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At least 973 records · Page 54Linked to original sources
PubMed1983

Stopped-flow solution scattering using synchrotron radiation: apparatus, data collection and data analysis.

We have constructed an experimental system, under remote control, for stopped-flow X-ray scattering using synchrotron radiation. It has been used, in conjunction with an annular detector and its associated electronics, to obtain good scattering curves, with time-slices as short as 200 ms, in a new study of the dissociation of the enzyme complex aspartate transcarbamylase. The data have been analysed by new statistical methods, and they agree well with the results from parallel chemical quench experiments. For studying dissociation reactions, stopped-flow X-ray scattering is a quite practical method, which need not use very much more material than conventional stopped-flow experiments.

Aspartate Carbamoyltransferase↗
PubMed2004

Detection and detrending in fMRI data analysis.

This article addresses the impact that colored noise, temporal filtering, and temporal detrending have on the fMRI analysis situation. Specifically, it is shown why the detection of event-related designs benefit more from pre-whitening than blocked designs in a colored noise structure. Both theoretical and empirical results are provided. Furthermore, a novel exploratory method for producing drift models that efficiently capture trends and drifts in the fMRI data is introduced. A comparison to currently employed detrending approaches is presented. It is shown that the novel exploratory model is able to remove a major part of the slowly varying drifts that are abundant in fMRI data. The value of such a model lies in its ability to remove drift components that otherwise would have contributed to a colored noise structure in the voxel time series.

Brain↗
PubMed2001

Users' demands regarding dental safety glasses. Combining a quantitative approach and grounded theory for the data analysis.

Eye infections are common among dentists and many are concerned, but few are using proper eye protection. To understand users' demands behind the low use of safety glasses, all dental teams in Sweden were asked which factors they found most important when choosing dental safety glasses, and rate the importance of 31 statements regarding ergonomic aspects of dental safety glasses in a questionnaire. Data were analysed using the Grounded Theory and a quantitative approach. Results showed that dentists ranked the visual aspects as most important and chair assistants the protective aspects. The highly visual demanding work performed by dentists requires safety glasses that are not yet available on the market, which might explain the low use.

Attitude of Health Personnel↗
PubMed1998

Methods for spherical data analysis and visualization.

A systematic analysis of the localization of objects in extra-personal space requires a three-dimensional method of documenting location. In auditory localization studies the location of a sound source is often reduced to a directional vector with constant magnitude with respect to the observer, data being plotted on a unit sphere with the observer at the origin. This is an attractive form of data representation as the relevant spherical statistical and graphical methods are well described. In this paper we collect together a set of spherical plotting and statistical procedures to visualize and summarize these data. We describe methods for visualizing auditory localization data without assuming that the principal components of the data are aligned with the coordinate system. As a means of comparing experimental techniques and having a common set of data for the verification of spherical statistics, the software (implemented in MATLAB) and database described in this paper have been placed in the public domain. Although originally intended for the visualization and summarization of auditory psychophysical data, these routines are sufficiently general to be applied in other situations involving spherical data.

Animals↗
PubMed2005

Delay Fokker-Planck equations, perturbation theory, and data analysis for nonlinear stochastic systems with time delays.

We study nonlinear stochastic systems with time-delayed feedback using the concept of delay Fokker-Planck equations introduced by Guillouzic, L'Heureux, and Longtin. We derive an analytical expression for stationary distributions using first-order perturbation theory. We demonstrate how to determine drift functions and noise amplitudes of this kind of systems from experimental data. In addition, we show that the Fokker-Planck perspective for stochastic systems with time delays is consistent with the so-called extended phase-space approach to time-delayed systems.

Journal Article↗
PubMed2006

Genetic associations in preterm birth: a primer of marker selection, study design, and data analysis.

