Alzheimer's disease is increased in diabetic patients. A defective insulin activity on the brain has been hypothesized to contribute to the neuronal cell dysregulation leading to AD, but the mechanism is not clear. We analyzed the effect of insulin on several molecular steps of amyloid precursor protein (APP) processing and β-amyloid (Aβ) intracellular accumulation in a panel of human neuronal cells and in human embryonic kidney 293 cells overexpressing APP-695. The data indicate that insulin, via its own receptor and the phosphatidylinositol-3-kinase/AKT pathway, influences APP phosphorylation at different sites. This rapid-onset, dose-dependent effect lasts many hours and mainly concerns dephosphorylation at the APP-T668 site. This effect of insulin was confirmed also in a human cortical neuronal cell line and in rat primary neurons. Cell fractionation and immunofluorescence studies indicated that insulin-induced APP-T668 dephosphorylation prevents the translocation of the APP intracellular domain fragment into the nucleus. As a consequence, insulin increases the transcription of antiamyloidogenic proteins such as the insulin-degrading enzyme, involved in Aβ degradation, and α-secretase. In contrast, the transcripts of pro-amyloidogenic proteins such as APP, β-secretase, and glycogen synthase kinase (Gsk)-3β are decreased. Moreover, cell exposure to insulin favors the nonamyloidogenic, α-secretase-dependent APP-processing pathway and reduces Aβ40 and Aβ42 intracellular accumulation, promoting their release in the extracellular compartment. The latter effects of insulin are independent of both Gsk-3β phosphorylation and APP-T668 dephosphorylation, as indicated by experiments with Gsk-3β inhibitors and with cells transfected with the nonphosphorylatable mutated APP-T668A analog. In human neuronal cells, therefore, insulin may prevent Aβ formation and accumulation by multiple mechanisms, both Gsk-3β dependent and independent.

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Apoptosis is a programmed cell death process, whose complexity led researchers to build mathematical models that could help to identify its crucial steps. In previous works, we theoretically analyzed and numerically simulated a model that describes a pathway from an external stimulus to caspase-3 activation. Here, the results of experiments performed on populations of synchronized cells treated with the inducer Apo2L/TRAIL are reported and are compared with model predictions. In particular, we have compared in vitro and in silico results relevant to the time evolutions of caspase-3 and caspase-8 activities, as well as of the dead cells fractions. In addition, the effect of the BAR gene silencing was evaluated. Caspase-3 activation and cell death is faster in silenced than in nonsilenced cells, thus confirming previous simulation results. Interestingly, Apo2L/TRAIL treatment in itself reduces the BAR gene expression. The qualitative agreement between model predictions and cell cultures behavior suggests that the model captures the essential features of the biological process and could be a tool in further studies of caspases activation. In this manuscript, we report the results of in vitro experiments aimed at revealing the dynamics of caspase activation in a cell population. A qualitative agreement between these results and a mathematical model describing a pathway from an external stimulus to caspase-3 activation was obtained, thus showing that the model captures the essential features of the biological process and may be a reliable tool in further studies of caspase activation.

In the past few years several mathematical models have been proposed to formally represent the biochemical processes that lead to the programmed death of the cell (apoptosis) starting from an intrinsic or extrinsic stimulus. In this paper we consider the model proposed by Eissing and colleagues in 2004 and, compared to the previously published results, provide several original contributions. We prove formally that the model can have one, two or three equilibrium states; one of these (the life equilibrium) represents the normal state of the cell: we state a stability criterion for this equilibrium and prove that its stability/instability is related to the number of equilibrium states. A large sample of models with randomly generated parameter vectors (representative of a population of cells) is numerically analyzed as regards both the equilibria and respective stability properties, and the dynamical behavior. Many patterns of stable/unstable equilibrium states, and different types of bifurcations are discovered. Correlations between model parameters, equilibrium patterns and equilibrium concentration of a critical protein are also carried out. The analysis of the dynamical time responses shows that the richness of behaviors accounted by the model is much larger than that implied by the classification into life-monostable, bistable, death-monostable models.