Enzyme polymorphism and clinical variability of diseases: a study of diabetes mellitus.

We investigated possible relations among four common neonatal manifestations of diabetic pregnancy (macrosomia, hypoglycemia, hypocalcemia, jaundice) and four enzyme polymorphisms (PGM1, ADA, AK1, ACP1 in a sample of infants born of diabetic mothers. The pattern of associations observed between the two sets of variables is consistent with known differences in enzymatic activity within phenotypes of each system, suggesting that low enzymatic activity may have unfavorable effects on fetal development and on adaptability of the neonate to the extrauterine environment, Some of the polymorphic enzymes studied influence fetal growth in normal pregnancy as well. Analysis of relations between genetic polymorphisms and the clinical pattern of common diseases may provide a better understanding of the genetic basis of the clinical variability of diseases within and between human populations.

Random assignment of intervention points in two phase single-case designs: data-division-specific distributions

The present study explores the statistical properties of a randomization test based on the random assignment of the intervention point in a two-phase (AB) single-case design. The focus is on randomization distributions constructed with the values of the test statistic for all possible random assignments and used to obtain p-values. The shape of those distributions is investigated for each specific data division defined by the moment in which the intervention is introduced. Another aim of the study consisted in testing the detection of inexistent effects (i.e., production of false alarms) in autocorrelated data series, in which the assumption of exchangeability between observations may be untenable. In this way, it was possible to compare nominal and empirical Type I error rates in order to obtain evidence on the statistical validity of the randomization test for each individual data division. The results suggest that when either of the two phases has considerably less measurement times, Type I errors may be too probable and, hence, the decision making process to be carried out by applied researchers may be jeopardized.

Extreme homogeneity among Brazilian wheat genotypes determined by RAPD markers

Random amplified polymorphic DNA markers (RAPD) were used to estimate the variability of 14 genotypes of Brazilian wheat (Triticum aestivum L.), using a set of 50 random 10mer primers. A total of 256 reproducibly scorable DNA amplification products were obtained from 48 of the primers, 83% of which were polymorphic. Genetic distances among genotypes were calculated and a dendrogram and a principal coordinates analysis showing the genetic relationships among them were obtained. Despite the low variability found (average genetic distance of 27%), two groups of genotypes could be identified, which probably reflect how they were formed. Studies such as this one may be important in the planning and development of future improvement programs for this plant species.

Report on Fly Ash Variability, MLR-81-2, 1981

The physical-chemical testing of fly ashes indicates that, under normal operating conditions, a low variability of results can be expected from a particular generating plant unit. However, unannounced changes in coal source and/or plant operations do occur and they may result in an ash with undesirable properties. Since these properties can be detected by physical-chemical testing, it is recommended that this testing be performed on a lot-by-lot basis when a plant is supplying fly ash to a construction project.

Isoenzymatic variability in wild potatoes

Two species of wild potato Solanum commersonii, subspecies commersonii and malmeanum, and S. chacoense, subspecies muelleri occur in southern Brazil. Their rusticity and easy adaptation to extreme climatic conditions make them valuable for breeding programs. The objective of this work was to analyze the isoenzymatic variability of 113 clones of wild potato subspecies. They were collected and maintained at Embrapa-Centro de Pesquisa Agropecuária de Clima Temperado, at Pelotas, RS, Brazil. Enzymes involved in energetic (group I) or in peripherical (group II) metabolism constituted the material used. Polyacrylamide horizontal gel electrophoresis was used to analyze peroxidase, aspartate transaminase, phosphoglucomutase and isocitrate dehydrogenase isoenzymes. Solanum spp. has considerable genetic variability for isoenzymatic patterns. Cluster analysis classified the clones into 51 subgroups, based on electrophoretic variants of group I enzymes, and into 89, when group II enzyme variants were added. Genotypic differentiation of S. chacoense muelleri in relation to S. commersonii commersonii and S. commersonii malmeanum is evident when expressed through similarity and cluster analysis.

