bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neuer Therapieansatz gegen AIDS: Fusionshemmstoffe
Authors: Holzgrabe Ulrike 
Published: January 2004

AbstractDie Behandlung HIV‐infizierter Patienten beschränkt sich im Augenblick auf den Einsatz von nukleosidischen und nicht‐nukleosidischen Reverse‐Transkriptase‐Hemmstoffen und Inhibitoren der HIV‐Protease. Da weder die Therapie noch die Prophylaxe des AIDS‐Ausbruches zufriedenstellend sind, wird nach weiteren Therapieansätzen gefahndet.
Farbenspiel im Spinnennetz: Spielwiese
Authors: Schlichting Hans Joachim 
Published: January 2004

AbstractIn Spinnennetzen kann man unter günstigen Bedingungen ein prächtiges Farbenspiel beobachten, das aus physikalischer Sicht hoch interessant ist. Wahrscheinlich hat es seine Ursache in einem Beugungseffekt an den dünnen Spinnenfäden und anschließender Interferenz.
Biegen und Brechen im Supercomputer: Duktile Verformungen und spröde Brüche von Kristallen
Authors: Buehler Markus J. , Gao Huajian 
Published: January 2004

AbstractOb sich ein Material unter Krafteinwirkung duktil verformt oder spröde bricht, hängt davon ab, wie sich in ihm Defekte ausbreiten. Um das zu untersuchen, „zerstören”︁ wir in Supercomputer‐Simulationen Nanokristalle, die bis zu einer Milliarde virtueller Atome enthalten. Die Simulationen zeigen zum Beispiel, wie sich Risse an der Grenzfläche zwischen einem härteren und einem weicheren Material ausbreiten. Sie erlauben auch nie zuvor gesehene Einblicke in die mikroskopischen Prozesse während der duktilen Verformung eines Metalls: Das kollektive Verhalten von vielen tausend Versetzungen führt zu einer Kaltverfestigung des Kristalls. Er wird spröde und bricht.
Physics on Stage III
Authors: Vollmer Michael 
Published: January 2004

AbstractVom 8. bis 15. November 2003 fand in Nordwijk, Holland, auf dem Gelände des europäischen Satelliten‐Testzentrums ESTEC zum dritten Mal das europäische Wissenschaftsfestival Physics on Stage [1] statt. Über 300 Teilnehmer aus 22 europäischen Ländern nahmen an diesem Ereignis teil.
Vom Arbeitshaus zur Supernova
Authors: Heering Peter 
Published: January 2004

AbstractIn der letzten Ausgabe stellten wir einige Arbeiten des Grafen von Rumford vor. Unter seinen vielfältigen Entwicklungen findet sich auch die Beschreibung eines der ersten Photometer. Diese Arbeiten aus dem Jahre 1792 führten letztlich zu einer Definition der Lichtstärke, die lange Zeit gebräuchlich war. Rumfords Konzept der Standardkerze findet sich heute unter anderem in der Astronomie wieder.
Auch Mesonen erfüllen Bellsche Ungleichung
Authors: Ziegler Thomas 
Published: January 2004

AbstractTeilchenphysikern bei Belle am KEKB‐Beschleuniger in Tsukuba, Japan, ist es erstmals gelungen eine Verletzung der Bellschen Ungleichung bei Elementarteilchen nachzuweisen [1]. Damit konnten sie die Vollständigkeit der Quantenmechanik erneut bestätigen.
Zeitdilatation erneut bestätigt
Authors: Saathoff Guido 
Published: January 2004

AbstractEine der weitreichendsten Konsequenzen der Speziellen Relativitätstheorie ist das Phänomen der Zeitdilatation. Diese wurde nun am Max‐Planck‐Institut für Kernphysik mit der bisher höchsten Genauigkeit gemessen [1].
Genetic association studies in Alzheimer's disease research: challenges and opportunities
Authors: Edland Steven D. , Slager Susan , Farrer Matthew 
Published: January 2004

