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Motivation: Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. Results: We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named Patika (Pathway Analysis Tool for Integration and Knowledge Acquisition). Patika is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that Patika will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development. Availability: A prototype of Patika is available upon request from the authors. Contact: patika@cs.bilkent.edu.tr * To whom correspondence should be addressed.

WOS: 000351056100052 PubMed: 25422229 Introduction: Human adiponectin (ApN) is a 30 kDa glycoprotein of 244-amino acids which is extensively produced by adipocytes. ApN acts via two receptors, namely adiponectin receptor-1 (Adipo-R1) and adiponectin receptor-2 (Adipo-R2). Studies have shown the presence of Adipo-R1 and Adipo-R2 expression immunohistochemically in human colorectal cancers (CRCs). However, only a few studies exist which investigated effects of adiponectin receptor expression on CRC characteristics. Objectives: In the present study, we aimed to explore Adipo-R1/-R2 expression in human colorectal cancers and any association with clinicopathological characteristics and survival. Materials and Methods: The study enrolled 58 colorectal cancer patients with tumor resection and a control group of 30 subjects with normal colon mucosa. Results: Positivity for Adipo-R1/-R2 expression was significantly more common in the control group in comparison to the patient group (both p

The early diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) is very important for treatment research and patient care purposes. Few biomarkers are currently considered in clinical settings, and their use is still optional. The objective of this work was to determine whether multimodal and nonpreviously AD associated features could improve the classification accuracy between AD, MCI, and healthy controls, which may impact future AD biomarkers. For this, Alzheimer's Disease Neuroimaging Initiative database was mined for case-control candidates. At least 652 baseline features extracted from MRI and PET analyses, biological samples, and clinical data up to February 2014 were used. A feature selection methodology that includes a genetic algorithm search coupled to a logistic regression classifier and forward and backward selection strategies was used to explore combinations of features. This generated diagnostic models with sizes ranging from 3 to 8, including well documented AD biomarkers, as well as unexplored image, biochemical, and clinical features. Accuracies of 0.85, 0.79, and 0.80 were achieved for HC-AD, HC-MCI, and MCI-AD classifications, respectively, when evaluated using a blind test set. In conclusion, a set of features provided additional and independent information to well-established AD biomarkers, aiding in the classification of MCI and AD. © 2015 Antonio Martínez-Torteya et al.

Discerning clusters of data points Cluster analysis is used in many disciplines to group objects according to a defined measure of distance. Numerous algorithms exist, some based on the analysis of the local density of data points, and others on predefined probability distributions. Rodriguez and Laio devised a method in which the cluster centers are recognized as local density maxima that are far away from any points of higher density. The algorithm depends only on the relative densities rather than their absolute values. The authors tested the method on a series of data sets, and its performance compared favorably to that of established techniques. Science , this issue p. 1492

Objetivo Describir los avances de Colombia en la eliminación del tétanos neonatal a partir de la información ofrecida por la vigilancia epidemiológica. Métodos Estudio descriptivo retrospectivo de la vigilancia epidemiológica del tétanos neonatal en Colombia para el período 1989-2005. Se consultó la información disponible de la notificación de este evento de interés en salud pública. Resultados En el periodo estudiado se notificaron en total 830 casos de tétanos neonatal. En 1989 la tasa del tétanos neonatal era del 0,22 por 1 000 nacidos vivos. En el 2005 se redujo a 0,01 por 1 000 nacidos vivos, es decir una disminución cercana al 94% de los casos. Conclusiones Teniendo en cuenta la información aportada por la vigilancia epidemiológica, el país ha logrado la meta de mantener una tasa

The recent emergence of the high-efficiency video coding (HEVC) standard promises to deliver significant bitrate savings over current and prior video compression standards, while also supporting higher resolutions that can meet the clinical acquisition spatiotemporal settings. The effective application of HEVC to medical ultrasound necessitates a careful evaluation of strict clinical criteria that guarantee that clinical quality will not be sacrificed in the compression process. Furthermore, the potential use of despeckle filtering prior to compression provides for the possibility of significant additional bitrate savings that have not been previously considered. This paper provides a thorough comparison of the use of MPEG-2, H.263, MPEG-4, H.264/AVC, and HEVC for compressing atherosclerotic plaque ultrasound videos. For the comparisons, we use both subjective and objective criteria based on plaque structure and motion. For comparable clinical video quality, experimental evaluation on ten videos demonstrates that HEVC reduces bitrate requirements by as much as 33.2% compared to H.264/AVC and up to 71% compared to MPEG-2. The use of despeckle filtering prior to compression is also investigated as a method that can reduce bitrate requirements through the removal of higher frequency components without sacrificing clinical quality. Based on the use of three despeckle filtering methods with both H.264/AVC and HEVC, we find that prior filtering can yield additional significant bitrate savings. The best performing despeckle filter (DsFlsmv) achieves bitrate savings of 43.6% and 39.2% compared to standard nonfiltered HEVC and H.264/AVC encoding, respectively. © 2014 IEEE. 19 2 668 676 Cited By :8

