cAMP compartmentation is responsible for a local activation of cardiac Ca2+ channels by beta-adrenergic agonists.

The role of cAMP subcellular compartmentation in the progress of beta-adrenergic stimulation of cardiac L-type calcium current (ICa) was investigated by using a method based on the use of whole-cell patch-clamp recording and a double capillary for extracellular microperfusion. Frog ventricular cells were sealed at both ends to two patch-clamp pipettes and positioned approximately halfway between the mouths of two capillaries that were separated by a 5-micron thin wall. ICa could be inhibited in one half or the other by omitting Ca2+ from one solution or the other. Exposing half of the cell to a saturating concentration of isoprenaline (ISO, 1 microM) produced a nonmaximal increase in ICa (347 +/- 70%; n = 4) since a subsequent application of ISO to the other part induced an additional effect of nearly similar amplitude to reach a 673 +/- 130% increase. However, half-cell exposure to forskolin (FSK, 30 microM) induced a maximal stimulation of ICa (561 +/- 55%; n = 4). This effect was not the result of adenylyl cyclase activation due to FSK diffusion in the nonexposed part of the cell. To determine the distant effects of ISO and FSK on ICa, the drugs were applied in a zero-Ca solution. Adding Ca2+ to the drug-containing solutions allowed us to record the local effect of the drugs. Dose-response curves for the local and distant effects of ISO and FSK on ICa were used as an index of cAMP concentration changes near the sarcolemma. We found that ISO induced a 40-fold, but FSK induced only a 4-fold, higher cAMP concentration close to the Ca2+ channels, in the part of the cell exposed to the drugs, than it did in the rest of the cell. cAMP compartmentation was greatly reduced after inhibition of phosphodiesterase activity with 3-isobutyl-methylxanthine, suggesting the colocalization of enzymes involved in the cAMP cascade. We conclude that beta-adrenergic receptors are functionally coupled to nearby Ca2+ channels via local elevations of cAMP.

Thermodynamic parameters for the helix-coil transition of oligopeptides: molecular dynamics simulation with the peptide growth method.

The helix-coil transition equilibrium of polypeptides in aqueous solution was studied by molecular dynamics simulation. The peptide growth simulation method was introduced to generate dynamic models of polypeptide chains in a statistical (random) coil or an alpha-helical conformation. The key element of this method is to build up a polypeptide chain during the course of a molecular transformation simulation, successively adding whole amino acid residues to the chain in a predefined conformation state (e.g., alpha-helical or statistical coil). Thus, oligopeptides of the same length and composition, but having different conformations, can be incrementally grown from a common precursor, and their relative conformational free energies can be calculated as the difference between the free energies for growing the individual peptides. This affords a straightforward calculation of the Zimm-Bragg sigma and s parameters for helix initiation and helix growth. The calculated sigma and s parameters for the polyalanine alpha-helix are in reasonable agreement with the experimental measurements. The peptide growth simulation method is an effective way to study quantitatively the thermodynamics of local protein folding.

Obtenção de gel mucoadesivo de nistatina para o tratamento da candidíase oral. Desenvolvimento e caracterização de dispersões sólidas de nistatina

