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Thin-layer chromatography and multivariate data analysis of willow bark extracts.

In most cases the pharmacological activity of plant extracts is not assigned to single components and often not all active ingredients are known. Approaches other than those considering single compounds only to analyze plant material have proven helpful for a better characterization of extracts in their entirety. In this study extracts of willow bark are analyzed by high-performance thin-layer chromatography (HPTLC) and two different pharmacological tests [the 2,2'-azobis (2-amidinopropane) dihydrochloride reaction and the xanthine/xanthine oxidase reaction] with the help of multivariate data analysis. Described are two models using the results of the chromatographic study of 22 various extracts of willow bark and their pharmacological properties. The chromatographic data are obtained by a special TLC scanner that enables measurement of HPTLC tracks simultaneously in the range of lambda = 200-400 nm. Additionally, the developed models are used to predict the activity of another three extracts of willow bark demonstrating the quality of the model.

Chromatography, Thin Layer↗

Precision in calculated rho, T1 and T2 images as a function of data analysis method.

In NMR imaging rho, T1 and T2 images are usually calculated from a set of partial saturation, saturation recovery or inversion recovery experiments with multiple echoes and multiple repetition times. Several methods can be envisaged to extract parameter images from such a set of source images. These methods to a greater or lesser extent take advantage of the fact that a multiple echo/multiple repetition time experiment provides a set of largely independent T1 and T2 measurements. In this study several data analysis methods, including weighted and non-weighted averaging of results of independent T1 and T2 measurements, weighted and non-weighted averaging of source images prior to data reduction and simultaneous three-parameter fitting, were compared against another in terms of precision, computational efficiency and robustness. The predicted performance of the examined methods was verified by stochastic simulation experiments.

Humans↗

Novelty seeking and rapid symptom improvement across active and sham accelerated iTBS conditions: A pooled individual-patient data analysis.

INTRODUCTION: Major depressive disorder (MDD) is highly prevalent and often treatment-resistant. Accelerated intermittent theta burst stimulation (aiTBS) is a promising intervention for treatment-resistant depression (TRD), though outcomes vary. Personality traits have been examined in relation to rTMS outcomes, yet their role in aiTBS remains underexplored. This pooled individual-patient-data analysis of two randomized, sham-controlled trials examined associations between baseline Temperament and Character Inventory (TCI) traits and one-week symptom change, and whether they differed by condition. METHODS: The left dorsolateral prefrontal cortex was targeted for 20 sessions over 4 days. Personality was assessed with the TCI, depression severity with the 17-item Hamilton Depression Rating Scale (HDRS-17). TCI-symptom-change associations were examined with a robust linear mixed-effects model, adjusting for age, gender, repeated measurements, and study membership. RESULTS: 104 participants were included (M/F 45/59; mean age 40.9 ± 12.7; active/sham 50/54). The model yielded a Time × Novelty Seeking interaction (β = -1.70, p = 0.021): higher baseline Novelty Seeking was associated with faster symptom reduction, without a between-arm difference. However, the interaction did not survive Holm correction across 14 trait-interaction tests (adjusted p = 0.294) and is therefore exploratory. No other interaction reached the uncorrected threshold. CONCLUSIONS: Higher baseline Novelty Seeking showed a nominal association with faster symptom reduction, without a difference between active and sham conditions. Because it did not survive multiplicity correction and was not reproduced in within-arm analyses, it is preliminary and may reflect contextual or nonspecific processes. Independent replication is required before temperament assessment can be clinically informative.

Humans↗

Constructing a prospective model of psychosocial adaptation in young adolescents with spina bifida: an application of optimal data analysis.

OBJECTIVE: To examine how individual- and family-level predictors in late childhood and preadolescence relate to psychosocial adaptation (i.e., scholastic success, social acceptance, and positive self-worth) in early adolescence. METHOD: This prospective longitudinal study includes 68 families of children with spina bifida and 68 comparison families of healthy children. Multimethod, multiinformant data were evaluated via optimal data analysis (ODA) and classification tree analysis (CTA) techniques. RESULTS: Factors best predicting psychosocial adaptation in early adolescence included (a) intrinsic motivation, (b) estimated verbal IQ, (c) behavioral conduct, (d) coping style, and (e) physical appearance. There were no significant group (spina bifida vs. able-bodied) effects. CONCLUSIONS: The final classification model correctly classified 77.8% of the total sample, indicating that this model had significant predictive capabilities. Results suggested that processes leading to psychosocial adaptation may be similar for youth with and without chronic illness.

