ALT The emergence of biological complexity can be viewed as a transition from fragmented local interactions to extensive integrated organization, raising the question of how large-scale connectivity emerges from simple interacting elements. We investigated whether this transition can be understood as a consequence of hypergraph percolation driven by higher-order interactions. We performed computational simulations where elementary units constituted nodes and collective interactions formed hyperedges of variable size. Increasing hyperedge density enabled the characterization of connected-component growth, fragmentation, interaction overlap, participation and structural redundancy. Critical transition regions were identified as sparse local assemblies rapidly reorganized into extensive connected structures. These transitions were characterized by abrupt expansion of the largest connected component, progressive consolidation of previously disconnected clusters and increasing overlap among hig

ALT Intentional communication has been studied extensively in primates, yet evidence from free-ranging non-ape species remains limited. Human-directed food-solicitation gestures in Hanuman langurs (Semnopithecus entellus) have recently been described, but whether these behaviours exhibit behavioural hallmarks associated with first-order intentionality remains unknown. Here, we experimentally investigated the presence of these hallmarks in free-ranging Hanuman langurs across six anthropogenic sites in southern West Bengal, India. We conducted 360 experimental and control trials and quantified behavioural markers commonly used to operationalize intentional communication. Experimental trials elicited audience checking, recipient-directed orientation, rapid approach responses, food-solicitation gestures and gestural flexibility, whereas these behaviours were rare or absent in control trials. Differences between experimental and control conditions were significant across all six study sites. Si

ALT Modern biological microscopy routinely generates large and complex image datasets, including multidimensional, multimodal, and time-resolved acquisitions. While imaging technologies have rapidly evolved, data management infrastructures within microscopy facilities often remain fragmented, relying on heterogeneous local solutions that are difficult to maintain, scale, and integrate with High-Performance Computing (HPC) centers and public data repositories. To address these issues, France BioImaging (FBI), the French national infrastructure for biological imaging, has developed FBI.DATA and the associated BioImage Cloud platform. This initiative aims to provide a coordinated national infrastructure connecting microscopy facilities, centralized storage resources, HPC environments, and public bioimaging archives through interoperable and scalable workflows.The proposed architecture combines open-source technologies including OMERO for image management, iRODS for distributed data orchestrat

ALT High-dimensional multicomponent systems, including immune and epigenetic repertoires, must selectively retain rare, beneficial components while purging a massive influx of suboptimal variants. We demonstrate that critical tuning of component control parameters through competition naturally implements proofreading in these systems. Competition for shared inputs pins the system to the marginal stability threshold of the most persistent species. This grants dominant species extended lifetimes, concentrating the population into dominant components while forcing less-stable variants into rapid drift-driven turnover. When aggregate drive exceeds a characteristic scale, this pinning fails, producing a non-selective state where component lifetimes scale as a universal power law with aggregate drive. Applying this framework to biological memory, we identify the hallmarks of this effect in plasma cell accumulation dynamics and propose that de-pinning transitions may represent failure points acro

ALT Computational simulation provides a powerful toolkit for in silico experimentation. However, while the field has developed best practices for the design and implementation of such models, there remains ambiguity in discussions about how to understand and/or interpret their results due to their inherent ability to overwhelm traditional frequentist statistics by simply increasing the number of trials simulated. This fails the discipline in two ways: first, it leaves the community unsure of what constitutes a best practice for uniform understanding, and second, it potentially overburdens computational studies that burn clock cycles solely to ensure "enough runs to satisfy peers" without any theoretical underpinning for a definition of "enough". We propose a simple and straightforward standard for when to stop simulating additional trials, the Ω test, designed to be analogous to the function of traditional frequentist P-tests. Community adoption of a reasonable and uniform standard will pe

ALT Spatially resolved transcriptomics (SRT) is transforming how we study tissues by measuring gene expression in cells in their spatial context. However, the field lacks robust methodological guidance on one of its most fundamental analytical steps: how to accurately segment cells and assign spatially localized transcripts to them. Major technical challenges include sparse molecular signals, transcript displacement, complex cellular morphologies, and the projection of three-dimensional tissue architecture onto two-dimensional imaging planes. These challenges make segmentation a major source of uncertainty, with errors that can propagate through downstream analyses and ultimately lead to misleading biological interpretations. Here, we argue that segmentation should be treated as a central unresolved problem in spatial omics rather than a routine preprocessing step. We review current approaches, highlight key methodological limitations, including the lack of appropriate metrics and gold-sta

ALT Candida albicans is a commensal microorganism that causes opportunistic infections, such as oral candidiasis, vaginitis affecting females, newborns, and immunocompromised patients. Biofilm formation can lead to a commensal organism becoming a life-threatening organism by introducing antifungal resistance. The experiment we did combines crystal violet staining for biofilm biomass and CFU counts to statistically construct an additive BVI model by analysing the experimental data. Our study on the data proposes a Biofilm-Virulence Index (BVI) as a novel and quantitative parameter for assessing antifungal drug resistance in Candida albicans. The effect of the drugs on inhibition zone diameter is twofold, first, linear increase with time during early biofilm formation, second, stabilizing in later phases and correlating directly with virulence. Most BVI values remained in the mild infection range, indicating successful virulence reduction by antifungal drugs. The BVI model model combines the

ALT Large language model (LLM) serving creates environmental impacts beyond carbon and water, including ecosystem damage through biodiversity-related pathways. We present BIRDS, a framework for Biodiversity Impact of Request-Driven LLM Serving. BIRDS defines request-level functional units, quantifies operational and embodied biodiversity impact, and introduces Quality-Normalized Biodiversity Impact (QNBI) to jointly analyze ecological impact and response quality. Across diverse workloads, models, GPUs, and regions, SYSTEM reveals that biodiversity impact accumulates at scale and exposes actionable quality-aware serving tradeoffs.

