A GPU-based computational framework that bridges neuron simulation and artificial intelligence.

Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical framework to generate algorithms for artificial intelligence (AI) systems. However, the expensive computational cost severely limits the applications in both the neuroscience and AI fields. The major bottleneck during simulating detailed compartment models is the ability of a simulator to solve large systems of linear equations. Here, we present a novel Dendritic Hierarchical Scheduling (DHS) method to markedly accelerate such a process. We theoretically prove that the DHS implementation is computationally optimal and accurate. This GPU-based method performs with 2-3 orders of magnitude higher speed than that of the classic serial Hines method in the conventional CPU platform. We build a DeepDendrite framework, which integrates the DHS method and the GPU computing engine of the NEURON simulator and demonstrate applications of DeepDendrite in neuroscience tasks. We investigate how spatial patterns of spine inputs affect neuronal excitability in a detailed human pyramidal neuron model with 25,000 spines. Furthermore, we provide a brief discussion on the potential of DeepDendrite for AI, specifically highlighting its ability to enable the efficient training of biophysically detailed models in typical image classification tasks.

Synthesis of Iron Nanometallic Glasses and Their Application in Cancer Therapy by a Localized Fenton Reaction.

Metallic glasses and cancer theranostics are emerging fields that do not seem to be related to each other. Herein, we report the facile synthesis of amorphous iron nanoparticles (AFeNPs) and their superior physicochemical properties compared to their crystalline counterpart, iron nanocrystals (FeNCs). The AFeNPs can be used for cancer theranostics by inducing a Fenton reaction in the tumor by taking advantage of the mild acidity and the overproduced H2 O2 in a tumor microenvironment: Ionization of the AFeNPs enables on-demand ferrous ion release in the tumor, and subsequent H2 O2 disproportionation leads to efficient (.)OH generation. The endogenous stimuli-responsive (.)OH generation in the presence AFeNPs enables a highly specific cancer therapy without the need for external energy input.