Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine

BACKGROUND: In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. METHODS/DESIGN: Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests and development of clinical prediction rules for the individual patients. These will be made accessible for clinicians. DISCUSSION: The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic and prognostic research.

Systematic Functional Analysis of BicD Serine Phosphorylation and Intragenic Suppression of a Female Sterile Allele of BicD

Protein phosphorylation is involved in posttranslational control of essentially all biological processes. Using mass spectrometry, recent analyses of whole phosphoproteomes led to the identification of numerous new phosphorylation sites. However, the function of most of these sites remained unknown. We chose the Drosophila Bicaudal-D protein to estimate the importance of individual phosphorylation events. Being involved in different cellular processes, BicD is required for oocyte determination, for RNA transport during oogenesis and embryogenesis, and for photoreceptor nuclei migration in the developing eye. The numerous roles of BicD and the available evidence for functional importance of BicD phosphorylation led us to identify eight phosphorylation sites of BicD, and we tested a total of 14 identified and suspected phosphoserine residues for their functional importance in vivo in flies. Surprisingly, all these serines turned out to be dispensable for providing sufficient basal BicD activity for normal growth and development. However, in a genetically sensitized background where the BicD(A40V) protein variant provides only partial activity, serine 103 substitutions are not neutral anymore, but show surprising differences. The S103D substitution completely inactivates the protein, whereas S103A behaves neutral, and the S103F substitution, isolated in a genetic screen, restores BicD(A40V) function. Our results suggest that many BicD phosphorylation events may either be fortuitous or play a modulating function as shown for Ser(103). Remarkably, amongst the Drosophila serines we found phosphorylated, Ser(103) is the only one that is fully conserved in mammalian BicD.

A Combinatorial Approach to the Variable Selection in Multiple Linear Regression: Analysis of Selwood et al Data set -A Case Study.

A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.

Critical issues in managing protected areas by multi-stakeholder participation - analysis of a process in the Swiss Alps

Balancing the frequently conflicting priorities of conservation and economic development poses a challenge to management of the Swiss Alps Jungfrau-Aletsch World Heritage Site (WHS). This is a complex societal problem that calls for a knowledge-based solution. This in turn requires a transdisciplinary research framework in which problems are defined and solved cooperatively by actors from the scientific community and the life-world. In this article we re-examine studies carried out in the region of the Swiss Alps Jungfrau-Aletsch WHS, covering three key issues prevalent in transdisciplinary settings: integration of stakeholders into participatory processes; perceptions and positions; and negotiability and implementation. In the case of the Swiss Alps Jungfrau-Aletsch WHS the transdisciplinary setting created a situation of mutual learning among stakeholders from different levels and backgrounds. However, the studies showed that the benefits of such processes of mutual learning are continuously at risk of being diminished by the power play inherent in participatory approaches.

Comparative Analysis of Evolving Software Systems Using the Gini Coefficient

Software metrics offer us the promise of distilling useful information from vast amounts of software in order to track development progress, to gain insights into the nature of the software, and to identify potential problems. Unfortunately, however, many software metrics exhibit highly skewed, non-Gaussian distributions. As a consequence, usual ways of interpreting these metrics --- for example, in terms of "average" values --- can be highly misleading. Many metrics, it turns out, are distributed like wealth --- with high concentrations of values in selected locations. We propose to analyze software metrics using the Gini coefficient, a higher-order statistic widely used in economics to study the distribution of wealth. Our approach allows us not only to observe changes in software systems efficiently, but also to assess project risks and monitor the development process itself. We apply the Gini coefficient to numerous metrics over a range of software projects, and we show that many metrics not only display remarkably high Gini values, but that these values are remarkably consistent as a project evolves over time.

Analysis of postprandial lipemia as a Cardiovascular Disease risk factor using genetic and clinical information: an Artificial Neural Network perspective

Clinical studies indicate that exaggerated postprandial lipemia is linked to the progression of atherosclerosis, leading cause of Cardiovascular Diseases (CVD). CVD is a multi-factorial disease with complex etiology and according to the literature postprandial Triglycerides (TG) can be used as an independent CVD risk factor. Aim of the current study is to construct an Artificial Neural Network (ANN) based system for the identification of the most important gene-gene and/or gene-environmental interactions that contribute to a fast or slow postprandial metabolism of TG in blood and consequently to investigate the causality of postprandial TG response. The design and development of the system is based on a dataset of 213 subjects who underwent a two meals fatty prandial protocol. For each of the subjects a total of 30 input variables corresponding to genetic variations, sex, age and fasting levels of clinical measurements were known. Those variables provide input to the system, which is based on the combined use of Parameter Decreasing Method (PDM) and an ANN. The system was able to identify the ten (10) most informative variables and achieve a mean accuracy equal to 85.21%.