A nistatina (NYS) é o fármaco de primeira escolha no tratamento da candidíase oral, que frequentemente acomete mais os indivíduos imunocomprometidos e pacientes com outras desordens (diabetes não tratada, neoplasias, imunodeficiências). No mercado brasileiro, a NYS é encontrada na forma de suspensão oral aquosa, onde o procedimento para sua administração consiste em bochechar o medicamento. Apesar de haver a indicação de que se mantenha o contato direto entre fármaco e a mucosa oral, na qual se encontra a Candida spp., o que aumentaria expressivamente o sucesso terapêutico, a suspensão não apresenta tal propriedade. Assim, a NYS que é fármaco com ação efetiva contra a candidíase oral, é considerada pertencente à Classe IV do Sistema de Classificação Biofarmacêutica, ou seja, apresenta baixa solubilidade e baixa permeabilidade. A baixa solubilidade pode comprometer sua disponibilidade na cavidade oral, e consequentemente, sua ação farmacológica. Diante desse quadro, o objetivo do presente trabalho foi o desenvolvimento de dispersões sólidas de NYS para o tratamento da candidíase oral, e sua posterior incorporação em gel mucoadesivo oral, favorecendo a formulação no local de ação. As dispersões sólidas são sistemas farmacêuticos, onde um fármaco pouco solúvel em água encontra-se dispersado em um carreador, no estado sólido. Os carreadores normalmente são hidrofílicos, o que permite que esses sistemas sejam empregados para aumentar a solubilidade aquosa do fármaco. Assim, foram desenvolvidas as dispersões sólidas de NYS, pelo método de eliminação do solvente, empregando como carreadores, lactose, HPMC, poloxamer 407 e poloxamer 188. Essas foram submetidas à caracterização por análise térmica, usando os ensaios de calorimetria exploratória diferencial (DSC) e termogravimetria/termogravimetria derivada (TG/DTG). Dentre essas dispersões sólidas, aquelas que se mostraram com comportamento térmico sugerindo a formação de um novo \"sistema\", foram analisadas por meio de ensaio de solubilidade. Dessa forma, a formulação NYS DS G2 (49) se destacou, pois apresentou maior solubilidade em água (4,484 mg/mL); em pH 5,5 (4,249 mg/mL) e em pH 7,0 (4,293 mg/mL), ou seja, houve um aumento de 1,426 vezes em água; 4,227 vezes em pH 5,5; e 2,743 vezes em pH 7,0. Essa formulação foi, por fim avaliada por difração de raio-X e espectroscopia de infravermelho com transformada de Fourier, técnicas que corroboraram com a análise térmica quanto à indicação de formação da dispersão sólida. Por sua vez, essa dispersão sólida foi incorporada em 4 bases de géis mucoadesivos de carbopol ® 934 PNF, alterando apenas a concentração do polímero (0,5; 1,0; 1,5; 2,0 %p/p). Foi observado que a liberação de NYS DS G2 (49) foi superior, quando comparada à liberação de NYS MP a partir do gel, e através do ensaio de mucoadesão, percebeu-se que os géis desenvolvidos apresentaram propriedades mucoadesivas compatíveis com relatos na literatura, independentemente da quantidade de carbopol ® empregada. As características reológicas foram distintas, e foi observado que as formulações Gel A e Gel B, que possuem menor quantidade de polímero, tiverem um indicativo de comportamento de fluido newtoniano, diferente dos demais, o que pode não ser desejado para esse tipo de forma farmacêutica tópica e semi-sólida. Ao final desse trabalho, pode-se concluir que foi possível desenvolver um sistema farmacêutico na forma de dispersão sólida com maior solubilidade que a NYS pura, e sua incorporação em uma forma farmacêutica mucoadesiva, e que a liberação da NYS na forma DS foi muito superior que o fármaco na forma \"convencional\", o que permite que a NYS esteja mais disponível na cavidade oral, e também junto à mucosa bucal, o que levaria a efeito farmacológico mais efetivo do antifúngico.

Multiple Perspectives on Academic Service-Learning Partnerships at the American University in Cairo: A Mixed Method Study

This mixed method study aimed to redress the gap in the literature on academic service-learning partnerships, especially in Eastern settings. It utilized Enos and Morton's (2003) theoretical framework to explore these partnerships at the American University in Cairo (AUC). Seventy-nine community partners, administrators, faculty members, and students from a diverse range of age, citizenship, racial, educational, and professional backgrounds participated in the study. Qualitative interviews were conducted with members of these four groups, and a survey with both close-ended and open-ended questions administered to students yielded 61 responses. Qualitative analyses revealed that the primary motivators for partners' engagement in service-learning partnerships included contributing to the community, enhancing students' learning and growth, and achieving the civic mission of the University. These partnerships were characterized by short-term relationships with partners' aspiring to progress toward long-term commitments. The challenges to these partnerships included issues pertaining to the institution, partnering organizations, culture, politics, pedagogy, students, and faculty members. Key strategies for improving these partnerships included institutionalizing service-learning in the University and cultivating an institutional culture supportive of community engagement. Quantitative analyses showed statistically significant relationships between students' scores on the Community Awareness and Interpersonal Effectiveness scales and their overall participation in community service activities inside and outside the classroom, as well as a statistically significant difference between their scores on the Community Awareness scale and department offering service-learning courses. The study's outcomes underscore the role of the local culture in shaping service-learning partnerships, as well as the role of both curricular and extracurricular activities in boosting students' awareness of their community and interpersonal effectiveness. Cultivating a culture of community engagement and building support mechanisms for engaged scholarship are among the critical steps required by public policy-makers in Egypt to promote service-learning in Egyptian higher education. Institutionalizing service-learning partnerships at AUC and enhancing the visibility of these partnerships on campus and in the community are essential to the future growth of these collaborations. Future studies should explore factors affecting community partners' satisfaction with these partnerships, top-down and bottom-up support to service-learning, the value of reflection to faculty members, and the influence of students' economic backgrounds on their involvement in service-learning partnerships.