Spontaneous preterm birth (PTB; delivery before 37 weeks gestation) is a primary risk factor for infant morbidity and mortality. The etiology is unclear, but there is evidence that there is a genetic predisposition to PTB. Armed with the suggestion of genetic risk factors and the failure to identify useful biomarkers, investigators are starting to actively pursue the role of genetic predisposition in PTB. Several studies have been done to date assessing the role of single gene variants. However, positive findings have failed to replicate. We argue that heterogeneity in study designs, definition of phenotype, single-nucleotide polymorphism (SNP) selection, population selection, and sample size makes data interpretation difficult in complex phenotypes such as PTB. In this review, we introduce general concepts of study designs in genetic epidemiology, selection of candidate genes and markers for analysis, and analytical methodologies. We also introduce how the concept of gene-gene interactions (biologic epistasis) and gene-environment interactions may affect the predisposition to PTB.

Female↗
PubMed1999

Crystallization and x-ray diffraction data analysis of human deoxyhaemoglobin A(0) fully stripped of any anions.

In this work, initial crystallographic studies of human haemoglobin (Hb) crystallized in isoionic and oxygen-free PEG solution are presented. Under these conditions, functional measurements of the O(2)-linked binding of water molecules and release of protons have evidenced that Hb assumes an unforeseen new allosteric conformation. The determination of the high-resolution structure of the crystal of human deoxy-Hb fully stripped of anions may provide a structural explanation for the role of anions in the allosteric properties of Hb and, particularly, for the influence of chloride on the Bohr effect, the mechanism by which Hb oxygen affinity is regulated by pH. X-ray diffraction data were collected to 1.87 A resolution using a synchrotron-radiation source. Crystals belong to the space group P2(1)2(1)2 and preliminary analysis revealed the presence of one tetramer in the asymmetric unit. The structure is currently being refined using maximum-likelihood protocols.

Allosteric Regulation↗
PubMed2006

Simulated data sets for single molecule kinetics: some limitations and complications of data analysis.

When the fluorescence intensity of a chromophore attached to or bound in an enzyme relates to a specific reactive step in the enzymatic reaction, a single molecule fluorescence study of the process reveals a time sequence in the fluorescence emission that can be analyzed to derive kinetic and mechanistic information. Reports of various experimental results and corresponding theoretical studies have provided a basis for interpreting these data and understanding the methodology. We have found it useful to parallel experiments with Monte Carlo simulations of potential models hypothesized to describe the reaction kinetics. The simulations can be adapted to include experimental limitations, such as limited data sets, and complexities such as dynamic disorder, where reaction rates appear to change over time. By using models that are known a priori, the simulations reveal some of the challenges of interpreting finite single-molecule data sets by employing various statistical signatures that have been identified.

Data Interpretation, Statistical↗
PubMed1998

Predicting the radiation control probability of heterogeneous tumour ensembles: data analysis and parameter estimation using a closed-form expression.

A closed-form formula describing the tumour control probability (tcp) of a heterogeneous collection of tumours has been obtained by analytically averaging the homogeneous double-exponential tcp formula over inter-tumour distributions of clonogen radiosensitivity, density and repopulation rate, tumour volume and dose. The formula can be straightforwardly and relatively quickly fitted to clinical data, yielding radiobiological parameter values for use in tcp modelling. The formula was fitted to published tcp data which catalogued tumour control records grouped by dose and tumour volume, and treatment duration. Fitted parameter values, confidence intervals and goodness-of-fit statistics were determined. The sets of parameter values obtained are unique only to within a scaling factor. The formula provides non-rejectable fits to data which grouped tcp by dose and volume when radiosensitivity parameters take values close to laboratory estimates, the fitted volume dependence parameter, however, taking rather high values. Good fits are obtainable with the intuitively reasonable volume parameter value of one, but with radiosensitivity values around one-third of their laboratory estimates. Non-rejectable fits to data which grouped tcp by dose and treatment duration may be obtained with radiosensitivity and repopulation rate parameters lying close to laboratory estimates.

Breast Neoplasms↗
PubMedDate not supplied

Statistical approaches to experimental design and data analysis of in vivo studies.

