Precision of distances and ordering of microsatellite markers in consensus linkage maps of chromosomes 1, 3 and 4 from two reciprocal chicken populations using bootstrap sampling

Some factors complicate comparisons between linkage maps from different studies. This problem can be resolved if measures of precision, such as confidence intervals and frequency distributions, are associated with markers. We examined the precision of distances and ordering of microsatellite markers in the consensus linkage maps of chromosomes 1, 3 and 4 from two F 2 reciprocal Brazilian chicken populations, using bootstrap sampling. Single and consensus maps were constructed. The consensus map was compared with the International Consensus Linkage Map and with the whole genome sequence. Some loci showed segregation distortion and missing data, but this did not affect the analyses negatively. Several inversions and position shifts were detected, based on 95% confidence intervals and frequency distributions of loci. Some discrepancies in distances between loci and in ordering were due to chance, whereas others could be attributed to other effects, including reciprocal crosses, sampling error of the founder animals from the two populations, F(2) population structure, number of and distance between microsatellite markers, number of informative meioses, loci segregation patterns, and sex. In the Brazilian consensus GGA1, locus LEI1038 was in a position closer to the true genome sequence than in the International Consensus Map, whereas for GGA3 and GGA4, no such differences were found. Extending these analyses to the remaining chromosomes should facilitate comparisons and the integration of several available genetic maps, allowing meta-analyses for map construction and quantitative trait loci (QTL) mapping. The precision of the estimates of QTL positions and their effects would be increased with such information.

Sexual differentiation of cortical spreading depression propagation after acute and kindled audiogenic seizures in the Wistar audiogenic rat (WAR)

Brain excitability diseases like epilepsy constitute one factor that influences brain electrophysiological features. Cortical spreading depression (CSD) is a phenomenon that can be altered by changes in brain excitability. CSD propagation was presently characterized in adult mate and female rats from a normal Wistar strain and from a genetically audiogenic seizure-prone strain, the Wistar audiogenic rat (WAR), both previously submitted (RAS(+)), or not (RAS(-)), to repetitive acoustic stimulation, to provoke audiogenic kindling in the WAR-strain. A gender-specific change in CSD-propagation was found. Compared to seizure-resistant animals, in the RAS- condition, mate and female WARs, respectively, presented CSD-propagation impairment and facilitation, characterized, respectively, by lower and higher propagation velocities (P<0.05). In contraposition, in the RAS(+) condition, mate and female WARs displayed, respectively, higher and tower CSD-propagation rates, as compared to the corresponding controls. In some Wistar and WAR females, we determined estrous cycle status on the day of the CSD-recording as being either estrous or diestrous; no cycle-phase-related differences in CSD-propagation velocities were detected. In contrast to other epilepsy models, such as Status Epilepticus induced by pilocarpine, despite the CSD-velocity reduction, in no case was CSD propagation blocked in WARs. The results suggest a gender-related, estrous cycle-phase-independent modification in the CSD-susceptibility of WAR rats, both in the RAS(+) and RAS(-) situation. (C) 2008 Elsevier B.V. All rights reserved.

The importance of scientific literacy in fostering education for sustainability: Theoretical considerations and preliminary findings from a Brazilian experience

Scientific literacy can be considered as a new demand of post-industrial society. It seems necessary in order to foster education for sustainability throughout students` academic careers. Universities striving to teach sustainability are being challenged to integrate a holistic perspective into a traditional undergraduate curriculum, which aims at specialization. This new integrative, inter- and transdisciplinary epistemological approach is necessary to cultivate autonomous citizenship, i.e., that each citizen be prepared to understand and participate in discussions about the complex contemporary issues posed by post-industrial society. This paper presents an epistemological framework to show the role of scientific literacy in fostering education for sustainability. We present a set of 26 collaborative concept maps (CCmaps) in order to illustrate an instance of theory becoming practice. During a required course for first-year undergraduate students (ACH 0011, Natural Sciences), climate change was presented and discussed in broad perspective by using CCmaps. We present students` CCmaps to show how they use concepts from quantitative and literacy disciplines to deal with the challenges posed by the need of achieving a sustainable development. (C) 2009 Elsevier Ltd. All rights reserved.

