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This article reports several recent discoveries related to the controlled transport of paramagnetic colloidal particles above magnetic garnet films. The garnet films are thin uniaxial ferromagnetic films in which ferromagnetic domains can be organized into symmetric patterns consisting of stripes or bubbles and generate strong local magnetic field gradients. Application of an external homogeneous magnetic field on a larger scale compared to the spatial periodicity of the magnetic pattern in the film modulates the potential generated at its surface and induces the controlled motion of colloidal particles placed above the film. Several novel dynamical regimes are observed and reported, from localized trajectories to direct particle transport, depending on the geometry of the underlying magnetic pattern and on the parameters, which control the external driving field, such as frequency, strength and direction. Moreover, we show that this strategy allows separation and sorting of bi-disperse particle systems based on the particle size as well as the transport of chemical or biological cargoes attached to the colloidal carriers. Controlled transport of micro-sized cargoes (chemical or biological) by colloidal particle carriers in a microfluidic environment can bring significant contributions in several fields from targeted drug delivery to the realization of precise fluid-based micro-scale devices. [ABSTRACT FROM AUTHOR]

Metabolism is a fascinating cell machinery underlying life and disease and genome-scale reconstructions provide us with a captivating view of its complexity. However, deciphering the relationship between metabolic structure and function remains a major challenge. In particular, turning observed structural regularities into organizing principles underlying systemic functions is a crucial task that can be significantly addressed after endowing complex network representations of metabolism with the notion of geometric distance. Here, we design a cartographic map of metabolic networks by embedding them into a simple geometry that provides a natural explanation for their observed network topology and that codifies node proximity as a measure of hidden structural similarities. We assume a simple and general connectivity law that gives more probability of interaction to metabolite/reaction pairs which are closer in the hidden space. Remarkably, we find an astonishing congruency between the architecture of E. coli and human cell metabolisms and the underlying geometry. In addition, the formalism unveils a backbone-like structure of connected biochemical pathways on the basis of a quantitative cross-talk. Pathways thus acquire a new perspective which challenges their classical view as self-contained functional units.