Cells dynamically generate, transmit, and dissipate stress. Central to these processes is the actomyosin cortex, an active contractile material that drives cellular mechanical behavior. While prior studies have focused on freely contracting actomyosin systems, the role of mechanical constraints such as adhesion to boundaries remains less explored. To address this, we employ reconstituted actomyosin gels to investigate cellular contractility. We study contraction dynamics under pinned boundary conditions, where the gel is adhered transversely to two opposing surfaces, mimicking supracellular actomyosin networks in tissues and embryos. We find that pinned contraction leads to stress buildup, delaying contraction, producing intermittent dynamics, and generating spatially nonuniform strain fields. Stress is relieved through several pathways, including active-stress-driven symmetric constriction and defect-driven processes such as boundary detachment and internal rupture. We develop a hydrodynamic model incorporating elastic, viscous, and active stress contributions that distinguishes between stress-accumulation and stress-release phases and links variations in active stress to the observed intermittent dynamics. The model predicts distinct energy relaxation rates before and after detachment events, providing insight into stress dissipation. We compare experiments with numerical simulations, which reproduce the observed behavior and reveal how internal energy is generated and dissipated during stress buildup and relaxation. Together, our results demonstrate how boundary conditions and spatial heterogeneity govern the mechanical behavior of contractile active gels. These findings provide insight into stress regulation in cellular and tissue-scale systems and may inform the design of adaptive soft materials and bioinspired robotic systems.

Collective emission in light-harvesting assemblies is governed by the local transition dipole and finite geometry of emitting units, a fact that point-dipole approximation obscures. To go beyond this picture, we develop a non-Hermitian Hamiltonian using the quantum electrodynamic dyadic Green's tensor for a purple bacteria. We construct it for the isolated 24-bacteriochlorophyll conical frustum and its P42$_1$2 crystallographic assembly. The P42$_1$2 unit-cell symmetry is found to invert the bright-dark ordering of the single ring, placing subradiant states at the low-energy end and revealing the entire crystal to be the energy-harvesting entity. Tilt-driven switching is activated only in crystal geometries where the finite dipole-carrier (LH2) lies perpendicular to the growth plane. Vacancy and orientational disorder work only in cooperation to renormalize the switching threshold from higher polar angles to lower values.

Multispecies ecosystems modelled by generalized Lotka-Volterra equations exhibit stationary population abundances, where large number of species often coexist. Understanding the precise conditions under which this is at all feasible and what triggers species extinctions is a key, outstanding problem in theoretical ecology. Using standard methods of random matrix theory, I show that distributions of species abundances are Gaussian at equilibrium, in the weakly interacting regime. One consequence is that feasibility is generically broken before stability, for large enough number of species. I further derive an analytical expression for the probability that $n=0,1,2,...$ species go extinct and conjecture that a single-parameter scaling law governs species extinctions. These results are corroborated by numerical simulations in a wide range of system parameters.

The RNA world hypothesis suggests a pathway of how life emerged on early earth. It assumes that life started with RNA based systems, capable of storing, transmitting and replicating information, envisioning that monomers and short RNA oligomers interact to form longer strands, eventually becoming catalytically active ribozymes. Key reactions in RNA pools are hybridization, dehybridization, templated ligation, and cleavage. Those reactions depend on many environmental parameters and the wide range of possible configurations among interacting strands. In order to scan such high dimensional parameter spaces, efficient descriptions are needed. Motif rate equations project complex strand reactor dynamics onto sequence motif space. Here we present a Bayesian inference framework to infer their parameters from ligation count data produced by strand reactor simulations. This provides a framework to match the simpler motif rate equations to more complex simulations. Additionally, it is a step towards inferring reaction rate constants directly from experimental data, including rigorous uncertainty estimation. This could be an essential procedure to connect theory and experiment, and deepen our understanding of the essential features necessary for life to emerge.

Since the publication of our review article Hyperspectral imaging solutions for brain tissue metabolic and hemodynamic monitoring: past, current and future developments in 2018, the technological and applicational landscape of the use of hyperspectral imaging (HSI) in brain sciences has evolved and transformed significantly. The number of studies and works where HSI has been deployed in its many forms to map and monitor the haemodynamic and metabolic states of cerebral tissues have grown exponentially, to such a point where an update on the cur-rent state of the art is timely, and we believe would be desirable for both long-term experts in the field, as well as for any new researcher approaching it for the first time. In this commentary, we provide a renewed perspective on the newest and latest developments in brain haemodynamic and metabolic monitoring with HSI over the past eight years. Our hope is that even greater breakthroughs and broader, more numerous novel applications will come forward in the future for the technology, that may benefit from this new overview, as they did from the original one.

