New research reveals an innovative wildlife forensics method that uses advanced genetic tools and local DNA databases to help authorities solve complex environmental crimes involving multiple species. By analyzing real cases of poisoned vultures and poached gazelles, thr research proves that even mixed or degraded evidence can be used to identify species, trace their origins, and confirm criminal activity beyond reasonable doubt. This is critical because wildlife crime is a major driver of biodiversity loss worldwide, and the ability to investigate and prosecute these cases effectively is essential for protecting endangered species and enforcing conservation laws.

Several species of fruit fly larvae have independently developed a preference for cooler temperatures, showing that evolution can follow similar paths in different species when facing similar environments. 

The way each larva crawls, including how fast they move and how often they turn, reveals their unique temperature preferences. 

Not only do species differ in the exact temperatures they prefer, but also in how flexible they are: some stick to a narrow range, while others are more adaptable. 

Computer simulations suggest that these behavioural differences come from changes in how the larvae’ nervous systems balance avoiding heat versus avoiding cold, rather than how sensitive they are to temperature itself. 

Scientists from A*STAR Institute of Molecular and Cell Biology (A*STAR IMCB) and Singapore General Hospital (SGH) developed an artificial intelligence (AI)-powered scoring system capable of predicting the recurrence of hepatocellular carcinoma (HCC), the most common form of liver cancer. Named the Tumour Immune Microenvironment Spatial (TIMES) score, this study was recently featured as the cover article in the scientific journal Nature—a recognition that underscores the global significance and impact of the research.