This study shows analytically and numerically how fluid flow inside egg cells helps keep the spindle, a key structure for cell division, securely positioned near the cell’s surface.

Advanced analysis of 3D fish trajectories reveals key behavioral patterns—rapid maneuvers and subtle orientation shifts—in male zebrafish contests that predict winner-loser dynamics, with losers escalating aggression toward the end.

Increasing chromosome numbers can enable novel traits in evolving organisms by enabling them to cross fitness valleys using redundancy, demonstrating how evolutionary innovation could select for the optimal number of chromosomes in polyploid bacteria.

AFEXplorer tailors AlphaFold’s predictions by incorporating user-defined constraints to generate alternative protein conformations that match specific functional states – a tool for exploring dynamic protein structures, such as kinase activation states and membrane transporter configurations.

Individual mitochondria transition between fragmented units and highly connected tubular structures. This study shows how the network’s architecture is linked to local parameters such as fusion and fission rates, and mechanical constraints.

This study shows analytically and numerically how fluid flow inside egg cells helps keep the spindle, a key structure for cell division, securely positioned near the cell’s surface.

Live imaging of developing Drosophila embryos reveals how internal and external stresses shape tissue shear and volumetric disorders, providing insights into the physical constraints acting during morphogenesis.

Stochastic simulations elucidate the roles and interplay of branching, connectivity and dynamical fusion and fission on transport of proteins and other molecules in mitochondrial networks.

Advanced analysis of 3D fish trajectories reveals key behavioral patterns—rapid maneuvers and subtle orientation shifts—in male zebrafish contests that predict winner-loser dynamics, with losers escalating aggression toward the end.

Studies of regenerating Hydra confined in narrow channels reveal that geometric frustration can induce multiaxial morphologies, suggesting that mechanical forces play a key role in patterning the animal’s body plan.

By extending a previous segmentation clock model to include memory, the authors offer new insights into entrainment and explain how embryonic cells can adapt their internal rhythms in response to external cues.

A dynamical systems analysis of scRNA-seq data reveals that during cell phenotypic transitions, intercommunity interactions spike to coordinate global gene expression reprogramming, guiding cells toward a specific phenotype.

Using a geometric deep learning model, this study demonstrates prediction of collective cell dynamics from static images using both experimental and synthetic datasets, and identifies key features influencing model accuracy with ablation study.

Operating near a bifurcation point, olfactory neurons achieve robust encoding of odor dynamics without the need for fine-tuning, a crucial property that might explain Drosophila’s ability to navigate fluctuating odor plumes.

Combining machine learning for structure prediction with quantum-inspired optimization for sequence selection, a new algorithm enables efficient and stable protein design.

Residue Level Alignment integrates protein sequence and structure information in a self-supervised model, improving speed and precision in predicting protein binding and structural stability.

Taking a control theory approach, a proposed method is able to guide plastic neural networks with arbitrary initial connectivity toward a desired function through adequate spatiotemporal stimulation, demonstrating a potential pathway to computation based on real neurons.

New experiments and modeling show that E. coli use proton-ion antiporters to modulate membrane potential, and that the strength of the resulting proton motive force governs the bacterial ability to maintain near-neutral pH and cellular homeostasis.

Sparse connectivity between brain hemispheres is sufficient to learn and achieve bilateral alignment based on a realistic local learning rule.

The well-coordinated movement of chromosomes from the cell’s periphery to its center—a critical aspect of cell division— can be driven by length-dependent pulling forces generated by motor proteins and passive crosslinkers, as shown in this study.

KnotFold, a method that mutates conserved cysteine residues in multiple sequence alignments to simulate protein coevolution, enables AlphaFold2 to correct mispredicted disulfide connectivity patterns.

A benchmark reveals a counterintuitive “withdrawal effect” where biological sensors become more sensitive after briefly recovering from high ligand exposure, even in comparison to a fresh sensor starting at a low-ligand concentration environment.

Cell size, stiffness, and environment geometry dictate cell migration patterns, which explains both healthy and cancer cell behaviors - this study provides a general framework to predict how cells respond to confinement.

Increasing chromosome numbers can enable novel traits in evolving organisms by enabling them to cross fitness valleys using redundancy, demonstrating how evolutionary innovation could select for the optimal number of chromosomes in polyploid bacteria.

Based on an in vitro 3D ECM model, filopodial cells characterized by their dynamic protrusions and enhanced motility, emerge as key drivers of tumor invasion, adapting to and remodeling their microenvironment.