The objective of any experiment is to obtain an unbiased and precise estimate of a treatment effect in an efficient manner. Statistical aspects of the design, conduct, and analysis of the experiment play a major role in determining whether this goal is met. We highlight some of the more important statistical issues that pertain to in vivo studies. Particular emphasis is placed on the role of randomization, the number of animals, the utilization of repeated measures data, adjustments for missing data, and dealing with multiple causes of death or treatment failure. The discussion is not intended to be a comprehensive guide to all the statistical issues that can occur in animal experiments. Rather, the objective is to acquaint researchers with components of the experiment that will require careful statistical thought.

Animals↗
PubMed2003

An algorithm for three-way data analysis that alternatively minimizes coupled vector (COV) resolution error and PARAFAC error.

A novel algorithm, alternatively minimizing coupled vector (COV) resolution error and PARAFAC error algorithm, is proposed in this paper. This algorithm can overcome the problem of slow convergence and is insensitive to the estimation of component number, such problems are unavoidable while using the traditional parallel factors analysis (PARAFAC) algorithm. In other words, this algorithm is capable of improving the computing speed and providing accurate resolutions provided that the number of factors used in the computation is no less than that of the actual underlying ones. The characteristic performances were demonstrated with a novel fluorescence data array.

Journal Article↗
PubMedDate not supplied

Comparison of alternative modelling techniques in estimating short-term effect of air pollution with application to the Italian meta-analysis data (MISA Study).

In 2002, serious criticism was raised about the use of standard statistical software (Splus, SAS, Stata) to fit Generalized Additive Models (GAM) to epidemiological time series data. This criticism concerns convergence problems of the backfitting algorithm and inappropriate use of a linear approximation in estimating standard errors of estimates for parametric terms, such as the effect of air pollution. Here we analysed the association between PM10 and Mortality/Hospital Admissions in the Italian Meta-analysis of Short-term effects of Air pollutants (MISA) using two alternative approaches that are not affected by the same drawbacks: GAM with penalized regression spline fitted by the direct method in R (GAM-R) software and Generalized Linear Models with natural cubic spline (GLM+NS). A sensitivity analysis is also provided varying number of degrees of freedom for the seasonality spline and modality of adjustment for confounding effect of temperature. Published theoretical results and a simulation study are provided in order to explain discrepancies between GLM+NS and GAM-R estimates. We conclude that in general the fully parametric GLM+NS approach retains better statistical properties than GAM-R that could bring to biased air pollution effect estimates unless a certain degree of under-smoothing for seasonality spline is settled.

Air Pollution↗
PubMed1999

Assessment of the quality and quantity of drug-drug interaction studies in recent NDA submissions: study design and data analysis issues.

This report investigates the quality and quantity of drug-drug interaction studies in recent new drug applications (NDAs). Eighty-nine studies contained in 14 NDAs submitted between December 1995 and November 1996 to the U.S. Food and Drug Administration (FDA) were reviewed. The results indicated that the median number of clinical drug-drug interaction studies per NDA was 6, almost double that of a 1994-1995 survey. In vitro metabolism data were present in 70% of the submissions. More than 50% of the submissions contained interaction studies using a battery of drugs (cimetidine, digoxin, or warfarin) without optimal use of the in vitro metabolism or in vivo mass balance data. Various study designs using a median number of 12 subjects were employed in the evaluation of drug-drug interactions. Some of the important study design factors such as dose size, dosing regimen, dosing duration, and timing of coadministration were considered, although not consistently, by the sponsors in their study design. Seventy-five percent of the studies used normal, healthy male subjects, and 25% used patients for whom the new molecular entities were intended. In 33% of the studies, female subjects were also recruited. Although the majority (80%) of the submissions still used p-values to determine the significance of drug interactions, 30% used a more relevant equivalence approach with 90% confidence intervals for key pharmacokinetic and/or pharmacodynamic parameter ratios to assess the extent of drug interactions. Overall, 82% of the studies concluded no interaction. Although population pharmacokinetic analysis can be a useful tool in studying drug-drug interactions, only 21% of the submissions used this approach. In summary, this assessment reveals that the quantity and quality of drug-drug interaction studies in NDAs have improved over the years. These improvements, as well as others that can be implemented, should result in more informative labeling and better patient care. FDA guidance for industry dealing with the design, analysis, and labeling language of in vivo metabolic drug-drug interactions has been developed to assist sponsors and FDA reviewers with these issues.

