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Inverse molecular generation is an essential task for drug discovery, and generative models offer a very promising avenue, especially when diffusion models are used. Despite their great success, existing methods are inherently limited by the lack of a semantic latent space that can not be navigated and perform targeted exploration to generate molecules with desired properties. Here, we present a property-guided diffusion model for generating desired molecules, which incorporates a sophisticated diffusion process capturing intricate interactions of nodes and edges within molecular graphs and leverages a time-dependent molecular property classifier to integrate desired properties into the diffusion sampling process. Furthermore, we extend our model to a multi-property-guided paradigm. Experimental results underscore the competitiveness of our approach in molecular generation, highlighting its superiority in generating desired molecules without the need for additional optimization steps. 

Hydrotropic solvents are a promising solvent in biomass processing due to their unique amphiphilic structure. This review summarizes recent advances in hydrotropic solvent systems with their chemical structure, amphiphilicity, roles, and mechanism.

 

Plant pathogens and herbivores can maintain forest diversity by reducing survival of tree seedlings close to conspecifics. However, how biogeographic variation in these natural enemies affects such distance‐dependent processes is unknown. Because invasive plants escape ecologically important enemies when introduced to a new range, distance‐dependent mortality may differ between their native and introduced ranges.

Here, we test whether the invasive treeTriadica sebiferaescaped distance‐dependent mortality when introduced to the United States from China, and examine the roles of natural enemies in native and introduced ranges. In both the United States and China, we performed field surveys along with field and greenhouse experiments with field‐collected soils and soil sterilization treatments.

In field surveys and the field experiment, insect damage onT. sebiferaseedlings decreased with distance to conspecific trees in the native range (China), but damage was low at all distances in the introduced range (United States). In the greenhouse experiment testing the effects of soil pathogens,T. sebiferaseedling mortality decreased with soil distance from conspecific trees in both ranges but distance‐independent mortality was higher in native range soils.

Our findings indicate that both insect herbivores and the soil biota contribute to distance‐dependent effects onT. sebiferain its native range. They suggest, however, that plants may more readily escape herbivore than soil biota distance‐dependent effects when introduced to a new range and so herbivores, rather than soil pathogens, contribute more strongly to biogeographic variation in distance‐dependent effects. These results highlight the importance of considering species biogeographic variation in distance‐dependent effects and teasing apart the roles that different natural enemies play when studying species coexistence, community diversity and biological invasions.

 

Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.