Who you are is how you travel: A framework for transportation mode detection using individual and environmental characteristics

With the increasing prevalence of geo-enabled mobile phone applications, researchers can collect mobility data at a relatively high spatial and temporal resolution. Such data, however, lack semantic information such as the interaction of individuals with the transportation modes available. On the other hand, traditional mobility surveys provide detailed snapshots of the relation between socio-demographic characteristics and choice of transportation modes. Transportation mode detection is currently approached using features such as speed, acceleration and direction either on their own or in combination with GIS data. Combining such information with socio-demographic characteristics of travellers has the potential of offering a richer modelling framework that could facilitate better transportation mode detection using variables such as age and disability. In this paper, we explore the possibility to include both elements of the environment and individual characteristics of travellers in the task of transportation mode detection. Using dynamic Bayesian Networks, we model the transition matrix to account for such auxiliary data by using an informative Dirichlet prior constructed using data from traditional mobility surveys. Results have shown that it is possible to achieve comparable accuracy with the most widely used classification algorithms while having a rich modelling framework, even in the case of sparse mobility data

Massive hematuria due to a congenital renal arteriovenous malformation mimicking a renal pelvis tumor: a case report

<p>Abstract</p> <p>Introduction</p> <p>Congenital renal arteriovenous malformations (AVMs) are very rare benign lesions. They are more common in women and rarely manifest in elderly people. In some cases they present with massive hematuria. Contemporary treatment consists of transcatheter selective arterial embolization which leads to resolution of the hematuria whilst preserving renal parenchyma.</p> <p>Case presentation</p> <p>A 72-year-old man, who was heavy smoker, presented with massive hematuria and flank pain. CT scan revealed a filling defect caused by a soft tissue mass in the renal pelvis, which initially led to the suspicion of a transitional cell carcinoma (TCC) of the upper tract, in view of the patient's age and smoking habits. However a subsequent retrograde study could not depict any filling defect in the renal pelvis. Selective right renal arteriography confirmed the presence of a renal AVM by demonstrating abnormal arterial communication with a vein with early visualization of the venous system. At the same time successful selective transcatheter embolization of the lesion was performed.</p> <p>Conclusion</p> <p>This case highlights the importance of careful diagnostic work-up in the evaluation of upper tract hematuria. In the case presented, a congenital renal AVM proved to be the cause of massive upper tract hematuria and flank pain in spite of the initial evidence indicating the likely diagnosis of a renal pelvis tumor.</p

A comprehensive review on carotenoids in foods and feeds: status quo, applications, patents, and research needs

Carotenoids are isoprenoids widely distributed in foods that have been always part of the diet of humans. Unlike the other so-called food bioactives, some carotenoids can be converted into retinoids exhibiting vitamin A activity, which is essential for humans. Furthermore, they are much more versatile as they are relevant in foods not only as sources of vitamin A, but also as natural pigments, antioxidants, and health-promoting compounds. Lately, they are also attracting interest in the context of nutricosmetics, as they have been shown to provide cosmetic benefits when ingested in appropriate amounts. In this work, resulting from the collaborative work of participants of the COST Action European network to advance carotenoid research and applications in agro-food and health (EUROCAROTEN, www.eurocaroten.eu, https://www.cost.eu/actions/CA15136/#tabs|Name:overview) research on carotenoids in foods and feeds is thoroughly reviewed covering aspects such as analysis, carotenoid food sources, carotenoid databases, effect of processing and storage conditions, new trends in carotenoid extraction, daily intakes, use as human, and feed additives are addressed. Furthermore, classical and recent patents regarding the obtaining and formulation of carotenoids for several purposes are pinpointed and briefly discussed. Lastly, emerging research lines as well as research needs are highlighted.This article is based upon work from COST Action (European network to advance carotenoid research and applications in agro-food and health, EUROCAROTEN, CA15136, www.eurocaroten.eu, https://www. cost.eu/actions/CA15136/#tabsjName:overview) supported by COST (European Cooperation in Science and Technology, http://www.cost. eu/).info:eu-repo/semantics/publishedVersio

Bayesian Bootstrap Inference for the ROC Surface

Accurate diagnosis of disease is of great importance in clinical practice and medical research. The receiver operating characteristic (ROC) surface is a popular tool for evaluating the discriminatory ability of continuous diagnostic test outcomes when there exist three ordered disease classes (e.g., no disease, mild disease, advanced disease). We propose the Bayesian bootstrap, a fully nonparametric method, for conducting inference about the ROC surface and its functionals, such as the volume under the surface. The proposed method is based on a simple, yet interesting, representation of the ROC surface in terms of placement variables. Results from a simulation study demonstrate the ability of our method to successfully recover the true ROC surface and to produce valid inferences in a variety of complex scenarios. An application to data from the Trail Making Test to assess cognitive impairment in Parkinson's disease patients is provided

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Telomerase RNA expression and DNA ploidy as prognostic markers of prostate carcinomas

Aims and background. The objective of this study was to determine whether there was a correlation between telomerase RNA expression and DNA ploidy status with clinicopathological parameters and biochemical recurrence after radical prostatectomy. Study design. Telomerase RNA expression and DNA ploidy were evaluated in imprint smear samples obtained from 112 prostates after radical prostatectomy. The results were correlated with pathological stage, Gleason score and serum PSA. Results. Positive telomerse RNA expression was detected in 67.8% of prostate carcinomas. The multiple linear regression model showed a statistically significance increase in telomerase RNA expression with increased Gleason score (P &lt;0.0001) and preoperative serum PSA values (P = 0.0125). DNA ploidy status also varied significantly with Gleason score (P &lt;0.0001) and preoperative serum PSA values (P = 0.0110). Five patients with diploid tumors and negative telomerase RNA expression developed a recurrence. However, recurrence was associated with DNA aneuploidy (P = 0.001) as well as with high telomerase RNA overexpression (P = 0.001). Conclusions. We conclude that telomerase RNA expression and DNA ploidy could be additional markers in the field of prognosis of prostate carcinomas