Predicting the columnar-to-equiaxed transition for a distribution of nucleation undercoolings

A deterministic mathematical model for steady-state unidirectional solidification is proposed to predict the columnar-to-equiaxed transition. In the model, which is an extension to the classic model proposed by Hunt [Hunt JD. Mater Sci Eng 1984;65:75], equiaxed grains nucleate according to either a normal or a log-normal distribution of nucleation undercoolings. Growth maps are constructed, indicating either columnar or equiaxed solidification as a function of the velocity of isotherms and temperature gradient. The fields A columnar and equiaxed growth change significantly with the spread of the nucleation undercooling distribution. Increasing the spread Favors columnar solidification if the dimensionless velocity of the isotherms is larger than 1. For a velocity less than 1, however, equiaxed solidification is initially favored, but columnar solidification is enhanced for a larger increase in the spread. This behavior was confirmed by a stochastic model, which showed that an increase in the distribution spread Could change the grain structure from completely columnar to 50% columnar grains. (c) 2008 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

The Stability of the Blood Oxygenation Level-Dependent Functional MRI Response to Motor Tasks Is Altered in Patients With Chronic Ischemic Stroke

Background and Purpose-Functional MRI is a powerful tool to investigate recovery of brain function in patients with stroke. An inherent assumption in functional MRI data analysis is that the blood oxygenation level-dependent (BOLD) signal is stable over the course of the examination. In this study, we evaluated the validity of such assumption in patients with chronic stroke. Methods-Fifteen patients performed a simple motor task with repeated epochs using the paretic and the unaffected hand in separate runs. The corresponding BOLD signal time courses were extracted from the primary and supplementary motor areas of both hemispheres. Statistical maps were obtained by the conventional General Linear Model and by a parametric General Linear Model. Results-Stable BOLD amplitude was observed when the task was executed with the unaffected hand. Conversely, the BOLD signal amplitude in both primary and supplementary motor areas was progressively attenuated in every patient when the task was executed with the paretic hand. The conventional General Linear Model analysis failed to detect brain activation during movement of the paretic hand. However, the proposed parametric General Linear Model corrected the misdetection problem and showed robust activation in both primary and supplementary motor areas. Conclusions-The use of data analysis tools that are built on the premise of a stable BOLD signal may lead to misdetection of functional regions and underestimation of brain activity in patients with stroke. The present data urge the use of caution when relying on the BOLD response as a marker of brain reorganization in patients with stroke. (Stroke. 2010; 41:1921-1926.)

Consistency in approximate entropy given by a volumetric estimate

Non-linear methods for estimating variability in time-series are currently of widespread use. Among such methods are approximate entropy (ApEn) and sample approximate entropy (SampEn). The applicability of ApEn and SampEn in analyzing data is evident and their use is increasing. However, consistency is a point of concern in these tools, i.e., the classification of the temporal organization of a data set might indicate a relative less ordered series in relation to another when the opposite is true. As highlighted by their proponents themselves, ApEn and SampEn might present incorrect results due to this lack of consistency. In this study, we present a method which gains consistency by using ApEn repeatedly in a wide range of combinations of window lengths and matching error tolerance. The tool is called volumetric approximate entropy, vApEn. We analyze nine artificially generated prototypical time-series with different degrees of temporal order (combinations of sine waves, logistic maps with different control parameter values, random noises). While ApEn/SampEn clearly fail to consistently identify the temporal order of the sequences, vApEn correctly do. In order to validate the tool we performed shuffled and surrogate data analysis. Statistical analysis confirmed the consistency of the method. (C) 2008 Elsevier Ltd. All rights reserved.

A Floating-point Extended Kalman Filter Implementation for Autonomous Mobile Robots

Localization and Mapping are two of the most important capabilities for autonomous mobile robots and have been receiving considerable attention from the scientific computing community over the last 10 years. One of the most efficient methods to address these problems is based on the use of the Extended Kalman Filter (EKF). The EKF simultaneously estimates a model of the environment (map) and the position of the robot based on odometric and exteroceptive sensor information. As this algorithm demands a considerable amount of computation, it is usually executed on high end PCs coupled to the robot. In this work we present an FPGA-based architecture for the EKF algorithm that is capable of processing two-dimensional maps containing up to 1.8 k features at real time (14 Hz), a three-fold improvement over a Pentium M 1.6 GHz, and a 13-fold improvement over an ARM920T 200 MHz. The proposed architecture also consumes only 1.3% of the Pentium and 12.3% of the ARM energy per feature.