Nanopartikelcharakterisierung: Untersuchung des Retentionsverhaltens in der AF-FFF und der bimodalen Größenverteilung sauer katalysierter Poly(organosiloxan)-Dispersionen

Polymere Hohlstrukturen eignen sich um eine große Anzahl an Gastmolekülen zu verkapseln und bieten somit interessante Anwendungsmöglichkeiten, z.B. im Bereich kontrollierter Transportsysteme. Solche wohl definierten Strukturen lassen sich mittels des Sol-Gel-Prozesses durch Hydrolyse und Kondensation von Dialkoxydialkyl- und Trialkoxyalkylsilanen in wässriger Dispersion in Gegenwart von Tensiden synthetisieren. Die Methode ermöglicht den Aufbau verschiedener Kern-Schale-Systeme, inklusive Hohlkugelarchitekturen, mit Durchmessern von 10-100 nm. Abhängig von den eingestellten Parametern wird dabei eine bimodale Größenverteilung der Partikel beobachtet. Die bimodalen Proben wurden mittels der circularen asymmetrischen Fluss Feld-Fluss Fraktionierung (CAFFFE) fraktioniert. NMR-Untersuchungen deuten darauf hin, dass die Ursache der bimodalen Verteilung in der Synthese der Kerndispersion zu liegen scheint. MALDI-TOF-MS und GC-Messungen zeigen, dass der Kern der größeren Partikel ausschließlich aus zyklischen Kondensationsprodukten besteht, während im Kernmaterial der kleineren Partikel zusätzlich noch lineare Polydimethylsiloxan-Ketten vorhanden sind. Unter der Annahme, dass PDMS als Ultrahydrophob wirkt, lässt sich die Ostwaldreifung als Ursache der Bimodalität ausmachen. Eine Erhöhung des PDMS-Anteils, der zur Stabilisierung gegen den Reifungsprozess notwendig ist, führt zu einer monomodalen Verteilung der erhaltenen Partikel.

A Diagnostic Test for the Mixing Distribution in a Generalised Linear Mixed Model

We introduce a diagnostic test for the mixing distribution in a generalised linear mixed model. The test is based on the difference between the marginal maximum likelihood and conditional maximum likelihood estimates of a subset of the fixed effects in the model. We derive the asymptotic variance of this difference, and propose a test statistic that has a limiting chi-square distribution under the null hypothesis that the mixing distribution is correctly specified. For the important special case of the logistic regression model with random intercepts, we evaluate via simulation the power of the test in finite samples under several alternative distributional forms for the mixing distribution. We illustrate the method by applying it to data from a clinical trial investigating the effects of hormonal contraceptives in women.

Application of well log tomography to the Dundee and Rogers City Limestones, Michigan Basin, USA

The Michigan Basin is located in the upper Midwest region of the United States and is centered geographically over the Lower Peninsula of Michigan. It is filled primarily with Paleozoic carbonates and clastics, overlying Precambrian basement rocks and covered by Pleistocene glacial drift. In Michigan, more than 46,000 wells have been drilled in the basin, many producing significant quantities of oil and gas since the 1920s in addition to providing a wealth of data for subsurface visualization. Well log tomography, formerly log-curve amplitude slicing, is a visualization method recently developed at Michigan Technological University to correlate subsurface data by utilizing the high vertical resolution of well log curves. The well log tomography method was first successfully applied to the Middle Devonian Traverse Group within the Michigan Basin using gamma ray log curves. The purpose of this study is to prepare a digital data set for the Middle Devonian Dundee and Rogers City Limestones, apply the well log tomography method to this data and from this application, interpret paleogeographic trends in the natural radioactivity. Both the Dundee and Rogers City intervals directly underlie the Traverse Group and combined are the most prolific reservoir within the Michigan Basin. Differences between this study and the Traverse Group include increased well control and “slicing” of a more uniform lithology. Gamma ray log curves for the Dundee and Rogers City Limestones were obtained from 295 vertical wells distributed over the Lower Peninsula of Michigan, converted to Log ASCII Standard files, and input into the well log tomography program. The “slicing” contour results indicate that during the formation of the Dundee and Rogers City intervals, carbonates and evaporites with low natural radioactive signatures on gamma ray logs were deposited. This contrasts the higher gamma ray amplitudes from siliciclastic deltas that cyclically entered the basin during Traverse Group deposition. Additionally, a subtle north-south, low natural radioactive trend in the center of the basin may correlate with previously published Dundee facies tracts. Prominent trends associated with the distribution of limestone and dolomite are not observed because the regional range of gamma ray values for both carbonates are equivalent in the Michigan Basin and additional log curves are needed to separate these lithologies.

