Transformation of Medicago truncatula with the arginine decarboxylase gene to modify polyamine metabolism toward water deficit resistance

Dissertation submitted to obtain a Ph.D. (Doutoramento) degree in Biology at the Instituto de Tecnologia Química e Biológica da Universidade Nova de Lisboa

Modulation of electrical stimulation applied to human physiology and clinical diagnostic

The use, manipulation and application of electrical currents, as a controlled interference mechanism in the human body system, is currently a strong source of motivation to researchers in areas such as clinical, sports, neuroscience, amongst others. In electrical stimulation (ES), the current applied to tissue is traditionally controlled concerning stimulation amplitude, frequency and pulse-width. The main drawbacks of the transcutaneous ES are the rapid fatigue induction and the high discomfort induced by the non-selective activation of nervous fibers. There are, however, electrophysiological parameters whose response, like the response to different stimulation waveforms, polarity or a personalized charge control, is still unknown. The study of the following questions is of great importance: What is the physiological effect of the electric pulse parametrization concerning charge, waveform and polarity? Does the effect change with the clinical condition of the subjects? The parametrization influence on muscle recruitment can retard fatigue onset? Can parametrization enable fiber selectivity, optimizing the motor fibers recruitment rather than the nervous fibers, reducing contraction discomfort? Current hardware solutions lack flexibility at the level of stimulation control and physiological response assessment. To answer these questions, a miniaturized, portable and wireless controlled device with ES functions and full integration with a generic biosignals acquisition platform has been created. Hardware was also developed to provide complete freedom for controlling the applied current with respect to the waveform, polarity, frequency, amplitude, pulse-width and duration. The impact of the methodologies developed is successfully applied and evaluated in the contexts of fundamental electrophysiology, psycho-motor rehabilitation and neuromuscular disorders diagnosis. This PhD project was carried out in the Physics Department of Faculty of Sciences and Technology (FCT-UNL), in straight collaboration with PLUX - Wireless Biosignals S.A. company and co-funded by the Foundation for Science and Technology.

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees : the PredictAL study

Background: Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods: A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score >= 8 in men and >= 5 in women. Results: 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions: The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.