Dynamic maps: a visual-analytic methodology for exploring spatio-temporal disease patterns

<p>Abstract</p> <p>Background</p> <p>Epidemiologic studies are often confounded by the human and environmental interactions that are complex and dynamic spatio-temporal processes. Hence, it is difficult to discover nuances in the data and generate pertinent hypotheses. Dynamic mapping, a method to simultaneously visualize temporal and spatial information, was introduced to elucidate such complexities. A conceptual framework for dynamic mapping regarding principles and implementation methods was proposed.</p> <p>Methods</p> <p>The spatio-temporal dynamics of <it>Salmonella </it>infections for 2002 in the U.S. elderly were depicted via dynamic mapping. Hospitalization records were obtained from the Centers of Medicare and Medicaid Services. To visualize the spatial relationship, hospitalization rates were computed and superimposed onto maps of environmental exposure factors including livestock densities and ambient temperatures. To visualize the temporal relationship, the resultant maps were composed into a movie.</p> <p>Results</p> <p>The dynamic maps revealed that the <it>Salmonella </it>infections peaked at specific spatio-temporal loci: more clusters were observed in the summer months and higher density of such clusters in the South. The peaks were reached when the average temperatures were greater than 83.4°F (28.6°C). Although the relationship of salmonellosis rates and occurrence of temperature anomalies was non-uniform, a strong synchronization was found between high broiler chicken sales and dense clusters of cases in the summer.</p> <p>Conclusions</p> <p>Dynamic mapping is a practical visual-analytic technique for public health practitioners and has an outstanding potential in providing insights into spatio-temporal processes such as revealing outbreak origins, percolation and travelling waves of the diseases, peak timing of seasonal outbreaks, and persistence of disease clusters.</p

Rho Kinases Regulate the Renewal and Neural Differentiation of Embryonic Stem Cells in a Cell Plating Density–Dependent Manner

[[abstract]]BACKGROUND: Rho kinases (ROCKs) mediate cell contraction, local adhesion, and cell motility, which are considered to be important in cell differentiation. We postulated that ROCKs are involved in controlling embryonic stem (ES) cell renewal and differentiation. METHODOLOGY/PRINCIPAL FINDINGS: CCE, a murine ES cell, was treated with Y-27632 for 48 to 96 hours and colony formation was evaluated. Y-27632 blocked CCE colony formation and induced CCE to grow as individual cells, regardless of the initial seeding cell density either at 10(4)/cm(2) ("high" seeding density) or 2x10(3)/cm(2) ("low" density). However, at high seeding density, Y-27632-treated cells exhibited reduction of alkaline phosphatase (AP) staining and Oct3/4 expression. They expressed SOX-1, nestin, and MAP2c, but not betaIII-tubulin or NG-2. They did not express endoderm or mesoderm lineage markers. After removal of Y-27632, the cells failed to form colonies or regain undifferentiated state. Silencing of ROCK-1 or ROCK-2 with selective small interference RNA induced CCE morphological changes similar to Y-27632. Silencing of ROCK-1 or ROCK-2 individually was sufficient to cause reduction of AP and Oct3/4, and expression of SOX-1, nestin, and MAP2c; and combined silencing of both ROCKs did not augment the effects exerted by individual ROCK siRNA. Y-27632-treated CCE cells seeded at 2x10(3) or 6.6x10(3) cells/cm(2) did not lose renewal factors or express differentiation markers. Furthermore, they were able to form AP-positive colonies after removal of Y-27632 and reseeding. Similar to ROCK inhibition by Y-27632, silencing of ROCK-1 or ROCK-2 in cells seeded at 2x10(3)/cm(2) did not change renewal factors. CONCLUSIONS/SIGNIFICANCE: We conclude that ROCKs promote ES cell colony formation, maintain them at undifferentiated state, and prevent them from neural differentiation at high seeding density. ROCK inhibition represents a new strategy for preparing large numbers of neural progenitor cells

