Sex differences in the computation of traveling distance

Path integration is known to provide information to keep track of spatial location. Surprisingly, few investigations concerning sex differences in computation of the traveling distance have been done. This work was aimed at analyzing the reproduction of both passive and active linear displacements in women and men. To this end, the displacement of blindfolded subjects was done in a wheelchair, then on foot, three times in each condition for a fixed distance. Copies of passive and active traveling distance, distance estimations and pointing responses towards the starting point were analyzed. In passive condition and comparatively to men, women error was larger. Whereas traveling distance was generally underestimated in women, it was overestimated in men. In active condition, no sex differences were observed. When blindfolded subjects have to estimate the traveling distance, the female error was larger than the male one. But, when subjects were asked to indicate the visual cue corresponding to the traveling distance, the male error was larger than the female one. Finally, pointing to the starting point (0°) after a whole-body rotation showed a larger deviation from 0° in men than in women. These results suggest that sex of the subjects influence brain computation of path integration information.

A program for the computation of power and determination of sample size in hierarchical experimental designs.

We have devised a program that allows computation of the power of F-test, and hence determination of appropriate sample and subsample sizes, in the context of the one-way hierarchical analysis of variance with fixed effects. The power at a fixed alternative is an increasing function of the sample size and of the subsample size. The program makes it easy to obtain the power of F-test for a range of values of sample and subsample sizes, and therefore the appropriate sizes based on a desired power. The program can be used for the 'ordinary' case of the one-way analysis of variance, as well as for hierarchical analysis of variance with two stages of sampling. Examples are given of the practical use of the program.

Wheat alleles introgress into selfing wild relatives: empirical estimates from approximate Bayesian computation in Aegilops triuncialis.

Extensive gene flow between wheat (Triticum sp.) and several wild relatives of the genus Aegilops has recently been detected despite notoriously high levels of selfing in these species. Here, we assess and model the spread of wheat alleles into natural populations of the barbed goatgrass (Aegilops triuncialis), a wild wheat relative prevailing in the Mediterranean flora. Our sampling, based on an extensive survey of 31 Ae. triuncialis populations collected along a 60 km × 20 km area in southern Spain (Grazalema Mountain chain, Andalousia, totalling 458 specimens), is completed with 33 wheat cultivars representative of the European domesticated pool. All specimens were genotyped with amplified fragment length polymorphism with the aim of estimating wheat admixture levels in Ae. triuncialis populations. This survey first confirmed extensive hybridization and backcrossing of wheat into the wild species. We then used explicit modelling of populations and approximate Bayesian computation to estimate the selfing rate of Ae. triuncialis along with the magnitude, the tempo and the geographical distance over which wheat alleles introgress into Ae. triuncialis populations. These simulations confirmed that extensive introgression of wheat alleles (2.7 × 10(-4) wheat immigrants for each Ae. triuncialis resident, at each generation) into Ae. triuncialis occurs despite a high selfing rate (Fis ≈ 1 and selfing rate = 97%). These results are discussed in the light of risks associated with the release of genetically modified wheat cultivars in Mediterranean agrosystems.

Predicting drug metabolism: experiment and/or computation?

Drug metabolism can produce metabolites with physicochemical and pharmacological properties that differ substantially from those of the parent drug, and consequently has important implications for both drug safety and efficacy. To reduce the risk of costly clinical-stage attrition due to the metabolic characteristics of drug candidates, there is a need for efficient and reliable ways to predict drug metabolism in vitro, in silico and in vivo. In this Perspective, we provide an overview of the state of the art of experimental and computational approaches for investigating drug metabolism. We highlight the scope and limitations of these methods, and indicate strategies to harvest the synergies that result from combining measurement and prediction of drug metabolism.

Approximate Bayesian Computation Reveals the Crucial Role of Oceanic Islands for the Assembly of Continental Biodiversity.

The perceived low levels of genetic diversity, poor interspecific competitive and defensive ability, and loss of dispersal capacities of insular lineages have driven the view that oceanic islands are evolutionary dead ends. Focusing on the Atlantic bryophyte flora distributed across the archipelagos of the Azores, Madeira, the Canary Islands, Western Europe, and northwestern Africa, we used an integrative approach with species distribution modeling and population genetic analyses based on approximate Bayesian computation to determine whether this view applies to organisms with inherent high dispersal capacities. Genetic diversity was found to be higher in island than in continental populations, contributing to mounting evidence that, contrary to theoretical expectations, island populations are not necessarily genetically depauperate. Patterns of genetic variation among island and continental populations consistently fitted those simulated under a scenario of de novo foundation of continental populations from insular ancestors better than those expected if islands would represent a sink or a refugium of continental biodiversity. We, suggest that the northeastern Atlantic archipelagos have played a key role as a stepping stone for transoceanic migrants. Our results challenge the traditional notion that oceanic islands are the end of the colonization road and illustrate the significant role of oceanic islands as reservoirs of novel biodiversity for the assembly of continental floras.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.