Adaptation, Psychological↗

A pooled data analysis of injury incidence in rugby league football.

OBJECTIVE: The aim of this study was to summarise the injury rates in professional rugby league football. METHODS: Previously published studies were identified from database searches of the literature from Medline, Sports Discus and Web of Science. A total of 18 articles, which reported the prospective injury data collection for at least one playing season in professional rugby league worldwide, were included. The definition of injury adopted required an injured player to miss the subsequent game through injury. Ten studies satisfied the injury definition criteria for inclusion. A review of articles and extraction of relevant data were carried out independently by two authors. RESULTS: A total of 517 injuries were reported during 12819 hours of exposure (753 games), which resulted in an overall injury rate of 40.3 injuries per 1000 hours [95% confidence interval (CI) 36.9 to 43.8]. Most injuries were to the lower half of the body (20.7 per 1000 hours, 95% CI 17.7 to 24), with the trunk receiving the least (6.7 per 1000 hours, 95% CI 5 to 8.6). CONCLUSIONS: Injury rates in professional rugby league are higher than in some other contact sports, probably because of the large number of physical collisions that take place. This pooled data analysis provides more accurate estimates of injury incidence in the game of professional rugby league football.

Athletic Injuries↗

Information tools for exploratory data analysis in population pharmacokinetics.

For a group of individuals, population pharmacokinetic studies describe the interindividual variability through a statistical distribution. These studies conducted during the drug development serve as a useful marker of the safety of the drug, provide information that might be decisive for future experiments and, in a clinical context, help establish guidelines for optimal use in each patient. As complementary tools to the existing statistical and graphical techniques for population pharmacokinetic data analysis, indexes derived from information theory were used to select the most appropriate modelfor the statistical distribution, to detect atypical individuals, and to screen influential covariates. The rationale for using these indexes is shown using simulated and real data.

Humans↗

Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis.

The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.

Analysis of Variance↗

Elemental content of Vietnamese rice. Part 2. Multivariate data analysis.

Rice samples were obtained from the Red River region and some other parts of Vietnam as well as from Yanco, Australia. These samples were analysed for 14 elements (P, K, Mg, Ca, Mn, Zn, Fe, Cu, Al, Na, Ni, As, Mo and Cd) by ICP-AES, ICP-MS and FAAS as described in Part 1. This data matrix was then submitted to multivariate data analysis by principal component analysis to investigate the influences of environmental and crop cultivation variables on the elemental content of rice. Results revealed that geographical location, grain variety, seasons and soil conditions are the most likely significant factors causing changes in the elemental content between the rice samples. To assess rice quality according to its elemental content and physio-biological properties, a multicriteria decision making method (PROMETHEE) was applied. With the Vietnamese rice, the sticky rice appeared to contain somewhat higher levels of nutritionally significant elements such as P, K and Mg than the non-sticky rice. Also, rice samples grown during the wet season have better levels of nutritionally significant mineral elements than those of the dry season, but in general, the wet season seemed to provide better overall elemental and physio-biological rice quality.

Environment↗

Multiparametric iterative self-organizing MR imaging data analysis technique for assessment of tissue viability in acute cerebral ischemia.

BACKGROUND AND PURPOSE: Defining viability and the potential for recovery of ischemic brain tissue can be very valuable for patient selection for acute stroke therapies. Multiparametric MR imaging analysis of ischemic lesions indicates that the ischemic lesion is inhomogeneous in degree of ischemic injury and recovery potential. We sought to define MR imaging characteristics of ischemic lesions that are compatible with viable tissue. METHODS: We included patients with supratentorial ischemic stroke who underwent multiparametric MR imaging studies (axial multi-spin-echo T2-weighted imaging, T1-weighted imaging, and diffusion-weighted imaging) at the acute (< 24 hours) and outcome (3 months) phases of stroke. Using the algorithm Iterative Self-Organizing Data Analysis Technique (ISODATA), the lesion was segmented into clusters and each was assigned a number, called the tissue signature (white matter = 1, CSF = 12, all others between these two). Recovery was defined as at least a 20% size reduction from the acute phase ISODATA lesion volume to the outcome phase T2-weighted imaging lesion volume. The tissue signature data were collapsed into the following categories: < or = 3, 4, 5, and > or = 6. Logistic regression analysis included the following parameters: lesion volume, tissue signature value, apparent diffusion coefficient (ADC) value, relative ADC (rADC) expressed as a ratio, T2 value, and T2 ratio. The model with the largest goodness of fit value was selected. RESULTS: We included 48 patients (female-male ratio, 26:22; age, 64 [+/-14] years; 15 treated with recombinant tissue plasminogen activator [rt-PA] within 3 hours of onset; median National Institutes of Health Stroke Scale score, 7 [range, 2-26]). Median symptom onset-to-MR imaging time interval was 9.5 hours. With ISODATA processing, we generated 200 region-of-interest tissue records (one to nine tissue records per patient). Regarding tissue recovery, we detected a three-way interaction among ADC, ISODATA tissue signature, and previous treatment with rt-PA (P = .003). In the group not treated with rt-PA, ischemic tissues with acute rADC greater than the median (0.79) and tissue signature < or = 4 were more likely to recover (80% vs. 31% and 13%, odds ratio [95% CI]: 0.12 [0.05, 0.30] and 0.04 [0.01, 0.18] for tissue signatures 5 and 6, respectively). CONCLUSION: ISODATA multiparametric MR imaging of acute stroke clearly shows inhomogeneity and different viability of the ischemic lesion. Ischemic tissues with lower acute phase ISODATA tissue signature values (< or = 4) and higher rADC values (> or = 0.79) are much more likely to recover than those with higher signature values or lower rADC values. The effect of these factors on tissue recovery, however, is dependent on whether preceding treatment with rt-PA had been performed. Our approach can be a valuable tool in the design of therapeutic stroke trials with an extended time window.

