Diagnosis Code Assignment Using Sparsity-Based Disease Correlation Embedding

© 1989-2012 IEEE. With the latest developments in database technologies, it becomes easier to store the medical records of hospital patients from their first day of admission than was previously possible. In Intensive Care Units (ICU), modern medical information systems can record patient events in relational databases every second. Knowledge mining from these huge volumes of medical data is beneficial to both caregivers and patients. Given a set of electronic patient records, a system that effectively assigns the disease labels can facilitate medical database management and also benefit other researchers, e.g., pathologists. In this paper, we have proposed a framework to achieve that goal. Medical chart and note data of a patient are used to extract distinctive features. To encode patient features, we apply a Bag-of-Words encoding method for both chart and note data. We also propose a model that takes into account both global information and local correlations between diseases. Correlated diseases are characterized by a graph structure that is embedded in our sparsity-based framework. Our algorithm captures the disease relevance when labeling disease codes rather than making individual decision with respect to a specific disease. At the same time, the global optimal values are guaranteed by our proposed convex objective function. Extensive experiments have been conducted on a real-world large-scale ICU database. The evaluation results demonstrate that our method improves multi-label classification results by successfully incorporating disease correlations

Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control

It is widely accepted that the complex dynamics characteristic of recurrent neural circuits contributes in a fundamental manner to brain function. Progress has been slow in understanding and exploiting the computational power of recurrent dynamics for two main reasons: nonlinear recurrent networks often exhibit chaotic behavior and most known learning rules do not work in robust fashion in recurrent networks. Here we address both these problems by demonstrating how random recurrent networks (RRN) that initially exhibit chaotic dynamics can be tuned through a supervised learning rule to generate locally stable neural patterns of activity that are both complex and robust to noise. The outcome is a novel neural network regime that exhibits both transiently stable and chaotic trajectories. We further show that the recurrent learning rule dramatically increases the ability of RRNs to generate complex spatiotemporal motor patterns, and accounts for recent experimental data showing a decrease in neural variability in response to stimulus onset

AGO6 Functions in RNA-Mediated Transcriptional Gene Silencing in Shoot and Root Meristems in Arabidopsis thaliana

RNA-directed DNA methylation (RdDM) is a small interfering RNA (siRNA)-mediated epigenetic modification that contributes to transposon silencing in plants. RdDM requires a complex transcriptional machinery that includes specialized RNA polymerases, named Pol IV and Pol V, as well as chromatin remodelling proteins, transcription factors, RNA binding proteins, and other plant-specific proteins whose functions are not yet clarified. In Arabidopsis thaliana, DICER-LIKE3 and members of the ARGONAUTE4 group of ARGONAUTE (AGO) proteins are involved, respectively, in generating and using 24-nt siRNAs that trigger methylation and transcriptional gene silencing of homologous promoter sequences. AGO4 is the main AGO protein implicated in the RdDM pathway. Here we report the identification of the related AGO6 in a forward genetic screen for mutants defective in RdDM and transcriptional gene silencing in shoot and root apical meristems in Arabidopsis thaliana. The identification of AGO6, and not AGO4, in our screen is consistent with the primary expression of AGO6 in shoot and root growing points

Observation of CR Anisotropy with ARGO-YBJ

The measurement of the anisotropies of cosmic ray arrival direction provides important informations on the propagation mechanisms and on the identification of their sources. In this paper we report the observation of anisotropy regions at different angular scales. In particular, the observation of a possible anisotropy on scales between $\sim$ 10 $^{\circ}$ and $\sim$ 30 $^{\circ}$ suggests the presence of unknown features of the magnetic fields the charged cosmic rays propagate through, as well as potential contributions of nearby sources to the total flux of cosmic rays. Evidence of new weaker few-degree excesses throughout the sky region $195^{\circ}\leq$ R.A. $\leq 315^{\circ}$ is reported for the first time.Comment: Talk given at 12th TAUP Conference 2011, 5-9 September 2011, Munich, German

Proteomic analysis of differential proteins in pancreatic carcinomas: Effects of MBD1 knock-down by stable RNA interference

<p>Abstract</p> <p>Background</p> <p>Methyl-CpG binding domain protein 1 (MBD1), a suppressor of gene transcription, may be involved in inactivation of tumor suppressor genes during tumorigenesis. Over-expression of MBD1 has been reported in human pancreatic carcinomas.</p> <p>Methods</p> <p>In this study, we established a MBD1-knock-down pancreatic cancer cell line (BxPC-3) using stable RNA interference, to compare the proteomic changes between control and MBD1-knock-down cells using two-dimensional gel electrophoresis and mass spectrometry.</p> <p>Results</p> <p>We identified five proteins that were up-regulated and nine proteins that were down-regulated. Most of the identified proteins are involved in tumorigenesis, some are prognostic biomarkers for human malignant tumors.</p> <p>Conclusion</p> <p>Our data suggest that these differential proteins may be associated with the function of MBD1, and provide some insight into the functional mechanism of MBD1 in the development of pancreatic cancer.</p

Transcriptomic Characterization of Temperature Stress Responses in Larval Zebrafish

Temperature influences nearly all biochemical, physiological and life history activities of fish, but the molecular mechanisms underlying the temperature acclimation remains largely unknown. Previous studies have identified many temperature-regulated genes in adult tissues; however, the transcriptional responses of fish larvae to temperature stress are not well understood. In this study, we characterized the transcriptional responses in larval zebrafish exposed to cold or heat stress using microarray analysis. In comparison with genes expressed in the control at 28°C, a total of 2680 genes were found to be affected in 96 hpf larvae exposed to cold (16°C) or heat (34°C) for 2 and 48h and most of these genes were expressed in a temperature-specific and temporally regulated manner. Bioinformatic analysis identified multiple temperature-regulated biological processes and pathways. Biological processes overrepresented among the earliest genes induced by temperature stress include regulation of transcription, nucleosome assembly, chromatin organization and protein folding. However, processes such as RNA processing, cellular metal ion homeostasis and protein transport and were enriched in genes up-regulated under cold exposure for 48 h. Pathways such as mTOR signalling, p53 signalling and circadian rhythm were enriched among cold-induced genes, while adipocytokine signalling, protein export and arginine and praline metabolism were enriched among heat-induced genes. Although most of these biological processes and pathways were specifically regulated by cold or heat, common responses to both cold and heat stresses were also found. Thus, these findings provide new interesting clues for elucidation of mechanisms underlying the temperature acclimation in fish