Parasite control practices on Swedish horse farms

Conclusion: The results show that routines for endoparasite control can be improved in many horse establishments. To increase the knowledge of equine endoparasite control and follow the recommendations for how to reduce the spread of anthelmintic resistance, a closer collaboration between parasitologists and veterinary practitioners is desirable

Children at danger: injury fatalities among children in San Diego County

External causes of death are important in the pediatric population worldwide. We performed an analysis of all injury-fatalities in children between ages zero and 17 years, between January 2000 and December 2006, in San Diego County, California, United States of America. Information was obtained from the County of San Diego Medical Examiner’s database. External causes were selected and grouped by intent and mechanism. Demographics, location of death and relation between the injury mechanism and time of death were described. There were 884 medico-legal examinations, of which 480 deaths were due to external causes. There majority were males (328, 68.3%) and whites (190, 39.6%). The most prevalent mechanism of injury leading to death was road traffic accidents (40.2%), followed by asphyxia (22.7%) and penetrating trauma (17.7%). Unintentional injuries occurred in 65.8% and intentional injuries, including homicide and suicide, occurred in 24.2 and 9.4%, respectively. Death occurred at the scene in 196 cases (40.9%). Most deaths occurred in highways (35.3%) and at home (28%). One hundred forty-six patients (30.4%) died in the first 24 h. Seven percent died 1 week after the initial injury. Among the cases that died at the scene, 48.3% were motor vehicle accidents, 20.9% were victims of firearms, 6.5% died from poisoning, 5% from hanging, and 4% from drowning. External causes remain an important cause of death in children in San Diego County. Specific strategies to decrease road-traffic accidents and homicides must be developed and implemented to reduce the burden of injury-related deaths in children

Automatic de-identification of textual documents in the electronic health record: a review of recent research

<p>Abstract</p> <p>Background</p> <p>In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here.</p> <p>Methods</p> <p>This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers.</p> <p>Results</p> <p>The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries.</p> <p>Conclusions</p> <p>In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication.</p

Stages of development and injury patterns in the early years: a population-based analysis

BACKGROUND: In Canada, there are many formal public health programs under development that aim to prevent injuries in the early years (e.g. 0–6). There are paradoxically no population-based studies that have examined patterns of injury by developmental stage among these young children. This represents a gap in the Canadian biomedical literature. The current population-based analysis explores external causes and consequences of injuries experienced by young children who present to the emergency department for assessment and treatment. This provides objective evidence about prevention priorities to be considered in anticipatory counseling and public health planning. METHODS: Four complete years of data (1999–2002; n = 5876 cases) were reviewed from the Kingston sites of the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP), an ongoing injury surveillance initiative. Epidemiological analyses were used to characterize injury patterns within and across age groups (0–6 years) that corresponded to normative developmental stages. RESULTS: The average annual rate of emergency department-attended childhood injury was 107 per 1000 (95% CI 91–123), with boys experiencing higher annual rates of injury than girls (122 vs. 91 per 1000; p < 0.05). External causes of injury changed substantially by developmental stage. This lead to the identification of four prevention priorities surrounding 1) the optimization of supervision; 2) limiting access to hazards; 3) protection from heights; and 4) anticipation of risks. CONCLUSION: This population-based injury surveillance analysis provides a strong evidence-base to inform and enhance anticipatory counseling and other public health efforts aimed at the prevention of childhood injury during the early years

PPARγ agonists inhibit growth and expansion of CD133+ brain tumour stem cells

Brain tumour stem cells (BTSCs) are a small population of cells that has self-renewal, transplantation, multidrug resistance and recurrence properties, thus remain novel therapeutic target for brain tumour. Recent studies have shown that peroxisome proliferator-activated receptor gamma (PPARγ) agonists induce growth arrest and apoptosis in glioblastoma cells, but their effects on BTSCs are largely unknown. In this study, we generated gliospheres with more than 50% CD133+ BTSC by culturing U87MG and T98G human glioblastoma cells with epidermal growth factor (EGF) and basic fibroblast growth factor (bFGF). In vitro treatment with PPARγ agonist, 15-Deoxy-Δ12,14-Prostaglandin J2 (15d-PGJ2) or all-trans retinoic acid resulted in a reversible inhibition of gliosphere formation in culture. Peroxisome proliferator-activated receptor gamma agonists inhibited the proliferation and expansion of glioma and gliosphere cells in a dose-dependent manner. Peroxisome proliferator-activated receptor gamma agonists also induced cell cycle arrest and apoptosis in association with the inhibition of EGF/bFGF signalling through Tyk2-Stat3 pathway and expression of PPARγ in gliosphere cells. These findings demonstrate that PPARγ agonists regulate growth and expansion of BTSCs and extend their use to target BTSCs in the treatment of brain tumour

