Swarms - The primary theoretical objective of RG.BIO was to extend equilibrium RG techniques to the off-equilibrium case of strongly correlated biological systems. We wrote a novel set of field dynamical equations for the description of swarms. After a considerable amount of theoretical work, RG.BIO found a new non-trivial RG fixed point, where both activity and inertial effects are relevant and calculated the dynamical critical exponent z at one loop. The final results are: experiments z=1.37 ± 0.11; numerical simulations z=1.35 ± 0.04; RG (one loop) z=1.35. These results concluded a long endeavor to prove that the RG can be applied successfully to strongly correlated biological systems. The harmony attained between theory, experiments and simulations is by far the most important result of RG.BIO.
Flocks - RG.BIO introduced a novel field theory for the description of anomalous correlations in flocks: a marginal speed-restoring force, which fiercely suppresses large speed fluctuations, while leaving virtually free small speed fluctuations, reproduces perfectly the experimental data on flocks. Collective turns in starling flocks propagate linearly with negligible attenuation, indicating the existence of an underdamped sector in the dispersion relation, which should yield a spin-wave form of the correlation function. To measure this one needs long time acquisitions, which was previously impossible with fixed 3D cameras. An experimental achievement of RG.BIO was the realization of a new panning system for 3D tracking. We successfully collected new long-time acquisitions on bird flocks, which allowed us to give an accurate determination of the correlation functions. What we discover left us startled: the very form of the correlation function seemed completely incompatible with the one predicted by the theory. In the end, we understood that we had to add a new Fermi-Pasta-Ulam-Tsingou coupling to the flocks equations of motion, to sustain soliton propagation. The results are excellent: we find linear propagation of information, even in presence of overdamped correlation functions identical to the experimental ones.
Stem Cells - Surgical use of cell-material constructs has attracted attention for more than 20 years, reflecting large and mostly unmet patient demand. Current approaches are based on in vitro expansion of bone marrow stromal cells (BMSCs) that imply long term out-of-control in vitro expansion. It has been discovered that BMSCs are highly heterogeneous in the way they grow in vitro and behave in vivo, which is one of the most critical issues preventing the development of standardized therapeutic approaches for skeletal tissue regeneration. We have tackled these problems by assessing the in vitro inherent growth property (pattern of clonal growth) of BMSCs. Through lineage tracing studies, RG.BIO investigated their developmental differences with the aim to identify the origin of the variability among the originating cells. We have determined that within each colony the number of inactive cells is strongly correlated to the kinetics of the colony, providing an important tool to differentiate different colonies. We also found an hereditary relation between the mother-daughter cells, which we are able to uncover by using a new definition of entropy of the colony.
Malaria mosquitos - RG.BIO carried out the first large-scale 3D analysis of malaria mosquito swarms, unveiling the mechanisms that regulate swarm structure and that govern mating choices. For the first time, we recorded male-female mating events in 3D, which is a remarkable progress in the field. These results represent the first step towards a quantitative description of swarming and courtship behavior in the key vector of malaria. The new 3D data directed our work in two main directions. On the one hand, we focused on the dynamics of courtship and mating. Here we faced the limitation of our original acquisition system, which could not discriminate between males and females, and we decided to develop a novel technique. On the other hand, we focused on the study of collective behavior. This required an experimental effort to expand our dataset, which now includes about 30 swarms, with up to 400 individuals, a key database for any future malaria studies.
