Comparative analysis of cancer genes in the human and chimpanzee genomes

Background: Cancer is a major medical problem in modern societies. However, the incidence of this disease in non-human primates is very low. To study whether genetic differences between human and chimpanzee could contribute to their distinct cancer susceptibility, we have examined in the chimpanzee genome the orthologous genes of a set of 333 human cancer genes. Results: This analysis has revealed that all examined human cancer genes are present in chimpanzee, contain intact open reading frames and show a high degree of conservation between both species. However, detailed analysis of this set of genes has shown some differences in genes of special relevance for human cancer. Thus, the chimpanzee gene encoding p53 contains a Pro residue at codon 72, while this codon is polymorphic in humans and can code for Arg or Pro, generating isoforms with different ability to induce apoptosis or interact with p73. Moreover, sequencing of the BRCA1 gene has shown an 8 Kb deletion in the chimpanzee sequence that prematurely truncates the co-regulated NBR2 gene. Conclusion: These data suggest that small differences in cancer genes, as those found in tumor suppressor genes, might influence the differences in cancer susceptibility between human and chimpanzee. Nevertheless, further analysis will be required to determine the exact contribution of the genetic changes identified in this study to the different cancer incidence in non-human primates.

An analysis of visual adaptation and contrast perception for tone mapping

Tone Mapping is the problem of compressing the range of a High-Dynamic Range image so that it can be displayed in a Low-Dynamic Range screen, without losing or introducing novel details: The final image should produce in the observer a sensation as close as possible to the perception produced by the real-world scene. We propose a tone mapping operator with two stages. The first stage is a global method that implements visual adaptation, based on experiments on human perception, in particular we point out the importance of cone saturation. The second stage performs local contrast enhancement, based on a variational model inspired by color vision phenomenology. We evaluate this method with a metric validated by psychophysical experiments and, in terms of this metric, our method compares very well with the state of the art.

Core Analysis of Portland Cement Concrete Slip Formed Barriers, January 2000

Premature deterioration of slip formed portland cement concrete (PCC) barriers is an ongoing problem in the Iowa Primary and Interstate highway system. The requirement to have a concrete mix which can be sufficiently pliable to be readily molded into the barrier shape and yet be sufficiently stiff to maintain a true shape and height immediately after molding is difficult to meet. A concrete mix which is stiff enough to maintain its shape immediately after molding is usually difficult to work with. It often contains open or hidden tears and large voids. One way to minimize the molding resistance is by additional vibration. If intensive vibration is applied, the entrapped air voids and tears in the concrete can usually be eliminated, however, in that process, the essential entrained air content can also be lost. In the evaluation of slip formed PCC barriers, it is common to find large voids, tears and a low entrained air content, all contributing to premature deterioration. A study was initiated to evaluate core samples taken from good and from bad appearing areas of various median barriers. Evaluations were done covering visual appearance, construction information, air content and chloride content.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

Field Experiments of Current Concrete Pavement Surface Characteristics Practices: Iowa Data Collection and Analysis, December 2005

One of the most important issues in portland cement concrete pavement research today is surface characteristics. The issue is one of balancing surface texture construction with the need for durability, skid resistance, and noise reduction. The National Concrete Pavement Technology Center at Iowa State University, in conjunction with the Federal Highway Administration, American Concrete Pavement Association, International Grinding and Grooving Association, Iowa Highway Research Board, and other states, have entered into a three-part National Surface Characteristics Program to resolve the balancing problem. As a portion of Part 2, this report documents the construction of 18 separate pavement surfaces for use in the first level of testing for the national project. It identifies the testing to be done and the limitations observed in the construction process. The results of the actual tests will be included in the subsequent national study reports.

Adaptive strategy for the statistical analysis of connectomes.

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.