ALT Simulation of post-prandial pharmacokinetics, such as muscle protein synthesis (MPS) through mTORC1 and insulin-induced glucose uptake, is often challenging due to the computational intensity of the multi-compartmental approach. In this study, I introduce an in silico metabolic simulator that uses bi-compartmental Bateman kinetic processes, gamma-variate distributions, and finite state machine reasoning to solve temporal differential equations instantaneously, generating metabolic curves and predictions depending on input meals. The novel underlying algorithm was custom-built entirely independent of third-party libraries or external services. This original computational engine, bridging the gap between academia and the digital health sector, is integrated within a web dashboard and provided as a service via REST APIs. The average response time is approximately 135 ms with a maximum below 750 ms. The multi-dimensional model was calibrated using a Landmark Validation approach across dive

ALT Biological systems exhibit marked molecular asymmetry, with proteins based predominantly on L-amino acids and nucleic acids and carbohydrates largely composed of D-sugars. Explanations for homochirality include asymmetric photochemistry, autocatalytic amplification, stochastic symmetry breaking and mineral-surface stereoselectivity, but these mechanisms only partially address the influence of finite geometry and collective spatial interactions on stereochemical stabilization. Inspired by recent developments in condensed-matter physics, we investigated whether coherent chirality could emerge from the interplay among nonlinear stereochemical amplification, stochastic fluctuations and boundary-dependent spatial constraints. We developed a reaction-diffusion simulation in which local stereochemical populations evolved within finite two-dimensional domains under spatial coupling and weak geometrical bias fields. Our model combined bistable autocatalytic dynamics, nearest-neighbor interactio

ALT We present an investigation of the applicability of topological data analysis (TDA) to the study of high-resolution confocal microscopy images of fibrin network structures from patients with oesophageal cancer undergoing intended curative surgery. Investigation of clot structure brings new knowledge about blood coagulation, risk of bleeding, and thrombosis in this group of patients. Images of fibrin network formation in the collected blood samples were captured by confocal microscopy and three-dimensional z-stacks were analysed. Each z-stack was cropped to a centre region for analysis, the validity of which is assessed in detail. Overall, we found no significant differences in fibrin network topology across the perioperative period, and no consistent differences in network structure between the standard and intervention groups.

ALT One of the main causes of death around the globe is malaria. Researchers have sought to develop predictive models for malaria outbreaks based on meteorological data, climate data and the breeding cycle of Plasmodium, the causative agent of malaria. This study predicts the severity of malaria based on environmental and biological factors. A logistic regression model was developed in this study to predict the severity of malaria based on such factors as sickle cell disease, stagnant water, garbage dump, wet lawns, and the use of treated mosquito nets, with an 83.3% accuracy rate. The study was carried out in the Bosomtwe District of Ghana with 417 respondents. It was deduced that although children in the District are highly prone to malaria infection, the severity is very low. The study recommends that not just having a good sample size alone is important during machine learning model development, but also having a good sample representation of the various class labels is equally importa

ALT Ligand receptor interactions are commonly assessed through equilibrium occupancy and pharmacodynamic measures that describe binding and saturation by means of bounded response curves. Thermodynamic approaches relate binding affinity to logarithmic concentration scaling, while probabilistic descriptions of occupancy arise from exponential relations. We introduce an exponential logarithmic descriptor (ELD) that integrates ligand availability and thermodynamic binding propensity within a single quantity. The logarithmic component corresponds to a thermodynamic term derived from concentration dependent free energy relations, whereas the exponential component is represented through an inverse normalized concentration term corresponding to the reciprocal of the exponential occupancy factor emerging from Boltzmann type binding formulations. We explored ELD behavior through numerical simulations spanning sub affinity, transition and saturating concentration regimes under multiple affinity cond

ALT Clinical interpretation often assumes that observable performance provides sufficient information about the organization of an adaptive system. However, similar observable performance may correspond to distinct latent organizations. This study extends a previous multi-level framework by introducing a fourth analytical level centered on longitudinal viability. Using an exploratory single-case design in a Parkinsonian patient, gait data were recorded with instrumented insoles under three occlusal conditions: neutral natural occlusion (ONL), a 2.5-degree increase in vertical dimension of occlusion (OC2.5), and a 3-degree increase in vertical dimension of occlusion (OC3). Two measurement sessions were conducted eleven weeks apart, during which the participant underwent a structured sensorimotor intervention. The vertical dimension of occlusion was considered as an experimentally varied constraint applied to an adaptive neuromechanical system. Although observable performance remained global