Acute Disease↗

Actigraphic assessment of sleep in insomnia: application of the Actigraph Data Analysis Software (ADAS).

The usefulness of the actigraph methodology has been demonstrated in normal individuals. However, the validity of actigraphy has been questioned in insomnia patients because of the considerable measurement error that has been reported between actigraphy (ACT) and polysomnography (PSG). Two independent investigations have reported errors of 48 and 49 min in total sleep time between ACT and PSG. With a new scoring method called the Actigraph Data Analysis Software, a reanalysis of one of these studies was conducted. Based on this reanalysis, we have obtained a measurement error of only 25 min between the two methods. This finding may be an indication of the advantage of this new scoring method. A strong correlation coefficient (r = 0.82, p < 0.0001) was noted between ACT and PSG for total sleep time, thus suggesting a high degree of accuracy of the actigraph methodology in assessing the sleep/wake profile of insomniacs.

Arousal↗

A comparison of data analysis methods for determining gas phase stabilities by CID: alkali metal complexes of polyether ionophore antibiotics.

The gas phase stabilities of Group I metal complexes of the polyether ionophore antibiotics lasalocid and monensin were investigated by collision induced dissociation mass spectrometry. Electrospray ionization was used with a triple quadrupole mass spectrometer for the determination of threshold dissociation energies upon application of increasing collision energies. Various data analysis techniques for the determination of dissociation energies are discussed to assess the most suitable method for determining the stabilities of the ionophore-metal complexes studied here. In all cases only the relative stabilities of different complexes may be obtained by the method presented in this study, which does not assess absolute gas phase dissociation energies. Correction factors have been applied, however, to account for the energy conversion during collisions of different metal complexes and the varying degrees of freedom of different sized ligands, allowing for the comparison of the stabilities of different ionophores with like-metals. The measured threshold dissociation energies were compared with respect to the ionic radius of the metal cation, revealing a maximum stability for the K+ complexes of both lasalocid and monensin. A striking decrease in the stabilities of the Rb+ and Cs+ complexes was observed and is believed to be related to a decreasing degree of coordination that the ionophores can accomplish with the larger metals.

Algorithms↗

Selection of differentially expressed genes in microarray data analysis.

One common objective in microarray experiments is to identify a subset of genes that express differentially among different experimental conditions, for example, between drug treatment and no drug treatment. Often, the goal is to determine the underlying relationship between poor versus good gene signatures for identifying biological functions or predicting specific therapeutic outcomes. Because of the complexity in studying hundreds or thousands of genes in an experiment, selection of a subset of genes to enhance relationships among the underlying biological structures or to improve prediction accuracy of clinical outcomes has been an important issue in microarray data analysis. Selection of differentially expressed genes is a two-step process. The first step is to select an appropriate test statistic and compute the P-value. The genes are ranked according to their P-values as evidence of differential expression. The second step is to assign a significance level, that is, to determine a cutoff threshold from the P-values in accordance with the study objective. In this paper, we consider four commonly used statistics, t-, S- (SAM), U-(Mann-Whitney) and M-statistics to compute the P-values for gene ranking. We consider the family-wise error and false discovery rate false-positive error-controlled procedures to select a limited number of genes, and a receiver-operating characteristic (ROC) approach to select a larger number of genes for assigning the significance level. The ROC approach is particularly useful in genomic/genetic profiling studies. The well-known colon cancer data containing 22 normal and 40 tumor tissues are used to illustrate different gene ranking and significance level assignment methods for applications to genomic/genetic profiling studies. The P-values computed from the t-, U- and M-statistics are very similar. We discuss the common practice that uses the P-value, false-positive error probability, as the primary criterion, and then uses the fold-change as a surrogate measure of biological significance for gene selection. The P-value and the fold-change can be pictorially shown simultaneously in a volcano plot. We also address several issues on gene selection.

