Time-series analysis of Campylobacter incidence in Switzerland

SUMMARY Campylobacteriosis has been the most common food-associated notifiable infectious disease in Switzerland since 1995. Contact with and ingestion of raw or undercooked broilers are considered the dominant risk factors for infection. In this study, we investigated the temporal relationship between the disease incidence in humans and the prevalence of Campylobacter in broilers in Switzerland from 2008 to 2012. We use a time-series approach to describe the pattern of the disease by incorporating seasonal effects and autocorrelation. The analysis shows that prevalence of Campylobacter in broilers, with a 2-week lag, has a significant impact on disease incidence in humans. Therefore Campylobacter cases in humans can be partly explained by contagion through broiler meat. We also found a strong autoregressive effect in human illness, and a significant increase of illness during Christmas and New Year's holidays. In a final analysis, we corrected for the sampling error of prevalence in broilers and the results gave similar conclusions.

Afdeyu Research Substation: Hydrometeorological Data Analysis 1984-2007

This report presents a basic analyis of the data collected on agroclimatology, erosion, and soil and water conservation at Afdeyu Station in the central highlands of Eritrea between 1984 and 2007. Datasets and graphs include rainfall, air and soil surface temperatures, soil loss, surface runoff, river discharge, and land use including cropping patterns of the measured catchment.

Report SCRP Monitoring and Data Analysis Training Project

Report on the project activities 2003.

Post-remission treatment with allogeneic stem cell transplantation in patients aged 60 years and older with acute myeloid leukaemia: a time-dependent analysis

BACKGROUND Acute myeloid leukaemia mainly affects elderly people, with a median age at diagnosis of around 70 years. Although about 50-60% of patients enter first complete remission upon intensive induction chemotherapy, relapse remains high and overall outcomes are disappointing. Therefore, effective post-remission therapy is urgently needed. Although often no post-remission therapy is given to elderly patients, it might include chemotherapy or allogeneic haemopoietic stem cell transplantation (HSCT) following reduced-intensity conditioning. We aimed to assess the comparative value of allogeneic HSCT with other approaches, including no post-remission therapy, in patients with acute myeloid leukaemia aged 60 years and older. METHODS For this time-dependent analysis, we used the results from four successive prospective HOVON-SAKK acute myeloid leukaemia trials. Between May 3, 2001, and Feb 5, 2010, a total of 1155 patients aged 60 years and older were entered into these trials, of whom 640 obtained a first complete remission after induction chemotherapy and were included in the analysis. Post-remission therapy consisted of allogeneic HSCT following reduced-intensity conditioning (n=97), gemtuzumab ozogamicin (n=110), chemotherapy (n=44), autologous HSCT (n=23), or no further treatment (n=366). Reduced-intensity conditioning regimens consisted of fludarabine combined with 2 Gy of total body irradiation (n=71), fludarabine with busulfan (n=10), or other regimens (n=16). A time-dependent analysis was done, in which allogeneic HSCT was compared with other types of post-remission therapy. The primary endpoint of the study was 5-year overall survival for all treatment groups, analysed by a time-dependent analysis. FINDINGS 5-year overall survival was 35% (95% CI 25-44) for patients who received an allogeneic HSCT, 21% (17-26) for those who received no additional post-remission therapy, and 26% (19-33) for patients who received either additional chemotherapy or autologous HSCT. Overall survival at 5 years was strongly affected by the European LeukemiaNET acute myeloid leukaemia risk score, with patients in the favourable risk group (n=65) having better 5-year overall survival (56% [95% CI 43-67]) than those with intermediate-risk (n=131; 23% [19-27]) or adverse-risk (n=444; 13% [8-20]) acute myeloid leukaemia. Multivariable analysis with allogeneic HSCT as a time-dependent variable showed that allogeneic HSCT was associated with better 5-year overall survival (HR 0·71 [95% CI 0·53-0·95], p=0·017) compared with non-allogeneic HSCT post-remission therapies or no post-remission therapy, especially in patients with intermediate-risk (0·82 [0·58-1·15]) or adverse-risk (0.39 [0·21-0·73]) acute myeloid leukaemia. INTERPRETATION Collectively, the results from these four trials suggest that allogeneic HSCT might be the preferred treatment approach in patients 60 years of age and older with intermediate-risk and adverse-risk acute myeloid leukaemia in first complete remission, but the comparative value should ideally be shown in a prospective randomised study. FUNDING None.

