SimpliFly: A Methodology for Simplification and Thematic Enhancement of Trajectories.

Movement data sets collected using today's advanced tracking devices consist of complex trajectories in terms of length, shape, and number of recorded positions. Multiple additional attributes characterizing the movement and its environment are often also included making the level of complexity even higher. Simplification of trajectories can improve the visibility of relevant information by reducing less relevant details while maintaining important movement patterns. We propose a systematic stepwise methodology for simplifying and thematically enhancing trajectories in order to support their visual analysis. The methodology is applied iteratively and is composed of: (a) a simplification step applied to reduce the morphological complexity of the trajectories, (b) a thematic enhancement step which aims at accentuating patterns of movement, and (c) the representation and interactive exploration of the results in order to make interpretations of the findings and further refinement to the simplification and enhancement process. We illustrate our methodology through an analysis example of two different types of tracks, aircraft and pedestrian movement

The DNA-polymorphism rs849142 is associated with skin toxicity induced by targeted anti-EGFR therapy using cetuximab

Skin toxicity (ST) is a frequent adverse effect (AE) in anti-epidermal growth factor receptor (EGFR)-targeted treatment of metastatic colorectal cancer (mCRC) resulting in decreased quality of life and problems in clinical management. We wanted to identify biomarkers predicting ST in this setting and focused on 70 DNA polymorphisms associated with acne, the (immunoglobulin fragment crystallizable region) Fcγ-receptor pathway, and systemic lupus erythematosus (SLE) applying next-generation-sequencing (NGS). For the analysis patients with mCRC treated with cetuximab were selected from the FIRE-3 study. A training group consisting of the phenotypes low (1) - and high-grade (3) ST (n = 16) and a validation group (n = 55) representing also the intermediate grade (2) were genotyped and investigated in a genotype-phenotype association analysis. The single nucleotide polymorphism (SNP) rs849142 significantly associated with ST in both the training- (p < 0.01) and validation-group (p = 0.04). rs849142 is located in an intron of the juxtaposed with another zinc finger protein 1 (JAZF1) gene. Haplotype analysis demonstrated significant linkage disequilibrium of rs849142 with JAZF1. Thus, rs849142 might be a predictive biomarker for ST in anti-EGFR treated mCRC patients. Its value in the clinical management of AE has to be validated in larger cohorts

Spirometry reference equations for central European populations from school age to old age.

Spirometry reference values are important for the interpretation of spirometry results. Reference values should be updated regularly, derived from a population as similar to the population for which they are to be used and span across all ages. Such spirometry reference equations are currently lacking for central European populations. To develop spirometry reference equations for central European populations between 8 and 90 years of age. We used data collected between January 1993 and December 2010 from a central European population. The data was modelled using "Generalized Additive Models for Location, Scale and Shape" (GAMLSS). The spirometry reference equations were derived from 118'891 individuals consisting of 60'624 (51%) females and 58'267 (49%) males. Altogether, there were 18'211 (15.3%) children under the age of 18 years. We developed spirometry reference equations for a central European population between 8 and 90 years of age that can be implemented in a wide range of clinical settings

Methylated free-circulating HPP1 DNA is an early response marker in patients with metastatic colorectal cancer

Detection of methylated free-circulating DNA (mfcDNA) for hyperplastic polyposis 1 (HPP1) in blood is correlated with a poor prognosis for patients with metastatic colorectal cancers (mCRC). Here, we analyzed the plasma levels of HPP1 mfcDNA in mCRC patients treated with a combination therapy containing a fluoropyrimidine, oxaliplatin and bevacizumab to test whether HPP1 mfcDNA is a suitable prognostic and response biomarker. From 467 patients of the prospective clinical study AIO-KRK-0207, mfcDNA was isolated from plasma samples at different time points and bisulfite-treated mfcDNA was quantified using methylation specific PCR. About 337 of 467 patients had detectable levels for HPP1 mfcDNA before start of treatment. The detection was significantly correlated with poorer overall survival (OS) (HR = 1.86; 95%CI 1.37-2.53). About 2-3 weeks after the first administration of combination chemotherapy, HPP1 mfcDNA was reduced to non-detectable levels in 167 of 337 patients. These patients showed a better OS compared with patients with continued detection of HPP1 mfcDNA (HR HPP1(sample 1: pos/ sample 2: neg) vs. HPP1(neg/neg) = 1.41; 95%CI 1.00-2.01, HPP1(neg,pos/pos) vs. HPP1(neg/neg) = 2.60; 95%CI 1.86-3.64). Receiver operating characteristic analysis demonstrated that HPP1 mfcDNA discriminates well between patients who do (not) respond to therapy according to the radiological staging after 12 or 24 weeks (AUC = 0.77 or 0.71, respectively). Detection of HPP1 mfcDNA can be used as a prognostic marker and an early marker for response (as early as 3-4 weeks after start of treatment compared with radiological staging after 12 or 24 weeks) to identify patients who will likely benefit from a combination chemotherapy with bevacizumab.info:eu-repo/semantics/publishedVersio