AbstractGenetic association studies have identified important risk factors for Alzheimer's disease and other diseases. However, the ease with which these methods can be applied and the shear number of polymorphisms in the human genome has led to a well‐characterized multiple comparison problem—given the number of genetic variants being tested, it is likely that many of the positive findings reported in the literature to date will prove to be false positive findings explained simply by random fluctuation in data and type I error. The disparity of findings in initial positive reports versus subsequent negative replication studies observed in the Alzheimer's disease literature underscores this problem. The problem of a high false positive rate can be addressed in part by using statistical correction for multiple comparisons in larger and statistically more powerful samples and in meta‐analyses of smaller samples. National initiatives are now being considered to address this problem by encouraging sharing of genetic material. Of equal concern in planning future initiatives are methodological issues that are the domain of the epidemiologist. In fact, it is possible that disparate findings across case–control studies reported to date may be explained in part by problems in the design, analysis and interpretation of these studies. The involvement of epidemiologists may improve the situation in this regard. For example, population stratification bias, control selection bias and prevalent case bias can be minimized by careful study design and by appropriate statistical analysis. Regarding interpretation of case–control studies, a more careful consideration of the strength of evidence for a given genetic variant may help to temper enthusiasm for, or appropriately qualify, positive findings. Epidemiologists have well‐developed causal criteria for this purpose. This paper reviews the current state of case–control studies of genetic variants in Alzheimer's disease from the epidemiological perspective. The problem of multiple comparisons and a high false positive rate is reviewed. The potential for bias in case–control studies of Alzheimer's disease is reviewed by way of example. Future initiatives to promote case–control studies of genetic variants in Alzheimer's disease can only benefit from increased awareness the tools of epidemiology. Copyright © 2004 John Wiley & Sons, Ltd.
Family‐based association tests for survival and times‐to‐onset analysis
Authors: Lange Christoph , Blacker Deborah , Laird Nan M. 
Published: January 2004

AbstractIn this paper, we discuss family‐based association test (FBATs) relating genetic data to survival and time‐to‐onset data. We show how the standard logrank and Wilcoxon statistics can be used with family data to develop tests of association. We prove that the FBAT‐logrank approach can be identical to the proportional hazard approach discussed in Mokliatchouk et al. (2000). Further, using simulation studies, we compare the power of the logrank, Wilcoxon and an approach developed for censored exponential data (Euro J Hum Gen 2001; 9:301–306). Based on the results of the simulation study, we suggest rules of thumb about which statistics to use in a given situation. An application of all three tests to an Alzheimer study illustrates the practical relevance of our discussion. Copyright © 2004 John Wiley & Sons, Ltd.
Population‐based studies of AD: message and methods: an epidemiologic view
Authors: Launer L. J. , Brock D. B. 
Published: January 2004

AbstractDementia is a growing public health problem because the numbers suffering the disease is increasing rapidly as the population ages. Over the past decade several longitudinal population‐based studies were initiated and are still on‐going. These studies will provide valuable insight into the risk factors for, and progression of dementia. However, there are several design and statistical challenges that are unique to studying dementia in the population and that need to be addressed. These challenges include aspects of both ascertainment of disease and definition of exposure. To reduce bias from prospective epidemiologic studies, not only are new approaches to definition of disease and exposure needed, but new epidemiologic or statistical methods may be required as well. Published in 2004 by John Wiley & Sons, Ltd.
Incidence and mortality of Alzheimer's disease or dementia using an illness‐death model
Authors: Commenges D. , Joly P. , Letenneur L. , Dartigues JF. 
Published: January 2004

AbstractWe present an illness‐death model for studying the incidence and the prevalence of Alzheimer's disease or dementia. We argue that the illness‐death model is better than a survival model for this purpose. In this model the best choice for the basic time‐scale is age. Then we present extensions of this model for incorporating covariates and taking account of a possible effect of calendar time. Calendar time is introduced via a proportional intensity model. We give the likelihood for a mixed discrete‐continuous observation pattern from this model: clinical status is observed at discrete visit‐times while the date of death is observed exactly or right‐censored. The penalized likelihood approach allows to non‐parametrically estimate the transition intensities. Application on the data of the Paquid study allows to produce estimates of the age‐specific incidence of dementia together with mortality rates of both demented and non‐demented subjects. Then the effect of calendar time and educational level are studied. Low educational level increases the risk of dementia. The risk of dementia increases with calendar time while the mortality of demented subjects decreases. The most likely explanation of this result seems to be in a shift in the diagnosis of dementia towards earlier stages of the disease prompted by a change in the perception of dementia and the arrival of new drugs. Copyright © 2004 John Wiley & Sons, Ltd.
A shared random effect parameter approach for longitudinal dementia data with non‐ignorable missing data
Authors: Gao Sujuan 
Published: January 2004

