Differential vascular adaptive response to stress exposure in male and female rats: Role of gonadal hormones and endothelial cells

Although there are reports concerning a vascular adaptive response to stress in males, this is not yet defined in females. The aim of this study was to delineate functional gender differences in the rat vascular adaptive response to stress and to determine the ability of sex hormones to modulate the stress-induced vascular adaptive response. Responses to noradrenaline were evaluated in aortas, with and without endothelium, from intact, gonadectomized and gonadectomized-hormone-replaced males and females submitted or not to stress (2-h immobilization). Reactivity of the aorta of stressed and non-stressed intact males and females (n = 6-14 per group) was also examined in the presence of L-NAME or indomethacin. Stress decreased and gonadectomy increased maximal responses to noradrenaline in aortas with intact endothelium from both genders. Stress also reduced noradrenaline potency in males. In females, but not males, stress decreased the gonadectomy-induced noradrenaline hyper-reactivity to near that of intact non-stressed rats. Hormone replacement restored the gonadectomy-induced impaired vascular adaptive response to stress. L-NAME, but not indomethacin, abolished the stress-induced decrease in aorta reactivity of males and females. None of the procedures altered reactivity of aortas denuded of endothelium. Conclusion: Stress-induced vascular adaptive responses show gender differences. The magnitude of the adaptive response is dependent on testicular hormones and involves endothelial nitric oxide-system hyperactivity.

The sympathetic adrenomedullary system, but not the hypothalamic-pituitary-adrenal axis, participates in aorta adaptive response to stress: nitric oxide involvement

Stress induced a decrease in the reactivity of the aorta to noradrenaline (NA), as a consequence of an endothelial nitric oxide (NO) system hyperactivity. The main characteristic of the stress response is activation of the hypothalamic-pituitary-adrenal (HPA) axis and sympathetic adrenomedullary (SA) system. The participation of the HPA axis and SA system in the decreased reactivity to NA in the aorta of rats exposed to 4-h immobilization was investigated. Concentration-response relationships for NA were obtained in the aorta, with and without endothelium, isolated from normal and stressed rats, following these procedures: (1) in the absence and presence of L-NAME; (2) after adrenalectomy (ADX) or not, in the absence or presence of L-NAME; (3) ADX rats treated or not with corticosterone; (4) ADX associated with stress; and (5) treated or not with reserpine. The reactivity of aorta without endothelium was unaffected by the procedures. The reactivity of aorta with endothelium was decreased by either stress or ADX. This effect was reversed by both L-NAME and corticosterone. ADX did not potentiate the decrease in the aorta reactivity induced by stress. Reserpine did not change the reactivity of aorta with endothelium from normal rats, but prevented the decrease in reactivity induced by stress. It is concluded that the HPA axis participates in endothelium-dependent modulation of aorta reactivity in normal conditions and that thr SA system participates in hyperactivity of the endothelial NO-system induced by stress, which is responsible for the decreased aorta reactivity to NA. (C) 2000 Elsevier B.V. B.V. All rights reserved.

Vascular adaptive responses to physical exercise and to stress are affected differently by nandrolone administration

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Do men and women use similar adaptive locomotion to clear static and dynamic obstacles?

Purpose. The purpose of this study was to analyze the influence of gender on the adaptive locomotion in the clearance of obstacles. Specifically, it was evaluated if there are differences in the space-temporal parameters between male and female in the clearance of and dynamic obstacles moving at both slow and fast speeds. Basic procedures. Five young male adults and five young female adults took part in this study. The task was performed in three conditions: static obstacle and dynamic obstacle - clearance perpendicular to the participant's trajectory at slow speed (1.07 m/s) and at fast speed (1.71 m/s). The trials were recorded by two digital cameras and spatial-temporal information was obtained. Main findings. The dynamic obstacle conditions required more visual inspection. The results showed different adaptive locomotion between the sexes. The distinct gait patterns were evidenced for the spatial and temporal variables and cadence in the three conditions. Conclusions. The women presented a more conservative behavior, which was evidenced by the increase of the length in the penultimate step and in the toe clearance.

