an LF pen and a fluorescence camera (FC), as well as to evaluate the clinical performance of these methods and conventional methods in detecting occlusal caries in permanent teeth by using the histologic gold standard for total validation of the sample.

FORA - A Fuzzy Set Based Framework for Online Reputation Management

The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly exhibit a disastrous influence on the online reputation of organizations. Based on social Web data, this study describes the building of an ontology based on fuzzy sets. At the end of a recurring harvesting of folksonomies by Web agents, the aggregated tags are purified, linked, and transformed to a so-called fuzzy grassroots ontology by means of a fuzzy clustering algorithm. This self-updating ontology is used for online reputation analysis, a crucial task of reputation management, with the goal to follow the online conversation going on around an organization to discover and monitor its reputation. In addition, an application of the Fuzzy Online Reputation Analysis (FORA) framework, lesson learned, and potential extensions are discussed in this article.

Effectiveness of fluorescence-based methods to detect in situ demineralization and remineralization on smooth surfaces.

This study aimed to evaluate the effectiveness of fluorescence-based methods (DIAGNOdent, LF; DIAGNOdent pen, LFpen, and VistaProof fluorescence camera, FC) in detecting demineralization and remineralization on smooth surfaces in situ. Ten volunteers wore acrylic palatal appliances, each containing 6 enamel blocks that were demineralized for 14 days by exposure to a 20% sucrose solution and 3 of them were remineralized for 7 days with fluoride dentifrice. Sixty enamel blocks were evaluated at baseline, after demineralization and 30 blocks after remineralization by two examiners using LF, LFpen and FC. They were submitted to surface microhardness (SMH) and cross-sectional microhardness analysis. The integrated loss of surface hardness (ΔKHN) was calculated. The intraclass correlation coefficient for interexaminer reproducibility ranged from 0.21 (FC) to 0.86 (LFpen). SMH, LF and LFpen values presented significant differences among the three phases. However, FC fluorescence values showed no significant differences between the demineralization and remineralization phases. Fluorescence values for baseline, demineralized and remineralized enamel were, respectively, 5.4 ± 1.0, 9.2 ± 2.2 and 7.0 ± 1.5 for LF; 10.5 ± 2.0, 15.0 ± 3.2 and 12.5 ± 2.9 for LFpen, and 1.0 ± 0.0, 1.0 ± 0.1 and 1.0 ± 0.1 for FC. SMH and ΔKHN showed significant differences between demineralization and remineralization phases. There was a negative and significant correlation between SMH and LF and LFpen in the remineralization phase. In conclusion, LF and LFpen devices were effective in detecting demineralization and remineralization on smooth surfaces provoked in situ.

Effectiveness of Fluorescence-based Methods in Monitoring Progression of Noncavitated Caries-like Lesions on Smooth Surfaces

Although there has been a significant decrease in caries prevalence in developed countries, the slower progression of dental caries requires methods capable of detecting and quantifying lesions at an early stage. The aim of this study was to evaluate the effectiveness of fluorescence-based methods (DIAGNOdent 2095 laser fluorescence device [LF], DIAGNOdent 2190 pen [LFpen], and VistaProof fluorescence camera [FC]) in monitoring the progression of noncavitated caries-like lesions on smooth surfaces. Caries-like lesions were developed in 60 blocks of bovine enamel using a bacterial model of Streptococcus mutans and Lactobacillus acidophilus . Enamel blocks were evaluated by two independent examiners at baseline (phase I), after the first cariogenic challenge (eight days) (phase II), and after the second cariogenic challenge (a further eight days) (phase III) by two independent examiners using the LF, LFpen, and FC. Blocks were submitted to surface microhardness (SMH) and cross-sectional microhardness analyses. The intraclass correlation coefficient for intra- and interexaminer reproducibility ranged from 0.49 (FC) to 0.94 (LF/LFpen). SMH values decreased and fluorescence values increased significantly among the three phases. Higher values for sensitivity, specificity, and area under the receiver operating characteristic curve were observed for FC (phase II) and LFpen (phase III). A significant correlation was found between fluorescence values and SMH in all phases and integrated loss of surface hardness (ΔKHN) in phase III. In conclusion, fluorescence-based methods were effective in monitoring noncavitated caries-like lesions on smooth surfaces, with moderate correlation with SMH, allowing differentiation between sound and demineralized enamel.

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.

A Hybrid Multimodal Non-Rigid Registration of MR Images Based on Diffeomorphic Demons

n this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

Influence of different professional prophylactic methods on fluorescence measurements for detection of occlusal caries

This study aimed to evaluate the influence of professional prophylactic methods on the DIAGNOdent 2095, DIAGNOdent 2190 and VistaProof performance in detecting occlusal caries. Assessments were performed in 110 permanent teeth at baseline and after bicarbonate jet or prophylactic paste and rinsing. Performance in terms of sensitivity improved after rinsing of the occlusal surfaces when the prophylactic paste was used. However, the sodium bicarbonate jet did not significantly influence the performance of the fluorescence-based methods. It can be concluded that different professional prophylactic methods can significantly influence the performance of fluorescence-based methods for occlusal caries detection.

