Parameter estimation for the distribution of single cell lag times.

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

Interstitial cells of Cajal are normally distributed in both ganglionated and aganglionic bowel in Hirschsprung's disease

Résumé Introduction : La chirurgie de la maladie de Hirschsprung est fréquemment compliquée d'une atteinte post-opératoire de la motilité intestinale. Des anomalies du système nerveux entérique (SNE) telles que la dysplasie neuronale intestinale de type B, l'hypoganglionose ou l'aganglionose, présents dans le segment abaissé, peuvent être la cause de certaines de ces complications mais aucune information n'est disponible quant au rôle des cellules interstitielles de Cajal (CIC) sur la motilité intestinale dans la phase post-opératoire. Ces cellules sont considérées avoir un rôle de pacemaker dans le tractus gastro-intestinal. L'objectif de cette étude était de décrire la distribution des CIC dans le segment proximal du côlon réséqué lors de cures chirurgicales de maladie de Hirschsprung et de confronter ces observations à l'évolution clinique post-opératoire. Matériel et Méthodes : L'incidence des complications post-opératoires a été déterminée par une revue rétrospective des dossiers de 48 patients opérés pour maladie de Hirschspung entre 1977 et 1999 et par l'étude histologique et immuno-histochimique des pièces réséquées chez ces patients. Nous avons comparé la distribution des CIC dans le segment proximal du côlon avec celle du côlon sain de 16 enfants contrôles par microscopie optique. L'immunohistochimie au c-Kit a été utilisée pour marquer spécifiquement les CIC sur échantillons paraffinés. Ces résultats ont ensuite été corrélés avec l'étude du SNE de ces mêmes segments, déterminée par immunohistochimie au CD56 et au protein gene product 9.5. Résultats Les complications post-opératoires suivantes furent identifiées : constipation 46%, constipation avec incontinence 15%, entérocolite 8%, décès 4% (probablement sur entérocolite). La distribution des CIC dans les segments proximaux réséqués chez les enfants avec maladie de Hirschsprung était identique à celle observée dans les segments de côlon sain, et ce indépendamment de la distribution normale ou anormale du SNE. Chez les enfants opérés pour maladie de Hirschsprung les segments réséqués présentaient les anomalies d'innervation suivantes : aganglionose 10.4%, hypoganglionose 12.5%, dysplasie neuronale intestinale de type B 6.3%, autres dysganglionoses 14.6%. Aucune relation entre ces anomalies d'innervation et les complications post-opératoires n'a été mise en évidence. Conclusion : La distribution des CIC est normale chez les patient opérés pour maladie de Hirschsprung, et ne contribue donc pas aux atteintes post-opératoires de la motilité intestinale. Cela signifie aussi que le réseau de CIC se développe noinialement dans le côlon humain, même en présence d'une innervation colique anormale ou absente. Abstract: Surgery for Hirschsprung's disease is often complicated by post-operative bowel motility disorders. The impact of intestinal neural histology on the surgical outcome has been previously studied, but no information is available concerning the influence of the distribution of interstitial cells of Cajal (ICC) on these complications. These cells are considered to be pacemakers in the gastrointestinal tract. The aim of this study was to assess the distribution of ICC in the proximal segment of resected bowel in Hirschsprung's disease and confront these results with the clinical outcome. Using immunohistochemistry for light microscopy, we compared the pattern of distribution of ICC in the proximal segment of resected bowel in Hirschsprung's disease with that in normal colon. We correlated these results with the corresponding neural intestinal histology determined by CD56 and the protein gene product 9.5 immunohistochemistry. The distribution of ICC in the proximal segment of resected bowel is identical to that of normal colon, regardless of normal or abnormal colon innervation. ICC distribution does not seem to contribute to post-operative bowel motility disorders in patients operated for Hirschsprung's disease.

Selection on a eumelanic ornament is stronger in the tropics than in temperate zones in the worldwide-distributed barn owl.