Data Interpretation, Statistical↗

Pharmacokinetic-pharmacodynamic modeling in the data analysis and interpretation of drug-induced QT/QTc prolongation.

In this review, factors affecting the QT interval and the methods that are currently in use in the analysis of drug effects on the QT interval duration are overviewed with the emphasis on (population) pharmacokinetic-pharmacodynamic (PK-PD) modeling. Among which the heart rate (HR) and the circadian rhythm are most important since they may interfere with the drug effect and need to be taken into account in the data analysis. The HR effect or the RR interval (the distance between 2 consecutive R peaks) effect is commonly eliminated before any further analysis, and many formulae have been suggested to correct QT intervals for changes in RR intervals. The most often used are Bazett and Fridericia formulae introduced in 1920. They are both based on the power function and differ in the exponent parameter. However, both assume the same exponent for different individuals. More recent findings do not confirm this assumption, and individualized correction is necessary to avoid under- or overcorrection that may lead to artificial observations of drug-induced QT interval prolongation. Despite the fact that circadian rhythm in QT and QTc intervals is a well-documented phenomenon, it is usually overlooked when drug effects are evaluated. This may result in a false-positive outcome of the analysis as the QTc peak due to the circadian rhythm may coincide with the peak of the drug plasma concentration. In view of these effects interfering with a potential drug effect on the QTc interval and having in mind low precision of QT interval measurements, a preferable way to evaluate the drug effect is to apply a population PK-PD modeling. In the literature, however, there are only a few publications in which population PK-PD modeling is applied to QT interval prolongation data, and they all refer to antiarrhythmic agents. In this review, after the most important sources of variability are outlined, a comprehensive population PK-PD model is presented that incorporates an individualized QT interval correction, a circadian rhythm in the individually corrected QT intervals, and a drug effect. The model application is illustrated using real data obtained with 2 compounds differing in their QT interval prolongation potential. The usefulness of combining data of several studies is stressed. Finally, the standard approach based on the raw observations and formal statistics, as described in the Preliminary Concept paper of the International Conference on Harmonization, is briefly compared with the method based on population PK-PD modeling, and the advantages of the latter are outlined.

Animals↗

Measured pore-water concentrations make equilibrium partitioning work--a data analysis.

There is an increasing body of evidence that the bioaccumulation of sediment-associated hydrophobic organic compounds (HOCs) is strongly influenced by sequestration. At present, it is not known how equilibrium partitioning theory (EqP), the most commonly employed approach for describing sediment bioaccumulation can be applied to sediments with sequestered contaminants. In this paper, we present freely dissolved pore-water concentrations of HOCs. These data were employed to interpret sediment bioaccumulation and sequestration data in order to arrive at a process based evaluation of EqP. The data analysis suggests that sediment bioaccumulation of compounds up to log K(ow) 7.5 in Tubificidae can be described as bioconcentration from pore-water. In addition, the pore-water concentrations of HOCs (4.5 < log K(ow) < 7.5) are established by equilibrium partitioning between the rapidly desorbing HOCs fraction in the sediment and the pore-water. Taken together, these findings indicate that EqP is a conceptually correct representation of sediment bioaccumulation, provided that sequestration is accounted for. This implies that the risk assessment of sediment-associated HOCs can be significantly simplified: With a method at hand for measuring freely dissolved pore-water concentrations of HOCs, it appears that HOCs' body residues in sediment dwelling organisms can be estimated on the basis of concentrations in pore-water and bioconcentration factors.

Animals↗

Efficacy of a foodlet-based multiple micronutrient supplement for preventing growth faltering, anemia, and micronutrient deficiency of infants: the four country IRIS trial pooled data analysis.