Summary: Representing models of cellular processes or pathways in a graphically rich form facilitates interpretation of biological observations and generation of new hypotheses. Solving biological problems using large pathway datasets requires software that can combine data mapping, querying and visualization as well as providing access to diverse data resources on the Internet. ChiBE is an open source software application that features user-friendly multi-view display, navigation and manipulation of pathway models in BioPAX format. Pathway views are rendered in a feature-rich format, and may be laid out and edited with state-of-the-art visualization methods, including compound or nested structures for visualizing cellular compartments and molecular complexes. Users can easily query and visualize pathways through an integrated Pathway Commons query tool and analyze molecular profiles in pathway context. Availability: http://www.bilkent.edu.tr/%7Ebcbi/chibe.html Contact: ugur@cs.bilkent.edu.tr Supplementary information: Supplementary data are available at Bioinformatics online.

This study aims to determine the most informative mammographic features for breast cancer diagnosis using mutual information (MI) analysis. Our Health Insurance Portability and Accountability Act-approved database consists of 44,397 consecutive structured mammography reports for 20,375 patients collected from 2005 to 2008. The reports include demographic risk factors (age, family and personal history of breast cancer, and use of hormone therapy) and mammographic features from the Breast Imaging Reporting and Data System lexicon. We calculated MI using Shannon's entropy measure for each feature with respect to the outcome (benign/malignant using a cancer registry match as reference standard). In order to evaluate the validity of the MI rankings of features, we trained and tested naïve Bayes classifiers on the feature with tenfold cross-validation, and measured the predictive ability using area under the ROC curve (AUC). We used a bootstrapping approach to assess the distributional properties of our estimates, and the DeLong method to compare AUC. Based on MI, we found that mass margins and mass shape were the most informative features for breast cancer diagnosis. Calcification morphology, mass density, and calcification distribution provided predictive information for distinguishing benign and malignant breast findings. Breast composition, associated findings, and special cases provided little information in this task. We also found that the rankings of mammographic features with MI and AUC were generally consistent. MI analysis provides a framework to determine the value of different mammographic features in the pursuit of optimal (i.e., accurate and efficient) breast cancer diagnosis. © 2013 Society for Imaging Informatics in Medicine.

An expert system having two stages is proposed for cardiac arrhythmia diagnosis. In the first stage, Fisher score is used for feature selection to reduce the feature space dimension of a data set. The second stage is classification stage in which least squares support vector machines classifier is performed by using the feature subset selected in the first stage to diagnose cardiac arrhythmia. Performance of the proposed expert system is evaluated by using an arrhythmia data set which is taken from UCI machine learning repository.

The cBio Cancer Genomics Portal (http://cbioportal.org) is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 5,000 tumor samples from 20 cancer studies. The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications. Cancer Discov; 2(5); 401–4. ©2012 AACR.

The aim of this paper is to describe a novel and completely automated technique for carotid artery (CA) recognition, far (distal) wall segmentation, and intima-media thickness (IMT) measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale-space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen-intima (LI) and media-adventitia (MA) interfaces for the far (distal) wall and IMT measurement. Our database of 365 B-mode longitudinal carotid images is taken from four different institutions covering different ethnic backgrounds. The ground-truth (GT) database was the average manual segmentation from three clinical experts. The mean distance ± standard deviation of CAMES with respect to GT profiles for LI and MA interfaces were 0.081 ± 0.099 and 0.082 ± 0.197 mm, respectively. The IMT measurement error between CAMES and GT was 0.078 ± 0.112 mm. CAMES was benchmarked against a previously developed automated technique based on an integrated approach using feature-based extraction and classifier (CALEX). Although CAMES underestimated the IMT value, it had shown a strong improvement in segmentation errors against CALEX for LI and MA interfaces by 8% and 42%, respectively. The overall IMT measurement bias for CAMES improved by 36% against CALEX. Finally, this paper demonstrated that the figure-of-merit of CAMES was 95.8% compared with 87.4% for CALEX. The combination of multiresolution CA recognition and far-wall segmentation led to an automated, low-complexity, real-time, and accurate technique for carotid IMT measurement. Validation on a multiethnic/multi-institutional data set demonstrated the robustness of the technique, which can constitute a clinically valid IMT measurement for assistance in atherosclerosis disease management. © 2011 IEEE. 21 3 1211 1222 Cited By :37