Whole body postmortem angiography with a high viscosity contrast agent solution using poly ethylene glycol as contrast agent dissolver

Postmortem minimal invasive angiography has already been implemented to support virtual autopsy examinations. An experimental approach in a porcine model to overcome an initially described artificial tissue edema artifact by using a poly ethylene glycol (PEG) containing contrast agent solution showed promising results. The present publication describes the first application of PEG in a whole corpse angiographic CT examination. A minimal invasive postmortem CT angiography was performed in a human corpse utilizing the high viscosity contrast agent solution containing 65% of PEG. Injection was carried out via the femoral artery into the aortic root in simulated cardiac output conditions. Subsequent CT scanning delivered the 3D volume data of the whole corpse. Visualization of the human arterial anatomy was excellent and the contrast agent distribution was generally limited to the arterial system as intended. As exceptions an enhancement of the brain, the left ventricular myocardium and the renal cortex became obvious. This most likely represented the stage of centralization of the blood circulation at the time of death with dilatation of the precapillary arterioles within these tissues. Especially for the brain this resulted in a distinctively improved visualization of the intracerebral structures by CT. However, the general tissue edema artifact of postmortem minimal invasive angiography examinations could be distinctively reduced.

A day in the life of PubMed: analysis of a typical day's query log.

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Geographic distribution and molecular diversity of Bartonella infections in moose, Alces alces, in Finland.

Moose, Alces alces (Artiodactyla: Cervidae) in Finland are heavily infested with deer keds, Lipoptena cervi (Diptera: Hippoboschidae). The deer ked, which carries species of the genus Bartonella, has been proposed as a vector for the transmission of bartonellae to animals and humans. Previously, bartonella DNA was found in deer keds as well as in moose blood collected in Finland. We investigated the prevalence and molecular diversity of Bartonella spp. infection from blood samples collected from free-ranging moose. Given that the deer ked is not present in northernmost Finland, we also investigated whether there were geographic differences in the prevalence of bartonella infection in moose. The overall prevalence of bartonella infection was 72.9% (108/148). Geographically, the prevalence was highest in the south (90.6%) and lowest in the north (55.9%). At least two species of bartonellae were identified by multilocus sequence analysis. Based on logistic regression analysis, there was no significant association between bartonella infection and either age or sex; however, moose from outside the deer ked zone were significantly less likely to be infected (P<0.015) than were moose hunted within the deer ked zone.

Genome characterization, prevalence and distribution of a Macula-like virus from Apis mellifera and Varroa destructor

Around 14 distinct virus species-complexes have been detected in honeybees, each with one or more strains or sub-species. Here we present the initial characterization of an entirely new virus species-complex discovered in honeybee (Apis mellifera L.) and varroa mite (Varroa destructor) samples from Europe and the USA. The virus has a naturally poly-adenylated RNA genome of about 6500 nucleotides with a genome organization and sequence similar to the Tymoviridae (Tymovirales; Tymoviridae), a predominantly plant-infecting virus family. Literature and laboratory analyses indicated that the virus had not previously been described. The virus is very common in French apiaries, mirroring the results from an extensive Belgian survey, but could not be detected in equally-extensive Swedish and Norwegian bee disease surveys. The virus appears to be closely linked to varroa, with the highest prevalence found in varroa samples and a clear seasonal distribution peaking in autumn, coinciding with the natural varroa population development. Sub-genomic RNA analyses show that bees are definite hosts, while varroa is a possible host and likely vector. The tentative name of Bee Macula-like virus (BeeMLV) is therefore proposed. A second, distantly related Tymoviridae-like virus was also discovered in varroa transcriptomes, tentatively named Varroa Tymo-like virus (VTLV).

Clinical and economic outcomes of serious postoperative infections following resection of common respiratory and gastrointestinal solid tumors

Unlike infections occurring during periods of chemotherapy-induced neutropenia, postoperative infections in patients with solid malignancy remain largely understudied. The purpose of this population-based study was to evaluate the clinical and economic burden, as well as the relationship of hospital surgical volume and outcomes associated with serious postoperative infection (SPI) – i.e., bacteremia/sepsis, pneumonia, and wound infection – following resection of common solid tumors.^ From the Texas Discharge Data Research File, we identified all Texas residents who underwent resection of cancer of the lung, esophagus, stomach, pancreas, colon, or rectum between 2002 and 2006. From their billing records, we identified ICD-9 codes indicating SPI and also subsequent SPI-related readmissions occurring within 30 days of surgery. Random-effects logistic regression was used to calculate the impact of SPI on mortality, as well as the association between surgical volume and SPI, adjusting for case-mix, hospital characteristics, and clustering of multiple surgical admissions within the same patient and patients within the same hospital. Excess bed days and costs were calculated by subtracting values for patients without infections from those with infections computed using multilevel mixed-effects generalized linear model by fitting a gamma distribution to the data using log link.^ Serious postoperative infection occurred following 9.4% of the 37,582 eligible tumor resections and was independently associated with an 11-fold increase in the odds of in-hospital mortality (95% Confidence Interval [95% CI], 6.7-18.5, P < 0.001). Patients with SPI required 6.3 additional hospital days (95% CI, 6.1 - 6.5) at an incremental cost of $16,396 (95% CI, $15,927–$16,875). There was a significant trend toward lower overall rates of SPI with higher surgical volume (P=0.037). ^ Due to the substantial morbidity, mortality, and excess costs associated with SPI following solid tumor resections and given that, under current reimbursement practices, most of this heavy burden is borne by acute care providers, it is imperative for hospitals to identify more effective prophylactic measures, so that these potentially preventable infections and their associated expenditures can be averted. Additional volume-outcomes research is also needed to identify infection prevention processes that can be transferred from higher- to lower-volume providers.^