Spatial variation in the pattern of natural selection can promote local adaptation and genetic differentiation between populations. Because heritable melanin-based ornaments can signal resistance to environmentally mediated elevation in glucocorticoids, to oxidative stress and parasites, populations may vary in the mean degree of melanic coloration if selection on these phenotypic aspects varies geographically. Within a population of Swiss barn owls (Tyto alba), the size of eumelanic spots is positively associated with survival, immunity and resistance to stress, but it is yet unknown whether Tyto species that face stressful environments evolved towards a darker eumelanic plumage. Because selection regimes vary along environmental gradients, we examined whether melanin-based traits vary clinally and are expressed to a larger extent in the tropics where parasites are more abundant than in temperate zones. To this end, we considered 39 barn owl species distributed worldwide. Barn owl species living in the tropics displayed larger eumelanic spots than those found in temperate zones. This was, however, verified in the northern hemisphere only. Parasites being particularly abundant in the tropics, they may promote the evolution of darker eumelanic ornaments.

Brain water mobility decreases after astrocytic aquaporin-4 inhibition using RNA interference.

Neuroimaging with diffusion-weighted imaging is routinely used for clinical diagnosis/prognosis. Its quantitative parameter, the apparent diffusion coefficient (ADC), is thought to reflect water mobility in brain tissues. After injury, reduced ADC values are thought to be secondary to decreases in the extracellular space caused by cell swelling. However, the physiological mechanisms associated with such changes remain uncertain. Aquaporins (AQPs) facilitate water diffusion through the plasma membrane and provide a unique opportunity to examine the molecular mechanisms underlying water mobility. Because of this critical role and the recognition that brain AQP4 is distributed within astrocytic cell membranes, we hypothesized that AQP4 contributes to the regulation of water diffusion and variations in its expression would alter ADC values in normal brain. Using RNA interference in the rodent brain, we acutely knocked down AQP4 expression and observed that a 27% AQP4-specific silencing induced a 50% decrease in ADC values, without modification of tissue histology. Our results demonstrate that ADC values in normal brain are modulated by astrocytic AQP4. These findings have major clinical relevance as they suggest that imaging changes seen in acute neurologic disorders such as stroke and trauma are in part due to changes in tissue AQP4 levels.

Total hemoglobin mass--a new parameter to detect blood doping?

PURPOSE: All kinds of blood manipulations aim to increase the total hemoglobin mass (tHb-mass). To establish tHb-mass as an effective screening parameter for detecting blood doping, the knowledge of its normal variation over time is necessary. The aim of the present study, therefore, was to determine the intraindividual variance of tHb-mass in elite athletes during a training year emphasizing off, training, and race seasons at sea level. METHODS: tHb-mass and hemoglobin concentration ([Hb]) were determined in 24 endurance athletes five times during a year and were compared with a control group (n = 6). An analysis of covariance was used to test the effects of training phases, age, gender, competition level, body mass, and training volume. Three error models, based on 1) a total percentage error of measurement, 2) the combination of a typical percentage error (TE) of analytical origin with an absolute SD of biological origin, and 3) between-subject and within-subject variance components as obtained by an analysis of variance, were tested. RESULTS: In addition to the expected influence of performance status, the main results were that the effects of training volume (P = 0.20) and training phases (P = 0.81) on tHb-mass were not significant. We found that within-subject variations mainly have an analytical origin (TE approximately 1.4%) and a very small SD (7.5 g) of biological origin. CONCLUSION: tHb-mass shows very low individual oscillations during a training year (<6%), and these oscillations are below the expected changes in tHb-mass due to Herythropoetin (EPO) application or blood infusion (approximately 10%). The high stability of tHb-mass over a period of 1 year suggests that it should be included in an athlete's biological passport and analyzed by recently developed probabilistic inference techniques that define subject-based reference ranges.