Inter- and intraobserver variability of measurements with Pentacam HR® in patients with mild to moderate keratoconus

Purpose: To evaluate inter- and intraobserver variability of indices crucial for detection of keratoconus progression derived from the Pentacam HR® (high-resolution) tomographer (OCULUS Optikgeräte GmbH, Wetzlar, Germany) in patients with mild to moderate keratoconus. Methods: Three repeated corneal topography measurements in the 25-picture mode by two independent observers were performed. The extent of variability across a large range of measurement parameters was analyzed including anterior and posterior corneal surface measurements, pachymetry values, corneal volume, anterior chamber volume and depth, and iridocorneal angle. The intraclass correlation coefficient (ICC) between and within each investigator was calculated to assess reproducibility and repeatability, respectively. Results: 31 eyes of 20 patients (mean age 31.6, SD ± 8.6) were included. Overall, the repeatability and reproducibility were excellent. The range of variability was reported by calculating the standard deviation of measurements. The detailed results are shown in Table 1. Conclusions: This study shows that the Pentacam HR® tomographer provides reliable measurements in patients with mild to moderate keratoconus. However, all parameters showed a certain range of variability. This should be taken into account when assessing keratoconus progression in order to distinguish true progression from variability in measurements. In addition, the excellent reproducibility suggests that the measurements can be reliably performed by different individuals from one visit to another.

Improvement of therapeutic drug monitoring of imatinib by Bayesian prediction of trough levels. Personalized drug dosage

Aims: Plasma concentrations of imatinib differ largely between patients despite same dosage, owing to large inter-individual variability in pharmacokinetic (PK) parameters. As the drug concentration at the end of the dosage interval (Cmin) correlates with treatment response and tolerability, monitoring of Cmin is suggested for therapeutic drug monitoring (TDM) of imatinib. Due to logistic difficulties, random sampling during the dosage interval is however often performed in clinical practice, thus rendering the respective results not informative regarding Cmin values.Objectives: (I) To extrapolate randomly measured imatinib concentrations to more informative Cmin using classical Bayesian forecasting. (II) To extend the classical Bayesian method to account for correlation between PK parameters. (III) To evaluate the predictive performance of both methods.Methods: 31 paired blood samples (random and trough levels) were obtained from 19 cancer patients under imatinib. Two Bayesian maximum a posteriori (MAP) methods were implemented: (A) a classical method ignoring correlation between PK parameters, and (B) an extended one accounting for correlation. Both methods were applied to estimate individual PK parameters, conditional on random observations and covariate-adjusted priors from a population PK model. The PK parameter estimates were used to calculate trough levels. Relative prediction errors (PE) were analyzed to evaluate accuracy (one-sample t-test) and to compare precision between the methods (F-test to compare variances).Results: Both Bayesian MAP methods allowed non-biased predictions of individual Cmin compared to observations: (A) - 7% mean PE (CI95% - 18 to 4 %, p = 0.15) and (B) - 4% mean PE (CI95% - 18 to 10 %, p = 0.69). Relative standard deviations of actual observations from predictions were 22% (A) and 30% (B), i.e. comparable to the intraindividual variability reported. Precision was not improved by taking into account correlation between PK parameters (p = 0.22).Conclusion: Clinical interpretation of randomly measured imatinib concentrations can be assisted by Bayesian extrapolation to maximum likelihood Cmin. Classical Bayesian estimation can be applied for TDM without the need to include correlation between PK parameters. Both methods could be adapted in the future to evaluate other individual pharmacokinetic measures correlated to clinical outcomes, such as area under the curve(AUC).

The co-evolution of culturally inherited altruistic helping and cultural transmission under random group formation.