Clinical Trials as Topic↗
PubMed2025

Uncertainty Modeling Outperforms Machine Learning for Microbiome Data Analysis.

Microbiome sequencing measures relative rather than absolute abundances, providing no direct information about total microbial load. Normalization methods attempt to compensate, but rely on strong, often untestable assumptions that can bias inference. Experimental measurements of load (e.g., qPCR, flow cytometry) offer a solution, but remain costly and uncommon. A recent high-profile study proposed that machine learning could bypass this limitation by predicting microbial load from sequencing data alone. To evaluate this claim, we assembled mutt, the largest public database of paired sequencing and load measurements, spanning 35 studies and over 15,000 samples. Using mutt, we show that published machine learning models fail to generalize: on average they perform worse than a naive baseline that always predicted the training set mean. These failures stem from covariate shift-limited shared taxa between studies, differences in community composition, and differences in preprocessing pipelines-that silently derail model inputs. In contrast, Bayesian partially identified models do not attempt to impute microbial load, but instead propagate scale uncertainty through downstream analyses. Across 30 benchmark datasets, Bayesian partially identified models consistently outperformed normalization and machine learning approaches, providing a principled and reproducible foundation for microbiome inference.

16S rRNA-seq↗
PubMed1986

Vitreous fluorophotometer data analysis by deconvolution.

The measurement process in fluorophotometry inherently involves a loss of information due to the finite sampling volume of the instrument. Mathematically, the effect is expressed as a convolution of the actual fluorescein distribution with the spread function of the instrument. Scattering by the ocular media can increase the spread function over that due to the instrument alone. A method is proposed for deconvolution of vitreous fluorophotometry data. Simulation studies and analyses of patient data demonstrate recovery of information with this method, including enhancement of retinal peaks and resolution of detail in the posterior vitreous which was not apparent from the original scans.

Data Display↗
PubMed1996

[Prevalence and distribution of stroke and transient ischemic insults: secondary data analysis of a representative sample of insured members of the General Local Insurance Dortmund].

Apoplexia is not only one of the leading causes of death, but also a major contributor to disability in the aged. Population based prevalence rates, though being of basic importance for describing and planning health care structures, are sparse in the Federal Republic of Germany. We estimated the prevalence of apoplexia and transient ischemic attack (TIA). Data were gathered from a 5% representative random sample of insured of the local statuatory health insurance (AOK) in Dortmund, Germany (n = 7447). Cases were identified by the diagnosis on medical certificates, being further validated internally by other patient data. The rough prevalence rate was 0.86% (m 0.79%, f 0.93%) for apoplexia and 0.6% (m 0.4%, f 0.78%) for TIA. Adjusted for age and sex to the whole population of the FRG (excluding the former German Democratic Republic) the prevalence rate was 0.75% (m 0.8%, f 0.7%) for apoplexia and 0.52% (m 0.41%, f 0.63%) for TIA. 65% of the insured with apoplexia were 70 years and older; their average age was 71.7 years. The average age of the insured with TIA was 65.4 years. Prevalence rates for apoplexia increased continuously by age and were higher for men than for women in all age groups. Prevalence rates for TIA also increased with age, but under men only to the age of 70; after that-simultaneous to a steep rise of apoplexia prevalence-no more TIAs were noticed.

Adult↗
PubMed1994

Potential for bias in severity adjusted hospital outcomes data: analysis of patients with rheumatic disease.