Visual Analytics for Epidemiologists: Understanding the Interactions Between Age, Time, and Disease with Multi-Panel Graphs

Visual analytics, a technique aiding data analysis and decision making, is a novel tool that allows for a better understanding of the context of complex systems. Public health professionals can greatly benefit from this technique since context is integral in disease monitoring and biosurveillance. We propose a graphical tool that can reveal the distribution of an outcome by time and age simultaneously.We introduce and demonstrate multi-panel (MP) graphs applied in four different settings: U.S. national influenza-associated and salmonellosis-associated hospitalizations among the older adult population (≥65 years old), 1991-2004; confirmed salmonellosis cases reported to the Massachusetts Department of Public Health for the general population, 2004-2005; and asthma-associated hospital visits for children aged 0-18 at Milwaukee Children's Hospital of Wisconsin, 1997-2006. We illustrate trends and anomalies that otherwise would be obscured by traditional visualization techniques such as case pyramids and time-series plots.MP graphs can weave together two vital dynamics--temporality and demographics--that play important roles in the distribution and spread of diseases, making these graphs a powerful tool for public health and disease biosurveillance efforts

On-demand priority traffic optimizer with fuzzy logic microcontroller

Current traffic control system in Malaysia is developed based on predetermined setup, where the system is not able to analyse the surrounding condition to optimize the green time. When there is an unusual traffic flow, the control system fails to control traffic flow efficiently, causing delays and requiring the assistance of traffic police. The main objective of this project is to explore the potential of fuzzy logic embedded control system in optimizing the traffic congestion corresponding to the priority traffic signal. The developed real time traffic-adaptive control system operates by prioritising the green light based on the received priority signals such as high flow rate phases and the emergency vehicles. A microcontroller-based traffic controller with computed algorithm was developed. The performance of the controller in reducing average waiting time and average vehicle queue length at a traffic intersection was evaluated. In overall, Fuzzy Logic managed to reduce 23% of average waiting time and 11% of average vehicles in queue at the intersection as compared to the conventional control

Laryngeal tuberculosis presenting as a supraglottic carcinoma: a case report and review of the literature

<p>Abstract</p> <p>Introduction</p> <p>Laryngeal tuberculosis used to be a common complication in advanced pulmonary tuberculosis. However, it has become a rare occurrence in developed countries since the introduction of antituberculous agents. Moreover, the pattern of the disease has changed over the years. Nowadays, it more closely resembles a laryngeal carcinoma than any other laryngeal illness.</p> <p>Case presentation</p> <p>We describe the case of a 50-year-old Caucasian man who presented with the clinical picture of laryngeal cancer, but which turned out to be tuberculosis. We illustrate the difficulty of recognizing laryngeal tuberculosis both clinically and even with radiological examination.</p> <p>Conclusion</p> <p>Although laryngeal tuberculosis is uncommon, especially in developed countries, it still occurs and should be considered as a differential diagnosis in any laryngeal disease, in particular in the case of a laryngeal carcinoma.</p

Time series modeling for syndromic surveillance

BACKGROUND: Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. METHODS: Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. RESULTS: Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. CONCLUSIONS: Time series methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization

Checklists in the operating room: Help or hurdle? A qualitative study on health workers' experiences

<p>Abstract</p> <p>Background</p> <p>Checklists have been used extensively as a cognitive aid in aviation; now, they are being introduced in many areas of medicine. Although few would dispute the positive effects of checklists, little is known about the process of introducing this tool into the health care environment. In 2008, a pre-induction checklist was implemented in our anaesthetic department; in this study, we explored the nurses' and physicians' acceptance and experiences with this checklist.</p> <p>Method</p> <p>Focus group interviews were conducted with a purposeful sample of checklist users (nurses and physicians) from the Department of Anaesthesia and Intensive Care in a tertiary teaching hospital. The interviews were analysed qualitatively using systematic text condensation.</p> <p>Results</p> <p>Users reported that checklist use could divert attention away from the patient and that it influenced workflow and doctor-nurse cooperation. They described senior consultants as both sceptical and supportive; a head physician with a positive attitude was considered crucial for successful implementation. The checklist improved confidence in unfamiliar contexts and was used in some situations for which it was not intended. It also revealed insufficient equipment standardisation.</p> <p>Conclusion</p> <p>Our findings suggest several issues and actions that may be important to consider during checklist use and implementation.</p

