A few-shot identification method for stochastic dynamical systems based on residual multipeaks adaptive sampling.

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.

Inhibition of PLA2G4A attenuated valproic acid- induced lysosomal membrane permeabilization and restored impaired autophagic flux: Implications for hepatotoxicity.

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.