Monitoring Butterfly Abundance: Beyond Pollard Walks

Most butterfly monitoring protocols rely on counts along transects (Pollard walks) to generate species abundance indices and track population trends. It is still too often ignored that a population count results from two processes: the biological process (true abundance) and the statistical process (our ability to properly quantify abundance). Because individual detectability tends to vary in space (e.g., among sites) and time (e.g., among years), it remains unclear whether index counts truly reflect population sizes and trends. This study compares capture-mark-recapture (absolute abundance) and count-index (relative abundance) monitoring methods in three species (Maculinea nausithous and Iolana iolas: Lycaenidae; Minois dryas: Satyridae) in contrasted habitat types. We demonstrate that intraspecific variability in individual detectability under standard monitoring conditions is probably the rule rather than the exception, which questions the reliability of count-based indices to estimate and compare specific population abundance. Our results suggest that the accuracy of count-based methods depends heavily on the ecology and behavior of the target species, as well as on the type of habitat in which surveys take place. Monitoring programs designed to assess the abundance and trends in butterfly populations should incorporate a measure of detectability. We discuss the relative advantages and inconveniences of current monitoring methods and analytical approaches with respect to the characteristics of the species under scrutiny and resources availability.

How much is there really? Why stereology is essential in lung morphometry

Quantitative data on lung structure are essential to set up structure-function models for assessing the functional performance of the lung or to make statistically valid comparisons in experimental morphology, physiology, or pathology. The methods of choice for microscopy-based lung morphometry are those of stereology, the science of quantitative characterization of irregular three-dimensional objects on the basis of measurements made on two-dimensional sections. From a practical perspective, stereology is an assumption-free set of methods of unbiased sampling with geometric probes, based on a solid mathematical foundation. Here, we discuss the pitfalls of lung morphometry and present solutions, from specimen preparation to the sampling scheme in multiple stages, for obtaining unbiased estimates of morphometric parameters such as volumes, surfaces, lengths, and numbers. This is demonstrated on various examples. Stereological methods are accurate, efficient, simple, and transparent; the precision of the estimates depends on the size and distribution of the sample. For obtaining quantitative data on lung structure at all microscopic levels, state-of-the-art stereology is the gold standard.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Primary care physician supply and other key determinants of health care utilisation: The case of Switzerland

Background The Swiss government decided to freeze new accreditations for physicians in private practice in Switzerland based on the assumption that demand-induced health care spending may be cut by limiting care offers. This legislation initiated an ongoing controversial public debate in Switzerland. The aim of this study is therefore the determination of socio-demographic and health system-related factors of per capita consultation rates with primary care physicians in the multicultural population of Switzerland. Methods The data were derived from the complete claims data of Swiss health insurers for 2004 and included 21.4 million consultations provided by 6564 Swiss primary care physicians on a fee-for-service basis. Socio-demographic data were obtained from the Swiss Federal Statistical Office. Utilisation-based health service areas were created and were used as observational units for statistical procedures. Multivariate and hierarchical models were applied to analyze the data. Results Models within the study allowed the definition of 1018 primary care service areas with a median population of 3754 and an average per capita consultation rate of 2.95 per year. Statistical models yielded significant effects for various geographical, socio-demographic and cultural factors. The regional density of physicians in independent practice was also significantly associated with annual consultation rates and indicated an associated increase 0.10 for each additional primary care physician in a population of 10,000 inhabitants. Considerable differences across Swiss language regions were observed with reference to the supply of ambulatory health resources provided either by primary care physicians, specialists, or hospital-based ambulatory care. Conclusion The study documents a large small-area variation in utilisation and provision of health care resources in Switzerland. Effects of physician density appeared to be strongly related to Swiss language regions and may be rooted in the different cultural backgrounds of the served populations.

Performance of fluorescence methods, radiographic examination and ICDAS II on occlusal surfaces in vitro

This study compared the performance of fluorescence-based methods, radiographic examination, and International Caries Detection and Assessment System (ICDAS) II on occlusal surfaces. One hundred and nineteen permanent human molars were assessed twice by 2 experienced dentists using the laser fluorescence (LF and LFpen) and fluorescence camera (FC) devices, ICDAS II and bitewing radiographs (BW). After measuring, the teeth were histologically prepared and assessed for caries extension. The sensitivities for dentine caries detection were 0.86 (FC), 0.78 (LFpen), 0.73 (ICDAS II), 0.51 (LF) and 0.34 (BW). The specificities were 0.97 (BW), 0.89 (LF), 0.65 (ICDAS II), 0.63 (FC) and 0.56 (LFpen). BW presented the highest values of likelihood ratio (LR)+ (12.47) and LR- (0.68). Rank correlations with histology were 0.53 (LF), 0.52 (LFpen), 0.41 (FC), 0.59 (ICDAS II) and 0.57 (BW). The area under the ROC curve varied from 0.72 to 0.83. Inter- and intraexaminer intraclass correlation values were respectively 0.90 and 0.85 (LF), 0.93 and 0.87 (LFpen) and 0.85 and 0.76 (FC). The ICDAS II kappa values were 0.51 (interexaminer) and 0.61 (intraexaminer). The BW kappa values were 0.50 (interexaminer) and 0.62 (intraexaminer). The Bland and Altman limits of agreement were 46.0 and 38.2 (LF), 55.6 and 40.0 (LFpen) and 1.12 and 0.80 (FC), for intra- and interexaminer reproducibilities. The posttest probability for dentine caries detection was high for BW and LF. In conclusion, LFpen, FC and ICDAS II presented better sensitivity and LF and BW better specificity. ICDAS II combined with BW showed the best performance and is the best combination for detecting caries on occlusal surfaces.