The identification and characterization of the Staphylococcus aureus microbial immunomodulatory molecules (MIMS) Map and Efb

Staphylococcus aureus is an opportunistic pathogen that is a major health threat in the clinical and community settings. An interesting hallmark of patients infected with S. aureus is that they do not usually develop a protective immune response and are susceptible to reinfection, in part because of the ability of S. aureus to modulate host immunity. The ability to evade host immune responses is a key contributor to the infection process and is critical in S. aureus survival and pathogenesis. This study investigates the immunomodulatory effects of two secreted proteins produced by S. aureus, the MHC class II analog protein (Map) and the extracellular fibrinogen-binding protein (Efb). Map has been demonstrated to modulate host immunity by interfering with T cell function. Map has been shown to significantly reduce T cell proliferative responses and significantly reduce delayed-type hypersensitivity responses to challenge antigen. In addition, the effects of Map on the infection process were tested in a mouse model of infection. Mice infected with Map− S. aureus (Map deficient strain) presented with significantly reduced levels of arthritis, osteomyelitis and abscess formation compared to mice infected with the wild-type Map+S. aureus strain suggesting that Map−S. aureus is much less virulent than Map+S. aureus. Furthermore, Map−S. aureus-infected nude mice developed arthritis and osteomyelitis to a severity similar to Map +S. aureus-infected controls, suggesting that T cells can affect disease outcome following S. aureus infection and Map may attenuate cellular immunity against S. aureus. The extracellular fibrinogen-binding protein (Efb) was identified when cultured S. aureus supernatants were probed with the complement component C3. The binding of C3 to Efb resulted in studies investigating the effects of Efb on complement activation. We have demonstrated that Efb can inhibit both the classical and alternative complement pathways. Moreover, we have shown that Efb can inhibit complement mediated opsonophagocytosis. Further studies have characterized the Efb-C3 binding interaction and localized the C3-binding domain to the C-terminal region of Efb. In addition, we demonstrate that Efb binds specifically to a region within the C3d fragment of C3. This study demonstrates that Map and Efb can interfere with both the acquired and innate host immune pathways and that these proteins contribute to the success of S. aureus in evading host immunity and in establishing disease. ^

Building a Globally Distributed Historical Sheet Map Set

This paper describes the procedures used to create a distributed collection of topographic maps of the Austro-Hungarian Empire, the Spezialkarte der Öesterriechisch-ungarnischen Monarchie, Masse. 1:75,000 der natur. This set of maps was published in Vienna over a period of years from 1877 to 1914. The part of the set used in this project includes 776 sheets; all sheets from all editions number over 3,665. The paper contains detailed information on how the maps were converted to digital images, how metadata were prepared, and how Web-browser access was created using ArcIMS Metadata Server. The project, funded by a 2004 National Leadership Grant from the Institute for Museums and Library Science (IMLS), was a joint project of the Homer Babbidge Library Map and Geographic Information Center at the University of Connecticut, the New York Public Library, and the American Geographical Society’s Map Library at the University of Wisconsin Milwaukee.

Verification of intensity modulated stereotactic radiotherapy using Monte Carlo calculations and EPID dosimetry

The purpose of this work was to develop a comprehensive IMSRT QA procedure that examined, using EPID dosimetry and Monte Carlo (MC) calculations, each step in the treatment planning and delivery process. These steps included verification of the field shaping, treatment planning system (RTPS) dose calculations, and patient dose delivery. Verification of each step in the treatment process is assumed to result in correct dose delivery to the patient. ^ The accelerator MC model was verified against commissioning data for field sizes from 0.8 × 0.8 cm 2 to 10 × 10 cm 2. Depth doses were within 2% local percent difference (LPD) in low gradient regions and 1 mm distance to agreement (DTA) in high gradient regions. Lateral profiles were within 2% LPD in low gradient regions and 1 mm DTA in high gradient regions. Calculated output factors were within 1% of measurement for field sizes ≥1 × 1 cm2. ^ The measured and calculated pretreatment EPID dose patterns were compared using criteria of 5% LPD, 1 mm DTA, or 2% of central axis pixel value with ≥95% of compared points required to pass for successful verification. Pretreatment field verification resulted in 97% percent of the points passing. ^ The RTPS and Monte Carlo phantom dose calculations were compared using 5% LPD, 2 mm DTA, or 2% of the maximum dose with ≥95% of compared points required passing for successful verification. RTPS calculation verification resulted in 97% percent of the points passing. ^ The measured and calculated EPID exit dose patterns were compared using criteria of 5% LPD, 1 mm DTA, or 2% of central axis pixel value with ≥95% of compared points required to pass for successful verification. Exit dose verification resulted in 97% percent of the points passing. ^ Each of the processes above verified an individual step in the treatment planning and delivery process. The combination of these verification steps ensures accurate treatment delivery to the patient. This work shows that Monte Carlo calculations and EPID dosimetry can be used to quantitatively verify IMSRT treatments resulting in improved patient care and, potentially, improved clinical outcome. ^