Synoptic Analysis of the New York March 1888 Blizzard

The meteorological circumstances that led to the Blizzard of March 1888 that hit New York are analysed in Version 2 of the “Twentieth Century Reanalysis” (20CR). The potential of this data set for studying historical extreme events has not yet been fully explored. A detailed analysis of 20CR data alongside other data sources (including historical instrumental data and weather maps) for historical extremes such as the March 1888 blizzard may give insights into the limitations of 20CR. We find that 20CR reproduces the circulation pattern as well as the temperature development very well. Regarding the absolute values of variables such as snow fall or minimum and maximum surface pressure, there is anunderestimation of the observed extremes, which may be due to the low spatial resolution of 20CR and the fact that only the ensemble mean is considered. Despite this drawback, the dataset allows us to gain new information due to its complete spatial and temporal coverage.

Phylogenetic analysis of Prevotella nigrescens, Prevotella intermedia and Porphyromonas gingivalis clinical strains reveals a clear species clustering

Prevotella nigrescens, Prevotella intermedia and Porphyromonas gingivalis are oral pathogens from the family Bacteroidaceae, regularly isolated from cases of gingivitis and periodontitis. In this study, the phylogenetic variability of these three bacterial species was investigated by means of 16S rRNA (rrs) gene sequence comparisons of a set of epidemiologically and geographically diverse isolates. For each of the three species, the rrs gene sequences of 11 clinical isolates as well as the corresponding type strains was determined. Comparison of all rrs sequences obtained with those of closely related species revealed a clear clustering of species, with only a little intraspecies variability but a clear difference in the rrs gene with respect to the next related taxon. The results indicate that the three species form stable, homogeneous genetic groups, which favours an rrs-based species identification of these oral pathogens. This is especially useful given the 7% sequence divergence between Prevotella intermedia and Prevotella nigrescens, since phenotypic distinction between the two Prevotella species is inconsistent or involves techniques not applicable in routine identification.

Phylogenetic analysis of Pasteurella multocida subspecies and molecular identification of feline P. multocida subsp. septica by 16S rRNA gene sequencing

Pasteurella multocida is commonly found in the oral cavity of cats and dogs. In humans it is known as an opportunistic pathogen after bites from these animals. Phenotypic identification of P. multocida based on biochemical reactions is often limited and usually only done on a species level, even though 3 subspecies are described. For molecular taxonomy and diagnostic purposes a phylogenetic analysis of the three subspecies of P. multocida based on their 16S rRNA (rrs) gene sequence was therefore carried out. We found P. multocida subsp. septica on a distinguished branch on the phylogenetic tree of Pasteurellaceae, due to a 1.5% divergence of its rrs gene compared to the two other, more closely related subspecies multocida and gallicida. This phylogenetic divergence can be used for the identification of P. multocida subsp. septica by rrs gene determination since they form a phylogenetically well isolated and defined group as shown with a set of feline isolates. Comparison to routine phenotypic identification shows the advantage of the sequence-based identification over conventional methods. It is therefore helpful for future unambiguous identification and molecular taxonomy of P. multocida as well as for epidemiological investigations.

Neighbourhood Diversity and Social Trust: An Empirical Analysis of Interethnic Contact and Group-specific Effects

To date, neighbourhood studies on ethnic diversity and social trust have revealed inconclusive findings. In this paper, three innovations are proposed in order to systemise the knowledge about neighbourhood ethnic diversity and the development of social trust. First, it is proposed to use a valid trust measure that is sensitive to the local neighbourhood context. Second, the paper argues for a conception of organically evolved neighbourhoods, rather than using local administrative units as readily available proxies for neighbourhood divisions. Thirdly, referring to intergroup contact theory and group-specific effects of diversity, the paper challenges the notion that ethnic diversity has overwhelmingly negative effects on social trust.