Electrical behavior of MIS devices based on Si nanoclusters embedded in SiOxNy and SiO2 films

We examined and compared the electrical properties of silica (SiO2) and silicon oxynitride (SiOxNy) layers embedding silicon nanoclusters (Sinc) integrated in metal-insulator-semiconductor (MIS) devices. The technique used for the deposition of such layers is the reactive magnetron sputtering of a pure SiO2 target under a mixture of hydrogen/argon plasma in which nitrogen is incorporated in the case of SiOxNy layer. Al/SiOxNy-Sinc/p-Si and Al/SiO2-Sinc/p-Si devices were fabricated and electrically characterized. Results showed a high rectification ratio (>104) for the SiOxNy-based device and a resistive behavior when nitrogen was not incorporating (SiO2-based device). For rectifier devices, the ideality factor depends on the SiOxNy layer thickness. The conduction mechanisms of both MIS diode structures were studied by analyzing thermal and bias dependences of the carriers transport in relation with the nitrogen content

Evaluation of the implementation of an integrated primary care network for prevention and management of cardiometabolic risk in Montréal

<p>Abstract</p> <p>Background</p> <p>The goal of this project is to evaluate the implementation of an integrated and interdisciplinary program for prevention and management of cardiometabolic risk (PCMR). The intervention is based on the Chronic Care Model. The study will evaluate the implementation of the PCMR in 6 of the 12 health and social services centres (CSSS) in Montréal, and the effects of the PCMR on patients and the practice of their primary care physicians up to 40 months following implementation, as well as the sustainability of the program. Objectives are: 1-to evaluate the effects of the PCMR and their persistence on patients registered in the program and the practice of their primary care physicians, by implementation site and degree of exposure to the program; 2-to assess the degree of implementation of PCMR in each CSSS territory and identify related contextual factors; 3-to establish the relationships between the effects observed, the degree of PCMR implementation and the related contextual factors; 4-to assess the impact of the PCMR on strengthening local services networks.</p> <p>Methods/Design</p> <p>The evaluation will use a mixed design that includes two complementary research strategies. The first strategy is similar to a quasi-experimental "before-after" design, based on a quantitative approach; it will look at the program's effects and their variations among the six territories. The effects analysis will use data from a clinical database and from questionnaires completed by participating patients and physicians. Over 3000 patients will be recruited. The second strategy corresponds to a multiple case study approach, where each of the six CSSS constitutes a case. With this strategy, qualitative methods will set out the context of implementation using data from semi-structured interviews with program managers. The quantitative data will be analyzed using linear or multilevel models complemented with an interpretive approach to qualitative data analysis.</p> <p>Discussion</p> <p>Our study will identify contextual factors associated with the effectiveness, successful implementation and sustainability of such a program. The contextual information will enable us to extrapolate our results to other contexts with similar conditions.</p> <p>Trial registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01326130">NCT01326130</a></p

Tamoxifen resistance in early breast cancer: statistical modelling of tissue markers to improve risk prediction

BACKGROUND: For over two decades, the Nottingham Prognostic Index (NPI) has been used in the United Kingdom to calculate risk scores and inform management about breast cancer patients. It is derived using just three clinical variables - nodal involvement, tumour size and grade. New scientific methods now make cost-effective measurement of many biological characteristics of tumour tissue from breast cancer biopsy samples possible. However, the number of potential explanatory variables to be considered presents a statistical challenge. The aim of this study was to investigate whether in ER+ tamoxifen-treated breast cancer patients, biological variables can add value to NPI predictors, to provide improved prognostic stratification in terms of overall recurrence-free survival (RFS) and also in terms of remaining recurrence free while on tamoxifen treatment (RFoT). A particular goal was to enable the discrimination of patients with a very low risk of recurrence. METHODS: Tissue samples of 401 cases were analysed by microarray technology, providing biomarker data for 72 variables in total, from AKT, BAD, HER, MTOR, PgR, MAPK and RAS families. Only biomarkers screened as potentially informative (i.e., exhibiting univariate association with recurrence) were offered to the multivariate model. The multiple imputation method was used to deal with missing values, and bootstrap sampling was used to assess internal validity and refine the model. RESULTS: Neither the RFS nor RFoT models derived included Grade, but both had better predictive and discrimination ability than NPI. A slight difference was observed between models in terms of biomarkers included, and, in particular, the RFoT model alone included HER2. The estimated 7-year RFS rates in the lowest-risk groups by RFS and RFoT models were 95 and 97%, respectively, whereas the corresponding rate for the lowest-risk group of NPI was 89%. CONCLUSION: The findings demonstrate considerable potential for improved prognostic modelling by incorporation of biological variables into risk prediction. In particular, the ability to identify a low-risk group with minimal risk of recurrence is likely to have clinical appeal. With larger data sets and longer follow-up, this modelling approach has the potential to enhance an understanding of the interplay of biological characteristics, treatment and cancer recurrence. British Journal of Cancer (2010) 102, 1503 - 1510. doi:10.1038/sj.bjc.6605627 www.bjcancer.co

