Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.

Feedback como estratégia de aprendizado no ensino médico

Fornecer feedback aos alunos é um importante aspecto da aprendizagem e um papel essencial dos docentes. No contexto da educação médica clínica, feedback se refere às informações que descrevem o desempenho dos alunos em determinada situação ou atividade. A habilidade de dar e receber feedback melhora os resultados da aprendizagem, uma vez que fornece a base para a aprendizagem autodirecionada e para a reflexão crítica, auxilia os alunos a corrigirem seus erros, reforça comportamentos desejáveis e mostra como o aluno pode melhorar. Apesar da evidente falta de feedback durante o curso médico, os alunos desejam e valorizam essa ferramenta construtiva, considerando-a um aspecto importante do ensino de qualidade. O feedback eficaz deve ser: assertivo, respeitoso, descritivo, oportuno e específico. Docentes e alunos deveriam ser preparados para dar e receber feedback. Coordenadores e diretores deveriam reconhecer o papel do feedback como uma importante estratégia de ensino- aprendizagem na graduação.

Feedback de usuários como subsídio para avaliação do estudante de medicina

A avaliação é fundamental para o processo ensino-aprendizagem. Diferentes métodos de avaliação e diversos atores envolvidos na avaliação podem fornecer elementos distintos, que, somados, fornecem melhor compreensão sobre a efetividade do processo educacional em suas variadas dimensões. A avaliação de habilidades e atitudes de estudantes tem recebido grande atenção recentemente. O envolvimento de pacientes no processo pode ser contributivo, pois sua perspectiva acrescenta informações ímpares. O presente estudo avaliou a aquisição de competências e habilidades de estudantes de Medicina no internato de Obstetrícia, sob o ponto de vista de gestantes. As pacientes responderam a um questionário segundo escala de Likert, com itens de avaliação divididos em habilidades de comunicação, exame físico e profissionalismo. Os resultados mostraram boa avaliação dos estudantes em geral, o que atribuímos ao sentimento de gratidão das pacientes. Algumas questões com maiores frequências de respostas negativas, porém, apontam aspectos que merecem maior atenção da escola médica pelo impacto que podem trazer à prática profissional. A perspectiva de pacientes na avaliação do estudante de Medicina poderá balizar estratégias de feedback para qualificar a formação médica.

Neural regulation of the stress response: glucocorticoid feedback mechanisms

The mammalian stress response is an integrated physiological and psychological reaction to real or perceived adversity. Glucocorticoids are an important component of this response, acting to redistribute energy resources to both optimize survival in the face of challenge and to restore homeostasis after the immediate challenge has subsided. Release of glucocorticoids is mediated by the hypothalamo-pituitary-adrenal (HPA) axis, driven by a neural signal originating in the paraventricular nucleus (PVN). Stress levels of glucocorticoids bind to glucocorticoid receptors in multiple body compartments, including the brain, and consequently have wide-reaching actions. For this reason, glucocorticoids serve a vital function in negative feedback inhibition of their own secretion. Negative feedback inhibition is mediated by a diverse collection of mechanisms, including fast, non-genomic feedback at the level of the PVN, stress-shut-off at the level of the limbic system, and attenuation of ascending excitatory input through destabilization of mRNAs encoding neuropeptide drivers of the HPA axis. In addition, there is evidence that glucocorticoids participate in stress activation via feed-forward mechanisms at the level of the amygdala. Feedback deficits are associated with numerous disease states, underscoring the necessity for adequate control of glucocorticoid homeostasis. Thus, rather than having a single, defined feedback ‘switch’, control of the stress response requires a wide-reaching feedback ‘network’ that coordinates HPA activity to suit the overall needs of multiple body systems.