OBJECTIVE: To examine the predictive validity of MedisGroups, a widely used method of measuring severity of illness, among patients with rheumatic disease and identify determinants of hospital outcomes, after adjusting for severity of illness. METHODS: Adult medical and surgical patients with rheumatic disease (5421) admitted to an academic medical center in 1988-90 were studied using a retrospective cohort design. Sociodemographic, clinical, and financial data were obtained from computerized hospital information systems. Severity of illness on admission was determined for each patient using MedisGroups, which classifies patients into groups of increasing severity. RESULTS: MedisGroups admission severity groups were highly related (p < 0.001) to inhospital mortality rates, which were 0.4, 0.8, 5.1 and 16.1%, respectively among patients in 4 groups of increasing severity. Controlling for MedisGroups admission severity using logistic regression, age, admission from the emergency room, and transfer from an acute care hospital were found to be additional independent predictors of mortality. MedisGroups severity groups were also directly related (p < 0.001) to length of stay and total hospital charges. Controlling for admission severity using linear regression, length of stay, and charges were independently related to several other variables; for example, length of stay was greater for patients admitted from the emergency room or transferred from other hospitals and for nonwhites, women, and older patients. Finally, within common individual diagnoses, these factors substantially increased the amount of variance in length of stay and charges explained by MedisGroups alone. CONCLUSIONS: Our findings demonstrate that after adjusting for severity of illness using MedisGroups, several other easily measured variables were associated with hospital outcomes in patients with rheumatic disease. Thus, generic severity systems, such as MedisGroups, may not adequately adjust outcomes among patients with rheumatic disease. Comparative hospital data based on these systems may be subject to bias.

Adult↗
PubMed1994

Corticotropin-releasing factor receptors in human small cell lung carcinoma cells: radioligand binding, second messenger, and northern blot analysis data.

Numerous peptides, growth factors, and receptors have been identified in small cell lung carcinoma (SCLC) cells. The present study was designed to examine the radioligand binding, second messenger, and messenger RNA (mRNA) characteristics of CRF receptors in a variety of SCLC lines and to compare their characteristics to CRF receptors in the mouse pituitary tumor AtT-20 cells. The human SCLC cell lines NCI-H69, H82, H146, H209, H345, H446, and H510A and control AtT-20 cells all demonstrated specific [125I]Tyr(o)-ovine CRF ([125I]oCRF) binding, which was linear with increasing protein concentrations, saturable, reversible, and of high affinity. NCI-H82 cells showed the highest level of specific [125I]oCRF binding (approximately 60% of the total binding). Scatchard analysis revealed a single homogeneous class of binding sites in NCI-H82 and AtT-20 cells, with Kd values of 263 +/- 48 and 285 +/- 75 pM, respectively, and binding capacities of 74 +/- 7 and 70 +/- 13 fmol/mg protein, respectively. [125I]oCRF-binding sites on NCI-H82 and AtT-20 cells had comparable pharmacological characteristics with the following rank order of inhibitory potencies: rat/human CRF approximately ovine CRF approximately bovine CRF > alpha-helical oCRF-(9-41) > bovine CRF-(1-41)OH >> vasoactive intestinal peptide, secretin, GH-releasing hormone. [125I]oCRF binding in the cell lines was inhibited by guanine nucleotides, suggesting a coupling of receptors to guanine nucleotide-binding proteins. The functional nature of the CRF receptor was demonstrated in second messenger studies in which rat/human CRF stimulated cAMP production in NCI-H82 and AtT-20 cells with comparable EC50 values of about 3 nM; the percent stimulation over basal activity was significantly higher in NCI-H82 cells (approximately 30-fold increase) than in AtT-20 cells (approximately 12-fold increase). Northern blot analysis of total RNA revealed the presence of a 2.6-kilobase mRNA band in NCI-H82 cells corresponding to the recently cloned human CRF receptor. In summary, the data demonstrate the presence of CRF receptors in SCLC cell lines with kinetic, pharmacological, second messenger, and mRNA characteristics comparable to those in pituitary and brain and suggest a possible role for CRF as a regulatory peptide in human SCLC.

Adenylyl Cyclases↗