Predicting microbiologically defined infection in febrile neutropenic episodes in children : global individual participant data multivariable meta-analysis

BACKGROUND: Risk-stratified management of fever with neutropenia (FN), allows intensive management of high-risk cases and early discharge of low-risk cases. No single, internationally validated, prediction model of the risk of adverse outcomes exists for children and young people. An individual patient data (IPD) meta-analysis was undertaken to devise one. METHODS: The 'Predicting Infectious Complications in Children with Cancer' (PICNICC) collaboration was formed by parent representatives, international clinical and methodological experts. Univariable and multivariable analyses, using random effects logistic regression, were undertaken to derive and internally validate a risk-prediction model for outcomes of episodes of FN based on clinical and laboratory data at presentation. RESULTS: Data came from 22 different study groups from 15 countries, of 5127 episodes of FN in 3504 patients. There were 1070 episodes in 616 patients from seven studies available for multivariable analysis. Univariable analyses showed associations with microbiologically defined infection (MDI) in many items, including higher temperature, lower white cell counts and acute myeloid leukaemia, but not age. Patients with osteosarcoma/Ewings sarcoma and those with more severe mucositis were associated with a decreased risk of MDI. The predictive model included: malignancy type, temperature, clinically 'severely unwell', haemoglobin, white cell count and absolute monocyte count. It showed moderate discrimination (AUROC 0.723, 95% confidence interval 0.711-0.759) and good calibration (calibration slope 0.95). The model was robust to bootstrap and cross-validation sensitivity analyses. CONCLUSIONS: This new prediction model for risk of MDI appears accurate. It requires prospective studies assessing implementation to assist clinicians and parents/patients in individualised decision making

Predicting infectious complications in neutropenic children and young people with cancer (IPD protocol)

<p>Abstract</p> <p>Background</p> <p>A common and potentially life-threatening complication of the treatment of childhood cancer is infection, which frequently presents as fever with neutropenia. The standard management of such episodes is the extensive use of intravenous antibiotics, and though it produces excellent survival rates of over 95%, it greatly inconveniences the three-fourths of patients who do not require such aggressive treatment. There have been a number of studies which have aimed to develop risk prediction models to stratify treatment. Individual participant data (IPD) meta-analysis in therapeutic studies has been developed to improve the precision and reliability of answers to questions of treatment effect and recently have been suggested to be used to answer questions regarding prognosis and diagnosis to gain greater power from the frequently small individual studies.</p> <p>Design</p> <p>In the IPD protocol, we will collect and synthesise IPD from multiple studies and examine the outcomes of episodes of febrile neutropenia as a consequence of their treatment for malignant disease. We will develop and evaluate a risk stratification model using hierarchical regression models to stratify patients by their risk of experiencing adverse outcomes during an episode. We will also explore specific practical and methodological issues regarding adaptation of established techniques of IPD meta-analysis of interventions for use in synthesising evidence derived from IPD from multiple studies for use in predictive modelling contexts.</p> <p>Discussion</p> <p>Our aim in using this model is to define a group of individuals at low risk for febrile neutropenia who might be treated with reduced intensity or duration of antibiotic therapy and so reduce the inconvenience and cost of these episodes, as well as to define a group of patients at very high risk of complications who could be subject to more intensive therapies. The project will also help develop methods of IPD predictive modelling for use in future studies of risk prediction.</p

Challenges in developing methods for quantifying the effects of weather and climate on water-associated diseases: A systematic review

