Experimental measurements of cilia distribution and fluid flow at the surface of reef-building coral uncover the crucial role of ciliary orientation in modulating nutrient transport.

This Perspective summarizes recent studies on how the humoral immune system learns to target unseen pathogen variants via feedback regulation during a limited number of antigen re-exposures, and outlines key questions at the intersection of statistical physics, machine learning, immunology, and evolutionary biology.

Using zero-crossing analysis, the authors extract diagnostically relevant information from the electric-field molecular fingerprints of human blood samples and, in a clinical study, show that deviations in zero-crossing time gaps are linked to the presence and progression of lung cancer.

This study shows that the simultaneous presence of error correction and modularity in biological systems is a typical co-occurrence rather than a coincidence, leading them to deduce a principle of error correction-enhanced evolvability.

Employing a minimal but biochemically relevant model of trigger waves, this study obtained an analytic expression for wave ignition thresholds in cell signaling in 1D and numerical solutions in 2D and 3D.

Molecular recognition sites evolve faster when coupled to time-dependent targets through an adaptive ratchet mechanism.

A robot collective can assemble and disassemble aggregates by altering local transport behavior, demonstrating that complex coordination can emerge from simple local rules.

A stochastic synaptic framework links spike timing to memory limits, showing how plasticity, noise, and homeostasis jointly shape learning, forgetting, and enforce a tradeoff between memory lifetime and early memory accuracy.

An enhanced form of mechanical proofreading during dynamic cell-cell contact helps reconcile robust clonal selection with tunable specificity in adaptive immune responses.

Two conditions subextensive mutual information and compressible interactions make neural population codes learnable from finite data revealing noise correlations as essential for neural coding.

A normalizing-flow framework maps the geometry and curvature of low-dimensional manifolds that harbor neural population activity, going beyond Gaussian and linearity assumptions to reveal nonlinear statistical dependencies among groups of neurons.

An agent-based model that incorporates photokinesis, gyrotaxis, and stochastic reorientation helps elucidate the mechanisms by which complex, population-scale diurnal cycles emerge from the swimming behavior of individual aquatic organisms.

Fluctuation-driven feedback allows eukaryotic gene silencing to selectively suppress harmful genetic elements, with aberrant transcription reinforcing silencing locally while modulating it globally.

This mathematical framework shows how intracellular gene expression transmitted through a chemically communicating and dividing cell population controls tissue development.

Turbulent transport plays an important role in fundamentally transforming odor signals from source to sensor.

Mobile membrane tethers dynamically alter wetting properties, driving the localization and organization of biomolecular condensates along complex cellular membrane geometries.

E. coli integrate environmental history through scale-free memory, performing recurrent, neural-like computation to balance growth and survival in fluctuating nutrient conditions.

Multistep reversible biochemical cascades produce a three-regime scaling structure, including apparent negative activation energies, that unifies how biological timing responds to temperature across species and scales.

A new analytical framework enables genome-wide evaluation of nucleosome positioning based on DNA elasticity.

While classical measures of spike variability could not distinguish activity across brain areas, a complementary information-theoretic measure revealed structured, stimulus-dependent dynamics in distributed brain circuits.

Canalization increases overall stability in gene regulatory networks, but transient states are disproportionately stabilized when compared to attractors that correspond to mature cell types.

Experimental measurements of cilia distribution and fluid flow at the surface of reef-building coral uncover the crucial role of ciliary orientation in modulating nutrient transport.

Atomic force microscopy is used to directly visualize conformational transitions in GM130 Golgi tether proteins, which drive condensate formation.

A framework that unifies active gel models of the actomyosin cortex and vertex models of tissues captures a number of seemingly disconnected time-dependent phenomenologies in epithelial monolayers.

The concept of inheritance entropy is introduced and experimentally demonstrated to quantitatively predict the hereditary variations in the proliferative power of stem cell lineages.

A stochastic transport model reveals that antibiotic-induced ribosome pausing triggers collective jamming on mRNA, making longer transcripts disproportionately vulnerable.

Experiments in a unicellular relative of animals validate the predictions of a model which treats organisms as Markovian Bayesian agents that learn from environmental states, providing insights into the link between within-lifetime learning and generational adaptation.

A slime mold confined by harmful blue light extensively explores the boundaries of the confinement before settling on the optimal escape strategy.

This work presents an E. coli chemosensory lattice that implements gain through non-equilibrium reactions between neighboring core signaling units rather than allosteric interactions, achieving high gain through time-scale separation.

Mapping evolutionary dynamics to Bayesian learning shows that organismal complexity tends to match environmental complexity, but rapid environmental changes may favor simpler forms.

Using disordered solids as a model, this work demonstrates how cyclic environmental change can produce robust system memory.

A simulated cortical network rapidly establishes functional circuitry through autonomous learning from mechanically coupled sensors.

Inhibition dynamics implemented in the Kuramoto model is able to reproduce the coexistence of scale free avalanches and encompassing bursts observed experimentally.

Nuclear condensates exhibit critical-like capillary behavior and unexpected bending elasticity, enabling their interfacial mechanics to be measured noninvasively in living cells.

A quantitative description of budding yeast polarization derived from live cell imaging enables systematic comparison of polarization phenotypes, revealing varying degrees of variation in physical characteristics.

This review article explores the discoveries about energy injection in cytoskeletal matter and proposes a unifying perspective that highlights how energy injection is itself a state-dependent, regulated process rather than a fixed external bath.