SAG2A protein from Toxoplasma gondii interacts with both innate and adaptive immune compartments of infected hosts

Abstract Background Toxoplasma gondii is an intracellular parasite that causes relevant clinical disease in humans and animals. Several studies have been performed in order to understand the interactions between proteins of the parasite and host cells. SAG2A is a 22 kDa protein that is mainly found in the surface of tachyzoites. In the present work, our aim was to correlate the predicted three-dimensional structure of this protein with the immune system of infected hosts. Methods To accomplish our goals, we performed in silico analysis of the amino acid sequence of SAG2A, correlating the predictions with in vitro stimulation of antigen presenting cells and serological assays. Results Structure modeling predicts that SAG2A protein possesses an unfolded C-terminal end, which varies its conformation within distinct strain types of T. gondii. This structure within the protein shelters a known B-cell immunodominant epitope, which presents low identity with its closest phyllogenetically related protein, an orthologue predicted in Neospora caninum. In agreement with the in silico observations, sera of known T. gondii infected mice and goats recognized recombinant SAG2A, whereas no serological cross-reactivity was observed with samples from N. caninum animals. Additionally, the C-terminal end of the protein was able to down-modulate pro-inflammatory responses of activated macrophages and dendritic cells. Conclusions Altogether, we demonstrate herein that recombinant SAG2A protein from T. gondii is immunologically relevant in the host-parasite interface and may be targeted in therapeutic and diagnostic procedures designed against the infection.

Apply response adaptive randomization to group sequential with early stopping

Group sequential methods and response adaptive randomization (RAR) procedures have been applied in clinical trials due to economical and ethical considerations. Group sequential methods are able to reduce the average sample size by inducing early stopping, but patients are equally allocated with half of chance to inferior arm. RAR procedures incline to allocate more patients to better arm; however it requires more sample size to obtain a certain power. This study intended to combine these two procedures. We applied the Bayesian decision theory approach to define our group sequential stopping rules and evaluated the operating characteristics under RAR setting. The results showed that Bayesian decision theory method was able to preserve the type I error rate as well as achieve a favorable power; further by comparing with the error spending function method, we concluded that Bayesian decision theory approach was more effective on reducing average sample size.^

The P-Adaptive BIEM Version in Elastostatics

This paper introduces the p-adaptive version of the boundary element method as a natural extension of the homonymous finite element approach. After a brief introduction to adaptive techniques through their finite element formulation in elastostatics, the concepts are cast into the boundary element environment. Thus, the p-adaptive version of boundary integral methods is shown to be a generalization of already well known ideas. In order to show the power of these numerical procedures, the results of two practical analysis using both methods are presented.

Adaptive neuro-fuzzy inference systems (ANFIS) for supervised classification of competence in MIS based on psychomotor skills

INTRODUCTION: Objective assessment of motor skills has become an important challenge in minimally invasive surgery (MIS) training.Currently, there is no gold standard defining and determining the residents' surgical competence.To aid in the decision process, we analyze the validity of a supervised classifier to determine the degree of MIS competence based on assessment of psychomotor skills METHODOLOGY: The ANFIS is trained to classify performance in a box trainer peg transfer task performed by two groups (expert/non expert). There were 42 participants included in the study: the non-expert group consisted of 16 medical students and 8 residents (< 10 MIS procedures performed), whereas the expert group consisted of 14 residents (> 10 MIS procedures performed) and 4 experienced surgeons. Instrument movements were captured by means of the Endoscopic Video Analysis (EVA) tracking system. Nine motion analysis parameters (MAPs) were analyzed, including time, path length, depth, average speed, average acceleration, economy of area, economy of volume, idle time and motion smoothness. Data reduction was performed by means of principal component analysis, and then used to train the ANFIS net. Performance was measured by leave one out cross validation. RESULTS: The ANFIS presented an accuracy of 80.95%, where 13 experts and 21 non-experts were correctly classified. Total root mean square error was 0.88, while the area under the classifiers' ROC curve (AUC) was measured at 0.81. DISCUSSION: We have shown the usefulness of ANFIS for classification of MIS competence in a simple box trainer exercise. The main advantage of using ANFIS resides in its continuous output, which allows fine discrimination of surgical competence. There are, however, challenges that must be taken into account when considering use of ANFIS (e.g. training time, architecture modeling). Despite this, we have shown discriminative power of ANFIS for a low-difficulty box trainer task, regardless of the individual significances between MAPs. Future studies are required to confirm the findings, inclusion of new tasks, conditions and sample population.

Indicators and Estimators in P-Adaptive Boundary Elements

The paper presents the possibility of implementing a p-adaptive process with the B.E.M. Although the exemples show that good results can be obtained with a limited amount of storage and with the simple ideas explained above, more research is needed in order to improve the two main problems of the method, i.e.: the criteria of where to refine and until what degree. Mathematically based reasoning is still lacking and will be useful to simplify the decission making. Nevertheless the method seems promising and, we hope, opens a path for a series of research lines of maximum interest. Although the paper has dealt only with plane potential problem the extension to plane elasticity as well as to 3-D potential problem is straight-forward.