Logistic regression with incompletely observed binary

Logistic regression is one of the most important tools in the analysis of epidemiological and clinical data. Such data often contain missing values for one or more variables. Common practice is to eliminate all individuals for whom any information is missing. This deletion approach does not make efficient use of available information and often introduces bias.^ Two methods were developed to estimate logistic regression coefficients for mixed dichotomous and continuous covariates including partially observed binary covariates. The data were assumed missing at random (MAR). One method (PD) used predictive distribution as weight to calculate the average of the logistic regressions performing on all possible values of missing observations, and the second method (RS) used a variant of resampling technique. Additional seven methods were compared with these two approaches in a simulation study. They are: (1) Analysis based on only the complete cases, (2) Substituting the mean of the observed values for the missing value, (3) An imputation technique based on the proportions of observed data, (4) Regressing the partially observed covariates on the remaining continuous covariates, (5) Regressing the partially observed covariates on the remaining continuous covariates conditional on response variable, (6) Regressing the partially observed covariates on the remaining continuous covariates and response variable, and (7) EM algorithm. Both proposed methods showed smaller standard errors (s.e.) for the coefficient involving the partially observed covariate and for the other coefficients as well. However, both methods, especially PD, are computationally demanding; thus for analysis of large data sets with partially observed covariates, further refinement of these approaches is needed. ^

POLYCHOTOMOUS LOGISTIC REGRESSION ANALYSIS (HYPERTENSION, CORONARY HEART DISEASE)

The history of the logistic function since its introduction in 1838 is reviewed, and the logistic model for a polychotomous response variable is presented with a discussion of the assumptions involved in its derivation and use. Following this, the maximum likelihood estimators for the model parameters are derived along with a Newton-Raphson iterative procedure for evaluation. A rigorous mathematical derivation of the limiting distribution of the maximum likelihood estimators is then presented using a characteristic function approach. An appendix with theorems on the asymptotic normality of sample sums when the observations are not identically distributed, with proofs, supports the presentation on asymptotic properties of the maximum likelihood estimators. Finally, two applications of the model are presented using data from the Hypertension Detection and Follow-up Program, a prospective, population-based, randomized trial of treatment for hypertension. The first application compares the risk of five-year mortality from cardiovascular causes with that from noncardiovascular causes; the second application compares risk factors for fatal or nonfatal coronary heart disease with those for fatal or nonfatal stroke. ^

Venous thromboembolism in patients with acute leukemia: Prevalence, incidence, recurrence of thrombosis, risk factors, and impact on survival

Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), is the third most preventable cardiovascular disease and a growing public health problem in the United States. The incidence of VTE remains high with an annual estimate of more than 600,000 symptomatic events. DVT affects an estimated 2 million American each year with a death toll of 300,000 persons per year from DVT-related PE. Leukemia patients are at high risk for both hemorrhage and thrombosis; however, little is known about thrombosis among acute leukemia patients. The ultimate goal of this dissertation was to obtain deep understanding of thrombotic issue among acute leukemia patients. The dissertation was presented in a format of three papers. First paper mainly looked at distribution and risk factors associated with development of VTE among patients with acute leukemia prior to leukemia treatment. Second paper looked at incidence, risk factors, and impact of VTE on survival of patients with acute lymphoblastic leukemia during treatment. Third paper looked at recurrence and risk factors for VTE recurrence among acute leukemia patients with an initial episode of VTE. Descriptive statistics, Chi-squared or Fisher's exact test, median test, Mann-Whitney test, logistic regression analysis, Nonparametric Estimation Kaplan-Meier with a log-rank test or Cox model were used when appropriate. Results from analyses indicated that acute leukemia patients had a high prevalence, incidence, and recurrent rate of VTE. Prior history of VTE, obesity, older age, low platelet account, presence of Philadelphia positive ALL, use of oral contraceptives or hormone replacement therapy, presence of malignancies, and co-morbidities may place leukemia patients at an increased risk for VTE development or recurrence. Interestingly, development of VTE was not associated with a higher risk of death among hospitalized acute leukemia patients.^

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^