Subclinical Hypothyroidism and the Risk of Stroke Events and Fatal Stroke: An Individual Participant Data Analysis

OBJECTIVE The objective was to determine the risk of stroke associated with subclinical hypothyroidism. DATA SOURCES AND STUDY SELECTION Published prospective cohort studies were identified through a systematic search through November 2013 without restrictions in several databases. Unpublished studies were identified through the Thyroid Studies Collaboration. We collected individual participant data on thyroid function and stroke outcome. Euthyroidism was defined as TSH levels of 0.45-4.49 mIU/L, and subclinical hypothyroidism was defined as TSH levels of 4.5-19.9 mIU/L with normal T4 levels. DATA EXTRACTION AND SYNTHESIS We collected individual participant data on 47 573 adults (3451 subclinical hypothyroidism) from 17 cohorts and followed up from 1972-2014 (489 192 person-years). Age- and sex-adjusted pooled hazard ratios (HRs) for participants with subclinical hypothyroidism compared to euthyroidism were 1.05 (95% confidence interval [CI], 0.91-1.21) for stroke events (combined fatal and nonfatal stroke) and 1.07 (95% CI, 0.80-1.42) for fatal stroke. Stratified by age, the HR for stroke events was 3.32 (95% CI, 1.25-8.80) for individuals aged 18-49 years. There was an increased risk of fatal stroke in the age groups 18-49 and 50-64 years, with a HR of 4.22 (95% CI, 1.08-16.55) and 2.86 (95% CI, 1.31-6.26), respectively (p trend 0.04). We found no increased risk for those 65-79 years old (HR, 1.00; 95% CI, 0.86-1.18) or ≥ 80 years old (HR, 1.31; 95% CI, 0.79-2.18). There was a pattern of increased risk of fatal stroke with higher TSH concentrations. CONCLUSIONS Although no overall effect of subclinical hypothyroidism on stroke could be demonstrated, an increased risk in subjects younger than 65 years and those with higher TSH concentrations was observed.

Time-Efficiency Analysis Comparing Digital and Conventional Workflows for Implant Crowns: A Prospective Clinical Crossover Trial

PURPOSE To compare time-efficiency in the production of implant crowns using a digital workflow versus the conventional pathway. MATERIALS AND METHODS This prospective clinical study used a crossover design that included 20 study participants receiving single-tooth replacements in posterior sites. Each patient received a customized titanium abutment plus a computer-aided design/computer-assisted manufacture (CAD/CAM) zirconia suprastructure (for those in the test group, using digital workflow) and a standardized titanium abutment plus a porcelain-fused-to-metal crown (for those in the control group, using a conventional pathway). The start of the implant prosthetic treatment was established as the baseline. Time-efficiency analysis was defined as the primary outcome, and was measured for every single clinical and laboratory work step in minutes. Statistical analysis was calculated with the Wilcoxon rank sum test. RESULTS All crowns could be provided within two clinical appointments, independent of the manufacturing process. The mean total production time, as the sum of clinical plus laboratory work steps, was significantly different. The mean ± standard deviation (SD) time was 185.4 ± 17.9 minutes for the digital workflow process and 223.0 ± 26.2 minutes for the conventional pathway (P = .0001). Therefore, digital processing for overall treatment was 16% faster. Detailed analysis for the clinical treatment revealed a significantly reduced mean ± SD chair time of 27.3 ± 3.4 minutes for the test group compared with 33.2 ± 4.9 minutes for the control group (P = .0001). Similar results were found for the mean laboratory work time, with a significant decrease of 158.1 ± 17.2 minutes for the test group vs 189.8 ± 25.3 minutes for the control group (P = .0001). CONCLUSION Only a few studies have investigated efficiency parameters of digital workflows compared with conventional pathways in implant dental medicine. This investigation shows that the digital workflow seems to be more time-efficient than the established conventional production pathway for fixed implant-supported crowns. Both clinical chair time and laboratory manufacturing steps could be effectively shortened with the digital process of intraoral scanning plus CAD/CAM technology.

Integrating sequence information in microarray data analysis by free energy modeling

Microarray technology is a high-throughput method for genotyping and gene expression profiling. Limited sensitivity and specificity are one of the essential problems for this technology. Most of existing methods of microarray data analysis have an apparent limitation for they merely deal with the numerical part of microarray data and have made little use of gene sequence information. Because it's the gene sequences that precisely define the physical objects being measured by a microarray, it is natural to make the gene sequences an essential part of the data analysis. This dissertation focused on the development of free energy models to integrate sequence information in microarray data analysis. The models were used to characterize the mechanism of hybridization on microarrays and enhance sensitivity and specificity of microarray measurements. ^ Cross-hybridization is a major obstacle factor for the sensitivity and specificity of microarray measurements. In this dissertation, we evaluated the scope of cross-hybridization problem on short-oligo microarrays. The results showed that cross hybridization on arrays is mostly caused by oligo fragments with a run of 10 to 16 nucleotides complementary to the probes. Furthermore, a free-energy based model was proposed to quantify the amount of cross-hybridization signal on each probe. This model treats cross-hybridization as an integral effect of the interactions between a probe and various off-target oligo fragments. Using public spike-in datasets, the model showed high accuracy in predicting the cross-hybridization signals on those probes whose intended targets are absent in the sample. ^ Several prospective models were proposed to improve Positional Dependent Nearest-Neighbor (PDNN) model for better quantification of gene expression and cross-hybridization. ^ The problem addressed in this dissertation is fundamental to the microarray technology. We expect that this study will help us to understand the detailed mechanism that determines sensitivity and specificity on the microarrays. Consequently, this research will have a wide impact on how microarrays are designed and how the data are interpreted. ^

