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Quantifying viral traits—including the adsorption rate, burst size, and latent period—is critical to characterize viral infection dynamics and develop predictive models of viral impacts across scales from cells to ecosystems. Here, we revisit the gold standard of viral trait estimation—the one-step growth curve—to assess the extent to which assumptions at the core of viral infection dynamics lead to ongoing and systematic biases in inferences of viral traits. We show that latent period estimates obtained via one-step growth curves systematically underestimate the mean latent period and, in turn, overestimate the rate of viral killing at population scales. By explicitly incorporating trait variability into a dynamical inference framework that leverages both virus and host time series, we provide a practical route to improve estimates of the mean and variance of viral traits across diverse virus–microbe systems.

Cardiomyocytes exhibit significant cell‐to‐cell variability due to differences in protein expression and post‐translational modifications in the cell membrane and the intracellular machinery. Resulting variability in action potential propagation and configuration is proposed to promote arrhythmia. However, such effects may be suppressed by tight electrical coupling of cells in the healthy heart, but not during pathological conditions where gap junction function is impaired. To investigate this, we employed a cell‐based mathematical model of cardiac electrophysiology, in which we systematically modified properties of individual cells and intercellular electrical connectivity (gap junctions). Despite the inclusion of marked variation in properties between cells, we observed electrical homogeneity when cells were well coupled. In contrast, lower and/or more variable gap junction connectivity resulted in nonhomogeneous action potential configuration and irregular timing of the depolarizing and repolarizing electrical wavefronts. Pro‐arrhythmic early after depolarizations also occurred under these conditions. These effects were effectively dampened in highly coupled cells. Nevertheless, differences in calcium homeostasis were not negated by gap junction coupling, indicating a limit to which electrical connections can homogenize mechanical function. Our findings underscore the critical role of intercellular coupling in maintaining cardiac stability and highlight the importance of studying cardiomyocytes within a syncytium rather than in isolation.

ABSTRACT Candida albicans is a major fungal pathogen of humans. It exists as a commensal in the oral cavity, gut or genital tract of most individuals, constrained by the local microbiota, epithelial barriers and immune defences. Their perturbation can lead to fungal outgrowth and the development of mucosal infections such as oropharyngeal or vulvovaginal candidiasis, and patients with compromised immunity are susceptible to life-threatening systemic infections. The importance of the interplay between fungus, host and microbiota in driving the transition from C. albicans commensalism to pathogenicity is widely appreciated. However, the complexity of these interactions, and the significant impact of fungal, host and microbiota variability upon disease severity and outcome, are less well understood. Therefore, we summarise the features of the fungus that promote infection, and how genetic variation between clinical isolates influences pathogenicity. We discuss antifungal immunity, how this differs between mucosae, and how individual variation influences a person's susceptibility to infection. Also, we describe factors that influence the composition of gut, oral and vaginal microbiotas, and how these affect fungal colonisation and antifungal immunity. We argue that a detailed understanding of these variables, which underlie fungal-host-microbiota interactions, will present opportunities for directed antifungal therapies that benefit vulnerable patients. The complexity and variability of FunHoMic interactions between the fungal pathogen, its human host and the Microbiota strongly influence the development and outcomes of the superficial and systemic Candida albicans infections that plague human health worldwide.

As cities expand, human mobility has become a central focus of urban planning and policy making to make cities more inclusive and sustainable. Initiatives such as the “15-minutes city” have been put in place to shift the attention from monocentric city configurations to polycentric structures, increasing the availability and diversity of local urban amenities. Ultimately they expect to increase local walkability and increase mobility within residential areas. While we know how urban amenities influence human mobility at the city level, little is known about spatial variations in this relationship. Here, we use mobile phone, census, and volunteered geographical data to measure geographic variations in the relationship between origin-destination flows and local urban accessibility in Barcelona. Using a Negative Binomial Geographically Weighted Regression model, we show that, globally, people tend to visit neighborhoods with better access to education and retail. Locally, these and other features change in sign and magnitude through the different neighborhoods of the city in ways that are not explained by administrative boundaries, and that provide deeper insights regarding urban characteristics such as rental prices. In conclusion, our work suggests that the qualities of a 15-minutes city can be measured at scale, delivering actionable insights on the polycentric structure of cities, and how people use and access this structure.

DNA methylation, also known as 5-methylcytosine, is an epigenetic modification that has crucial functions in plant growth, development and adaptation. The cellular DNA methylation level is tightly regulated by the combined action of DNA methyltransferases and demethylases. Protein complexes involved in the targeting and interpretation of DNA methylation have been identified, revealing intriguing roles of methyl-DNA binding proteins and molecular chaperones. Structural studies and in vitro reconstituted enzymatic systems have provided mechanistic insights into RNA-directed DNA methylation, the main pathway catalysing de novo methylation in plants. A better understanding of the regulatory mechanisms will enable locus-specific manipulation of the DNA methylation status. CRISPR–dCas9-based epigenome editing tools are being developed for this goal. Given that DNA methylation patterns can be stably transmitted through meiosis, and that large phenotypic variations can be contributed by epimutations, epigenome editing holds great promise in crop breeding by creating additional phenotypic variability on the same genetic material. This Review outlines progress in understanding the mechanisms of DNA methylation regulation in plants. Studies in various plants have revealed novel and diverse biological functions of DNA methylation that might assist in developing epigenome editing approaches suitable for crop breeding.