Measured microarray genomic and metabolic data are a rich source of information about the biological systems they represent. For example, time-series biological data can be used to construct dynamic genetic regulatory network models, which can be used to design intervention strategies to cure or manage major diseases. Also, copy number data can be used to determine the locations and extent of aberrations in chromosome sequences. Unfortunately, measured biological data are usually contaminated with errors that mask the important features in the data. Therefore, these noisy measurements need to be filtered to enhance their usefulness in practice. Wavelet-based multiscale filtering has been shown to be a powerful denoising tool. In this work, different batch as well as online multiscale filtering techniques are used to denoise biological data contaminated with white or colored noise. The performances of these techniques are demonstrated and compared to those of some conventional low-pass filters using two case studies. The first case study uses simulated dynamic metabolic data, while the second case study uses real copy number data. Simulation results show that significant improvement can be achieved using multiscale filtering over conventional filtering techniques. 2004-2012 IEEE. Qatar Foundation;Qatar National Research Fund Scopus

cited By 13; In vivo counting measurements, used for the monitoring of workers with internal contamination risks, are based on the use of calibration physical phantoms. However, such phantoms do not exist for female subjects. Computational calibration using numerical representations, Mesh and non-uniform rational basis spline (NURBS) geometries, was thus considered. The study presented here is focused on the creation of different female thoracic phantoms with various breast sizes and chest girths. These 3D models are used to estimate the radiation attenuation with morphology and the resulting variation of the calibration coefficient of a typical 4-germanium in vivo counting system. A basic Mesh female thoracic phantom was created from the International Commission on Radiological Protection Adult Female Reference Computational Phantom. Using this basic phantom, different chest girths (85, 90, 100, 110, and 120) and cup sizes (A to F) were created representing the most common thoracic female morphologies, as recommended by the available and relevant literature. Variation of breast tissue composition and internal organ volumes with morphology were also considered. As a result, 34 thoracic female phantoms were created combining different cup sizes and chest girths. For the 85 chest girth, at very low energies (15 keV), a relative counting efficiency variation of about 85% was observed between the A and E cups. As a result of this study, breast size dependent calibration coefficients, between 15 keV and 1.4 MeV, were obtained and tabulated for a typical lung counting germanium system. © 2010 Health Physics Society.

Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations' carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982-1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann- Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast. Fil: Alcaraz Segura, Domingo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina. Universidad de Almería; España Fil: Liras, Elisa. Universidad de Almería; España Fil: Tabik, Siham. Universidad de Málaga; España Fil: Paruelo, José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Cabello, Javier. Universidad de Almería; España

The web-based tool "Stoffenmanager" was initially developed to assist small- and medium-sized enterprises in the Netherlands to make qualitative risk assessments and to provide advice on control at the workplace. The tool uses a mechanistic model to arrive at a "Stoffenmanager score" for exposure. In a recent study it was shown that variability in exposure measurements given a certain Stoffenmanager score is still substantial. This article discusses an extension to the tool that uses a Bayesian methodology for quantitative workplace/scenario-specific exposure assessment. This methodology allows for real exposure data observed in the company of interest to be combined with the prior estimate (based on the Stoffenmanager model). The output of the tool is a company-specific assessment of exposure levels for a scenario for which data is available. The Bayesian approach provides a transparent way of synthesizing different types of information and is especially preferred in situations where available data is sparse, as is often the case in small- and medium sized-enterprises. Real-world examples as well as simulation studies were used to assess how different parameters such as sample size, difference between prior and data, uncertainty in prior, and variance in the data affect the eventual posterior distribution of a Bayesian exposure assessment.

