High-precision tracking of human foragers reveals adaptive social information use in the wild

Researchers combined high-precision GPS tracking, video recording, and computational modeling to study how people make foraging decisions in real competitive settings. Rather than relying on lab experiments, they observed large-scale foraging competitions to capture genuine spatial search behavior. Their analysis revealed that social context strongly shapes foraging dynamics: when individuals were struggling to find resources, they turned to cues from others to guide their search, and they stayed longer in patches when competitors were nearby. At higher social densities, this produced more concentrated, area-restricted searching. Agent-based simulations helped confirm these behavioral patterns arose from adaptive use of personal, social, and environmental information together. The work demonstrates that sociality is a central driver of human foraging choices in natural settings, and offers a methodological framework for using high-resolution tracking data to investigate real-world decision-making and cognition more broadly.

Read the original article →

Multiple protein structure alignment at scale with FoldMason

Comparing protein structures across many sequences is critical for understanding evolutionary relationships, especially when sequence similarity alone fails. This work presents FoldMason, a progressive multiple structural alignment (MSTA) tool designed to handle hundreds of thousands of protein structures simultaneously. FoldMason builds on two existing pairwise structural aligners, Foldseek and TM-align, achieving alignment quality that matches or surpasses current leading MSTA methods while running roughly 100 times faster. The authors validated the tool using Flaviviridae glycoproteins, showing that its alignments enable reliable phylogenetic inference even among proteins so divergent they fall below the sequence "twilight zone." FoldMason also computes alignment confidence scores and generates interactive visualizations. As large-scale structural databases continue to grow through computational prediction, having a fast, accurate, and freely available MSTA tool addresses a genuine bottleneck in comparative protein analysis.

Read the original article →

From sequence to function: Bridging single-molecule kinetics and molecular diversity

Single-molecule methods can reveal how individual biomolecules move, fold, and interact, but traditionally they examine one sequence at a time—making large-scale studies slow and expensive. This review examines how recent technical advances are overcoming that bottleneck by enabling highly multiplexed single-molecule experiments that simultaneously monitor millions of molecules spanning thousands of distinct sequences. By linking real-time dynamic behavior to specific nucleic acid or protein sequences, these approaches map how sequence variation reshapes the energetic landscapes governing structure and molecular interactions. Although the field is still maturing, early applications are already connecting sequence-level diversity to functional outcomes at a scale previously impossible. The authors highlight emerging opportunities this creates in drug discovery, where dynamic binding information matters, as well as in molecular diagnostics and functional genomics, where understanding sequence-function relationships across large molecular libraries is increasingly valuable.

Read the original article →

The evolution of gene regulation in mammalian cerebellum development

Researchers investigated how gene regulation has evolved in the developing cerebellum across mammals, a brain region that expanded notably during human evolution. By profiling gene expression and chromatin accessibility at single-nucleus resolution in six species—human, bonobo, macaque, marmoset, mouse, and opossum—they mapped both conserved and divergent regulatory networks. Sequence-based computational models identified core regulatory codes tied to cell identity, and by extending these models to predict chromatin accessibility across 240 mammalian species, the team reconstructed the evolutionary trajectories of human regulatory elements. This approach pinpointed elements under positive selection and linked them to specific gene expression changes, including the evolutionary gain of THRB expression in cerebellar progenitor cells. The work clarifies which regulatory programs are broadly shared across mammals and which are lineage-specific, offering new insight into the molecular basis of human brain evolution.

Read the original article →