Predicting hospital-onset Clostridium difficile using patient mobility data: A network approach

This is the final version. Available from Cambridge University Press via the DOI in this record. Objective: To examine the relationship between unit-wide Clostridium difficile infection (CDI) susceptibility and inpatient mobility and to create contagion centrality as a new predictive measure of CDI. Design: Retrospective cohort study. Methods: A mobility network was constructed using 2 years of patient electronic health record data for a 739-bed hospital (n = 72,636 admissions). Network centrality measures were calculated for each hospital unit (node) providing clinical context for each in terms of patient transfers between units (ie, edges). Daily unit-wide CDI susceptibility scores were calculated using logistic regression and were compared to network centrality measures to determine the relationship between unit CDI susceptibility and patient mobility. Results: Closeness centrality was a statistically significant measure associated with unit susceptibility (P< .05), highlighting the importance of incoming patient mobility in CDI prevention at the unit level. Contagion centrality (CC) was calculated using inpatient transfer rates, unit-wide susceptibility of CDI, and current hospital CDI infections. The contagion centrality measure was statistically significant (P< .05) with our outcome of hospital-onset CDI cases, and it captured the additional opportunities for transmission associated with inpatient transfers. We have used this analysis to create easily interpretable clinical tools showing this relationship as well as the risk of hospital-onset CDI in real time, and these tools can be implemented in hospital EHR systems Conclusions: Quantifying and visualizing the combination of inpatient transfers, unit-wide risk, and current infections help identify hospital units at risk of developing a CDI outbreak and, thus, provide clinicians and infection prevention staff with advanced warning and specific location data to inform prevention efforts.University of Rochester Clinical and Translational Science InstituteNational Institutes of HealthBurroughs Wellcome Fund Institutional Program Unifying Population and Laboratory Based Science

Properties of healthcare teaming networks as a function of network construction algorithms

This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: The Center for Medicare Services Outpatient Claims DE-SynPUF (DE-SynPUF)\cite{RN120} test set is publicly available from the CMS web site. The full 2013 Medicare Part B Limited Data Set for Medicare claims can be obtained from the Center for Medicare Services. This data is bound by a privacy and limited distribution agreement, as well as HIPAA regulations, and thus cannot be made public with this manuscript. However, the files can be requested from the Center for Medicare Services by individual investigators and used to reproduce our findings. Release of the derived networks is also limited by Medicare requirements to remove nodes and edges where the total number of shared patients 11 shared patients, and these are available on figshare.com as referenced in the Supplemental Data section of the manuscript.Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other, and to map how patients traverse the network of providers. Most healthcare service network models have been constructed from patient claims data, using billing claims to link a patient with a specific provider in time. The data sets can be quite large (106±108 individual claims per year), making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks, which as we demonstrate, can be dramatically different. To address this issue, we compared the properties of healthcare networks constructed using different algorithms from 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: Binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We find that each algorithm produced networks with substantially different topological properties, as reflected by numbers of edges, network density, assortativity, clustering coefficients and other structural measures. Provider networks adhered to a power law, while organization networks were best fit by a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and network density, and greatly altered measures of vertex prominence such as the betweenness centrality. Data analysis identified patterns in the distance patients travel between network providers, and a striking set of teaming relationships between providers in the Northeast United States and Florida, likely due to seasonal residence patterns of Medicare beneficiaries. We conclude that the choice of network construction algorithm is critical for healthcare network analysis, and discuss the implications of our findings for selecting the algorithm best suited to the type of analysis to be performed.National Institute of HealthPhilip Templeton FoundationUniversity of Rochester Center for Health Informatic