Geographic variations and temporal trends of Salmonella-associated hospitalization in the U.S. elderly, 1991-2004: A time series analysis of the impact of HACCP regulation

<p>Abstract</p> <p>Background</p> <p>About 1.4 million <it>Salmonella </it>infections, a common food-borne illness, occur in the U.S. annually; the elderly (aged 65 or above) are most susceptible. In 1997, the USDA introduced the Pathogen Reduction and Hazard Analysis and Critical Control Points Systems (PR/HACCP) which demands regular <it>Salmonella </it>testing in various establishments processing meat products, such as broiler chickens. Impact evaluations of PR/HACCP on hospitalizations related to <it>Salmonella </it>are lacking.</p> <p>Methods</p> <p>Hospitalization records of the U.S. elderly in 1991-2004 were obtained from the Centers of Medicare and Medicaid Services. Harmonic regression analyses were performed to evaluate the long-term trends of <it>Salmonella</it>-related hospitalizations in pre- and post-HACCP periods. Seasonal characteristics of the outcome in the nine Census divisions of the contiguous U.S. were also derived and contrasted.</p> <p>Results</p> <p>Predicted rates decreased in most divisions after 1997, except South Atlantic, East South Central, and West South Central. These three divisions also demonstrated higher overall hospitalization rates, pronounced seasonal patterns, and consistent times to peak at about 32^ndto 34^thweek of the year.</p> <p>Conclusion</p> <p>The impact of HACCP was geographically different. South Atlantic, East South Central, and West South Central divisions should be targeted in further <it>Salmonella </it>preventive programs. Further research is needed to identify the best program type and timing of implementation.</p

The Effect of Algorithms on Copy Number Variant Detection

BACKGROUND: The detection of copy number variants (CNVs) and the results of CNV-disease association studies rely on how CNVs are defined, and because array-based technologies can only infer CNVs, CNV-calling algorithms can produce vastly different findings. Several authors have noted the large-scale variability between CNV-detection methods, as well as the substantial false positive and false negative rates associated with those methods. In this study, we use variations of four common algorithms for CNV detection (PennCNV, QuantiSNP, HMMSeg, and cnvPartition) and two definitions of overlap (any overlap and an overlap of at least 40% of the smaller CNV) to illustrate the effects of varying algorithms and definitions of overlap on CNV discovery. METHODOLOGY AND PRINCIPAL FINDINGS: We used a 56 K Illumina genotyping array enriched for CNV regions to generate hybridization intensities and allele frequencies for 48 Caucasian schizophrenia cases and 48 age-, ethnicity-, and gender-matched control subjects. No algorithm found a difference in CNV burden between the two groups. However, the total number of CNVs called ranged from 102 to 3,765 across algorithms. The mean CNV size ranged from 46 kb to 787 kb, and the average number of CNVs per subject ranged from 1 to 39. The number of novel CNVs not previously reported in normal subjects ranged from 0 to 212. CONCLUSIONS AND SIGNIFICANCE: Motivated by the availability of multiple publicly available genome-wide SNP arrays, investigators are conducting numerous analyses to identify putative additional CNVs in complex genetic disorders. However, the number of CNVs identified in array-based studies, and whether these CNVs are novel or valid, will depend on the algorithm(s) used. Thus, given the variety of methods used, there will be many false positives and false negatives. Both guidelines for the identification of CNVs inferred from high-density arrays and the establishment of a gold standard for validation of CNVs are needed