Increased antiparkinson efficacy of the combined administration of VEGF- and GDNF-loaded nanospheres in a partial lesion model of Parkinson's disease

Current research efforts are focused on the application of growth factors, such as glial cell line-derived neurotrophic factor (GDNF) and vascular endothelial growth factor (VEGF), as neuroregenerative approaches that will prevent the neurodegenerative process in Parkinson's disease. Continuing a previous work published by our research group, and with the aim to overcome different limitations related to growth factor administration, VEGF and GDNF were encapsulated in poly(lactic-co-glycolic acid) nanospheres (NS). This strategy facilitates the combined administration of the VEGF and GDNF into the brain of 6-hydroxydopamine (6-OHDA) partially lesioned rats, resulting in a continuous and simultaneous drug release. The NS particle size was about 200 nm and the simultaneous addition of VEGF NS and GDNF NS resulted in significant protection of the PC-12 cell line against 6-OHDA in vitro. Once the poly(lactic-co-glycolic acid) NS were implanted into the striatum of 6-OHDA partially lesioned rats, the amphetamine rotation behavior test was carried out over 10 weeks, in order to check for in vivo efficacy. The results showed that VEGF NS and GDNF NS significantly decreased the number of amphetamine-induced rotations at the end of the study. In addition, tyrosine hydroxylase immunohistochemical analysis in the striatum and the external substantia nigra confirmed a significant enhancement of neurons in the VEGF NS and GDNF NS treatment group. The synergistic effect of VEGF NS and GDNF NS allows for a reduction of the dose by half, and may be a valuable neurogenerative/neuroreparative approach for treating Parkinson's disease.

Low Climate Stabilisation under Diverse Growth and Convergence Scenarios

4 p.

Low Climate Stabilisation under Diverse Growth and Convergence Scenarios

9 p.

Model of sources: a proposal for the hierarchy, merging strategy and representation of the information sources in virtual models of historical buildings

Contributed to: Fusion of Cultures: XXXVIII Annual Conference on Computer Applications and Quantitative Methods in Archaeology – CAA2010 (Granada, Spain, Apr 6-9, 2010)

An observer-based vaccination control law for an SEIR epidemic model based on feedback linearization techniques for nonlinear systems

This paper presents a vaccination strategy for fighting against the propagation of epidemic diseases. The disease propagation is described by an SEIR (susceptible plus infected plus infectious plus removed populations) epidemic model. The model takes into account the total population amounts as a refrain for the illness transmission since its increase makes the contacts among susceptible and infected more difficult. The vaccination strategy is based on a continuous-time nonlinear control law synthesised via an exact feedback input-output linearization approach. An observer is incorporated into the control scheme to provide online estimates for the susceptible and infected populations in the case when their values are not available from online measurement but they are necessary to implement the control law. The vaccination control is generated based on the information provided by the observer. The control objective is to asymptotically eradicate the infection from the population so that the removed-by-immunity population asymptotically tracks the whole one without precise knowledge of the partial populations. The model positivity, the eradication of the infection under feedback vaccination laws and the stability properties as well as the asymptotic convergence of the estimation errors to zero as time tends to infinity are investigated.

Spinal circuits can accommodate interaction torques during multijoint limb movements

The dynamic interaction of limb segments during movements that involve multiple joints creates torques in one joint due to motion about another. Evidence shows that such interaction torques are taken into account during the planning or control of movement in humans. Two alternative hypotheses could explain the compensation of these dynamic torques. One involves the use of internal models to centrally compute predicted interaction torques and their explicit compensation through anticipatory adjustment of descending motor commands. The alternative, based on the equilibrium-point hypothesis, claims that descending signals can be simple and related to the desired movement kinematics only, while spinal feedback mechanisms are responsible for the appropriate creation and coordination of dynamic muscle forces. Partial supporting evidence exists in each case. However, until now no model has explicitly shown, in the case of the second hypothesis, whether peripheral feedback is really sufficient on its own for coordinating the motion of several joints while at the same time accommodating intersegmental interaction torques. Here we propose a minimal computational model to examine this question. Using a biomechanics simulation of a two-joint arm controlled by spinal neural circuitry, we show for the first time that it is indeed possible for the neuromusculoskeletal system to transform simple descending control signals into muscle activation patterns that accommodate interaction forces depending on their direction and magnitude. This is achieved without the aid of any central predictive signal. Even though the model makes various simplifications and abstractions compared to the complexities involved in the control of human arm movements, the finding lends plausibility to the hypothesis that some multijoint movements can in principle be controlled even in the absence of internal models of intersegmental dynamics or learned compensatory motor signals.