Towards Closed-loop Deep Brain Stimulation: Behavior Recognition from Human STN

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders such as Parkinson’s disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient’s behavior. Thus behavior detection is a major step in designing such systems. Various physiological signals can be used to recognize the behaviors. Subthalamic Nucleus (STN) Local field Potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. This thesis proposes novel detection and classification techniques for behavior recognition based on deep brain LFP. Behavior detection from such signals is the vital step in developing the next generation of closed-loop DBS devices. LFP recordings from 13 subjects are utilized in this study to design and evaluate our method. Recordings were performed during the surgery and the subjects were asked to perform various behavioral tasks. Various techniques are used understand how the behaviors modulate the STN. One method studies the time-frequency patterns in the STN LFP during the tasks. Another method measures the temporal inter-hemispheric connectivity of the STN as well as the connectivity between STN and Pre-frontal Cortex (PFC). Experimental results demonstrate that different behaviors create different m odulation patterns in STN and it’s connectivity. We use these patterns as features to classify behaviors. A method for single trial recognition of the patient’s current task is proposed. This method uses wavelet coefficients as features and support vector machine (SVM) as the classifier for recognition of a selection of behaviors: speech, motor, and random. The proposed method is 82.4% accurate for the binary classification and 73.2% for classifying three tasks. As the next step, a practical behavior detection method which asynchronously detects behaviors is proposed. This method does not use any priori knowledge of behavior onsets and is capable of asynchronously detect the finger movements of PD patients. Our study indicates that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from STN. We utilize a non-linear regression method to measure this inter-hemispheric connectivity and to detect the finger movements. Our experimental results using STN LFP recorded from eight patients with PD demonstrate this is a promising approach for behavior detection and developing novel closed-loop DBS systems.

A novel information theory method for filter feature selection

In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation of the mutual information between features and classes. We bypass the estimation of the probability density function with the aid of the entropic-graphs approximation of Rényi entropy, and the subsequent approximation of the Shannon one. The complexity of such bypassing process does not depend on the number of dimensions but on the number of patterns/samples, and thus the curse of dimensionality is circumvented. We show that it is then possible to outperform a greedy algorithm based on the maximal relevance and minimal redundancy criterion. We successfully test our method both in the contexts of image classification and microarray data classification.

An evolutive approach for the delineation of local labour markets

This paper presents a new approach to the delineation of local labour markets based on evolutionary computation. The main objective is the regionalisation of a given territory into functional regions based on commuting flows. According to the relevant literature, such regions are defined so that (a) their boundaries are rarely crossed in daily journeys to work, and (b) a high degree of intra-area movement exists. This proposal merges municipalities into functional regions by maximizing a fitness function that measures aggregate intra-region interaction under constraints of inter-region separation and minimum size. Real results are presented based on the latest database from the Census of Population in the Region of Valencia. Comparison between the results obtained through the official method which currently is most widely used (that of British Travel-to-Work Areas) and those from our approach is also presented, showing important improvements in terms of both the number of different market areas identified that meet the statistical criteria and the degree of aggregate intra-market interaction.

A memetic algorithm for the delineation of local labour markets

Given a territory composed of basic geographical units, the delineation of local labour market areas (LLMAs) can be seen as a problem in which those units are grouped subject to multiple constraints. In previous research, standard genetic algorithms were not able to find valid solutions, and a specific evolutionary algorithm was developed. The inclusion of multiple ad hoc operators allowed the algorithm to find better solutions than those of a widely-used greedy method. However, the percentage of invalid solutions was still very high. In this paper we improve that evolutionary algorithm through the inclusion of (i) a reparation process, that allows every invalid individual to fulfil the constraints and contribute to the evolution, and (ii) a hillclimbing optimisation procedure for each generated individual by means of an appropriate reassignment of some of its constituent units. We compare the results of both techniques against the previous results and a greedy method.

Vibration frequency measurement using a local multithreshold technique

In this paper, we demonstrate the use of a video camera for measuring the frequency of small-amplitude vibration movements. The method is based on image acquisition and multilevel thresholding and it only requires a video camera with high enough acquisition rate, not being necessary the use of targets or auxiliary laser beams. Our proposal is accurate and robust. We demonstrate the technique with a pocket camera recording low-resolution videos with AVI-JPEG compression and measuring different objects that vibrate in parallel or perpendicular direction to the optical sensor. Despite the low resolution and the noise, we are able to measure the main vibration modes of a tuning fork, a loudspeaker and a bridge. Results are successfully compared with design parameters and measurements with alternative devices.

Local convergence of quasi-Newton methods under metric regularity

We consider quasi-Newton methods for generalized equations in Banach spaces under metric regularity and give a sufficient condition for q-linear convergence. Then we show that the well-known Broyden update satisfies this sufficient condition in Hilbert spaces. We also establish various modes of q-superlinear convergence of the Broyden update under strong metric subregularity, metric regularity and strong metric regularity. In particular, we show that the Broyden update applied to a generalized equation in Hilbert spaces satisfies the Dennis–Moré condition for q-superlinear convergence. Simple numerical examples illustrate the results.

