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PubMed2005

Input parameter sensitivity analysis and comparison of quantification models for continuous arterial spin labeling.

The regional cerebral blood flow (rCBF) values determined using continuous arterial spin labeling (CASL) are subject to several sources of variability, including natural physiologic variations, sensitivity to the input parameters, and the use of different quantification models. To date, a thorough analysis of the impact of input parameters and the choice of quantification model has not been performed. These sources of variability were investigated through computer simulations using bootstrap techniques on actual CASL data. Coefficients of variation for representative single voxels were 6.7% for gray matter and 29% for white matter, and for eight-voxel regions of interest they were 4.5% for gray matter and 23% for white matter. Comparison of nine CASL quantification models showed differences in gray matter rCBF values of up to 42%. An analysis of the sensitivity of the rCBF to input parameters for each of the nine quantification models demonstrated that accurate quantification of the inversion efficiency, tissue and arterial blood longitudinal relaxation times, and transit times were critical in calculating precise rCBF values. The large potential variations in rCBF and the effect of the choice of quantification model suggest that interpreting absolute rCBF values in CASL studies can be challenging and requires great care.

Adult↗

PubMed2005

PASTA: pointwise assessment of streamline tractography attributes.

Diffusion tensor MRI tractography aims to reconstruct noninvasively the 3D trajectories of white matter fasciculi within the brain, providing neuroscientists and clinicians with a potentially useful tool for mapping brain architecture. While this technique is widely used to visualize white matter pathways, the associated uncertainty in fiber orientation and artifacts have, to date, not been visualized in conjunction with the trajectory data. In this work, the bootstrap method was used to determine the distributions of diffusion indices such as trace and anisotropy, together with the uncertainty in fiber orientation. A novel visualization scheme was developed to encode this information at each point along reconstructed trajectories. By integrating these schemes into a graphical user interface, a new tool which we call PASTA (Pointwise Assessment of Streamline Tractography Attributes) was created to facilitate identification of artifacts in tractography that would otherwise go undetected.

Brain Mapping↗

PubMed2006

Precision in measurements of perfusion and microvascular permeability with T1-weighted dynamic contrast-enhanced MRI.

Dynamic contrast-enhanced MRI is used to estimate microvascular parameters by tracer kinetics analysis. The time for the contrast agent to travel from the artery to the tissue of interest (bolus arrival time (BAT)) is an important parameter that must be measured in such studies because inaccurate estimates or neglect of BAT contribute to inaccuracy in model fitting. Furthermore, although the precision with which these parameters are estimated is very important, it is rarely reported. To address these issues, two investigations were undertaken. First, simulated data were used to validate an independent method for estimation of BAT. Second, the adiabatic approximation to the tissue homogeneity model was fitted to experimental data acquired in prostate and muscle tissue of 22 patients with prostate cancer. A bootstrap error analysis was performed to estimate the precision of parameter estimates. The independent method of estimating BAT was found to be more accurate and precise than a model-fitting approach. Estimated precisions for parameters measured in the prostate gland were 14% for extraction fraction (median coefficient of variation), 19% for blood flow, 28% for permeability-surface area product, 35% for volume of the extravascular-extracellular space, and 36% for blood volume. Techniques to further reduce uncertainty are discussed.

Algorithms↗

PubMed2007

Variance of estimated DTI-derived parameters via first-order perturbation methods.

In typical applications of diffusion tensor imaging (DTI), DT-derived quantities are used to make a diagnostic, therapeutic, or scientific determination. In such cases it is essential to characterize the variability of these tensor-derived quantities. Parametric and empirical methods have been proposed to estimate the variance of the estimated DT, and quantities derived from it. However, the former method cannot be generalized since a parametric distribution cannot be found for all DT-derived quantities. Although powerful empirical methods, such as the bootstrap, are available, they require oversampling of the diffusion-weighted imaging (DWI) data. Statistical perturbation methods represent a hybrid between parametric and empirical approaches, and can overcome the primary limitations of both methods. In this study we used a first-order perturbation method to obtain analytic expressions for the variance of DT-derived quantities, such as the trace, fractional anisotropy (FA), eigenvalues, and eigenvectors, for a given experimental design. We performed Monte Carlo (MC) simulations of DTI experiments to test and validate these formulae, and to determine their range of applicability for different experimental design parameters, including the signal-to-noise ratio (SNR), diffusion gradient sampling scheme, and number of DWI acquisitions. This information should be useful for designing DTI studies and assessing the quality of inferences drawn from them.