Secondary data analysis of a pilot study of use of an instructional video for dietary assessment

Introduction. Food frequency questionnaires (FFQ) are used study the association between dietary intake and disease. An instructional video may potentially offer a low cost, practical method of dietary assessment training for participants thereby reducing recall bias in FFQs. There is little evidence in the literature of the effect of using instructional videos on FFQ-based intake. Objective. This analysis compared the reported energy and macronutrient intake of two groups that were randomized either to watch an instructional video before completing an FFQ or to view the same instructional video after completing the same FFQ. Methods. In the parent study, a diverse group of students, faculty and staff from Houston Community College were randomized to two groups, stratified by ethnicity, and completed an FFQ. The "video before" group watched an instructional video about completing the FFQ prior to answering the FFQ. The "video after" group watched the instructional video after completing the FFQ. The two groups were compared on mean daily energy (Kcal/day), fat (g/day), protein (g/day), carbohydrate (g/day) and fiber (g/day) intakes using descriptive statistics and one-way ANOVA. Demographic, height, and weight information was collected. Dietary intakes were adjusted for total energy intake before the comparative analysis. BMI and age were ruled out as potential confounders. Results. There were no significant differences between the two groups in mean daily dietary intakes of energy, total fat, protein, carbohydrates and fiber. However, a pattern of higher energy intake and lower fiber intake was reported in the group that viewed the instructional video before completing the FFQ compared to those who viewed the video after. Discussion. Analysis of the difference between reported intake of energy and macronutrients showed an overall pattern, albeit not statistically significant, of higher intake in the video before versus the video after group. Application of instructional videos for dietary assessment may require further research to address the validity of reported dietary intakes in those who are randomized to watch an instructional video before reporting diet compared to a control groups that does not view a video.^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

The relationship between obesity, autoimmune disease, and C-reactive protein: A secondary data analysis of the National Health and Nutrition Examination Survey (NHANES) 2009--2010

Autoimmune diseases are a group of inflammatory conditions in which the body's immune system attacks its own cells. There are over 80 diseases classified as autoimmune disorders, affecting up to 23.5 million Americans. Obesity affects 32.3% of the US adult population, and could also be considered an inflammatory condition, as indicated by the presence of chronic low-grade inflammation. C-reactive protein (CRP) is a marker of inflammation, and is associated with both adiposity and autoimmune inflammation. This study sought to determine the cross-sectional association between obesity and autoimmune diseases in a large, nationally representative population derived from NHANES 2009–10 data, and the role CRP might play in this relationship. Overall, the results determined that individuals with autoimmune disease were 2.11 times more likely to report being overweight than individuals without autoimmune disease and that CRP had a mediating affect on the obesity-autoimmune relationship. ^

DEVELOPMENT OF NOVEL METHODS TO MINIMIZE THE IMPACT OF SEQUENCING ERRORS IN THE NEXT-GENERATION SEQUENCING DATA ANALYSIS

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

Determinants of government consumption expenditure in developing countries : a panel data analysis

The paper focuses on the recent pattern of government consumption expenditure in developing countries and estimates the determinants which have influenced government expenditure. Using a panel data set for 111 developing countries from 1984 to 2004, this study finds evidence that political and institutional variables as well as governance variables significantly influence government expenditure. Among other results, the paper finds new evidence of Wagner's law which states that peoples' demand for service and willingness to pay is income-elastic hence the expansion of public economy is influenced by the greater economic affluence of a nation (Cameron1978). Corruption is found to be influential in explaining the public expenditure of developing countries. On the contrary, size of the economy and fractionalization are found to have significant negative association with government expenditure. In addition, the study finds evidence that public expenditure significantly shrinks under military dictatorship compared with other form of governance.

Optimal fits of diffusion constants from single-time data points of Brownian trajectories

Experimental methods based on single particle tracking (SPT) are being increasingly employed in the physical and biological sciences, where nanoscale objects are visualized with high temporal and spatial resolution. SPT can probe interactions between a particle and its environment but the price to be paid is the absence of ensemble averaging and a consequent lack of statistics. Here we address the benchmark question of how to accurately extract the diffusion constant of one single Brownian trajectory. We analyze a class of estimators based on weighted functionals of the square displacement. For a certain choice of the weight function these functionals provide the true ensemble averaged diffusion coefficient, with a precision that increases with the trajectory resolution.

Time-motion analysis on Chinese male field hockey players

The aim of the study was to evaluate the match work-rate of Chinese field hockey players by analyzing the distance covered at different intensities pooled by specific positions during different periods of matches. Thirty-eight players from twenty-four male field hockey matches at the 11th Chinese National Games were filmed and analyzed.

Time-motion analysis on Chinese male field hockey players

The aim of the study was to evaluate the match work-rate of Chinese field hockey players by analyzing the distance covered at different intensities pooled by specific positions during different periods of matches. Thirty-eight players from twenty-four male field hockey matches at the 11th Chinese National Games were filmed and analyzed.mas