An Artificial Neural Network for Image Classification Inspired by the Aversive Olfactory Learning Neural Circuit in Caenorhabditis elegans.

This study introduces an artificial neural network (ANN) for image classification task, inspired by the aversive olfactory learning neural circuit in Caenorhabditis elegans (C. elegans). Although artificial neural networks (ANNs) have demonstrated remarkable performance in various tasks, they still encounter challenges including excessive parameterization, high training costs and limited generalization capabilities, etc.

The "weaken-fill-repair" model for cell budding: Linking cell wall biosynthesis with mechanics.

The interplay between cellular mechanics and biochemical processes in the cell cycle is not well understood. We propose a quantitative model of cell budding in as a "weaken-fill-repair" process, linking Newtonian mechanics of the cell wall with biochemical changes that affect its properties. Our model reveals that (1) oscillations in mother cell size during budding are an inevitable outcome of the process; (2) asymmetric division is necessary for the daughter cell to maintain mechanical stiffness; and (3) although various aspects of the cell are constrained and interconnected, the budding process is governed by a single reduced parameter, ψ, which balances osmolyte accumulation with enzymatic wall-weakening to ensure homeostasis.