Algorithms↗

PubMed2001

Variability of frequency and phase between antagonistic muscle pairs in pathological human tremors.

We investigated the electromyographic activity (EMG) of flexor and extensor muscles with different hand positions in patients with essential (ET) and parkinsonian (PD) tremor. Using a previously developed bootstrap method and standard cross-spectral analysis, we performed statistical tests to assess the effect of hand position on: (1) the frequency of the EMG; and (2) the phase between the EMGs recorded from antagonistic muscle pairs. Frequency as well as phases changed significantly with different positions of the hands but not during the recordings when the position was left unchanged. Besides confirmation that frequency and phase are stationary and reliable parameters during short-term recordings under controlled laboratory conditions, these results are of particular interest for ambulatory long-term tremor measurements. A higher variability of the estimated parameters reported in long-term recordings may perhaps reflect a patient's mobility only. Our study shows that long-term recording systems should have the means to monitor the patient's movements to provide reliable results.

Diagnosis, Differential↗

PubMed2005

Sural and radial sensory responses in healthy adults: diagnostic implications for polyneuropathy.

We prospectively performed sural and radial sensory nerve conduction studies in 92 healthy subjects, aged between 21 and 88 years, both to determine the lower limits of normal (LLN) and to assess the effects of age and body mass index (BMI) on the sural and radial sensory nerve action potential (SNAP) amplitudes and on the sural/radial amplitude ratio (SRAR). Using the nonparametric bootstrap method to calculate 95% confidence intervals, we found that the 5% LLN values for sural and radial SNAPs were 14 microV and 25.5 microV in subjects aged < or =39 years, 7 microV and 17.4 microV in subjects aged 40-59 years, and 3 microV and 12 microV in subjects aged > or =60 years. The 5% LLN for SRAR for all patients was 0.21. Sural and radial SNAP amplitudes but not SRAR were strongly and inversely correlated with age and BMI. These age-adjusted normal values and revised SRAR will aid in the electrodiagnosis of polyneuropathy.

Adult↗

PubMed2026

Associations of Illness Perception, Resignation Coping, and Social Support With Self-Regulatory Fatigue in Patients With Type 2 Diabetes: A Cross-Sectional Study.

AIMS: To examine the associations among illness perception, resignation coping, social support, and self-regulatory fatigue (SRF) in patients with Type 2 diabetes mellitus. The study specifically explores whether resignation coping and social support exhibit indirect associations with SRF in the context of illness perception. DESIGN: A cross-sectional study. METHODS: From November 2024 to October 2025, a convenience sample of 302 adult patients with T2DM was recruited from a tertiary general hospital in China. Participants completed validated instruments with established psychometric properties, namely the Brief Illness Perception Questionnaire, the Medical Coping Modes Questionnaire, the Perceived Social Support Scale, and the Self-Regulatory Fatigue Scale. Statistical analyses included Spearman correlation and serial mediation analysis using the PROCESS Macro (Model 6) with bias-corrected bootstrapping. RESULTS: SRF was positively correlated with negative illness perception (r = 0.579, p < 0.01) and resignation coping (r = 0.612, p < 0.01), and negatively correlated with social support (r = -0.598, p < 0.01). Serial mediation analysis revealed that illness perception was associated with SRF through indirect pathways involving resignation coping and social support. Resignation coping and social support mediated the association between illness perception and self-regulatory fatigue, both individually and sequentially. CONCLUSIONS: Negative illness perception correlates with higher SRF. This observed correlation is additionally linked to indirect pathways involving resignation coping and lower social support. Collectively, these findings highlight a pattern of interrelated cognitive (illness perception), behavioural (resignation coping), and resource (social support) factors that are associated with self-regulatory fatigue in this cross-sectional study. IMPLICATIONS FOR THE PROFESSION: The findings offer a clear, evidence-based framework for nursing practice. They highlight the potential value of integrated assessment and intervention that simultaneously addresses patients' illness beliefs, maladaptive coping strategies, and social support systems, which are associated with lower SRF and better diabetes self-management. REPORTING METHOD: This study adheres to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies. PATIENT OR PUBLIC CONTRIBUTION: Patients participated solely as research participants by providing survey data. They were not involved in the study design, implementation, data analysis, interpretation, or manuscript preparation. All patients provided written informed consent prior to questionnaire completion.