Caenorhabditis elegans germinal center kinase (Gck-1) is a p-body component that inhibits precocious ectopic MAP kinase dependent meiotic maturation

The Caenorhabditis elegans germline is an excellent model system for studying meiosis, as the gonad contains germ cells in all stages of meiosis I prophase in a linear temporal and spatial pattern. To form healthy gametes, many events must be coordinated. Failure of any step in the process can reduce fertility. Here, we describe a C. elegans Germinal Center Kinase, GCK-1, that is essential for the accurate progression of germ cells through meiosis I prophase. In the absence of GCK-1, germ cells undergo precocious maturation due to the activation of a specific MAP kinase isoform. Furthermore, GCK-1 localizes to P-bodies, RNP particles that have been implicated in RNA degradation and translational control. Like two other components of C. elegans germline P-bodies, GCK-1 functions to limit physiological germ cell apoptosis. This is the first study to identify a role for a GCK-III kinase in metazoan germ cell development and to link P-body function with MAP kinase activation and germ cell maturation. ^

Logistic regression models for ordinal response: A study of self-efficacy in colorectal cancer screening

The ordinal logistic regression models are used to analyze the dependant variable with multiple outcomes that can be ranked, but have been underutilized. In this study, we describe four logistic regression models for analyzing the ordinal response variable. ^ In this methodological study, the four regression models are proposed. The first model uses the multinomial logistic model. The second is adjacent-category logit model. The third is the proportional odds model and the fourth model is the continuation-ratio model. We illustrate and compare the fit of these models using data from the survey designed by the University of Texas, School of Public Health research project PCCaSO (Promoting Colon Cancer Screening in people 50 and Over), to study the patient’s confidence in the completion colorectal cancer screening (CRCS). ^ The purpose of this study is two fold: first, to provide a synthesized review of models for analyzing data with ordinal response, and second, to evaluate their usefulness in epidemiological research, with particular emphasis on model formulation, interpretation of model coefficients, and their implications. Four ordinal logistic models that are used in this study include (1) Multinomial logistic model, (2) Adjacent-category logistic model [9], (3) Continuation-ratio logistic model [10], (4) Proportional logistic model [11]. We recommend that the analyst performs (1) goodness-of-fit tests, (2) sensitivity analysis by fitting and comparing different models.^

Proton therapy versus intensity modulated x-ray therapy in the treatment of prostate cancer: Estimating secondary cancer risks

External beam radiation therapy is used to treat nearly half of the more than 200,000 new cases of prostate cancer diagnosed in the United States each year. During a radiation therapy treatment, healthy tissues in the path of the therapeutic beam are exposed to high doses. In addition, the whole body is exposed to a low-dose bath of unwanted scatter radiation from the pelvis and leakage radiation from the treatment unit. As a result, survivors of radiation therapy for prostate cancer face an elevated risk of developing a radiogenic second cancer. Recently, proton therapy has been shown to reduce the dose delivered by the therapeutic beam to normal tissues during treatment compared to intensity modulated x-ray therapy (IMXT, the current standard of care). However, the magnitude of stray radiation doses from proton therapy, and their impact on this incidence of radiogenic second cancers, was not known. ^ The risk of a radiogenic second cancer following proton therapy for prostate cancer relative to IMXT was determined for 3 patients of large, median, and small anatomical stature. Doses delivered to healthy tissues from the therapeutic beam were obtained from treatment planning system calculations. Stray doses from IMXT were taken from the literature, while stray doses from proton therapy were simulated using a Monte Carlo model of a passive scattering treatment unit and an anthropomorphic phantom. Baseline risk models were taken from the Biological Effects of Ionizing Radiation VII report. A sensitivity analysis was conducted to characterize the uncertainty of risk calculations to uncertainties in the risk model, the relative biological effectiveness (RBE) of neutrons for carcinogenesis, and inter-patient anatomical variations. ^ The risk projections revealed that proton therapy carries a lower risk for radiogenic second cancer incidence following prostate irradiation compared to IMXT. The sensitivity analysis revealed that the results of the risk analysis depended only weakly on uncertainties in the risk model and inter-patient variations. Second cancer risks were sensitive to changes in the RBE of neutrons. However, the findings of the study were qualitatively consistent for all patient sizes and risk models considered, and for all neutron RBE values less than 100. ^

