Quality/Safety Section : Introducing the journal's quality/safety section

Quality/Safety Section. Contributor/Author : "Catherine Messick Jones"With this issue, we are launching a Quality/ Safety Section to focus on quality improvement, patient safety topics and methods important to Hospitalists.Includes bibliographical reference

Something has to change

"When you have the thought, 'Something has to change', what do you do? Often, the decision to change is prompted by a problematic or undesired outcome, or a process that is frankly broken. What change is required in order to solve the problem?"Kristin Hahn-Cover, Catherine Messick Jones (Division of Hospital Medicine, Department of Medicine, University of Missouri)Includes bibliographical reference

Using the Memories of Multiscale Machines to Characterize Complex Systems

A scheme is presented to extract detailed dynamical signatures from successive measurements of complex systems. Relative entropy based time series tools are used to quantify the gain in predictive power of increasing past knowledge. By lossy compression, data is represented by increasingly coarsened symbolic strings. Each compression resolution is modeled by a machine: a finite memory transition matrix. Applying the relative entropy tools to each machine's memory exposes correlations within many time scales. Examples are given for cardiac arrhythmias and different heart conditions are distinguished.Comment: 4 pages, 2 figure

Solvent content of protein crystals from diffraction intensities by Independent Component Analysis

An analysis of the protein content of several crystal forms of proteins has been performed. We apply a new numerical technique, the Independent Component Analysis (ICA), to determine the volume fraction of the asymmetric unit occupied by the protein. This technique requires only the crystallographic data of structure factors as input.Comment: 9 pages, 2 figures, 1 tabl

RNALogo: a new approach to display structural RNA alignment

Regulatory RNAs play essential roles in many essential biological processes, ranging from gene regulation to protein synthesis. This work presents a web-based tool, RNALogo, to create a new graphical representation of the patterns in a multiple RNA sequence alignment with a consensus structure. The RNALogo graph can indicate significant features within an RNA sequence alignment and its consensus RNA secondary structure. RNALogo extends Sequence logos, and specifically incorporates RNA secondary structures and mutual information of base-paired regions into the graphical representation. Each RNALogo graph is composed of stacks of letters, with one stack for each position in the consensus RNA secondary structure. RNALogo provides a convenient and high configurable logo generator. An RNALogo graph is generated for each RNA family in Rfam, and these generated logos are accumulated into a gallery of RNALogo. Users can search or browse RNALogo graphs in this gallery to receive additional perspectives of known RNA families. RNALogo is now available at: http://rnalogo.mbc.nctu.edu.tw/

From Pig to Pacifier: Chitterling-Associated Yersiniosis Outbreak among Black Infants

In this case-control study of Yersinia enterocolitica infections among black infants, chitterling preparation was significantly associated with illness (p<0.001). Of 13 samples of chitterlings tested, 2 were positive for Yersinia intermedia and 5 for Salmonella. Decontamination of chitterlings before sale with methods such as irradiation should be strongly considered

Optimal measurement of visual motion across spatial and temporal scales

Sensory systems use limited resources to mediate the perception of a great variety of objects and events. Here a normative framework is presented for exploring how the problem of efficient allocation of resources can be solved in visual perception. Starting with a basic property of every measurement, captured by Gabor's uncertainty relation about the location and frequency content of signals, prescriptions are developed for optimal allocation of sensors for reliable perception of visual motion. This study reveals that a large-scale characteristic of human vision (the spatiotemporal contrast sensitivity function) is similar to the optimal prescription, and it suggests that some previously puzzling phenomena of visual sensitivity, adaptation, and perceptual organization have simple principled explanations.Comment: 28 pages, 10 figures, 2 appendices; in press in Favorskaya MN and Jain LC (Eds), Computer Vision in Advanced Control Systems using Conventional and Intelligent Paradigms, Intelligent Systems Reference Library, Springer-Verlag, Berli

ROSEFW-RF: the winner algorithm for the ECBDL’14 big data competition: an extremely imbalanced big data bioinformatics problem

The application of data mining and machine learning techniques to biological and biomedicine data continues to be an ubiquitous research theme in current bioinformatics. The rapid advances in biotechnology are allowing us to obtain and store large quantities of data about cells, proteins, genes, etc., that should be processed. Moreover, in many of these problems such as contact map prediction, the problem tackled in this paper, it is difficult to collect representative positive examples. Learning under these circumstances, known as imbalanced big data classification, may not be straightforward for most of the standard machine learning methods. In this work we describe the methodology that won the ECBDL’14 big data challenge for a bioinformatics big data problem. This algorithm, named as ROSEFW-RF, is based on several MapReduce approaches to (1) balance the classes distribution through random oversampling, (2) detect the most relevant features via an evolutionary feature weighting process and a threshold to choose them, (3) build an appropriate Random Forest model from the pre-processed data and finally (4) classify the test data. Across the paper, we detail and analyze the decisions made during the competition showing an extensive experimental study that characterize the way of working of our methodology. From this analysis we can conclude that this approach is very suitable to tackle large-scale bioinformatics classifications problems