BACKGROUND:: Peutz-Jeghers syndrome (PJS) is a rare autosomal dominant disorder, and women with this syndrome are at an increased risk of developing intestinal and extraintestinal malignancies including breast and gynecologic malignancies. This case report presents a patient with PJS with a concomitant breast cancer, bilateral stromal tumors with annular tubules of the ovaries, and adenoma malignum of the cervix. CASE:: A 43-year-old woman presented with an advanced-stage breast cancer and a pelvic mass. The patient was treated with neoadjuvant chemotherapy followed by laparotomy with a hysterectomy and oophorectomy. Final pathologic examination revealed a concomitant breast cancer with metastasis to the ovaries, bilateral stromal tumors with annular tubules of the ovaries, and adenoma malignum of the cervix. CONCLUSIONS:: Patients with PJS are at a high risk for intestinal and extraintestinal malignancies and can present with multiple concomitant malignancies.

OBJECTIVE: To evaluate methods for monitoring monthly aggregated hospital adverse event data that display clustering, non-linear trends and possible autocorrelation. DESIGN: Retrospective audit. SETTING: The Northern Hospital, Melbourne, Australia. PARTICIPANTS: 171,059 patients admitted between January 2001 and December 2006. Measurements: The analysis is illustrated with 72 months of patient fall injury data using a modified Shewhart U control chart, and charts derived from a quasi-Poisson generalised linear model (GLM) and a generalised additive mixed model (GAMM) that included an approximate upper control limit. RESULTS: The data were overdispersed and displayed a downward trend and possible autocorrelation. The downward trend was followed by a predictable period after December 2003. The GLM-estimated incidence rate ratio was 0.98 (95% CI 0.98 to 0.99) per month. The GAMM-fitted count fell from 12.67 (95% CI 10.05 to 15.97) in January 2001 to 5.23 (95% CI 3.82 to 7.15) in December 2006 (p<0.001). The corresponding values for the GLM were 11.9 and 3.94. Residual plots suggested that the GLM underestimated the rate at the beginning and end of the series and overestimated it in the middle. The data suggested a more rapid rate fall before 2004 and a steady state thereafter, a pattern reflected in the GAMM chart. The approximate upper two-sigma equivalent control limit in the GLM and GAMM charts identified 2 months that showed possible special-cause variation. CONCLUSION: Charts based on GAMM analysis are a suitable alternative to Shewhart U control charts with these data.

BACKGROUND: It remains unclear over whether it is possible to develop an epidemic forecasting model for transmission of Dengue fever in Queensland, Australia. OBJECTIVES: To examine the potential impact of El Niño/Southern Oscillation (ENSO) on the transmission of dengue fever in Queensland, Australia and explore the possibility of developing a forecast model of dengue fever. METHODS: Data on the Southern Oscillation Index (SOI), an indicator of ENSO activity, were obtained from the Australian Bureau of Meteorology. Numbers of dengue fever cases notified and the numbers of postcode areas (PA) with dengue fever cases between January 1993 and December 2005 were obtained from the Queensland Health and relevant population data were obtained from the Australia Bureau of Statistics. A multivariate Seasonal Auto-regressive Integrated Moving Average (SARIMA) model was developed and validated by dividing the data file into two datasets: the data from January 1993 - December 2003 were used to construct a model and those from January 2004 - December 2005 were used to validate it. RESULTS: A decrease in the average SOI (i.e., warmer conditions) during the preceding 3 - 12 months was significantly associated with an increase in the monthly numbers of PA with dengue fever cases (beta =- 0.038; p = 0.019). Predicted values from the SARIMA model were consistent with the observed values in the validation dataset (root-mean-square percentage error: 1.93%). CONCLUSIONS: Climate variability is directly and/or indirectly associated with dengue transmission and the development of a SOI-based epidemic forecasting system is possible for dengue fever in Queensland, Australia.

Control charts are being increasingly used to summarise sequential rates of hospital adverse events (AEs). They are designed to detect departures from stable, predictable processes and are therefore appropriate when information about the mean value and variability of the relevant time-series data is available, from when the process is or has been in a stable, predictable state. This is often the case with binary data AEs such as surgical site infections and surgical mortality. However, it may not always be possible to determine the stable predictable rate at which events such as patient falls, pressure ulcers, medication errors or new isolates of a multiresistant organism (MRO) occur. Furthermore, such a rate may sometimes not exist, as is frequently the case with antibiotic usage and MRO prevalence data. It may then be better to employ time-series methods to analyse and present the data. A convenient approach is to employ spline-regression or a generalised additive model.

