Proceedings of the Royal Society B: Biological Sciences

Collective animal behavior occurs in high-stakes contexts where failing to coordinate effectively with group-mates can spell disaster for individuals. Yet, identifying instances of coordination failure is challenging, meaning their evolutionary effects remain mysterious. Synchronous calls in alternating frog choruses (i.e., inadvertent signal collisions) are unambiguous failure events that impose steep attractiveness costs. We modeled tungara frog chorusing dynamics to reveal the sensorimotor and social mechanisms underpinning synchrony. Ultimately, inter-male variation in two key sensorimotor attributes, the periods of male calling rhythms and call latencies, generated divergent synchrony engagement patterns. Modeling female preferences revealed that these varied behavioral outcomes then yielded disparate attractiveness consequences. By mechanistically linking the causes and consequences of coordination failure, we demonstrate that non-random failure patterns in collectives generate selection gradients that refine sensorimotor tuning.

Does the distribution of fitness effects of new mutations vary across the genome? Under the classical Fisher Geometric Model (FGM) we might not expect it to. In FGM, phenotypic traits are envisioned as dimensions of a landscape, with fitness determined by position in the landscape, i.e., the particular combination of traits of an individual. New mutations are represented by vectors that move from an ancestral to a new phenotype. In classical FGM these vectors affect all trait dimensions simultaneously (universal pleiotropy). However, introducing partial and modular pleiotropy into an FGM framework leads to an expectation that parameters of the DFE will vary with mutational pleiotropy-the number of traits affected by individual mutations. Here we address this prediction by investigating whether traits related to mutational pleiotropy, expression level and network connectivity, affect the parameters of the DFE using whole genome data from A. thaliana and C. grandiflora, two closely related Brassica species that vary significantly in their demography and mating system, and therefore, in effective population size and the effects of linked selection. Results were similar across both species. We found that expression level and network connectivity were predictive of the parameters of the deleterious DFE, even once co-correlations among genome biology traits were accounted for. Our results suggest that, across the genome, molecular evolutio(high mutational pleiotropy). nary patterns agree with the predictions of FGM, albeit relaxing the assumption of universal pleiotropy, and that variation in mutational pleiotropy among genes is sufficient to have detectible effects on the DFE. Significance statementHow do the effects of new mutations vary across the genome? If mutations in some genes affect many traits (high mutational pleiotropy), we hypothesise they will be more strongly deleterious, with lower variance in their selective effects. We test this by investigating the distribution of effects of new mutations across genes that vary in features that are related to mutational pleiotropy: expression level, gene network connectivity, and number of associated GO terms. The mean strength and coefficient of variation of selection of new mutations varied across genes with different features in the manner expected by our hypothesis. This demonstrates that important parameters of molecular evolution can vary across the genome with genome architecture.

Interception of moving objects requires the nervous system to compensate for sensory delays and uncertainty, yet how behavior is controlled remains debated. Key questions concern whether predictive processes play any role at all and, if so, whether they rely on simple motion extrapolation or incorporate internalized physical priors, such as gravity. Another open question is whether observers adopt a single control strategy or flexibly switch between predictive and reactive control - or between different predictive strategies - depending on task demands. To address these questions, we developed a virtual interception task in which participants intercepted moving targets under systematically varied conditions. We manipulated gravity (1g vs. 0g), visual availability (occluded vs. non-occluded), target velocity, and the initial spatial configuration of the ball and paddle (same vs. opposite side). Results indicate that interception is supported by predictive mechanisms across conditions. Behavioral patterns during occluded 0g trials suggest that participants extrapolate target motion using expectations consistent with gravity. Target velocity, visual occlusion, and task geometry modulated movement strategies, indicating that predictive control is flexibly adapted to task demands. These findings support the view that interception relies on predictive internal models incorporating structured physical priors while revealing flexible, context-dependent adaptations to sensory and task constraints.