Long-term morphological and hormonal follow-up in a single unit on 115 patients with adrenal incidentalomas

We investigated the natural course of adrenal incidentalomas in 115 patients by means of a long-term endocrine and morphological (CT) follow-up protocol (median 4 year, range 1–7 year). At entry, we observed 61 subclinical hormonal alterations in 43 patients (mainly concerning the ACTH–cortisol axis), but confirmatory tests always excluded specific endocrine diseases. In all cases radiologic signs of benignity were present. Mean values of the hormones examined at last follow-up did not differ from those recorded at entry. However in individual patients several variations were observed. In particular, 57 endocrine alterations found in 43 patients (37.2%) were no longer confirmed at follow-up, while 35 new alterations in 31 patients (26.9%) appeared de novo. Only four alterations in three patients (2.6%) persisted. Confirmatory tests were always negative for specific endocrine diseases. No variation in mean mass size was found between values at entry (25.4±0.9 mm) and at follow-up (25.7±0.9 mm), although in 32 patients (27.8%) mass size actually increased, while in 24 patients (20.8%) it decreased. In no case were the variations in mass dimension associated with the appearance of radiological criteria of malignancy. Kaplan–Meier curves indicated that the cumulative risk for mass enlargement (65%) and for developing endocrine abnormalities (57%) over time was progressive up to 80 months and independent of haemodynamic and humoral basal characteristics. In conclusion, mass enlargement and the presence or occurrence over time of subclinical endocrine alterations are frequent and not correlated, can appear at any time, are not associated with any basal predictor and, finally, are not necessarily indicative of malignant transformation or of progression toward overt disease

Gene set analysis exploiting the topology of a pathway

<p>Abstract</p> <p>Background</p> <p>Recently, a great effort in microarray data analysis is directed towards the study of the so-called gene sets. A gene set is defined by genes that are, somehow, functionally related. For example, genes appearing in a known biological pathway naturally define a gene set. The gene sets are usually identified from a priori biological knowledge. Nowadays, many bioinformatics resources store such kind of knowledge (see, for example, the Kyoto Encyclopedia of Genes and Genomes, among others). Although pathways maps carry important information about the structure of correlation among genes that should not be neglected, the currently available multivariate methods for gene set analysis do not fully exploit it.</p> <p>Results</p> <p>We propose a novel gene set analysis specifically designed for gene sets defined by pathways. Such analysis, based on graphical models, explicitly incorporates the dependence structure among genes highlighted by the topology of pathways. The analysis is designed to be used for overall surveillance of changes in a pathway in different experimental conditions. In fact, under different circumstances, not only the expression of the genes in a pathway, but also the strength of their relations may change. The methods resulting from the proposal allow both to test for variations in the strength of the links, and to properly account for heteroschedasticity in the usual tests for differential expression.</p> <p>Conclusions</p> <p>The use of graphical models allows a deeper look at the components of the pathway that can be tested separately and compared marginally. In this way it is possible to test single components of the pathway and highlight only those involved in its deregulation.</p