AbstractA significant source of missing data in longitudinal epidemiologic studies on elderly individuals is death. It is generally believed that these missing data by death are non‐ignorable to likelihood based inference. Inference based on data only from surviving participants in the study may lead to biased results. In this paper we model both the probability of disease and the probability of death using shared random effect parameters. We also propose to use the Laplace approximation for obtaining an approximate likelihood function so that high dimensional integration over the distributions of the random effect parameters is not necessary. Parameter estimates can be obtained by maximizing the approximate log‐likelihood function. Data from a longitudinal dementia study will be used to illustrate the approach. A small simulation is conducted to compare parameter estimates from the proposed method to the ‘naive’ method where missing data is considered at random. Copyright © 2004 John Wiley & Sons, Ltd.
Adjusting for non‐ignorable verification bias in clinical studies for Alzheimer's disease
Authors: Zhou Xiao‐Hua , Castelluccio Pete 
Published: January 2004

AbstractA common problem for comparing the relative accuracy of two screening tests for Alzheimer's disease (AD) in a two‐stage design study is verification bias. If the verification bias can be assumed to be ignorable, Zhou and Higgs have proposed a maximum likelihood approach to compare the relative accuracy of screening tests in a two‐stage design study. However, if the verification mechanism also depends on the unobserved disease status, the ignorable assumption does not hold. In this paper, we discuss how to use a profile likelihood approach to compare the relative accuracy of two screening tests for AD without assuming the ignorable verification bias mechanism. Copyright © 2004 John Wiley & Sons, Ltd.
Multivariate longitudinal models for complex change processes
Authors: Beckett L. A. , Tancredi D. J. , Wilson R. S. 
Published: January 2004

AbstractLongitudinal studies offer us an opportunity to develop detailed descriptions of the process of growth and development or of the course of progression of chronic diseases. Most longitudinal analyses focus on characterizing change over time in a single outcome variable and identifying predictors of growth or decline. Both growth and degenerative diseases, however, are complex processes with multiple markers of change, so that it may be important to model more than one outcome measure and to understand their relationship over time. We consider random effects models for the association between the trajectories of two outcomes over time, and then compare their properties to approaches based on separate ordinary least‐squares estimates of change. We then illustrate with an example from the Religious Orders Study, a longitudinal cohort study of more than 900 members of Catholic religious orders who have had up to eight annual clinical examinations. Copyright © 2004 John Wiley & Sons, Ltd.
Test bias in a cognitive test: differential item functioning in the CASI
Authors: Crane Paul K. , Belle Gerald van , Larson Eric B. 
Published: January 2004

AbstractAssessment of test bias is important to establish the construct validity of tests. Assessment of differential item functioning (DIF) is an important first step in this process. DIF is present when examinees from different groups have differing probabilities of success on an item, after controlling for overall ability level. Here, we present analysis of DIF in the Cognitive Assessment Screening Instrument (CASI) using data from a large cohort study of elderly adults. We developed an ordinal logistic regression modelling technique to assess test items for DIF. Estimates of cognitive ability were obtained in two ways based on responses to CASI items: using traditional CASI scoring according to the original test instructions as well as using item response theory (IRT) scoring. Several demographic characteristics were examined for potential DIF, including ethnicity and gender (entered into the model as dichotomous variables), and years of education and age (entered as continuous variables). We found that a disappointingly large number of items had DIF with respect to at least one of these demographic variables. More items were found to have DIF with traditional CASI scoring than with IRT scoring. This study demonstrates a powerful technique for the evaluation of DIF in psychometric tests. The finding that so many CASI items had DIF suggests that previous findings of differences between groups in cognitive functioning as measured by the CASI may be due to biased test items rather than true differences between groups. The finding that IRT scoring diminished the impact of DIF is discussed. Some preliminary suggestions for how to deal with items found to have DIF in cognitive tests are made. The advantages of the DIF detection techniques we developed are discussed in relation to other techniques for the evaluation of DIF. Copyright © 2004 John Wiley & Sons, Ltd.
Reconsidering the odds ratio as a measure of 2×2 association in a population
Authors: Kraemer Helena Chmura 
Published: January 2004

