Ferdinando Giacco

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previous issues of the contest, the goal was not only to identify the best algorithm, but also to provide a collaborative effort: the decision fusion of the best individual algorithms was aiming at further improving the classification performances and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper(More)
The assumption underlying current diabetes treatment is that lowering the level of time-averaged glucose concentrations, measured as HbA1c, prevents microvascular complications. However, 89% of variation in risk of retinopathy, microalbuminuria, or albuminuria is due to elements of glycemia not captured by mean HbA1c values. We show that transient exposure(More)
The antiapoptotic protein PED/PEA-15 features an Akt phosphorylation motif upstream from Ser(116). In vitro, recombinant PED/PEA-15 was phosphorylated by Akt with a stoichiometry close to 1. Based on Western blotting with specific phospho-Ser(116) PED/PEA-15 antibodies, Akt phosphorylation of PED/PEA-15 occurred mainly at Ser(116). In addition, a mutant of(More)
Differences in susceptibility to diabetic nephropathy (DN) between mouse strains with identical levels of hyperglycemia correlate with renal levels of oxidative stress, shown previously to play a central role in the pathogenesis of DN. Susceptibility to DN appears to be genetically determined, but the critical genes have not yet been identified.(More)
We compared the performance of several supervised classification algorithms on multi-source remotely sensed images. Apart from the Multi-Layer Perceptron, K-Nearest-Neighbour and Radial Basis Function network approaches, we looked more in detail at the Support Vector Machine classifier, which recently showed promising results in our setting. In particular,(More)
We study the storage and retrieval of phase-coded patterns as stable dynamical attractors in recurrent neural networks, for both an analog and a integrate and fire spiking model. The synaptic strength is determined by a learning rule based on spike-time-dependent plasticity, with an asymmetric time window depending on the relative timing between pre and(More)
Cell migration is dependent on the control of signaling events that play significant roles in creating contractile force and in contributing to wound closure. We evaluated wound closure in fibroblasts from mice overexpressing (TgPED) or lacking ped/pea-15 (KO), a gene overexpressed in patients with type 2 diabetes. Cultured skin fibroblasts isolated from(More)
We study the collective dynamics of a Leaky Integrate and Fire network in which precise relative phase relationship of spikes among neurons are stored, as attractors of the dynamics, and selectively replayed at different time scales. Using an STDP-based learning process, we store in the connectivity several phase-coded spike patterns, and we find that,(More)
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