Evaluation of an integrated system for classification, assessment and comparison of services for long-term care in Europe: the eDESDE-LTC study

Background: The harmonization of European health systems brings with it a need for tools to allow the standardized collection of information about medical care. A common coding system and standards for the description of services are needed to allow local data to be incorporated into evidence-informed policy, and to permit equity and mobility to be assessed. The aim of this project has been to design such a classification and a related tool for the coding of services for Long Term Care (DESDE-LTC), based on the European Service Mapping Schedule (ESMS). Methods: The development of DESDE-LTC followed an iterative process using nominal groups in 6 European countries. 54 researchers and stakeholders in health and social services contributed to this process. In order to classify services, we use the minimal organization unit or “Basic Stable Input of Care” (BSIC), coded by its principal function or “Main Type of Care” (MTC). The evaluation of the tool included an analysis of feasibility, consistency, ontology, inter-rater reliability, Boolean Factor Analysis, and a preliminary impact analysis (screening, scoping and appraisal). Results: DESDE-LTC includes an alpha-numerical coding system, a glossary and an assessment instrument for mapping and counting LTC. It shows high feasibility, consistency, inter-rater reliability and face, content and construct validity. DESDE-LTC is ontologically consistent. It is regarded by experts as useful and relevant for evidence-informed decision making. Conclusion: DESDE-LTC contributes to establishing a common terminology, taxonomy and coding of LTC services in a European context, and a standard procedure for data collection and international comparison.

Improving classification using a Confidence Matrix based on weak classifiers applied to OCR

This paper proposes a new feature representation method based on the construction of a Confidence Matrix (CM). This representation consists of posterior probability values provided by several weak classifiers, each one trained and used in different sets of features from the original sample. The CM allows the final classifier to abstract itself from discovering underlying groups of features. In this work the CM is applied to isolated character image recognition, for which several set of features can be extracted from each sample. Experimentation has shown that the use of CM permits a significant improvement in accuracy in most cases, while the others remain the same. The results were obtained after experimenting with four well-known corpora, using evolved meta-classifiers with the k-Nearest Neighbor rule as a weak classifier and by applying statistical significance tests.

Morphological classification of microtidal sand and gravel beaches

A new classification of microtidal sand and gravel beaches with very different morphologies is presented below. In 557 studied transects, 14 variables were used. Among the variables to be emphasized is the depth of the Posidonia oceanica. The classification was performed for 9 types of beaches: Type 1: Sand and gravel beaches, Type 2: Sand and gravel separated beaches, Type 3: Gravel and sand beaches, Type 4: Gravel and sand separated beaches, Type 5: Pure gravel beaches, Type 6: Open sand beaches, Type 7: Supported sand beaches, Type 8: Bisupported sand beaches and Type 9: Enclosed beaches. For the classification, several tools were used: discriminant analysis, neural networks and Support Vector Machines (SVM), the results were then compared. As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer. Finally, an architecture with 30 neurons was chosen. Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid). The results obtained for the discriminant analysis were not as good as those obtained for the other two methods (ANN and SVM) which showed similar success.

A Novel Prediction Method for Early Recognition of Global Human Behaviour in Image Sequences

Human behaviour recognition has been, and still remains, a challenging problem that involves different areas of computational intelligence. The automated understanding of people activities from video sequences is an open research topic in which the computer vision and pattern recognition areas have made big efforts. In this paper, the problem is studied from a prediction point of view. We propose a novel method able to early detect behaviour using a small portion of the input, in addition to the capabilities of it to predict behaviour from new inputs. Specifically, we propose a predictive method based on a simple representation of trajectories of a person in the scene which allows a high level understanding of the global human behaviour. The representation of the trajectory is used as a descriptor of the activity of the individual. The descriptors are used as a cue of a classification stage for pattern recognition purposes. Classifiers are trained using the trajectory representation of the complete sequence. However, partial sequences are processed to evaluate the early prediction capabilities having a specific observation time of the scene. The experiments have been carried out using the three different dataset of the CAVIAR database taken into account the behaviour of an individual. Additionally, different classic classifiers have been used for experimentation in order to evaluate the robustness of the proposal. Results confirm the high accuracy of the proposal on the early recognition of people behaviours.

Global behavior of the Douglas–Rachford method for a nonconvex feasibility problem

In recent times the Douglas–Rachford algorithm has been observed empirically to solve a variety of nonconvex feasibility problems including those of a combinatorial nature. For many of these problems current theory is not sufficient to explain this observed success and is mainly concerned with questions of local convergence. In this paper we analyze global behavior of the method for finding a point in the intersection of a half-space and a potentially non-convex set which is assumed to satisfy a well-quasi-ordering property or a property weaker than compactness. In particular, the special case in which the second set is finite is covered by our framework and provides a prototypical setting for combinatorial optimization problems.