Humans and other animals often act in environments that are at least partly familiar, where aspects of the spatial layout are known. Although such knowledge is known to support navigation and spatial cognition, its role in the online control of action remains unclear. We investigated whether drivers use knowledge of road layout to guide steering in high and low visibility and, if so, the form of such knowledge. In two simulated driving experiments (total N = 90), participants repeatedly drove winding roads containing segments with and without fog. Drivers who repeatedly experienced the same road exhibited more stable steering and lane positioning than drivers encountering novel roads, but only when visibility was reduced. These advantages were accompanied by superior performance on post-tests assessing knowledge of road geometry. We next examined the form of such knowledge by dissociating global knowledge of road layout from local associations between landmarks and road segments. Disrupting landmark-road segment associations produced the largest impairment in steering performance. The benefits of prior experience were largely preserved when road-segment order was scrambled but landmark associations remained intact. These findings show that spatial knowledge can support moment-to-moment steering control when visibility is reduced. Rather than relying on a globally coherent representation of the environment, drivers use local associations between landmarks and upcoming road geometry to anticipate future demands. More broadly, the results elucidate how familiarity with environmental structure contributes to the control of action when visual information is degraded, revealing a close interplay between spatial knowledge and visual control. Significance StatementPeople routinely act within surroundings they have encountered before, from commuting on the same streets to walking familiar hallways. Whether the spatial knowledge acquired from such experience actually shapes online visual control remains an open question. Using a simulated driving task, we show that familiarity with a road improves steering stability specifically when visibility is reduced, and that this benefit depends on learned associations between landmarks and upcoming road geometry rather than a global cognitive map. The results indicate that spatial knowledge plays a key role in moment-to-moment control, letting drivers anticipate road segments they cannot yet see. Unfamiliar roads and impaired spatial learning may compound the risks of poor visibility, suggesting a role for driver-assistance systems that leverage landmarks.

1. Sandy beaches along urbanized coasts are increasingly managed through beach nourishment and hard infrastructure, yet these interventions often constrain natural dune-building processes. Along the Belgian coast, where much of the beach-dune interface is bordered by dikes, promenades and intensive recreation, strandline vegetation may provide an overlooked mechanism for retaining sand and initiating embryo dune development. 2. We assessed the potential for four pioneer dune plant species (Cakile maritima, Calamagrostis arenaria, Elymus farctus and Salsola kali) to establish, develop vegetation cover and contribute to sand accumulation along the Belgian coast. Using field surveys from 2017-2023, LiDAR-derived beach elevation and annual sediment dynamics, we modelled species occurrence and abundance/cover in low-disturbance reference zones and projected these relationships across the wider coastline. 3. Occurrence models identified where abiotic conditions allow plants to establish and persist until the late growing season, whereas zero-inflated abundance/cover models estimated expected vegetation development across environmental gradients. Predicted occurrence was widespread for several species, suggesting that the abiotic gradients modelled here are not the primary constraints on potential establishment across large parts of the coast. In contrast, expected abundance/cover showed stronger species-specific responses, particularly to sand accretion, indicating that sediment dynamics mainly affect post-establishment vegetation development rather than occurrence alone. 4. Independent field measurements of embryo dunes showed positive relationships between vegetation cover and local sand accumulation for all four species. When scaled using spatial predictions of potential abundance/cover, pioneer vegetation could retain substantial volumes of sand, with Cakile maritima contributing the largest share, followed by Salsola kali, Elymus farctus and Calamagrostis arenaria. Estimated volumes depended on assumptions about whether vegetation occurs as dispersed units or aggregated patches. 5. Synthesis and applications. Our results show that, even along a heavily urbanized and nourished coastline, abiotic conditions can support strandline vegetation and embryo dune initiation where disturbance is reduced. Management actions such as limiting trampling, adapting beach cleaning and protecting strandline vegetation could enhance the retention of nourished sand and support nature-based coastal defense. Rather than replacing engineered interventions, strandline vegetation may increase the efficiency with which available sediment is retained within the beach-dune system.

Ecological roles are treated as discrete, bounded units of biological organization, even as evidence shows that many taxa are versatile, performing more than one of them. Each record of versatility represents a boundary crossing, yet current categorical paradigms prevent this cumulative evidence from reshaping the roles themselves. We solve this by introducing the ecological multiverse, a self-correcting framework that turns boundary crossings into a network of role connectivity. Applied to Fungi, the multiverse recasts the major form of plant pathogenicity from an isolated disease role into a central hub linking much of fungal functional space, especially benign plant symbioses and decomposition. By exposing this topology, the multiverse transforms categorical views of ecological function into a dynamic map, revealing pathways of role change as organisms and knowledge evolve.

This study examined the extent to which goodness of pronunciation (GoP) scores and phonological posterior probabilities capture perceptual ratings of speech severity in individuals with motor speech disorders (MSD). Speech recordings of the word catastrophe were obtained from 489 participants, including 333 neurologically typical controls and 156 individuals with MSD. GoP scores were derived using traditional acoustic features and self-supervised speech representations, including WavLM and XLS-R, across multiple modeling approaches, while phonological posterior probabilities were extracted using Phonet. Model performance was evaluated using Kendall's rank correlations, regression, and receiver operating characteristic analyses against speech-language pathologists' perceptual ratings of sound distortion and intelligibility. Both GoP and phonological posterior probabilities were significantly associated with perceptual ratings. Self-supervised speech representations substantially outperformed traditional acoustic features, with WavLM-based GoP using k-nearest neighbors achieving the strongest performance. Across correlation, regression, and classification analyses, GoP consistently outperformed phonological posterior probabilities for both sound distortion and intelligibility. Age and gender had minimal influence on model-derived measures or their relationships with perceptual ratings. These findings demonstrate the value of self-supervised GoP as an objective measure of speech impairment while highlighting the complementary role of phonological posterior probabilities in characterizing articulatory aspects of motor speech disorders.