Long-term citalopram administration reduces responsiveness of HPA axis in patients with major depression: relationship with S-citalopram concentrations in plasma and cerebrospinal fluid (CSF) and clinical response.

RATIONALE: A dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis is a well-documented neurobiological finding in major depression. Moreover, clinically effective therapy with antidepressant drugs may normalize the HPA axis activity. OBJECTIVE: The aim of this study was to test whether citalopram (R/S-CIT) affects the function of the HPA axis in patients with major depression (DSM IV). METHODS: Twenty depressed patients (11 women and 9 men) were challenged with a combined dexamethasone (DEX) suppression and corticotropin-releasing hormone (CRH) stimulation test (DEX/CRH test) following a placebo week and after 2, 4, and 16 weeks of 40 mg/day R/S-CIT treatment. RESULTS: The results show a time-dependent reduction of adrenocorticotrophic hormone (ACTH) and cortisol response during the DEX/CRH test both in treatment responders and nonresponders within 16 weeks. There was a significant relationship between post-DEX baseline cortisol levels (measured before administration of CRH) and severity of depression at pretreatment baseline. Multiple linear regression analyses were performed to identify the impact of psychopathology and hormonal stress responsiveness and R/S-CIT concentrations in plasma and cerebrospinal fluid (CSF). The magnitude of decrease in cortisol responsivity from pretreatment baseline to week 4 on drug [delta-area under the curve (AUC) cortisol] was a significant predictor (p<0.0001) of the degree of symptom improvement following 16 weeks on drug (i.e., decrease in HAM-D21 total score). The model demonstrated that the interaction of CSF S-CIT concentrations and clinical improvement was the most powerful predictor of AUC cortisol responsiveness. CONCLUSION: The present study shows that decreased AUC cortisol was highly associated with S-CIT concentrations in plasma and CSF. Therefore, our data suggest that the CSF or plasma S-CIT concentrations rather than the R/S-CIT dose should be considered as an indicator of the selective serotonergic reuptake inhibitors (SSRIs) effect on HPA axis responsiveness as measured by AUC cortisol response.

Benchmarking therapeutic drug monitoring software: A review of available computer tools

Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.

Hemispheric competence for auditory spatial representation.

Sound localization relies on the analysis of interaural time and intensity differences, as well as attenuation patterns by the outer ear. We investigated the relative contributions of interaural time and intensity difference cues to sound localization by testing 60 healthy subjects: 25 with focal left and 25 with focal right hemispheric brain damage. Group and single-case behavioural analyses, as well as anatomo-clinical correlations, confirmed that deficits were more frequent and much more severe after right than left hemispheric lesions and for the processing of interaural time than intensity difference cues. For spatial processing based on interaural time difference cues, different error types were evident in the individual data. Deficits in discriminating between neighbouring positions occurred in both hemispaces after focal right hemispheric brain damage, but were restricted to the contralesional hemispace after focal left hemispheric brain damage. Alloacusis (perceptual shifts across the midline) occurred only after focal right hemispheric brain damage and was associated with minor or severe deficits in position discrimination. During spatial processing based on interaural intensity cues, deficits were less severe in the right hemispheric brain damage than left hemispheric brain damage group and no alloacusis occurred. These results, matched to anatomical data, suggest the existence of a binaural sound localization system predominantly based on interaural time difference cues and primarily supported by the right hemisphere. More generally, our data suggest that two distinct mechanisms contribute to: (i) the precise computation of spatial coordinates allowing spatial comparison within the contralateral hemispace for the left hemisphere and the whole space for the right hemisphere; and (ii) the building up of global auditory spatial representations in right temporo-parietal cortices.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

3D gait assessment in young and elderly subjects using foot-worn inertial sensors.

This study describes the validation of a new wearable system for assessment of 3D spatial parameters of gait. The new method is based on the detection of temporal parameters, coupled to optimized fusion and de-drifted integration of inertial signals. Composed of two wirelesses inertial modules attached on feet, the system provides stride length, stride velocity, foot clearance, and turning angle parameters at each gait cycle, based on the computation of 3D foot kinematics. Accuracy and precision of the proposed system were compared to an optical motion capture system as reference. Its repeatability across measurements (test-retest reliability) was also evaluated. Measurements were performed in 10 young (mean age 26.1±2.8 years) and 10 elderly volunteers (mean age 71.6±4.6 years) who were asked to perform U-shaped and 8-shaped walking trials, and then a 6-min walking test (6MWT). A total of 974 gait cycles were used to compare gait parameters with the reference system. Mean accuracy±precision was 1.5±6.8cm for stride length, 1.4±5.6cm/s for stride velocity, 1.9±2.0cm for foot clearance, and 1.6±6.1° for turning angle. Difference in gait performance was observed between young and elderly volunteers during the 6MWT particularly in foot clearance. The proposed method allows to analyze various aspects of gait, including turns, gait initiation and termination, or inter-cycle variability. The system is lightweight, easy to wear and use, and suitable for clinical application requiring objective evaluation of gait outside of the lab environment.