Reduced Apaf-1 expression in human cutaneous melanomas

Malignant melanoma is a life-threatening skin cancer due to its highly metastatic character and resistance to radio- and chemotherapy. It is believed that the ability to evade apoptosis is the key mechanism for the rapid growth of cancer cells. However, the exact mechanism for failure in the apoptotic pathway in melanoma cells is unclear. p53, the most frequently mutated tumour suppressor gene in human cancers, is a key apoptosis inducer. However, p53 mutation is only found in 15–20% of melanoma biopsies. Recently, it was found that Apaf-1, a downstream target of p53, is inactivated in metastatic melanoma. Specifically, loss of heterozygosity (LOH) of the Apaf-1 gene was found in 40% of metastatic melanoma. To determine if loss of Apaf-1 expression is indeed involved in melanoma progression, we employed the tissue microarray technology and examined Apaf-1 expression in 70 human primary malignant melanoma biopsies by immunohistochemistry. Our data showed that Apaf-1 expression is significantly reduced in melanoma cells compared with normal nevi (χ2=6.02, P=0.014). Our results also revealed that loss of Apaf-1 was not associated with the tumour thickness, ulceration or subtype, patient's gender, age and 5-year survival. In addition, our in vitro apoptosis assay revealed that overexpression of Apaf-1 can sensitise melanoma cells to anticancer drug treatment. Taken together, our data indicate that Apaf-1 expression is significantly reduced in human melanoma and that Apaf-1 may serve as a therapeutic target in melanoma

Processing of inconsistent emotional information: an fMRI study

Previous studies investigating the anterior cingulate cortex (ACC) have relied on a number of tasks which involved cognitive control and attentional demands. In this fMRI study, we tested the model that ACC functions as an attentional network in the processing of language. We employed a paradigm that requires the processing of concurrent linguistic information predicting that the cognitive costs imposed by competing trials would engender the activation of ACC. Subjects were confronted with sentences where the semantic content conflicted with the prosodic intonation (CONF condition) randomly interspaced with sentences which conveyed coherent discourse components (NOCONF condition). We observed the activation of the rostral ACC and the middle frontal gyrus when the NOCONF condition was subtracted from the CONF condition. Our findings provide evidence for the involvement of the rostral ACC in the processing of complex competing linguistic stimuli, supporting theories that claim its relevance as a part of the cortical attentional circuit. The processing of emotional prosody involved a bilateral network encompassing the superior and medial temporal cortices. This evidence confirms previous research investigating the neuronal network that supports the processing of emotional information

Chicken genome analysis reveals novel genes encoding biotin-binding proteins related to avidin family

BACKGROUND: A chicken egg contains several biotin-binding proteins (BBPs), whose complete DNA and amino acid sequences are not known. In order to identify and characterise these genes and proteins we studied chicken cDNAs and genes available in the NCBI database and chicken genome database using the reported N-terminal amino acid sequences of chicken egg-yolk BBPs as search strings. RESULTS: Two separate hits showing significant homology for these N-terminal sequences were discovered. For one of these hits, the chromosomal location in the immediate proximity of the avidin gene family was found. Both of these hits encode proteins having high sequence similarity with avidin suggesting that chicken BBPs are paralogous to avidin family. In particular, almost all residues corresponding to biotin binding in avidin are conserved in these putative BBP proteins. One of the found DNA sequences, however, seems to encode a carboxy-terminal extension not present in avidin. CONCLUSION: We describe here the predicted properties of the putative BBP genes and proteins. Our present observations link BBP genes together with avidin gene family and shed more light on the genetic arrangement and variability of this family. In addition, comparative modelling revealed the potential structural elements important for the functional and structural properties of the putative BBP proteins

A Survey on Continuous Time Computations

We provide an overview of theories of continuous time computation. These theories allow us to understand both the hardness of questions related to continuous time dynamical systems and the computational power of continuous time analog models. We survey the existing models, summarizing results, and point to relevant references in the literature

