Fungi produce a vast and complex array of chemical compounds known as secondary metabolites. While not essential for their basic growth, these molecules play critical roles in how fungi interact with their environment, defend against competitors, and communicate. The genetic blueprints for these compounds are neatly organized into biosynthetic gene clusters. Thanks to breakthroughs in genomics, metabolomics, and synthetic biology, we are now able to explore these pathways like never before, even awakening "silent" gene clusters to uncover novel molecules. This Article Collection aims to bring together the latest research and cutting-edge perspectives in this dynamic field.

Understanding fungal secondary metabolism is vital for both science and society. Many of our most important medicines, including the antibiotic penicillin, the immunosuppressant cyclosporin, and cholesterol-lowering statins, originated from fungi. As we face growing challenges like antibiotic resistance, the fungal kingdom represents a massive, untapped resource for discovering new drugs. On the other hand, some fungal metabolites are harmful mycotoxins that can contaminate food supplies, posing a significant threat to global health and food security. By studying how these compounds are made, we can unlock new therapeutic solutions and develop better strategies to protect our food.

This Article Collection will explore the multifaceted world of fungal secondary metabolism and biosynthesis. We invite contributions on a range of subtopics, including but not limited to: (1) The discovery, structure, and function of novel secondary metabolites; (2) The use of genomics and bioinformatics to identify and analyze biosynthetic gene clusters; (3) The genetic and epigenetic mechanisms that regulate these pathways; (4) The application of synthetic biology and heterologous expression to produce new compounds; and (5) The ecological roles and evolutionary origins of fungal secondary metabolites. We welcome Original Research articles, Reviews, Methods, and Perspectives to provide a comprehensive overview of the field.

5 Keywords:

Fungal secondary metabolites

Biosynthesis

Synthetic biology

Genomic mining

Metabolic regulation

Extended reality (XR) aims for "immersion," requiring displays to simultaneously deliver a wide field of view (FOV) and true 3D imagery free of vergence-accommodation conflict (VAC). Researchers in China have reported a near-eye light-field display architecture based on a heterogeneous metalens array. By integrating lens and spatially heterogeneous prism phase designs with nanoimprint technology, the array overcomes the aberration-induced FOV limit of conventional microlens arrays, providing a hardware path for next-generation immersive XR displays.

In the International Journal of Extreme Manufacturing, researchers have built a flexible and ultra-fast artificial synapse printed entirely from room-temperature liquid inks that dissolves on demand in six minutes. The work shows that high-performance and brain-inspired hardware does not require extreme vacuum chambers, rare metals, or permanent electronic waste.

The research group of Xuefeng Jiang at East China Normal University has long focused on the scientific research of upgrading and degrading waste plastics. Relying on a self-built photocatalytic reaction instrumentation platform, they have established a room-temperature and ambient-pressure catalytic upgrading and recycling system covering various strongly inert polymers such as polyester, polyphenylene sulfide, polysulfone, and gem-dimethyl plastics. Recently, in collaboration with Yujie Song of Hainan University, they achieved the efficient conversion of polystyrene to high-purity benzoic acid under room-temperature, ambient-pressure, and visible light conditions using a homogeneous/multiphase synergistic dynamic enhanced photocatalysis strategy. The article was published as an open access Research Article in CCS Chemistry, the flagship journal of the Chinese Chemical Society.

With the rapid development of 6G space–air–ground integrated communication networks, low Earth orbit (LEO) satellite constellations, leveraging their advantages of wide-area coverage and freedom from geographic constraints, have become key infrastructure for achieving global seamless connectivity. However, due to the relative motion among satellites in different orbits, inter-satellite links (ISLs) exhibit periodic dynamic on–off characteristics, among which a portion of the interruptions are predictable topological changes. Conventional Open Shortest Path First (OSPF) protocols compute shortest paths solely based on link distance, without considering link effective duration or bandwidth constraints, rendering them inadequate for adapting to the dynamic topological characteristics of satellite networks. Although fast reroute strategies can address sudden link failures, they consume substantial bandwidth resources and cannot provide protection for all nodes across the entire network. Therefore, how to proactively switch service paths before predictable link interruptions occur, so as to minimize service disruption and resource overhead, has become a core issue in ensuring service continuity in LEO satellite networks.

With growing concerns over the impact threat of near-Earth small bodies and the utilization of space resources, the orbital evolution of binary asteroid systems has become an important subject in space science. When describing the full two-body dynamics of such systems, the gravitational potential of irregular bodies is determined by both their positions and attitudes, leading to coupling between translational and rotational motions, and the resulting model complexity significantly exceeds that of the classical two-body problem. Although existing numerical methods, such as explicit Runge–Kutta integrators, are widely used, they fail to preserve the symplectic structure and Lie group geometric properties of the system. In long-term simulations, key conserved quantities such as total energy and angular momentum are prone to numerical drift, severely undermining the long-term credibility of orbital predictions. While Lie group variational integrators can preserve geometric structure to a certain extent, their implicit equations are formulated on Lie group elements, which incurs substantial computational overhead. Therefore, how to construct a high-performance integration method that simultaneously achieves numerical accuracy, structure preservation, and computational efficiency has become a core challenge in the long-term evolutionary simulation of binary asteroid systems.

With the intensifying space confrontation in geostationary orbit (GEO), the U.S. GSSAP (Geosynchronous Space Situational Awareness Program) satellites have conducted hundreds of close-range observation operations on dozens of on-orbit satellites in the vicinity of GEO. The acquisition of multi-aspect information from non-cooperative targets has thus become a critical component of space security assessment. Close-range spacecraft operations, which employ relative motion configurations such as fly-around, hovering, and drifting flight, provide an effective technical means for approaching and observing targets to obtain multi-aspect payload information. However, existing studies predominantly focus on the control design of a single relative motion configuration, which fails to satisfy the complex mission requirements of multi-aspect observation. The combination of multiple models for observation presents multiple challenges, including smooth switching between modes, fuel optimization, strategy design algorithms, and analysis of payload parameter effects. Therefore, how to coordinately plan a sequential combination of multiple close-range operation models under minimum fuel constraints to efficiently acquire multi-aspect information of non-cooperative targets has become a key bottleneck in enhancing space situational awareness capabilities.