Trabecular bone score (TBS) the new parameter of 2D texture analysis for the evaluation of 3D bone micro architecture status

X-ray is a technology that is used for numerous applications in the medical field. The process of X-ray projection gives a 2-dimension (2D) grey-level texture from a 3- dimension (3D) object. Until now no clear demonstration or correlation has positioned the 2D texture analysis as a valid indirect evaluation of the 3D microarchitecture. TBS is a new texture parameter based on the measure of the experimental variogram. TBS evaluates the variation between 2D image grey-levels. The aim of this study was to evaluate existing correlations between 3D bone microarchitecture parameters - evaluated from μCT reconstructions - and the TBS value, calculated on 2D projected images. 30 dried human cadaveric vertebrae were acquired on a micro-scanner (eXplorer Locus, GE) at isotropic resolution of 93 μm. 3D vertebral body models were used. The following 3D microarchitecture parameters were used: Bone volume fraction (BV/TV), Trabecular thickness (TbTh), trabecular space (TbSp), trabecular number (TbN) and connectivity density (ConnD). 3D/2D projections has been done by taking into account the Beer-Lambert Law at X-ray energy of 50, 100, 150 KeV. TBS was assessed on 2D projected images. Correlations between TBS and the 3D microarchitecture parameters were evaluated using a linear regression analysis. Paired T-test is used to assess the X-ray energy effects on TBS. Multiple linear regressions (backward) were used to evaluate relationships between TBS and 3D microarchitecture parameters using a bootstrap process. BV/TV of the sample ranged from 18.5 to 37.6% with an average value at 28.8%. Correlations' analysis showedthat TBSwere strongly correlatedwith ConnD(0.856≤r≤0.862; p<0.001),with TbN (0.805≤r≤0.810; p<0.001) and negatively with TbSp (−0.714≤r≤−0.726; p<0.001), regardless X-ray energy. Results show that lower TBS values are related to "degraded" microarchitecture, with low ConnD, low TbN and a high TbSp. The opposite is also true. X-ray energy has no effect onTBS neither on the correlations betweenTBS and the 3Dmicroarchitecture parameters. In this study, we demonstrated that TBS was significantly correlated with 3D microarchitecture parameters ConnD and TbN, and negatively with TbSp, no matter what X-ray energy has been used. This article is part of a Special Issue entitled ECTS 2011. Disclosure of interest: None declared.

Selection on a eumelanic ornament is stronger in the tropics than in temperate zones in the worldwide-distributed barn owl.

Spatial variation in the pattern of natural selection can promote local adaptation and genetic differentiation between populations. Because heritable melanin-based ornaments can signal resistance to environmentally mediated elevation in glucocorticoids, to oxidative stress and parasites, populations may vary in the mean degree of melanic coloration if selection on these phenotypic aspects varies geographically. Within a population of Swiss barn owls (Tyto alba), the size of eumelanic spots is positively associated with survival, immunity and resistance to stress, but it is yet unknown whether Tyto species that face stressful environments evolved towards a darker eumelanic plumage. Because selection regimes vary along environmental gradients, we examined whether melanin-based traits vary clinally and are expressed to a larger extent in the tropics where parasites are more abundant than in temperate zones. To this end, we considered 39 barn owl species distributed worldwide. Barn owl species living in the tropics displayed larger eumelanic spots than those found in temperate zones. This was, however, verified in the northern hemisphere only. Parasites being particularly abundant in the tropics, they may promote the evolution of darker eumelanic ornaments.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

Probabilistic evidential assessment of gunshot residue particle evidence (Part II) : Bayesian parameter estimation for experimental count data.

Part I of this series of articles focused on the construction of graphical probabilistic inference procedures, at various levels of detail, for assessing the evidential value of gunshot residue (GSR) particle evidence. The proposed models - in the form of Bayesian networks - address the issues of background presence of GSR particles, analytical performance (i.e., the efficiency of evidence searching and analysis procedures) and contamination. The use and practical implementation of Bayesian networks for case pre-assessment is also discussed. This paper, Part II, concentrates on Bayesian parameter estimation. This topic complements Part I in that it offers means for producing estimates useable for the numerical specification of the proposed probabilistic graphical models. Bayesian estimation procedures are given a primary focus of attention because they allow the scientist to combine (his/her) prior knowledge about the problem of interest with newly acquired experimental data. The present paper also considers further topics such as the sensitivity of the likelihood ratio due to uncertainty in parameters and the study of likelihood ratio values obtained for members of particular populations (e.g., individuals with or without exposure to GSR).

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.