Understanding human functioning using graphical models

<p>Abstract</p> <p>Background</p> <p>Functioning and disability are universal human experiences. However, our current understanding of functioning from a comprehensive perspective is limited. The development of the International Classification of Functioning, Disability and Health (ICF) on the one hand and recent developments in graphical modeling on the other hand might be combined and open the door to a more comprehensive understanding of human functioning. The objective of our paper therefore is to explore how graphical models can be used in the study of ICF data for a range of applications.</p> <p>Methods</p> <p>We show the applicability of graphical models on ICF data for different tasks: Visualization of the dependence structure of the data set, dimension reduction and comparison of subpopulations. Moreover, we further developed and applied recent findings in causal inference using graphical models to estimate bounds on intervention effects in an observational study with many variables and without knowing the underlying causal structure.</p> <p>Results</p> <p>In each field, graphical models could be applied giving results of high face-validity. In particular, graphical models could be used for visualization of functioning in patients with spinal cord injury. The resulting graph consisted of several connected components which can be used for dimension reduction. Moreover, we found that the differences in the dependence structures between subpopulations were relevant and could be systematically analyzed using graphical models. Finally, when estimating bounds on causal effects of ICF categories on general health perceptions among patients with chronic health conditions, we found that the five ICF categories that showed the strongest effect were plausible.</p> <p>Conclusions</p> <p>Graphical Models are a flexible tool and lend themselves for a wide range of applications. In particular, studies involving ICF data seem to be suited for analysis using graphical models.</p

Graphical modeling of binary data using the LASSO: a simulation study

Background: Graphical models were identified as a promising new approach to modeling high-dimensional clinical data. They provided a probabilistic tool to display, analyze and visualize the net-like dependence structures by drawing a graph describing the conditional dependencies between the variables. Until now, the main focus of research was on building Gaussian graphical models for continuous multivariate data following a multivariate normal distribution. Satisfactory solutions for binary data were missing. We adapted the method of Meinshausen and Buhlmann to binary data and used the LASSO for logistic regression. Objective of this paper was to examine the performance of the Bolasso to the development of graphical models for high dimensional binary data. We hypothesized that the performance of Bolasso is superior to competing LASSO methods to identify graphical models. Methods: We analyzed the Bolasso to derive graphical models in comparison with other LASSO based method. Model performance was assessed in a simulation study with random data generated via symmetric local logistic regression models and Gibbs sampling. Main outcome variables were the Structural Hamming Distance and the Youden Index. We applied the results of the simulation study to a real-life data with functioning data of patients having head and neck cancer. Results: Bootstrap aggregating as incorporated in the Bolasso algorithm greatly improved the performance in higher sample sizes. The number of bootstraps did have minimal impact on performance. Bolasso performed reasonable well with a cutpoint of 0.90 and a small penalty term. Optimal prediction for Bolasso leads to very conservative models in comparison with AIC, BIC or cross-validated optimal penalty terms. Conclusions: Bootstrap aggregating may improve variable selection if the underlying selection process is not too unstable due to small sample size and if one is mainly interested in reducing the false discovery rate. We propose using the Bolasso for graphical modeling in large sample sizes

Prevalence of adrenal masses in Japanese patients with type 2 diabetes mellitus

<p>Abstract</p> <p>Introduction</p> <p>To date, there have been no reports on the prevalence of adrenal masses in type 2 diabetic patients. The present study aimed to evaluate the prevalence of adrenal incidentaloma in type 2 diabetic patients in Japan.</p> <p>Subjects</p> <p>We retrospectively evaluated the presence of adrenal masses using abdominal CT scans in 304 type 2 diabetic patients. In those with adrenal masses, we examined the hormone production capacity of the adrenal mass.</p> <p>Results</p> <p>Fourteen patients (4.6%) had an adrenal mass. Hormonal analysis identified one case as having subclinical Cushing's syndrome, two with primary aldosteronism. Eleven cases had non-functioning masses.</p> <p>Discussion</p> <p>The reported prevalence of adrenal incidentaloma in normal subjects is 0.6-4.0% in abdominal CT scan series. Our results show a relatively high prevalence of adrenal tumors in diabetic patients. On the other hand, the frequency of functional adenoma in diabetic patients is 21.4%, which is similar to that of normal subjects.</p> <p>Conclusion</p> <p>Although further studies are needed to evaluate the prevalence of adrenal tumors in diabetic patients, our data suggest that evaluation of the presence of adrenal masses may be needed in patients with type 2 diabetes mellitus.</p