AbstractThe odds ratio (OR) is probably the most widely used measure of 2×2 association in epidemiology, but it often produces results that are puzzling or misleading. Receiver operating characteristic (ROC) methods are used to take a fresh look at the OR and show where and why such puzzling results arise. When researchers choose to report a summary measure of association, the OR is one of many measures of association that might be considered, not one that should be considered the ‘gold standard’ of 2×2 measures of association. In a randomized clinical trial with binary outcome for success, either the success or failure rates in treatment and control groups might be reported separately or the number needed to treat to achieve one extra success, to emphasize the cost of unnecessary treatment needed to achieve a success. In studies assessing reliability or heritability, we recommend the intraclass kappa. In studies in which one binary variable is assessed against a binary criterion, we recommend the weighted kappa. Copyright © 2004 John Wiley & Sons, Ltd.
Selecting pre‐screening items for early intervention trials of dementia—a case study
Authors: Li Lang , Huang Jeffrey , Sun Sharon , Shen Jianzhao , Unverzagt Frederick W. , Gao Sujuan , Hendrie Hugh H. , Hall Kathleen , Hui Siu L. 
Published: January 2004

AbstractOur goal was to review and extend statistical methods for discriminating between normal subjects and those with dementia or cognitive impairment. We compared six different methods to one constructed by expert opinion, in their brevity and predictive power. The methods include logistic regression and neural networks, with standard and least absolute shrinkage and selection operator (LASSO) variable selection, as well as decision trees with and without boosting. These methods were applied to the baseline data of a subgroup of subjects in a dementia study, using their screening interview items to predict their clinical diagnosis of normal or non‐normal (cognitively impaired or demented). The derived models were then validated on a different subgroup of subjects in the same study who had the screening and clinical diagnosis two to five years later. Performance of different models was compared based on their sensitivity and specificity in the validation sample. Generally, the six statistical methods performed slightly to moderately better than the expert‐opinion model. Neural networks generally performed better than the logistic and decision tree models. LASSO improved the performance of logistic and neural network models, but it eliminated few input variables in the neural network. The single decision tree performed at least as well as the standard logistic model, and with fewer items, making it an attractive pre‐screening tool. Using the boosting option for decision trees did not substantially improve the performance. We recommend that for each situation, different methods of classification should be attempted to obtain optimal results for a given purpose. Copyright © 2004 John Wiley & Sons, Ltd.
Designing a large prevention trial: statistical issues
Authors: Kryscio Richard J. , Mendiondo Marta S. , Schmitt Frederick A. , Markesbery William R. 
Published: January 2004

AbstractRecent research in Alzheimer's disease (AD) is centred about the early detection and prevention of this disease. Several recent moderate size clinical trials targeted at high risk cohorts have been designed along this theme. There have been few attempts to design a large trial to prevent this disease in elderly individuals at low risk for the disease. The purpose of this paper is to suggest a framework for designing a simple, large AD prevention trial. This framework uses a discrete time hazard model for decreasing the incidence of AD when participants are randomly assigned to one or more active prevention agents or placebo. This design allows for differential incidence among participants due to age, family history, genetic disposition, and ethnicity. It takes into account the length of the follow‐up period, participant mortality, drop‐outs, drop‐ins, and loss to follow‐up. This framework is illustrated by PREADVISE, a recently initiated large add‐on prevention trial investigating the use of anti‐oxidants for preventing AD among men enrolled in a even larger prostate cancer prevention study, SELECT. Copyright © 2004 John Wiley & Sons, Ltd.
Analytical, practical and regulatory issues in prevention studies
Authors: Ellenberg Susan S. 
Published: January 2004