Changed epitopes drive the antigenic drift for influenza A (H3N2) viruses

<p>Abstract</p> <p>Background</p> <p>In circulating influenza viruses, gradually accumulated mutations on the glycoprotein hemagglutinin (HA), which interacts with infectivity-neutralizing antibodies, lead to the escape of immune system (called antigenic drift). The antibody recognition is highly correlated to the conformation change on the antigenic sites (epitopes), which locate on HA surface. To quantify a changed epitope for escaping from neutralizing antibodies is the basis for the antigenic drift and vaccine development.</p> <p>Results</p> <p>We have developed an epitope-based method to identify the antigenic drift of influenza A utilizing the conformation changes on epitopes. A changed epitope, an antigenic site on HA with an accumulated conformation change to escape from neutralizing antibody, can be considered as a "key feature" for representing the antigenic drift. According to hemagglutination inhibition (HI) assays and HA/antibody complex structures, we statistically measured the conformation change of an epitope by considering the number of critical position mutations with high genetic diversity and antigenic scores. Experimental results show that two critical position mutations can induce the conformation change of an epitope to escape from the antibody recognition. Among five epitopes of HA, epitopes A and B, which are near to the receptor binding site, play a key role for neutralizing antibodies. In addition, two changed epitopes often drive the antigenic drift and can explain the selections of 24 WHO vaccine strains.</p> <p>Conclusions</p> <p>Our method is able to quantify the changed epitopes on HA for predicting the antigenic variants and providing biological insights to the vaccine updates. We believe that our method is robust and useful for studying influenza virus evolution and vaccine development.</p

Enumerating Pathways of Proton Abstraction Based on a Spatial and Electrostatic Analysis of Residues in the Catalytic Site

The pathways of proton abstraction (PA), a key aspect of most catalytic reactions, is often controversial and highly debated. Ultrahigh-resolution diffraction studies, molecular dynamics, quantum mechanics and molecular mechanic simulations are often adopted to gain insights in the PA mechanisms in enzymes. These methods require expertise and effort to setup and can be computationally intensive. We present a push button methodology – Proton abstraction Simulation (PRISM) – to enumerate the possible pathways of PA in a protein with known 3D structure based on the spatial and electrostatic properties of residues in the proximity of a given nucleophilic residue. Proton movements are evaluated in the vicinity of this nucleophilic residue based on distances, potential differences, spatial channels and characteristics of the individual residues (polarity, acidic, basic, etc). Modulating these parameters eliminates their empirical nature and also might reveal pathways that originate from conformational changes. We have validated our method using serine proteases and concurred with the dichotomy in PA in Class A β-lactamases, both of which are hydrolases. The PA mechanism in a transferase has also been corroborated. The source code is made available at www.sanchak.com/prism

Longitudinal assessment of PCBs and chlorinated pesticides in pregnant women from Western Canada

BACKGROUND: Maternal exposures to organochlorines prior to pregnancy are considered a risk to neonatal welfare, specifically in relation to neurocognitive functions. There is growing interest in the evaluation of maternal blood testing as a marker for fetal exposure as well as the variable geographic distribution of these priority chemicals. METHODS: Three hundred and twenty-three women in the second trimester of pregnancy entered the study at a prenatal clinic providing genetic counselling information. Subjects who had an indication for genetic amniocentesis based on late maternal age were eligible to participate. Two hundred and thirty-eight completed an environmental questionnaire. A sample of amniotic fluid was taken for karyotype analysis in 323 women and blood samples during pregnancy (209), at birth (105) and from the umbilical cord (97) and breast milk (47) were also collected. These samples were tested for 29 PCB congeners and organochlorine pesticides. RESULTS: The concentrations of PCB 153 in these media were relatively low in relation to other studies. Σ PCBs measurements in samples taken during the second trimester of pregnancy, at birth and in the umbilical cord were strongly correlated. Specific measurements of PCB 153 and PCB 180 among those subjects with completed sampling of blood samples from mothers and cord samples were significantly correlated. The concentrations of PCBs and pesticides did not differ in relation to prior spontaneous abortion history. There were no organochlorines present in the amniotic fluid at the current level of quantification. CONCLUSION: Pregnant women from the Western Canada region of Calgary, Alberta are exposed to relatively low concentrations of organochlorines. Measurement of maternal blood during the second trimester of pregnancy can reliably estimate the fetal exposure to PCBs. This estimate is reliable for Group 2 and 3 PCBs as well as PCB 153 and PCB 180. The amniotic fluid does not contain measurable concentrations of pesticides and PCBs under the conditions of the levels of quantification