Land use and land cover change (LULCC) has directly played an important role in the observed climate change. In this paper, we considered Dujiangyan City and its environs (DCEN) to study the future scenario in the years 2025, 2030, and 2040 based on the 2018 simulation results from 2007 and 2018 LULC maps. This study evaluates the spatial and temporal variations of future LULCC, including the future potential landscape risk (FPLR) area of the 2008 great (8.0 Mw) earthquake of south-west China. The Cellular automata–Markov chain (CA-Markov) model and multicriteria based analytical hierarchy process (MC-AHP) approach have been considered using the integration of remote sensing and GIS techniques. The analysis shows future LULC scenario in the years 2025, 2030, and 2040 along with the FPLR pattern. Based on the results of the future LULCC and FPLR scenarios, we have provided suggestions for the development in the close proximity of the fault lines for the future strong magnitude earthquakes. Our results suggest a better and safe planning approach in the Belt and Road Corridor (BRC) of China to control future Silk-Road Disaster, which will also be useful to urban planners for urban development in a safe and sustainable manner.

Sustained proliferation is a significant driver of cancer progression. Cell-cycle advancement is coupled with cell size, but it remains unclear how multiple cells interact to control their volume in 3D clusters. In this study, we propose a mechano-osmotic model to investigate the evolution of volume dynamics within multicellular systems. Volume control depends on an interplay between multiple cellular constituents, including gap junctions, mechanosensitive ion channels, energy-consuming ion pumps, and the actomyosin cortex, that coordinate to manipulate cellular osmolarity. In connected cells, we show that mechanical loading leads to the emergence of osmotic pressure gradients between cells with consequent increases in cellular ion concentrations driving swelling. We identify how gap junctions can amplify spatial variations in cell volume within multicellular spheroids and, further, describe how the process depends on proliferation-induced solid stress. Our model may provide new insight into the role of gap junctions in breast cancer progression. Cell proliferation is regulated by cell volume, but it is unclear how individual cancer cells coordinate to regulate cell volumes in 3D clusters. Here the authors propose a mechano-osmotic model to analyse the exchange of fluid and ions between connected cells and their environment in response to proliferation-induced solid stress.

Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is important because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress-response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found several examples of pulsatile expression. Single-cell growth rates were often anticorrelated with reporter levels, with changes in growth preceding changes in expression. These dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that fluctuations in both gene expression and growth dynamics in stress-response networks have direct consequences on survival.

Open cellular convection (OCC) over, for example, the North Sea is often observed in connection with cold-air outbreaks. It is accompanied by large temporal and spatial variability in wind speed, which affects offshore wind energy in the area. This study uses the global Model for Prediction Across Scales (MPAS), with regional mesh refinement down to convection-permitting scales of 2 km, to simulate an OCC episode in the North Sea, with a focus on wind-speed variability. Modelled data are combined with wind speeds retrieved from satellite data and in situ measurements to investigate the spatial and temporal variability of offshore wind speeds under OCC conditions from a synoptic to mesoscale perspective, and to examine the model’s ability to represent the OCC structures and wind-speed variability. The model can simulate realistic OCC structures and mesoscale wind-speed variability within the limits set by the effective model resolution. Under OCC conditions, significant differences from climatological conditions are found in the spatial wind-speed power spectrum and in 10-min wind-speed step changes. The very high horizontal mesh-cell spacing in the refinement region of 2 km, and the focus on OCC wind-speed variability, makes this the first investigation of this kind using the MPAS modelling framework with mesh refinement.

The spatial and temporal representation of land use and land cover (LULC) changes helps to understand the interactions between natural habitats and other areas and to plan for sustainability. Research on the models used to determine the spatio-temporal change of LULC and simulation of possible future scenarios provides a perspective for future planning and development strategies. Landsat 5 TM for 1990, Landsat 7 ETM + for 2006, and Landsat 8 OLI for 2022 satellite imageries were used to estimate spatial and temporal variations of transition potentials and future LULC simulation. Independent variables (DEM, slope, and distances to roads and buildings) and the cellular automata–artificial neural network (CA-ANN) model integrated in the MOLUSCE plugin of QGIS were used. The CA-ANN model was used to predict the LULC maps for 2038 and 2054, and the results suggest that artificial surfaces will continue to increase. The Düzce City center’s artificial surfaces grew by 100% between 1990 and 2022, from 16.04 to 33.10 km 2 , and are projected to be 41.13 km 2 and 50.32 km 2 in 2038 and 2054, respectively. Artificial surfaces, which covered 20% of the study area in 1990, are estimated to cover 64.07% in 2054. If this trend continues, most of the 1st-class agricultural lands may be lost. The study’s results can assist local governments in their land management strategies and aid them in planning for the future. The results suggest that policies are necessary to control the expansion of artificial surfaces, ensuring a balanced distribution of land use.