PPARγ agonists inhibit growth and expansion of CD133+ brain tumour stem cells

Brain tumour stem cells (BTSCs) are a small population of cells that has self-renewal, transplantation, multidrug resistance and recurrence properties, thus remain novel therapeutic target for brain tumour. Recent studies have shown that peroxisome proliferator-activated receptor gamma (PPARγ) agonists induce growth arrest and apoptosis in glioblastoma cells, but their effects on BTSCs are largely unknown. In this study, we generated gliospheres with more than 50% CD133+ BTSC by culturing U87MG and T98G human glioblastoma cells with epidermal growth factor (EGF) and basic fibroblast growth factor (bFGF). In vitro treatment with PPARγ agonist, 15-Deoxy-Δ12,14-Prostaglandin J2 (15d-PGJ2) or all-trans retinoic acid resulted in a reversible inhibition of gliosphere formation in culture. Peroxisome proliferator-activated receptor gamma agonists inhibited the proliferation and expansion of glioma and gliosphere cells in a dose-dependent manner. Peroxisome proliferator-activated receptor gamma agonists also induced cell cycle arrest and apoptosis in association with the inhibition of EGF/bFGF signalling through Tyk2-Stat3 pathway and expression of PPARγ in gliosphere cells. These findings demonstrate that PPARγ agonists regulate growth and expansion of BTSCs and extend their use to target BTSCs in the treatment of brain tumour

Using the SaTScan method to detect local malaria clusters for guiding malaria control programmes

Mpumalanga Province, South Africa is a low malaria transmission area that is subject to malaria epidemics. SaTScan methodology was used by the malaria control programme to detect local malaria clusters to assist disease control planning. The third season for case cluster identification overlapped with the first season of implementing an outbreak identification and response system in the area. SaTScan™ software using the Kulldorf method of retrospective space-time permutation and the Bernoulli purely spatial model was used to identify malaria clusters using definitively confirmed individual cases in seven towns over three malaria seasons. Following passive case reporting at health facilities during the 2002 to 2005 seasons, active case detection was carried out in the communities, this assisted with determining the probable source of infection. The distribution and statistical significance of the clusters were explored by means of Monte Carlo replication of data sets under the null hypothesis with replications greater than 999 to ensure adequate power for defining clusters. SaTScan detected five space-clusters and two space-time clusters during the study period. There was strong concordance between recognized local clustering of cases and outbreak declaration in specific towns. Both Albertsnek and Thambokulu reported malaria outbreaks in the same season as space-time clusters. This synergy may allow mutual validation of the two systems in confirming outbreaks demanding additional resources and cluster identification at local level to better target resources. Exploring the clustering of cases assisted with the planning of public health activities, including mobilizing health workers and resources. Where appropriate additional indoor residual spraying, focal larviciding and health promotion activities, were all also carried out

Spatial point analysis based on dengue surveys at household level in central Brazil

<p>Abstract</p> <p>Background</p> <p>Dengue virus (DENV) affects nonimunne human populations in tropical and subtropical regions. In the Americas, dengue has drastically increased in the last two decades and Brazil is considered one of the most affected countries. The high frequency of asymptomatic infection makes difficult to estimate prevalence of infection using registered cases and to locate high risk intra-urban area at population level. The goal of this spatial point analysis was to identify potential high-risk intra-urban areas of dengue, using data collected at household level from surveys.</p> <p>Methods</p> <p>Two household surveys took place in the city of Goiania (~1.1 million population), Central Brazil in the year 2001 and 2002. First survey screened 1,586 asymptomatic individuals older than 5 years of age. Second survey 2,906 asymptomatic volunteers, same age-groups, were selected by multistage sampling (census tracts; blocks; households) using available digital maps. Sera from participants were tested by dengue virus-specific IgM/IgG by EIA. A Generalized Additive Model (GAM) was used to detect the spatial varying risk over the region. Initially without any fixed covariates, to depict the overall risk map, followed by a model including the main covariates and the year, where the resulting maps show the risk associated with living place, controlled for the individual risk factors. This method has the advantage to generate smoothed risk factors maps, adjusted by socio-demographic covariates.</p> <p>Results</p> <p>The prevalence of antibody against dengue infection was 37.3% (95%CI [35.5–39.1]) in the year 2002; 7.8% increase in one-year interval. The spatial variation in risk of dengue infection significantly changed when comparing 2001 with 2002, (ORadjusted = 1.35; p < 0.001), while controlling for potential confounders using GAM model. Also increasing age and low education levels were associated with dengue infection.</p> <p>Conclusion</p> <p>This study showed spatial heterogeneity in the risk areas of dengue when using a spatial multivariate approach in a short time interval. Data from household surveys pointed out that low prevalence areas in 2001 surveys shifted to high-risk area in consecutive year. This mapping of dengue risks should give insights for control interventions in urban areas.</p

Spatial Evaluation and Modeling of Dengue Seroprevalence and Vector Density in Rio de Janeiro, Brazil

Dengue is a major public health problem in many tropical regions of the world, including Brazil, where Aedes aegypti is the main vector. We present a household study that combines data on dengue fever seroprevalence, recent dengue infection, and vector density, in three neighborhoods of Rio de Janeiro, Brazil, during its most devastating dengue epidemic to date. This integrated entomological–serological survey showed evidence of silent transmission even during a severe epidemic. Also, past exposure to dengue virus was highly associated with age and living in areas of high movement of individuals and social/commercial activity. No association was observed between household infestation index and risk of dengue infection in these areas. Our findings are discussed in the light of current theories regarding transmission thresholds and relative role of mosquitoes and humans as vectors of dengue viruses