Humans↗

PubMed2026

Associations Between Short Video Exposure, Empathy and Attitudes Toward End-Of-Life Care Among Nursing Students: A Cross-Sectional Study.

AIM: This cross-sectional study examined the associations between short video exposure, nursing students' empathy, and attitudes toward end-of-life (EOL) care, and tested whether perceived impact is statistically consistent with an indirect pathway in these relationships. DESIGN: A descriptive cross-sectional study. METHODS: In total, 534 undergraduate nursing students were included. Data were collected using a self-designed questionnaire, including the Attitudes Toward Care of the Dying Scale and the Jefferson Scale of Empathy-Health Professions Student version for empathy assessment. Statistical analysis for correlation and mediation analysis (PROCESS macro) was performed. RESULTS: 85.96% of students watch short videos for more than 30 min daily, with more than 60% of them viewing EOL-related content. Students with prior caregiving experience or formal palliative care education showed significantly higher empathy and more positive attitudes (p < 0.05). Exposure to medical and EOL-related short videos was positively correlated with perceived impact, empathy, and positive EOL attitudes, with effect sizes ranging from very weak to modest (r = 0.10 to 0.27). The data were consistent with an indirect pathway between short video exposure and empathy via perceived impact (indirect effect = 0.04; 95% bootstrap CI [0.01, 0.08]). However, for EOL attitudes, short video exposure showed a direct association rather than an indirect pathway via perceived impact (direct effect = 0.09, p < 0.01). CONCLUSION: In this cross-sectional study, short video exposure was modestly associated with nursing students' empathy, with data consistent with an indirect pathway via perceived impact; the observed associations explained only approximately 1% to 7% of the variance in the outcome variables. However, reshaping EOL attitudes may require more systematic education beyond brief video exposure. These findings are hypothesis-generating and await validation through longitudinal and experimental research using standardized video content. IMPLICATIONS FOR NURSING PRACTICE: Nursing educators should consider integrating curated short video content into palliative care curricula to enhance students' empathy and perceived impact of end-of-life education. However, brief video exposure alone may be insufficient to reshape deeper end-of-life attitudes, suggesting the need for comprehensive, multi-modal educational strategies.

Humans↗

PubMedDate not supplied

A claims data approach to defining an episode of care.

OBJECTIVE: To utilize health services research techniques in developing an episode of care using an administrative data set. This method is demonstrated for an episodic clinical condition, migraine. DATA SOURCES: Medicaid administrative data set of 3,372 patients with a diagnosis of migraine (ICD-9-CM 346.0, 346.1) in the state of Pennsylvania between May 1990 and March 1992. STUDY DESIGN: The duration of a migraine episode was measured by assessing the magnitude of resource utilization and the proportion of patients with charges in the period after the index migraine as compared to the period before the index migraine. A confidence interval (CI) was developed around each measure using bootstrap techniques. DATA COLLECTION METHODS: All charge data were extracted daily for a 113-day observation period surrounding each index migraine in order to observe the duration of impact of a migraine diagnosis on resource utilization. PRINCIPAL FINDINGS: The lower limits of both the 95% and 99% CIs for the difference in charges are greater than 0 for three weeks. The lower limits of both CIs for the difference in the proportion of patients with charges are above 0 for six weeks. CONCLUSIONS: Our analysis demonstrates that a health services research framework can be used to define an episode of care for a chronic disease category such as migraine. This method can be used to evaluate episodes of care for clinical studies of limited or episodic conditions and to complement clinical expertise in developing time horizons for clinical trials.

Adult↗

PubMed2005

Normalization and analysis of residual variation in two-dimensional gel electrophoresis for quantitative differential proteomics.

Although two-dimensional gel electrophoresis (2-DE) has long been a favorite experimental method to screen proteomes, its reproducibility is seldom analyzed with the assistance of quantitative error models. The lack of models of residual distributions that can be used to assign likelihood to differential expression reflects the difficulty in tackling the combined effect of variability in spot intensity and uncertain recognition of the same spot in different gels. In this report we have analyzed a series of four triplicate two-dimensional gels of chicken embryo heart samples at two distinct development stages to produce such a model of residual distribution. In order to achieve this reference error model, a nonparametric procedure for consistent spot intensity normalization had to be established, and is also reported here. In addition to variability in normalized intensity due to various sources, the residual variation between replicates was observed to be compounded by failure to identify the spot itself (gel alignment). The mixed effect is reflected by variably skewed bimodal density distributions of residuals. The extraction of a global error model that accommodated such distribution was achieved empirically by machine learning, specifically by bootstrapped artificial neural networks. The model described is being used to assign confidence values to observed variations in arbitrary 2-DE gels in order to quantify the degree of over-expression and under-expression of protein spots.