An adaptive population importance sampler

Monte Carlo (MC) methods are widely used in signal processing, machine learning and communications for statistical inference and stochastic optimization. A well-known class of MC methods is composed of importance sampling and its adaptive extensions (e.g., population Monte Carlo). In this work, we introduce an adaptive importance sampler using a population of proposal densities. The novel algorithm provides a global estimation of the variables of interest iteratively, using all the samples generated. The cloud of proposals is adapted by learning from a subset of previously generated samples, in such a way that local features of the target density can be better taken into account compared to single global adaptation procedures. Numerical results show the advantages of the proposed sampling scheme in terms of mean absolute error and robustness to initialization.

Rate-Adaptive LDPC-based key reconciliation for high performance quantum key distribution

The postprocessing or secret-key distillation process in quantum key distribution (QKD) mainly involves two well-known procedures: information reconciliation and privacy amplification. Information or key reconciliation has been customarily studied in terms of efficiency. During this, some information needs to be disclosed for reconciling discrepancies in the exchanged keys. The leakage of information is lower bounded by a theoretical limit, and is usually parameterized by the reconciliation efficiency (or inefficiency), i.e. the ratio of additional information disclosed over the Shannon limit. Most techniques for reconciling errors in QKD try to optimize this parameter. For instance, the well-known Cascade (probably the most widely used procedure for reconciling errors in QKD) was recently shown to have an average efficiency of 1.05 at the cost of a high interactivity (number of exchanged messages). Modern coding techniques, such as rate-adaptive low-density parity-check (LDPC) codes were also shown to achieve similar efficiency values exchanging only one message, or even better values with few interactivity and shorter block-length codes.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

A relaxation method of an alternating iterative algorithm for the Cauchy problem in linear isotropic elasticity

We propose two algorithms involving the relaxation of either the given Dirichlet data (boundary displacements) or the prescribed Neumann data (boundary tractions) on the over-specified boundary in the case of the alternating iterative algorithm of Kozlov et al. [16] applied to Cauchy problems in linear elasticity. A convergence proof of these relaxation methods is given, along with a stopping criterion. The numerical results obtained using these procedures, in conjunction with the boundary element method (BEM), show the numerical stability, convergence, consistency and computational efficiency of the proposed method.

Approximation Classes for Adaptive Methods

* This work has been supported by the Office of Naval Research Contract Nr. N0014-91-J1343, the Army Research Office Contract Nr. DAAD 19-02-1-0028, the National Science Foundation grants DMS-0221642 and DMS-0200665, the Deutsche Forschungsgemeinschaft grant SFB 401, the IHP Network “Breaking Complexity” funded by the European Commission and the Alexan- der von Humboldt Foundation.

Evaluating the Effectiveness of Discrete Trial Procedures for Teaching Receptive Discrimination to Children with Autism Spectrum Disorders

Research has found that children with autism spectrum disorders (ASD) show significant deficits in receptive language skills (Wiesmer, Lord, & Esler, 2010). One of the primary goals of applied behavior analytic intervention is to improve the communication skills of children with autism by teaching receptive discriminations. Both receptive discriminations and receptive language entail matching spoken words with corresponding objects, symbols (e.g., pictures or words), actions, people, and so on (Green, 2001). In order to develop receptive language skills, children with autism often undergo discrimination training within the context of discrete trial training. This training entails teaching the learner how to respond differentially to different stimuli (Green, 2001). It is through discrimination training that individuals with autism learn and develop language (Lovaas, 2003). The present study compares three procedures for teaching receptive discriminations: (1) simple/conditional (Procedure A), (2) conditional only (Procedure B), and (3) conditional discrimination of two target cards (Procedure C). Six children, ranging in age from 2-years-old to 5-years-old, with an autism diagnosis were taught how to receptively discriminate nine sets of stimuli. Results suggest that the extra training steps included in the simple/conditional and conditional only procedures may not be necessary to teach children with autism how to receptively discriminate. For all participants, Procedure C appeared to be the most efficient and effective procedure for teaching young children with autism receptive discriminations. Response maintenance and generalization probes conducted one-month following the end of training indicate that even though Procedure C resulted in less training sessions overall, no one procedure resulted in better maintenance and generalization than the others. In other words, more training sessions, as evident with the simple/conditional and conditional only procedures, did not facilitate participants’ ability to accurately respond or generalize one-month following training. The present study contributes to the literature on what is the most efficient and effective way to teach receptive discrimination during discrete trial training to children with ASD. These findings are critical as research shows that receptive language skills are predictive of better outcomes and adaptive behaviors in the future.