The web-based tool "Stoffenmanager" was initially developed to assist small- and medium-sized enterprises in the Netherlands to make qualitative risk assessments and to provide advice on control at the workplace. The tool uses a mechanistic model to arrive at a "Stoffenmanager score" for exposure. In a recent study it was shown that variability in exposure measurements given a certain Stoffenmanager score is still substantial. This article discusses an extension to the tool that uses a Bayesian methodology for quantitative workplace/scenario-specific exposure assessment. This methodology allows for real exposure data observed in the company of interest to be combined with the prior estimate (based on the Stoffenmanager model). The output of the tool is a company-specific assessment of exposure levels for a scenario for which data is available. The Bayesian approach provides a transparent way of synthesizing different types of information and is especially preferred in situations where available data is sparse, as is often the case in small- and medium sized-enterprises. Real-world examples as well as simulation studies were used to assess how different parameters such as sample size, difference between prior and data, uncertainty in prior, and variance in the data affect the eventual posterior distribution of a Bayesian exposure assessment.

The authors automated the selection of foods in a computer system that compiles and processes tailored FFQ. For the selection of food items, several methods are available. The aim of the present study was to compare food lists made by MOM2, which identifies food items with highest between-person variance in intake of the nutrients of interest without taking other items into account, with food lists made by forward regression. The name MOM2 refers to the variance, which is the second moment of the nutrient intake distribution. Food items were selected for the nutrients of interest from 2d of recorded intake in 3524 adults aged 25-65 years. Food lists by 80% MOM2 were compared to those by 80% explained variance for regression on differences between the number and type of food items, and were evaluated on (1) the percentage of explained variance and (2) percentage contribution to population intake computed for the selected items on the food list. MOM2 selected the same food items for Ca, a few more for fat and vitamin C, and a few less for carbohydrates and dietary fibre than forward regression. Food lists by MOM2 based on 80% of variance in intake covered 75-87% of explained variance for different nutrients by regression and contributed 53-75% to total population intake. Concluding, for developing food lists of FFQ, it appears sufficient to select food items based on the contribution to variance in nutrient intake without taking covariance into account. © 2010 The Authors.

Aim of thesis was to create an electronic version of an information database and the e-learning system, focusing on predatory insects and mites. The e-learning system provides information about the main types of predatory insects and mites used in biological plant protection, including the types of naturally occurring entomofauna and acarifauna agroecosystems in the Czech Republic. The system contains information about the taxonomy, morphology, development cycles, prey, methods of control, etc. Thesis is a combination of text, tables, photographs and line drawings from professional publications. The various components of the system are interconnected through hyperlinks. The system includes information on the ecotoxicology, dictionary terms and the ability to search based on various criteria. In the photo gallery you can find together 310 images, which are intended to create a picture of the morphology, development cycles and behavior of individual organisms.

This work deals with making factual database for crop Zea mays L. For the creation of database and educational system has been used language HTML and cascading style sheets to format the graphic.

This work deals with making factual database for crop Humulus lupulus L. The information, contained in the database falls within the protection of plants and more specifically to the field phytopatological, entomological and phytosanitary. Literature research provides an overview of the issue and information technology. The database has been compiled in the years 2007 - 2009 and the idea is to create a system for diagnosis and effective source of information for plant protection. For the creation of databases and educational system have been used languages PHP, HTML and cascading style sheets to format the graphic. For the purposes of the database was used by the SQL language and relational version of MySQL. The system is a detailed description, bionomics and protection. The system also contains a considerable number of pictures. The results are presented as a guide for working with the system.

The regulation of gene expression in a cell relies to a major extent on transcription factors, proteins which recognize and bind the DNA at specific binding sites (response elements) within promoter regions associated with each gene. We present an information theoretic approach to modeling transcriptional regulatory networks, in terms of a simple "sequence-matching" rule and the statistics of the occurrence of binding sequences of given specificity in random promoter regions. The crucial biological input is the distribution of the amount of information coded in these cognate response elements and the length distribution of the promoter regions. We provide an analysis of the transcriptional regulatory network of yeast Saccharomyces cerevisiae, which we extract from the available databases, with respect to the degree distributions, clustering coefficient, degree correlations, rich-club coefficient and the k-core structure. We find that these topological features are in remarkable agreement with those predicted by our model, on the basis of the amount of information coded in the interaction between the transcription factors and response elements., Turkish Academy of Sciences (TÜBA)

Cataloged from PDF version of article. There is an accelerating demand to access the visual content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. In this paper, a framework for content-based retrieval of historical documents in the Ottoman Empire archives is presented. The documents are stored as textual images, which are compressed by constructing a library of symbols occurring in a document, and the symbols in the original image are then replaced with pointers into the codebook to obtain a compressed representation of the image. The features in wavelet and spatial domain based on angular and distance span of shapes are used to extract the symbols. In order to make content-based retrieval in historical archives, a query is specified as a rectangular region in an input image and the same symbol-extraction process is applied to the query region. The queries are processed on the codebook of documents and the query images are identified in the resulting documents using the pointers in textual images. The querying process does not require decompression of images. The new content-based retrieval framework is also applicable to many other document archives using different scripts.