Limited migration results in kin selective pressure on helping behaviors under a wide range of ecological, demographic and life-history situations. However, such genetically determined altruistic helping can evolve only when migration is not too strong and group size is not too large. Cultural inheritance of helping behaviors may allow altruistic helping to evolve in groups of larger size because cultural transmission has the potential to markedly decrease the variance within groups and augment the variance between groups. Here, we study the co-evolution of culturally inherited altruistic helping behaviors and two alternative cultural transmission rules for such behaviors. We find that conformist transmission, where individuals within groups tend to copy prevalent cultural variants (e.g., beliefs or values), has a strong adverse effect on the evolution of culturally inherited helping traits. This finding is at variance with the commonly held view that conformist transmission is a crucial factor favoring the evolution of altruistic helping in humans. By contrast, we find that under one-to-many transmission, where individuals within groups tend to copy a "leader" (or teacher), altruistic helping can evolve in groups of any size, although the cultural transmission rule itself hitchhikes rather weakly with a selected helping trait. Our results suggest that culturally determined helping behaviors are more likely to be driven by "leaders" than by popularity, but the emergence and stability of the cultural transmission rules themselves should be driven by some extrinsic factors.

The data treatment dependent variability of U-Pb zircon ages obtained using mono-collector, sector field, laser ablation ICP-MS

U-Pb dating of zircons by laser ablation inductively coupled plasma mass spectrometry (LA-ICPMS) is a widely used analytical technique in Earth Sciences. For U-Pb ages below 1 billion years (1 Ga), Pb-206/U-238 dates are usually used, showing the least bias by external parameters such as the presence of initial lead and its isotopic composition in the analysed mineral. Precision and accuracy of the Pb/U ratio are thus of highest importance in LA-ICPMS geochronology. We consider the evaluation of the statistical distribution of the sweep intensities based on goodness-of-fit tests in order to find a model probability distribution fitting the data to apply an appropriate formulation for the standard deviation. We then discuss three main methods to calculate the Pb/U intensity ratio and its uncertainty in the LA-ICPMS: (1) ratio-of-the-mean intensities method, (2) mean-of-the-intensity-ratios method and (3) intercept method. These methods apply different functions to the same raw intensity vs. time data to calculate the mean Pb/U intensity ratio. Thus, the calculated intensity ratio and its uncertainty depend on the method applied. We demonstrate that the accuracy and, conditionally, the precision of the ratio-of-the-mean intensities method are invariant to the intensity fluctuations and averaging related to the dwell time selection and off-line data transformation (averaging of several sweeps); we present a statistical approach how to calculate the uncertainty of this method for transient signals. We also show that the accuracy of methods (2) and (3) is influenced by the intensity fluctuations and averaging, and the extent of this influence can amount to tens of percentage points; we show that the uncertainty of these methods also depends on how the signal is averaged. Each of the above methods imposes requirements to the instrumentation. The ratio-of-the-mean intensities method is sufficiently accurate provided the laser induced fractionation between the beginning and the end of the signal is kept low and linear. We show, based on a comprehensive series of analyses with different ablation pit sizes, energy densities and repetition rates for a 193 nm ns-ablation system that such a fractionation behaviour requires using a low ablation speed (low energy density and low repetition rate). Overall, we conclude that the ratio-of-the-mean intensities method combined with low sampling rates is the most mathematically accurate among the existing data treatment methods for U-Pb zircon dating by sensitive sector field ICPMS.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Biological exposure indicators: quantification of biological variability using toxicokinetic modeling

Compartmental and physiologically based toxicokinetic modeling coupled with Monte Carlo simulation were used to quantify the impact of biological variability (physiological, biochemical, and anatomic parameters) on the values of a series of bio-indicators of metal and organic industrial chemical exposures. A variability extent index and the main parameters affecting biological indicators were identified. Results show a large diversity in interindividual variability for the different categories of biological indicators examined. Measurement of the unchanged substance in blood, alveolar air, or urine is much less variable than the measurement of metabolites, both in blood and urine. In most cases, the alveolar flow and cardiac output were identified as the prime parameters determining biological variability, thus suggesting the importance of workload intensity on absorbed dose for inhaled chemicals.