Measures of fit in multiple correspondence analysis of crisp and fuzzy coded data

When continuous data are coded to categorical variables, two types of coding are possible: crisp coding in the form of indicator, or dummy, variables with values either 0 or 1; or fuzzy coding where each observation is transformed to a set of "degrees of membership" between 0 and 1, using co-called membership functions. It is well known that the correspondence analysis of crisp coded data, namely multiple correspondence analysis, yields principal inertias (eigenvalues) that considerably underestimate the quality of the solution in a low-dimensional space. Since the crisp data only code the categories to which each individual case belongs, an alternative measure of fit is simply to count how well these categories are predicted by the solution. Another approach is to consider multiple correspondence analysis equivalently as the analysis of the Burt matrix (i.e., the matrix of all two-way cross-tabulations of the categorical variables), and then perform a joint correspondence analysis to fit just the off-diagonal tables of the Burt matrix - the measure of fit is then computed as the quality of explaining these tables only. The correspondence analysis of fuzzy coded data, called "fuzzy multiple correspondence analysis", suffers from the same problem, albeit attenuated. Again, one can count how many correct predictions are made of the categories which have highest degree of membership. But here one can also defuzzify the results of the analysis to obtain estimated values of the original data, and then calculate a measure of fit in the familiar percentage form, thanks to the resultant orthogonal decomposition of variance. Furthermore, if one thinks of fuzzy multiple correspondence analysis as explaining the two-way associations between variables, a fuzzy Burt matrix can be computed and the same strategy as in the crisp case can be applied to analyse the off-diagonal part of this matrix. In this paper these alternative measures of fit are defined and applied to a data set of continuous meteorological variables, which are coded crisply and fuzzily into three categories. Measuring the fit is further discussed when the data set consists of a mixture of discrete and continuous variables.

A New Model for Designing a Product Line Using TURF Analysis

This paper introduces the approach of using TURF analysis to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.

Caring for family caregivers: An analysis of a family-centered intervention

Objective To assess the effectiveness of Problem-Solving Therapy (PST) on family caregivers through the use of scales to measure anxiety, depression and emotional distress; and to explore facilitating factors and obstacles for its use based on the narrative of nurses. Method A clinical trial and an exploratory focus group with the use of mixed analysis methodology. The study was conducted in a primary health care center in Tarragona, Spain, and the sample consisted of 122 family caregivers who were included in the home care service, and 10 nurses who participated in the intervention group. Family caregivers with evident symptoms of anxiety, depression and emotional distress received PST in the intervention group. The intervention group also consisted of a discussion with eight nurses, which was transcribed and submitted to content analysis. Conclusion Problem-Solving Therapy proved to be effective in reducing perceived anxiety, depression and emotional distress. We identified its strong points and obstacles as described by nurses.



Violence as a research object and intervention in the health field: an analysis from the production of the Research Group on Gender, Health and Nursingi

The study aimed to describe how violence is revealed in the production of the Research Group on Gender, Health and Nursing. This is a historical research of qualitative approach, which evaluated the production of the Research Group, through content analysis. The results show gender as a central category in determining violence and health practices. This aspect determines limitations on professional practices of coping, such as the invisibility of the problem. The female autonomy, the use of alcohol and drugs and social vulnerability play an important relation with the phenomenon and the bond is revealed as potentiality of health practices to address the problem. Conclusion: The gender perspective in nursing research is an innovative field and counter-hegemonic, a possibility to assume a meaning of praxis by transforming potential of understanding and modes of intervention in the phenomenon of gender violence.

Analysis of malaria associated genetic traits in Cabo Verde, a melting pot of European and sub Saharan settlers

Malaria has occurred in the Cabo Verde archipelago with epidemic characteristics since its colonization. Nowadays, it occurs in Santiago Island alone and though prophylaxis is not recommended by the World Health Organization, studies have highlight the prospect of malaria becoming a serious public health problem as a result of the presence of antimalarial drug resistance associated with mutations in the parasite populations and underscore the need for tighter surveillance. Despite the presumptive weak immune status of the population, severe symptoms of malaria are not observed and many people present a subclinical course of the disease. No data on the prevalence of sicklecell trait and red cell glucose-6-phosphate dehydrogenase deficiency (two classical genetic factors associated with resistance to severe malaria) were available for the Cabo Verde archipelago and, therefore, we studied the low morbidity from malaria in relation to the particular genetic characteristics of the human host population. We also included the analysis of the pyruvate kinase deficiency associated gene, reported as putatively associated with resistance to the disease. Allelic frequencies of the polymorphisms examined are closer to European than to African populations and no malaria selection signatures were found. No association was found between the analyzed human factors and infection but one result is of high interest: a linkage disequilibrium test revealed an association of distant loci in the PKLR gene and adjacent regions, only in non-infected individuals. This could mean a more conserved gene region selected in association to protection against the infection and/or the disease.