Diets of infants across the world are commonly deficient in multiple micronutrients during the period of growth faltering and dietary transition from milk to solid foods. A randomized placebo controlled trial was carried out in Indonesia, Peru, South Africa, and Vietnam, using a common protocol to investigate whether improving status for multiple micronutrients prevented growth faltering and anemia during infancy. The results of the pooled data analysis of the 4 countries for growth, anemia, and micronutrient status are reported. A total of 1134 infants were randomized to 4 treatment groups, with 283 receiving a daily placebo (P), 283 receiving a weekly multiple micronutrient supplement (WMM), 280 received a daily multiple micronutrient (DMM) supplement, and 288 received daily iron (DI) supplements. The DMM group had a significantly greater weight gain, growing at an average rate of 207 g/mo compared with 192 g/mo for the WMM group, and 186 g/mo for the DI and P groups. There were no differences in height gain. DMM was also the most effective treatment for controlling anemia and iron deficiency, besides improving zinc, retinol, tocopherol, and riboflavin status. DI supplementation alone increased zinc deficiency. The prevalence of multiple micronutrient deficiencies at baseline was high, with anemia affecting the majority, and was not fully controlled even after 6 mo of supplementation. These positive results indicate the need for larger effectiveness trials to examine how to deliver supplements at the program scale and to estimate cost benefits. Consideration should also be given to increasing the dosages of micronutrients being delivered in the foodlets.

Anemia↗

Secondary anthropometric data analysis of the National Food Consumption Survey in South Africa: the double burden.

OBJECTIVE: There is an increase in the prevalence of overweight and obesity in children worldwide, including South Africa. We investigated the prevalences of overweight, obesity, and stunting in a current generation of children (ages 12 to 108 mo), which has a high prevalence of stunting, and evaluated the determinants of both nutritional disorders. METHODS: Secondary data analysis of the weight and height measurements of 12- to 108-mo-old children (weighted n = 2200, non-weighted n = 2894) during the 1999 National Food Consumption Survey in South Africa is reported. The body mass index reference percentiles recommended for use in children by the International Obesity Task Force were used to determine the prevalence of overweight and obesity, and the National Center for Health Statistics (NCHS) percentiles were used to determine the prevalence of stunting. RESULTS: Nationally, the prevalence of stunting (height-for-age < or = -2 standard deviations, NCHS 50th percentile) in these children was 19.3% (95% confidence interval [CI] = 17.49 to 21.16) and was highest in 1- to 3-y-old children (24.4%) and in children of farm workers on commercial farms (25.6%). The prevalence of combined overweight and obesity (body mass index > or = 25 kg/m(2) in 17.1%, 95% CI = 15.00 to 19.23) at the national level was nearly as high as that for stunting. Further, the types of determinants for stunting and overweight were generally similar (although directionally opposite in degree of risk conferred) and included type of housing, type of toilet in the home, fuel used in cooking, presence of a refrigerator or stove, presence of a television in the house, educational level of the caregiver, and maternal education level. An example of the directionally opposite degree of risk is exemplified by the use of paraffin as a fuel being protective against being overweight (odds ratio = 0.78, 95% CI = 0.63 to 0.97) but predictive of an increased risk for stunting (odds ratio = 1.24, 95% CI = 1.04 to 1.48). Stunting itself conferred an increased risk (odds ratio = 1.80, 95% CI = 1.48 to 2.20) of being overweight. CONCLUSION: Certain defined determinants appear to play important roles in children's nutritional outcomes in relation to stunting and to overweight and obesity.

Anthropometry↗

A regularity statistic for medical data analysis.

A new statistic has been developed to quantify the amount of regularity in data. This statistic, ApEn (approximate entropy), appears to have potential application throughout medicine, notably in electrocardiogram and related heart rate data analyses and in the analysis of endocrine hormone release pulsatility. The focus of this article is ApEn. We commence with a simple example of what we are trying to discern. We then discuss exact regularity statistics and practical difficulties of using them in data analysis. The mathematic formula development for ApEn concludes the Solution section. We next discuss the two key input requirements, followed by an account of a pilot study successfully applying ApEn to neonatal heart rate analysis. We conclude with the important topic of ApEn as a relative (not absolute) measure, potential applications, and some caveats about appropriate usage of ApEn. Appendix A provides example ApEn and entropy computations to develop intuition about these measures. Appendix B contains a Fortran program for computing ApEn. This article can be read from at least three viewpoints. The practitioner who wishes to use a "black box" to measure regularity should concentrate on the exact formula, choices for the two input variables, potential applications, and caveats about appropriate usage. The physician who wishes to apply ApEn to heart rate analysis should particularly note the pilot study discussion. The more mathematically inclined reader will benefit from discussions of the relative (comparative) property of ApEn and from Appendix A.

Algorithms↗