The objective of the Vegetal Estrogens in Nutrition and the Skeleton (VENUS) project was to evaluate existing data on dietary exposure to compounds with oestrogenic and anti-oestrogenic effects present in plant foods as constituents or contaminants, and to identify and disseminate in vitro and in vivo methodologies to analyse the effects of such compounds on bone. To permit the assessment of exposure to isoflavones in European populations (Italy, the UK, Ireland, The Netherlands), the VENUS database of phyto-oestrogen levels in foods was established. Data on the isoflavone (genistein and daidzein) content of 791 foods, including almost 300 foods commonly consumed in Europe, were collected. Levels of coumestrol, formononetin and biochanin A in a limited number of foods were also included. Lignan levels (secoisolariciresinol and matairesinol) in 158 foods were incorporated into the database, which also contains information on the references sourced for the compositional data, on the analytical methods used by each author and on the number of foods analysed in each reference. The VENUS database was constructed in Microsoft® Access 2000, which is widely available as part of Microsoft® Office Professional. This paper outlines the procedures used for the selection and evaluation of existing literature data for incorporation into the database. In addition, the design of the database is described, along with the data entry and quality control procedures used in its construction. Limitations of the data are discussed and guidelines for its use are provided. Chemicals/CAS: biochanin A, 491-80-5; coumestrol, 479-13-0; daidzein, 486-66-8; formononetin, 485-72-3; genistein, 446-72-0; matairesinol, 580-72-3; secoisolariciresinol, 145265-02-7, 29388-59-8, 75365-01-4; Estrogens, Non-Steroidal; Isoflavones; Phytoestrogens; Plant Preparations

The aim of this study was to identify the level of isoflavone intake (total isoflavones, daidzein and genistein) in four European countries: Ireland, Italy, The Netherlands and the UK. For this purpose national food composition databases of isoflavone content were created in a comparable way, using the Vegetal Estrogens in Nutrition and the Skeleton (VENUS) analytical database as a common basis, and appropriate food consumption data were selected. The isoflavone intake in Ireland, Italy, The Netherlands and the UK is on average less than 1 mg/d. Small groups of consumers of soya foods could be identified in Ireland, The Netherlands and the UK. The estimated intake levels are low compared with those found in typical Asian diets (∼20-100 mg/d) and also low compared with levels where physiological effects are expected (60-100 mg/d). The results (including a subgroup analysis of soya product consumers) showed that such levels are difficult to achieve with the European diets studied here. Chemicals/CAS: daidzein, 486-66-8; genistein, 446-72-0; isoflavone, 574-12-9; daidzein, 486-66-8; Genistein, 446-72-0; Isoflavones

The objective of the Vegetal Estrogens in Nutrition and the Skeleton (VENUS) project was to evaluate existing data on dietary exposure to compounds with oestrogenic and anti-oestrogenic effects present in plant foods as constituents or contaminants, and to identify and disseminate in vitro and in vivo methodologies to analyse the effects of such compounds on bone. To permit the assessment of exposure to isoflavones in European populations (Italy, the UK, Ireland, The Netherlands), the VENUS database of phyto-oestrogen levels in foods was established. Data on the isoflavone (genistein and daidzein) content of 791 foods, including almost 300 foods commonly consumed in Europe, were collected. Levels of coumestrol, formononetin and biochanin A in a limited number of foods were also included. Lignan levels (secoisolariciresinol and matairesinol) in 158 foods were incorporated into the database, which also contains information on the references sourced for the compositional data, on the analytical methods used by each author and on the number of foods analysed in each reference. The VENUS database was constructed in Microsoft® Access 2000, which is widely available as part of Microsoft® Office Professional. This paper outlines the procedures used for the selection and evaluation of existing literature data for incorporation into the database. In addition, the design of the database is described, along with the data entry and quality control procedures used in its construction. Limitations of the data are discussed and guidelines for its use are provided. Chemicals/CAS: biochanin A, 491-80-5; coumestrol, 479-13-0; daidzein, 486-66-8; formononetin, 485-72-3; genistein, 446-72-0; matairesinol, 580-72-3; secoisolariciresinol, 145265-02-7, 29388-59-8, 75365-01-4; Estrogens, Non-Steroidal; Isoflavones; Phytoestrogens; Plant Preparations