Animals↗

PubMed2003

The role of human glandular kallikrein 2 for prediction of pathologically organ confined prostate cancer.

BACKGROUND: In recent studies serum levels of human glandular kallikrein 2 (hK2) demonstrated significant differences in pathologically organ-confined versus non-organ-confined prostate cancer (PCa). In this study we investigated whether hK2 adds independent information when considered together with traditionally used parameters to predict organ confined (pT2a/b) PCa. METHODS: Serum levels of hK2, total and free prostate-specific antigens (PSA) were obtained one day before radical prostatectomy in 245 consecutive men. These were included with clinical stage and biopsy Gleason grade into univariate analysis and multivariate logistic regression models. RESULTS: pT2a/b PCa was found in n = 148 patients. In univariate analysis all preoperative parameters demonstrated significant association with the presence of pT2a/b PCa. Using multivariate logistic regression model hK2 (P = 0.022), clinical stage (P < 0.0001), and Gleason grade (P < 0.0001) were independent predictors of pT2a/b PCa whereas PSA (P = 0.3) was not. In bootstrap corrected logistic regression based nomograms the addition of hK2 density marginally enhanced predictive accuracy when PSA, PSA density, clinical stage, and Gleason grade were considered (AUC = 0.879 without hK2 density and 0.883 with hK2 density). CONCLUSIONS: hK2 and hK2 density could independently predict pT2a/b PCa. However, improvement in predictive accuracy was marginal when nomograms based on traditional variables were complemented with this serum marker.

Area Under Curve↗

PubMed2002

Physicochemical explanation of peptide binding to HLA-A*0201 major histocompatibility complex: a three-dimensional quantitative structure-activity relationship study.

A three-dimensional quantitative structure-activity relationship method for the prediction of peptide binding affinities to the MHC class I molecule HLA-A*0201 was developed by applying the CoMSIA technique on a set of 266 peptides. To increase the self consistency of the initial CoMSIA model, the poorly predicted peptides were excluded from the training set in a stepwise manner and then included in the study as a test set. The final model, based on 236 peptides and considering the steric, electrostatic, hydrophobic, hydrogen bond donor, and hydrogen bond acceptor fields, had q2 = 0.683 and r2 = 0.891. The stability of this model was proven by cross-validations in two and five groups and by a bootstrap analysis of the non-cross-validated model. The residuals between the experimental pIC50 (-logIC50) values and those calculated by "leave-one-out" cross-validation were analyzed. According to the best model, 63.2% of the peptides were predicted with /residuals/ < or = 0.5 log unit; 29.3% with 1.0 < or = /residuals/ < 0.5; and 7.5% with /residuals/ > 1.0 log unit. The mean /residual/ value was 0.489. The coefficient contour maps identify the physicochemical property requirements at each position in the peptide molecule and suggest amino acid sequences for high-affinity binding to the HLA-A*0201 molecule.

Amino Acid Sequence↗

PubMed2003

Simplicial edge representation of protein structures and alpha contact potential with confidence measure.

Protein representation and potential function are two important ingredients for studying protein folding, equilibrium thermodynamics, and sequence design. We introduce a novel geometric representation of protein contact interactions using the edge simplices from the alpha shape of the protein structure. This representation can eliminate implausible neighbors that are not in physical contact, and can avoid spurious contact between two residues when a third residue is between them. We developed statistical alpha contact potential using an odds-ratio model. A studentized bootstrap method was then introduced to assess the 95% confidence intervals for each of the 210 propensity parameters. We found, with confidence, that there is significant long-range propensity (>30 residues apart) for hydrophobic interactions. We tested alpha contact potential for native structure discrimination using several sets of decoy structures, and found that it often performs comparably with atom-based potentials requiring many more parameters. We also show that accurate geometric representation is important, and that alpha contact potential has better performance than potential defined by cutoff distance between geometric centers of side chains. Hierarchical clustering of alpha contact potentials reveals natural grouping of residues. To explore the relationship between shape and physicochemical representations, we tested the minimum alphabet size necessary for native structure discrimination. We found that there is no significant difference in performance of discrimination when alphabet size varies from 7 to 20, if geometry is represented accurately by alpha simplicial edges. This result suggests that the geometry of packing plays an important role, but the specific residue types are often interchangeable.

