Summary: Lipid droplets (LDs) are ubiquitous and specialized organelles in eukaryotic cells. Consisting of a triacylglycerol core surrounded by a monolayer of membrane lipids, LDs are decorated with proteins and have myriad functions, from carbon/energy storage to membrane lipid remodeling and signal transduction. The biogenesis and turnover of LDs are therefore tightly coordinated with cellular metabolic needs in a fluctuating environment. Lipid droplet turnover requires remodeling of the protein coat, lipolysis, autophagy and fatty acid β‐oxidation. Several key components of these processes have been identified in Chlamydomonas (Chlamydomonas reinhardtii), including the major lipid droplet protein, a CXC‐domain containing regulatory protein, the phosphatidylethanolamine‐binding DTH1 (DELAYED IN TAG HYDROLYSIS1), two lipases and two enzymes involved in fatty acid β‐oxidation. Here, we review LD turnover and discuss its physiological significance in Chlamydomonas, a major model green microalga in research on algal oil.

In this study, a novel type of swarm intelligence algorithm referred as the anas platyrhynchos optimizer is proposed by simulating the cluster action of the anas platyrhynchos. Starting from the core of swarm intelligence algorithm, on the premise of the use of few parameters and ease in implementation, the mathematical model and algorithm flow of the anas platyrhynchos optimizer are given, and the balance between global search and local development in the algorithm is ensured. The algorithm was applied to a benchmark function and a cooperative path planning solution for multi-UAVs as a means of testing the performance of the algorithm. The optimization results showed that the anas platyrhynchos optimizer is more superior in solving optimization problems compared with the mainstream intelligent algorithm. This study provides a new idea for solving more engineering problems.