Objective:To examine the hypothesis that there is sufficient agreement between percentage of households purchasing selected foods using household budget surveys and percentage of individuals consuming these foods as determined in individual-based surveys to allow the former to act as a surrogate for the latter when estimating food chemical intakes using household budget data.Design:Database study.Setting:Databases from Sweden, The Netherlands, Ireland and the UK.Subjects:319 foods (Sweden n=60, The Netherlands n=80, Ireland n=90, UK n=89).Results:Pearson correlations demonstrated a high degree of linear association between % households purchasing and % consumers (r=0.86). Regression analysis defined a close positive relationship between the two datasets (slope 0.95, intercept +2.74). Across countries, using the regression equation, the % households predicted % consumers to within 5% of the true value for between 33 and 48% of foods and to within 10% for between 53 and 78% of foods.Conclusions:Values for % households can be used as a crude surrogate for % consumers and can thus play a role in improving estimates of food additive intake.

Objective: To examine the hypothesis that there is sufficient agreement between percentage of households purchasing selected foods using household budget surveys and percentage of individuals consuming these foods as determined in individual-based surveys to allow the former to act as a surrogate for the latter when estimating food chemical intakes using household budget data. Design: Database study. Setting: Databases from Sweden, The Netherlands, Ireland and the UK. Subjects: 319 foods (Sweden n = 60, The Netherlands n= 80, Ireland n=90, UK n=89). Results: Pearson correlations demonstrated a high degree of linear association between % households purchasing and % consumers (r=0.86). Regression analysis defined a close positive relationship between the two datasets (slope 0.95, intercept +2.74). Across countries, using the regression equation, the % households predicted % consumers to within 5% of the true value for between 33 and 48% of foods and to within 10% for between 53 and 78% of foods. Conclusions: Values for % households can be used as a crude surrogate for % consumers and can thus play a role in improving estimates of food additive intake.

Purpose: The incidence of neuroendocrine neoplasms is increasing. This work aimed at: (i) establishing worldwide incidence trend of low-grade neuroendocrine neoplasms; (ii) defining the incidence and temporal trend of high-grade neuroendocrine neoplasms in USA utilizing the Surveillance Epidemiology and End Results database; (iii) comparing trends for low-grade vs. high-grade neuroendocrine neoplasms. Methods: We conducted a literature search on MEDLINE and Scopus databases and incidence trends were plotted for 1973-2012. The Surveillance Epidemiology and End Results database was used to identify incidence rates in USA for 1973-2012. Incidence rates were stratified according to histological grade, gender and ethnicity. Trends were summarized as annual percent change and corresponding 95% confidence interval. Results: 11 studies were identified involving 72,048 cases; neuroendocrine neoplasm incidence rates increased over time in all countries for all sites, except for appendix. In Surveillance Epidemiology and End Results low-grade neuroendocrine neoplasm incidence rate increased from 1.09 in 1973 to 3.51 per 100,000 in 2012. During this interval, high-grade neuroendocrine neoplasm incidence rate increased from 2.54 to 10.52 per 100,000. African Americans had the highest rates of digestive neuroendocrine neoplasms with male prevalence in high-grade. Conclusions: Our data indicate an increase in the incidence of neuroendocrine neoplasms as a worldwide phenomenon, affecting most anatomical sites and involving both low-grade and high-grade neoplasms. © 2017, The Author(s).

The aim of this study was to identify the level of isoflavone intake (total isoflavones, daidzein and genistein) in four European countries: Ireland, Italy, The Netherlands and the UK. For this purpose national food composition databases of isoflavone content were created in a comparable way, using the Vegetal Estrogens in Nutrition and the Skeleton (VENUS) analytical database as a common basis, and appropriate food consumption data were selected. The isoflavone intake in Ireland, Italy, The Netherlands and the UK is on average less than 1 mg/d. Small groups of consumers of soya foods could be identified in Ireland, The Netherlands and the UK. The estimated intake levels are low compared with those found in typical Asian diets (∼20-100 mg/d) and also low compared with levels where physiological effects are expected (60-100 mg/d). The results (including a subgroup analysis of soya product consumers) showed that such levels are difficult to achieve with the European diets studied here. Chemicals/CAS: daidzein, 486-66-8; genistein, 446-72-0; isoflavone, 574-12-9; daidzein, 486-66-8; Genistein, 446-72-0; Isoflavones