Amino Acid Sequence↗

PubMed2005

Predicting protein functional sites with phylogenetic motifs.

In this report, we demonstrate that phylogenetic motifs, sequence regions conserving the overall familial phylogeny, represent a promising approach to protein functional site prediction. Across our structurally and functionally heterogeneous data set, phylogenetic motifs consistently correspond to functional sites defined by both surface loops and active site clefts. Additionally, the partially buried prosthetic group regions of cytochrome P450 and succinate dehydrogenase are identified as phylogenetic motifs. In nearly all instances, phylogenetic motifs are structurally clustered, despite little overall sequence proximity, around key functional site features. Based on calculated false-positive expectations and standard motif identification methods, we show that phylogenetic motifs are generally conserved in sequence. This result implies that they can be considered motifs in the traditional sense as well. However, there are instances where phylogenetic motifs are not (overall) well conserved in sequence. This point is enticing, because it implies that phylogenetic motifs are able to identify key sequence regions that traditional motif-based approaches would not. Further, phylogenetic motif results are also shown to be consistent with evolutionary trace results, and bootstrapping is used to demonstrate tree significance.

Amino Acid Motifs↗

PubMed1989

The surface area of monomeric proteins: significance of power law behavior.

The coefficients in a power law fit of accessible area versus molecular weight for high-resolution monomeric protein structures are assessed with respect to statistical accuracy using bootstrap analyses, and with respect to physical significance using model systems and the concept of roughness or fractal structure of the protein surface.

Models, Statistical↗

PubMed2002

Natural variation in baseline data: when do we call a new sample 'resistant'?

Mortality of pear psylla to amitraz was studied by means of bioassays. Variation between samples, temporal variation within the season in one orchard and spatial variation between Swiss regions were considered. Variation between samples was large enough to produce different Probit functions and LC50 values. Temporal and spatial variations were too small to indicate resistance. Prediction intervals of the pooled functions using bootstrapping were calculated to determine if future samples come from a population with decreased sensitivity. Probabilistic criteria on the population level were proposed for resistance.

Animals↗

PubMed2002

Improved approximate confidence intervals for the mean of a log-normal random variable.

Data analysts often compute approximate 100 (1-alpha) per cent confidence intervals for the mean of a log-normal random variable due to the computational effort required for exact intervals. We evaluate two simple approximations and demonstrate that the probabilities with which the intervals fail to capture the population mean (that is, the coverage error) can range from well above the desired level, alpha, to very near zero in small to moderate sample sizes (n < or = 100). The performance of a more sophisticated approximation, implemented via numerical integration or bootstrap sampling, is noticeably improved, but also suffers from coverage errors that are too large when n < or = 25. A new procedure is developed which outperforms existing approximations. Computing these improved intervals requires the integration of standard distribution functions. The calculations are straightforward, however, and lead to satisfactory coverage errors for n as small as 5. A related method that avoids the integration step generally outperforms existing simple approximations for n < or = 100, while maintaining the coverage error at or below alpha. Programs to implement the new procedures are provided in an Appendix.

Benzene↗

PubMed2001

Analysis of failure time hierarchical data in the presence of competing risks with application to oral contraceptive pill use in Egypt.

Problems of practical interest in the analysis of data on contraceptive use, from Demographic and Health Surveys (DHS), include the estimation of the cause-specific probability of discontinuation by time t (the cumulative incidence function), in the presence of other competing causes and the evaluation of the effect of covariates on the cause-specific hazards of discontinuation. Methods of analysis of failure time data with competing risks are by now fairly well developed in the case of a simple random sample. However, the data from the DHS are clustered by geographical areas and include multiple episodes per woman. For a marginal (population average) approach, we propose using methods developed for simple random samples with standard errors calculated using a double bootstrap to take account of the clustered hierarchical nature of the data. In the conditional approach, the cause-specific hazards are modelled as log-linear functions of the covariates conditional on random effects of clusters and women, using a three-level multinomial discrete-time logit model. The methods are applied to data from Egypt 1992 DHS on the oral contraceptive pill use.

Adolescent↗