Some last thoughts on compositional data analysis

One of the disadvantages of old age is that there is more past than future: this,however, may be turned into an advantage if the wealth of experience and, hopefully,wisdom gained in the past can be reflected upon and throw some light on possiblefuture trends. To an extent, then, this talk is necessarily personal, certainly nostalgic,but also self critical and inquisitive about our understanding of the discipline ofstatistics. A number of almost philosophical themes will run through the talk: searchfor appropriate modelling in relation to the real problem envisaged, emphasis onsensible balances between simplicity and complexity, the relative roles of theory andpractice, the nature of communication of inferential ideas to the statistical layman, theinter-related roles of teaching, consultation and research. A list of keywords might be:identification of sample space and its mathematical structure, choices betweentransform and stay, the role of parametric modelling, the role of a sample spacemetric, the underused hypothesis lattice, the nature of compositional change,particularly in relation to the modelling of processes. While the main theme will berelevance to compositional data analysis we shall point to substantial implications forgeneral multivariate analysis arising from experience of the development ofcompositional data analysis…

The contributions of rare objects in correspondence analysis

Correspondence analysis, when used to visualize relationships in a table of counts(for example, abundance data in ecology), has been frequently criticized as being too sensitiveto objects (for example, species) that occur with very low frequency or in very few samples. Inthis statistical report we show that this criticism is generally unfounded. We demonstrate this inseveral data sets by calculating the actual contributions of rare objects to the results ofcorrespondence analysis and canonical correspondence analysis, both to the determination ofthe principal axes and to the chi-square distance. It is a fact that rare objects are oftenpositioned as outliers in correspondence analysis maps, which gives the impression that theyare highly influential, but their low weight offsets their distant positions and reduces their effecton the results. An alternative scaling of the correspondence analysis solution, the contributionbiplot, is proposed as a way of mapping the results in order to avoid the problem of outlying andlow contributing rare objects.

Factor analysis of the North American Spine Society outcome assessment instrument: a study based on a spine registry of patients treated with lumbar and cervical disc arthroplasty.

BACKGROUND CONTEXT: Studies involving factor analysis (FA) of the items in the North American Spine Society (NASS) outcome assessment instrument have revealed inconsistent factor structures for the individual items. PURPOSE: This study examined whether the factor structure of the NASS varied in relation to the severity of the back/neck problem and differed from that originally recommended by the developers of the questionnaire, by analyzing data before and after surgery in a large series of patients undergoing lumbar or cervical disc arthroplasty. STUDY DESIGN/SETTING: Prospective multicenter observational case series. PATIENT SAMPLE: Three hundred ninety-one patients with low back pain and 553 patients with neck pain completed questionnaires preoperatively and again at 3 to 6 and 12 months follow-ups (FUs), in connection with the SWISSspine disc arthroplasty registry. OUTCOME MEASURES: North American Spine Society outcome assessment instrument. METHODS: First, an exploratory FA without a priori assumptions and subsequently a confirmatory FA were performed on the 17 items of the NASS-lumbar and 19 items of the NASS-cervical collected at each assessment time point. The item-loading invariance was tested in the German version of the questionnaire for baseline and FU. RESULTS: Both NASS-lumbar and NASS-cervical factor structures differed between baseline and postoperative data sets. The confirmatory analysis and item-loading invariance showed better fit for a three-factor (3F) structure for NASS-lumbar, containing items on "disability," "back pain," and "radiating pain, numbness, and weakness (leg/foot)" and for a 5F structure for NASS-cervical including disability, "neck pain," "radiating pain and numbness (arm/hand)," "weakness (arm/hand)," and "motor deficit (legs)." CONCLUSIONS: The best-fitting factor structure at both baseline and FU was selected for both the lumbar- and cervical-NASS questionnaires. It differed from that proposed by the originators of the NASS instruments. Although the NASS questionnaire represents a valid outcome measure for degenerative spine diseases, it is able to distinguish among all major symptom domains (factors) in patients undergoing lumbar and cervical disc arthroplasty; overall, the item structure could be improved. Any potential revision of the NASS should consider its factorial structure; factorial invariance over time should be aimed for, to allow for more precise interpretations of treatment success.