The variation of the oxygen enhancement ratio (OER) across linear energy transfer (LET) currently lacks a comprehensive mechanistic interpretation and a mechanistic model. Our earlier research revealed a significant correlation between the distribution of double-strand breaks (DSBs) within 3D genome and radiation-induced cell death, which offers valuable insights into the oxygen effect. We propose a model where the reaction of oxygen is represented as the probability of inducing DNA strand breaks. Then it is integrated into a track-structure Monte Carlo simulation to investigate the impact of oxygen on the distribution of DSBs within 3D genome. Using the parameters from our previous study, we calculate the OER values related to cell survival. Results show that the incidence ratios of clustered DSBs within a single topologically associating domain (TAD) (case 2) and within frequently interacting TADs (case 3) under aerobic and hypoxic conditions align with the trend in the OER of cell survival across LET. Our OER curves exhibit good correspondence with experimental data. This study provides a potentially mechanistic explanation for changes in OER across LET. High-LET irradiation leads to dense ionization events, resulting in an overabundance of lesions that readily induce case 2 and case 3, which have substantially higher probabilities of cell killing than other damage patterns. This may contribute to the main mechanism governing the variation of OER for high LET. Our study further underscores the importance of the DSB distribution within 3D genome in the context of radiation-induced cell death.

Decision-making is the process of selecting an action among alternatives, allowing biological and artificial systems to navigate complex environments and optimize behavior. While neural systems rely on neuron-based sensory processing and evaluation, decision-making also occurs in organisms without a centralized organizing unit, such as the unicellular slime mold \textit{Physarum polycephalum}. Unlike neural systems, P. polycephalum relies on rhythmic peristaltic contractions to drive internal flows and redistribute mass, allowing it to adapt to its environment. However, while previous studies have focused on the outcomes of these decisions, the underlying mechanical principles that govern this mass relocation remain unknown. Here, we investigate the exploration process of P. polycephalum confined by blue light into polygonal shapes up to its escape. While the escape occurs along the longest axis of the polygones, independent of confinement shape, the exploration process prior to escape extends protrusions almost everywhere around a shape boundary. We find protrusions to align with the direction of peristaltic contraction waves driving mass relocation. Mapping out contraction modes during exploration in detail we observe an ongoing switching between different dominant principle contraction modes. Only over the course of time does the organism ultimately settle on the contraction mode most efficient for transport, which coincides with the escape. Thus, we find that only harsh environmental confinement triggers optimal behaviour which is reached by long time re-organization of the flow patterns. Our findings provide insights into the mechanics of decision-making in non-neuronal organisms, shedding light on how decentralized systems process environmental constraints to drive adaptive behavior.

Charge diffusion through desoxyribonucleic acid (DNA) is a physico-chemical phenomenon that on the one hand is being explored for technological purposes, on the other hand is applied by nature for various informational processes in life. With regard to the latter, increasing experimental and theoretical evidence indicates that charge diffusion through DNA is involved in basic steps of DNA replication and repair, as well as regulation of gene expression via epigenetic mechanisms such as DNA methylation or DNA binding of proteins. From the physics point of view, DNA supports a metallic-like behavior with long-range charge mobility. Nevertheless, particularly considering a living environment, charge mobility in DNA needs to take into account omnipresent noise and disorder. Here, we analyze quantum diffusion of single charges along DNA-inspired two-dimensional tight-binding lattices in presence of different sources of intrinsic and environmental fluctuations. It is shown that double-strand lattices, parametrized according to atomistic calculations of DNA sequences, offer a complex network of pathways between sites and may give rise to long-distance coherence phenomena. These effects strongly depend on carrier type (electrons, holes), the energetic profile of the lattice (composition) as well as the type of noise and disorder. Of particular interest are spatially correlated low-frequency fluctuations which may support coherent charge transfer over distances of a few sites. Our results may trigger further experimental activities aiming at investigating charge mobility in DNA both in the native in-vivo context as well as on artificial platforms.