AbstractPrevention studies, as distinguished from studies investigating treatments for established disease, present some distinct challenges. Perhaps the most extensive experience with preventive agents is in the area of infectious diseases; vaccines have been extremely effective in preventing many such diseases. Vaccines have been, and continue to be, studied in other disease areas such as certain cancers, but as yet have not achieved success outside of infectious disease prevention. One obvious and important feature of prevention studies is that they enrol healthy individuals; thus such studies require particularly high standards for the safety of those enrolled (and those who might ultimately receive the product being tested). Prevention studies often need to be quite large, as the types of diseases most important to prevent tend to be uncommon. Large studies usually require simplified approaches; to ensure high quality of data on the key variables it may be necessary to compromise on the amount of data collected, frequency of data collection, and other aspects of trial design. The reliability of randomization and blinding may be especially important in these large studies, as bias could easily overwhelm the small effects that are usually sought. Often, biomarkers thought to indicate developing but as yet subclinical disease, will be important to evaluate; whether such markers can serve as primary endpoints in prevention studies has been a contentious issue in many contexts. Studies in older populations, such as those at risk for Alzheimer's Disease, raise challenges such as accounting for competing risks, and considering potential interactions of preventive agents with multiple medications often used by the elderly. Published in 2004 by John Wiley & Sons, Ltd.
The evaluation of disease modifying therapies in Alzheimer's disease: a regulatory viewpoint
Authors: Mani Ranjit B. 
Published: January 2004

AbstractSeveral drugs have received marketing approval in this country for the treatment of dementia of the Alzheimer's type. Their approval has been based on clinical trial designs that do not permit a distinction to be made between an effect of the drug on the symptoms of that disease, and an effect on the pathophysiological mechanisms that underlie that disorder. The latter effect has been referred to as ‘disease‐modifying.’In recent years there has been considerable interest in developing disease‐modifying treatments for Alzheimer's disease (AD), using either specific clinical designs, or surrogate markers, such as brain imaging modalities. This paper outlines the regulatory framework governing how the Food and Drug Administration addresses new drug claims, the current basis for approving drugs for the treatment of AD, clinical trial designs that have been proposed as a means of demonstrating disease‐modifying effects, a general and regulatory background to the use of surrogate markers in drug development, and, finally, views about the possible role of surrogate markers, especially brain imaging, as outcome measures in clinical trials intended to produce disease‐modifying effects in Alzheimer's Disease. Copyright © 2004 John Wiley & Sons, Ltd.
A comparison of classification methods for differentiating fronto‐temporal dementia from Alzheimer's disease using FDG‐PET imaging
Authors: Higdon Roger , Foster Norman L. , Koeppe Robert A. , DeCarli Charles S. , Jagust William J. , Clark Christopher M. , Barbas Nancy R. , Arnold Steven E. , Turner R. Scott , Heidebrink Judith L. , Minoshima Satoshi 
Published: January 2004

AbstractFlurodeoxyglucose positron emission tomography (FDG‐PET) is being explored to determine its ability to differentiate between a diagnosis of Alzheimer's disease (AD) and fronto‐temporal dementia (FTD). We have examined statistical discrimination procedures to help achieve this purpose and compared the results to visual ratings of FDG‐PET images. The methods are applied to a data set of 48 subjects with autopsy confirmed diagnoses of AD or FTD (these subjects come from a multi‐centre collaborative study funded by the National Alzheimer's Coordinating Center). FDG‐PET images are composed of thousands of voxels (volume elements) so one is left with a situation where there are vastly more variables than subjects. Therefore, it is necessary to perform a data reduction before a statistical procedure can be applied. Approaches using both the entire image and summary statistics calculated on a number of volumes of interest (VOI) are examined. We performed the data reduction techniques of principal components analysis (PCA) and partial least‐squares (PLS) on the entire image and then used linear discriminant analysis (LDA), quadratic (QDA) or logistic regression (LR) to classify subjects as having AD or FTD. Some of these methods achieve diagnostic accuracy (as assessed by leave‐one‐out cross‐validation) that is similar to visual ratings by expert raters. Methods using PLS appear to be more successful. Averaging or using VOI data may also be helpful. Copyright © 2004 John Wiley & Sons, Ltd.