ABSTRACT: BACKGROUND: To allow direct comparison of bloodstream infection (BSI) rates between hospitals for performance measurement, observed rates need to be risk adjusted according to the types of patients cared for by the hospital. However, attribute data on all individual patients are often unavailable and hospital-level risk adjustment needs to be done using indirect indicator variables of patient case mix, such as hospital level. We aimed to identify medical services associated with high or low BSI rates, and to evaluate the services provided by the hospital as indicators that can be used for more objective hospital-level risk adjustment. METHODS: From February 2001-December 2007, 1719 monthly BSI counts were available from 18 hospitals in Queensland, Australia. BSI outcomes were stratified into four groups: overall BSI (OBSI), Staphylococcus aureus BSI (STAPH), intravascular device-related S. aureus BSI (IVD-STAPH) and methicillin-resistant S. aureus BSI (MRSA). Twelve services were considered as candidate risk-adjustment variables. For OBSI, STAPH and IVD-STAPH, we developed generalized estimating equation Poisson regression models that accounted for autocorrelation in longitudinal counts. Due to a lack of autocorrelation, a standard logistic regression model was specified for MRSA. RESULTS: Four risk services were identified for OBSI: AIDS (IRR 2.14, 95% CI 1.20 to 3.82), infectious diseases (IRR 2.72, 95% CI 1.97 to 3.76), oncology (IRR 1.60, 95% CI 1.29 to 1.98) and bone marrow transplants (IRR 1.52, 95% CI 1.14 to 2.03). Four protective services were also found. A similar but smaller group of risk and protective services were found for the other outcomes. Acceptable agreement between observed and fitted values was found for the OBSI and STAPH models but not for the IVD-STAPH and MRSA models. However, the IVD-STAPH and MRSA models successfully discriminated between hospitals with higher and lower BSI rates. CONCLUSIONS: The high model goodness-of-fit and the higher frequency of OBSI and STAPH outcomes indicated that hospital-specific risk adjustment based on medical services provided would be useful for these outcomes in Queensland. The low frequency of IVD-STAPH and MRSA outcomes indicated that development of a hospital-level risk score was a more valid method of risk adjustment for these outcomes.

Molecular machines drive essential biological processes, with the component parts of these machines each contributing a partial function or structural element. Mitochondria are organelles of eukaryotic cells, and depend for their biogenesis on a set of molecular machines for protein transport. How these molecular machines evolved is a fundamental question. Mitochondria were derived from an alpha-proteobacterial endosymbiont, and we identified in alpha-proteobacteria the component parts of a mitochondrial protein transport machine. In bacteria, the components are found in the inner membrane, topologically equivalent to the mitochondrial proteins. Although the bacterial proteins function in simple assemblies, relatively little mutation would be required to convert them to function as a protein transport machine. This analysis of protein transport provides a blueprint for the evolution of cellular machinery in general.

ABSTRACT: BACKGROUND: Understanding spatio-temporal variation in malaria incidence provides a basis for effective disease control planning and monitoring. METHODS: Monthly surveillance data between 1991 and 2006 for Plasmodium vivax and Plasmodium falciparum malaria across 128 counties were assembled for Yunnan, a province of China with one of the highest burdens of malaria. County-level Bayesian Poisson regression models of incidence were constructed, with effects for rainfall, maximum temperature and temporal trend. The model also allowed for spatial variation in county-level incidence and temporal trend, and dependence between incidence in June-September and the preceding January-February. RESULTS: Models revealed strong associations between malaria incidence and both rainfall and maximum temperature. There was a significant association between incidence in June-September and the preceding January-February. Raw standardised morbidity ratios showed a high incidence in some counties bordering Myanmar, Laos and Vietnam, and counties in the Red River valley. Clusters of counties in south-western and northern Yunnan were identified that had high incidence not explained by climate. The overall trend in incidence decreased, but there was significant variation between counties. CONCLUSIONS: Dependence between incidence in summer and the preceding January-February suggests a role of intrinsic host-pathogen dynamics. Incidence during the summer peak might be predictable based on incidence in January-February, facilitating malaria control planning, scaled months in advance to the magnitude of the summer malaria burden. Heterogeneities in county-level temporal trends suggest that reductions in the burden of malaria have been unevenly distributed throughout the province.

