RESUMEN
Neural networks are popular data-driven modeling tools that come with high data collection costs. This paper proposes a residual-based multipeaks adaptive sampling (RMAS) algorithm, which can reduce the demand for a large number of samples in the identification of stochastic dynamical systems. Compared to classical residual-based sampling algorithms, the RMAS algorithm achieves higher system identification accuracy without relying on any hyperparameters. Subsequently, combining the RMAS algorithm and neural network, a few-shot identification (FSI) method for stochastic dynamical systems is proposed, which is applied to the identification of a vegetation biomass change model and the Rayleigh-Van der Pol impact vibration model. We show that the RMAS algorithm modifies residual-based sampling algorithms and, in particular, reduces the system identification error by 76% with the same sample sizes. Moreover, the surrogate model accurately predicts the first escape probability density function and the P bifurcation behavior in the systems, with the error of less than 1.59×10-2. Finally, the robustness of the FSI method is validated.
RESUMEN
Valproic acid (VPA) has broad efficacy against several seizures but causes liver injury limiting its prolonged clinical use. Some studies have demonstrated that VPA-induced hepatotoxicity is characterized by microvesicular hepatic steatosis. However, novel detailed mechanisms to explain VPA-induced hepatic steatosis and experimentally rigorously validated protective agents are still lacking. In this study, 8-week-old C57BL/6J mice were gavaged with VPA (500 mg/kg/d) for 4 weeks to establish an in vivo model of VPA-induced chronic liver injury. Quantitative proteomic and non-targeted lipidomic analyses were performed to explore the underlying mechanisms of VPA-induced hepatotoxicity. As a result, VPA-induced hepatotoxicity is associated with impaired autophagic flux, which is attributed to lysosomal dysfunction. Further studies revealed that VPA-induced lysosomal membrane permeabilization (LMP), allows soluble lysosomal enzymes to leak into the cytosol, which subsequently led to impaired lysosomal acidification. A lower abundance of glycerophospholipids and an increased abundance of lysophospholipids in liver tissues of mice in the VPA group strongly indicated that VPA-induced LMP may be mediated by the activation of phospholipase PLA2G4A. Metformin (Met) acted as a potential protective agent attenuating VPA-induced liver dysfunction and excessive lipid accumulation. Molecular docking and cellular thermal shift assays demonstrated that Met inhibited the activity of PLA2G4A by directly binding to it, thereby ameliorating VPA-induced LMP and autophagic flux impairment. In conclusion, this study highlights the therapeutic potential of targeting PLA2G4A-mediated lysosomal dysfunction in VPA-induced hepatotoxicity.