Infectious diseases attributable to unsafe water supply, sanitation and hygiene (e.g. Cholera, Leptospirosis, Giardiasis) remain an important cause of morbidity and mortality, especially in low-income countries. Climate and weather factors are known to affect the transmission and distribution of infectious diseases and statistical and mathematical modelling are continuously developing to investigate the impact of weather and climate on water-associated diseases. There have been little critical analyses of the methodological approaches. Our objective is to review and summarize statistical and modelling methods used to investigate the effects of weather and climate on infectious diseases associated with water, in order to identify limitations and knowledge gaps in developing of new methods. We conducted a systematic review of English-language papers published from 2000 to 2015. Search terms included concepts related to water-associated diseases, weather and climate, statistical, epidemiological and modelling methods. We found 102 full text papers that met our criteria and were included in the analysis. The most commonly used methods were grouped in two clusters: process-based models (PBM) and time series and spatial epidemiology (TS-SE). In general, PBM methods were employed when the bio-physical mechanism of the pathogen under study was relatively well known (e.g. Vibrio cholerae); TS-SE tended to be used when the specific environmental mechanisms were unclear (e.g. Campylobacter). Important data and methodological challenges emerged, with implications for surveillance and control of water-associated infections. The most common limitations comprised: non-inclusion of key factors (e.g. biological mechanism, demographic heterogeneity, human behavior), reporting bias, poor data quality, and collinearity in exposures. Furthermore, the methods often did not distinguish among the multiple sources of time-lags (e.g. patient physiology, reporting bias, healthcare access) between environmental drivers/exposures and disease detection. Key areas of future research include: disentangling the complex effects of weather/climate on each exposure-health outcome pathway (e.g. person-to-person vs environment-to-person), and linking weather data to individual cases longitudinally

Registered Replication Report: Dijksterhuis and van Knippenberg (1998)

Dijksterhuis and van Knippenberg (1998) reported that participants primed with a category associated with intelligence ("professor") subsequently performed 13% better on a trivia test than participants primed with a category associated with a lack of intelligence ("soccer hooligans"). In two unpublished replications of this study designed to verify the appropriate testing procedures, Dijksterhuis, van Knippenberg, and Holland observed a smaller difference between conditions (2%-3%) as well as a gender difference: Men showed the effect (9.3% and 7.6%), but women did not (0.3% and -0.3%). The procedure used in those replications served as the basis for this multilab Registered Replication Report. A total of 40 laboratories collected data for this project, and 23 of these laboratories met all inclusion criteria. Here we report the meta-analytic results for those 23 direct replications (total N = 4,493), which tested whether performance on a 30-item general-knowledge trivia task differed between these two priming conditions (results of supplementary analyses of the data from all 40 labs, N = 6,454, are also reported). We observed no overall difference in trivia performance between participants primed with the "professor" category and those primed with the "hooligan" category (0.14%) and no moderation by gender

DNA Barcode Sequence Identification Incorporating Taxonomic Hierarchy and within Taxon Variability

For DNA barcoding to succeed as a scientific endeavor an accurate and expeditious query sequence identification method is needed. Although a global multiple–sequence alignment can be generated for some barcoding markers (e.g. COI, rbcL), not all barcoding markers are as structurally conserved (e.g. matK). Thus, algorithms that depend on global multiple–sequence alignments are not universally applicable. Some sequence identification methods that use local pairwise alignments (e.g. BLAST) are unable to accurately differentiate between highly similar sequences and are not designed to cope with hierarchic phylogenetic relationships or within taxon variability. Here, I present a novel alignment–free sequence identification algorithm–BRONX–that accounts for observed within taxon variability and hierarchic relationships among taxa. BRONX identifies short variable segments and corresponding invariant flanking regions in reference sequences. These flanking regions are used to score variable regions in the query sequence without the production of a global multiple–sequence alignment. By incorporating observed within taxon variability into the scoring procedure, misidentifications arising from shared alleles/haplotypes are minimized. An explicit treatment of more inclusive terminals allows for separate identifications to be made for each taxonomic level and/or for user–defined terminals. BRONX performs better than all other methods when there is imperfect overlap between query and reference sequences (e.g. mini–barcode queries against a full–length barcode database). BRONX consistently produced better identifications at the genus–level for all query types

Cholangiocarcinoma

Exploratory laparotomy is frequently used to diagnose, treat, or palliate cholangiocarcinoma although surgery is rarely curative. In light of newly developed percutaneous and endoscopic approaches to diagnosis and therapy, we reviewed our experience with 35 cases of cholangiocarcinoma diagnosed and treated at the University of Michigan Medical Center from 1979 to 1984. Percutaneous transhepatic cholangiography (PTCA) was performed in 34 cases of which only four were resectable. All 22 patients who had preoperative cholangiograms suggesting unresectability had confirmation of this at surgery. Surgical palliation was accomplished with a combination of internal and percutaneous drainage in most cases. Angiographic, cytologic, and laboratory data are presented. PTCA accurately predicted unresectability of cholangiocarcinoma and is superior to angiography in this respect. In patients with cholangiocarcinoma, percutaneous and endoscopic approaches offer alternatives to surgery for diagnosis and palliation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/44406/1/10620_2005_Article_BF01798361.pd