SUMMARYSchistosomiasis remains one of the most prevalent parasitic diseases in developing countries. After malaria, schistosomiasis is the most important tropical disease in terms of human morbidity with significant economic and public health consequences. Although schistosomiasis has recently attracted increased focus and funding for control, it has been estimated that less than 20% of the funding needed to control the disease in Africa is currently available. In this article the following issues are discussed: the rationale, development and objectives of the Schistosomiasis Control Initiative (SCI)-supported programmes; the management approaches followed to achieve implementation by each country; mapping, monitoring and evaluation activities with quantifiable impact of control programmes; monitoring for any potential drug resistance; and finally exit strategies within each country. The results have demonstrated that morbidity due to schistosomiasis has been reduced by the control programmes. While challenges remain, the case for the control of schistosomiasis has been strengthened by research by SCI teams and the principle that a national programme using 'preventive chemotherapy' can be successfully implemented in sub-Saharan Africa, whenever the resources are available. SCI and partners are now actively striving to raise further funds to expand the coverage of integrated control of neglected tropical diseases (NTDs) in sub-Saharan Africa.

ABSTRACT: BACKGROUND: Reliable and updated maps of helminth (worm) infection distributions are essential to target control strategies to those populations in greatest need. Although many surveys have been conducted in endemic countries, the data are rarely available in a form that is accessible to policy makers and the managers of public health programmes. This is especially true in sub-Saharan Africa, where empirical data are seldom in the public domain. In an attempt to address the paucity of geographical information on helminth risk, this article describes the development of an updated global atlas of human helminth infection, showing the example of East Africa. METHODS: Empirical, cross-sectional estimates of infection prevalence conducted since 1980 were identified using electronic and manual search strategies of published and unpublished sources. A number of inclusion criteria were imposed for identified information, which was extracted into a standardized database. Details of survey population, diagnostic methods, sample size and numbers infected with schistosomes and soil-transmitted helminths were recorded. A unique identifier linked each record to an electronic copy of the source document, in portable document format. An attempt was made to identify the geographical location of each record using standardized geolocation procedures and the assembled data were incorporated into a geographical information system. RESULTS: At the time of writing, over 2,748 prevalence surveys were identified through multiple search strategies. Of these, 2,612 were able to be geolocated and mapped. More than half (58%) of included surveys were from grey literature or unpublished sources, underlining the importance of reviewing in-country sources. 66% of all surveys were conducted since 2000. Comprehensive, countrywide data are available for Burundi, Rwanda and Uganda. In contrast, information for Kenya and Tanzania is typically clustered in specific regions of the country, with few records from areas with very low population density and/or environmental conditions which are unfavourable for helminth transmission. Information is presented on the prevalence and geographical distribution for the major helminth species. CONCLUSIONS: For all five countries, the information assembled in the current atlas provides the most reliable, up-to-date and comprehensive source of data on the distribution of common helminth infections to guide the rational implementation of control efforts.

We examine the photophysics of a colloidal suspension of C(60) particles in a micellar solution of Triton X-100 and water, prepared via a new synthesis which allows high-concentration suspensions. The particle sizes are characterized by transmission electron microscopy and dynamic light scattering and found to be somewhat polydisperse in the range of 10-100 nm. The suspension is characterized optically by UV-vis spectroscopy, femtosecond transient absorption spectroscopy, laser flash photolysis, and z-scan. The ground-state absorbance spectrum shows a broad absorbance feature centered near 450 nm which is indicative of colloidal C(60). The transient absorption dynamics, presented for the first time with femtosecond resolution, are very similar to that of thin films of C(60) and indicate a strong quenching of the singlet excited state on short time scales and evidence of little intersystem crossing to a triplet excited state. Laser flash photolysis reveals that a triplet excited-state absorption spectrum, which is essentially identical in shape to that of molecular C(60) solutions, does indeed arise, but with much lower magnitude and somewhat shorter lifetime. Z-scan analysis confirms that the optical response of this material is dominated by nonlinear scattering.