A new avalanche model for solar flares

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Drug-loaded nanocarriers : passive targeting and crossing of biological barriers

Poor bioavailability and poor pharmacokinetic characteristics are some of the leading causes of drug development failure. Therefore, poorly-soluble drugs, fragile proteins or nucleic acid products may benefit from their encapsulation in nanosized vehicles, providing enhanced solubilisation, protection against degradation, and increased access to pathological compartments. A key element for the success of drug-loaded nanocarriers (NC) is their ability to either cross biological barriers themselves or allow loaded drugs to traverse them to achieve optimal pharmacological action at pathological sites. Depending on the mode of administration, NC may have to cross different physiological barriers in their journey towards their target. In this review, the crossing of biological barriers by passive targeting strategies will be presented for intravenous delivery (vascular endothelial lining, particularly for tumour vasculature and blood-brain barrier targeting), oral administration (gastrointestinal lining) and upper airway administration (pulmonary epithelium). For each specific barrier, background information will be provided on the structure and biology of the tissues involved as well as available pathways for nano-objects or loaded drugs (diffusion and convection through fenestration, transcytosis, tight junction crossing, etc.). The determinants of passive targeting − size, shape, surface chemistry, surface patterning of nanovectors − will be discussed in light of current results. Perspectives on each mode of administration will be presented. The focus will be on polymeric nanoparticles and dendrimers although advances in liposome technology will be also reported as they represent the largest body in the drug delivery literature.

A Coupled 2 × 2D Babcock–Leighton Solar Dynamo Model. I. Surface Magnetic Flux Evolution

The need for reliable predictions of the solar activity cycle motivates the development of dynamo models incorporating a representation of surface processes sufficiently detailed to allow assimilation of magnetographic data. In this series of papers we present one such dynamo model, and document its behavior and properties. This first paper focuses on one of the model's key components, namely surface magnetic flux evolution. Using a genetic algorithm, we obtain best-fit parameters of the transport model by least-squares minimization of the differences between the associated synthetic synoptic magnetogram and real magnetographic data for activity cycle 21. Our fitting procedure also returns Monte Carlo-like error estimates. We show that the range of acceptable surface meridional flow profiles is in good agreement with Doppler measurements, even though the latter are not used in the fitting process. Using a synthetic database of bipolar magnetic region (BMR) emergences reproducing the statistical properties of observed emergences, we also ascertain the sensitivity of global cycle properties, such as the strength of the dipole moment and timing of polarity reversal, to distinct realizations of BMR emergence, and on this basis argue that this stochasticity represents a primary source of uncertainty for predicting solar cycle characteristics.