A space-time analysis of reported shigellosis and salmonellosis cases in Texas from 2000 to 2004

Background. The purpose of this study was to describe the risk factors and demographics of persons with salmonellosis and shigellosis and to investigate both seasonal and spatial variations in the occurrence of these infections in Texas from 2000 to 2004, utilizing time series analyses and the geographic information system digital mapping methods. ^ Methods. Spatial Analysis: MapInfo software was used to map the distribution of age-adjusted rates of reported shigellosis and salmonellosis in Texas from 2000–2004 by zip codes. Census data on above or below poverty level, household income, highest level of educational attainment, race, ethnicity, and urban/rural community status was obtained from the 2000 Decennial Census for each zip code. The zip codes with the upper 10% and lower 10% were compared using t-tests and logistic regression to determine whether there were any potential risk factors. ^ Temporal analysis. Seasonal patterns in the prevalence of infections in Texas from 2000 to 2003 were determined by performing time-series analysis on the numbers of cases of salmonellosis and shigellosis. A linear regression was also performed to assess for trends in the incidence of each disease, along with auto-correlation and multi-component cosinor analysis. ^ Results. Spatial analysis: Analysis by general linear model showed a significant association between infection rates and age, with young children aged less than 5 and those aged 5–9 years having increased risk of infection for both disease conditions. The data demonstrated that those populations with high percentages of people who attained a higher than high school education were less likely to be represented in zip codes with high rates of shigellosis. However, for salmonellosis, logistic regression models indicated that when compared to populations with high percentages of non-high school graduates, having a high school diploma or equivalent increased the odds of having a high rate of infection. ^ Temporal analysis. For shigellosis, multi-component cosinor analyses were used to determine the approximated cosine curve which represented a statistically significant representation of the time series data for all age groups by sex. The shigellosis results show 2 peaks, with a major peak occurring in June and a secondary peak appearing around October. Salmonellosis results showed a single peak and trough in all age groups with the peak occurring in August and the trough occurring in February. ^ Conclusion. The results from this study can be used by public health agencies to determine the timing of public health awareness programs and interventions in order to prevent salmonellosis and shigellosis from occurring. Because young children depend on adults for their meals, it is important to increase the awareness of day-care workers and new parents about modes of transmission and hygienic methods of food preparation and storage. ^

An ordinal logistic regression model with misclassification of the outcome variable and categorical covariate

Ordinal outcomes are frequently employed in diagnosis and clinical trials. Clinical trials of Alzheimer's disease (AD) treatments are a case in point using the status of mild, moderate or severe disease as outcome measures. As in many other outcome oriented studies, the disease status may be misclassified. This study estimates the extent of misclassification in an ordinal outcome such as disease status. Also, this study estimates the extent of misclassification of a predictor variable such as genotype status. An ordinal logistic regression model is commonly used to model the relationship between disease status, the effect of treatment, and other predictive factors. A simulation study was done. First, data based on a set of hypothetical parameters and hypothetical rates of misclassification was created. Next, the maximum likelihood method was employed to generate likelihood equations accounting for misclassification. The Nelder-Mead Simplex method was used to solve for the misclassification and model parameters. Finally, this method was applied to an AD dataset to detect the amount of misclassification present. The estimates of the ordinal regression model parameters were close to the hypothetical parameters. β1 was hypothesized at 0.50 and the mean estimate was 0.488, β2 was hypothesized at 0.04 and the mean of the estimates was 0.04. Although the estimates for the rates of misclassification of X1 were not as close as β1 and β2, they validate this method. X 1 0-1 misclassification was hypothesized as 2.98% and the mean of the simulated estimates was 1.54% and, in the best case, the misclassification of k from high to medium was hypothesized at 4.87% and had a sample mean of 3.62%. In the AD dataset, the estimate for the odds ratio of X 1 of having both copies of the APOE 4 allele changed from an estimate of 1.377 to an estimate 1.418, demonstrating that the estimates of the odds ratio changed when the analysis includes adjustment for misclassification. ^