To estimate the life expectancy gains that could be realised from increases in Queenslanders physical activity (PA) levels. Design Lifetable analysis Setting, Participants We modelled the 2025 Queensland population aged [≥]40 years. Modelled scenarios We applied two approaches. In the first, we estimated life expectancy differences between device-measured PA quartiles, with quartile1 representing the least active and quartile 4 the most active. In the second, we compared observed device-measured PA levels in Queensland with scenarios in which all individuals moved to either [≥]12,000 steps/day or [≤]2,000 steps/day. We converted the steps per day by age group and PA quartile into equivalent daily minutes of moderate-intensity walking at 4.8 km/h. Additional scenarios were explored in sensitivity analyses. Main outcomes Changes in life expectancy, and total life-years gained over the lifetime of the modelled population. Benefits were also translated into minutes of life gained per additional hour walked. Results If all Queenslanders aged [≥]40 years were as active as the most active quartile, life expectancy at birth could be 88.3 years, an increase of 4.8 years above the life expectancy at observed activity levels. The life expectancy differences between individuals in the least active quartile and the most active quartile was 9.7 years. Achieving the activity level of the most active quartile would require individuals in the lowest activity quartile to undertake an additional 85.9 minutes/day of moderate-intensity walking, with each extra hour of PA associated with an average gain of approximately 3 hours (177 minutes) of life. In step-based modelling, life expectancy in the most active scenario (all achieving [≥]12,000 steps/day) was higher by {approx}7.1 years compared with the least active scenario (all at [≤]2,000 steps/day). Conclusions Increasing PA could yield meaningful gains in life expectancy for Queenslanders, with the largest gains seen in least active individuals. Our findings strengthen the case for prioritising investment in PA -promoting programs and environments.

AO_SCPLOWBSTRACTC_SCPLOWO_LICommunity assembly graphs (CAGs) summarize which species combinations can coexist and how single-species invasions drive transitions between them, encoding the pathways, alternative endpoints, and cycles that make up a communitys assembly history. Constructing CAGs from dynamical models requires methods that are both computationally tractable and faithful to the underlying ecological dynamics. However, existing methods rely on restrictive assumptions, such as global stability, that exclude alternative stable states and non-equilibrium dynamics known to occur in empirical systems. C_LIO_LIWe develop a computational pipeline that constructs CAGs from any generalized Lotka-Volterra model. Building on the invasion graph framework and its connection to permanence, the pipeline verifies that community dynamics are bounded, identifies which subsets of species coexist in the sense of permanence, determines which single-species invasions are dynamically realized, and assigns each community a topographic height equal to the length of the longest assembly path leading to it. We also provide a numerical algorithm to simulate the dynamics of community assembly. C_LIO_LIWe prove several general properties of the resulting graphs, including that a successful invader is never subsequently excluded and that, in the absence of assembly cycles, permanent communities can be reassembled by introducing their species one at a time in the right order. We prove that the CAG faithfully reproduces the compositional shifts seen in the numerically simulated dynamics of assembly. Applying the pipeline to three empirically based models (a New Zealand grassland, a European pasture, and a Puerto Rican ant community), we show how competition strength and mutualistic feedbacks reshape the assembly landscape and how intransitive competition generates assembly cycles. C_LIO_LIOur approach accommodates alternative stable states and non-equilibrium dynamics without requiring global stability, and it turns the long-standing landscape metaphor into a quantitative, mechanistically grounded object by resolving what "height" means. More broadly, it makes the topography of the assembly pathways measurable, providing a way to compare the historical contingency and predictability of the assembly in ecological systems. C_LI

Plant-associated bacteria can improve plant performance under abiotic stress, but beneficial functions in plant microbiomes may depend on defined combinations of microorganisms rather than individual isolates alone. Here, we developed a cube-based screening strategy to identify functional synthetic microbial communities (SynComs) from 135 quinoa-associated bacterial isolates while preserving combinatorial diversity and traceability of isolate-level contributions. The isolates were divided into five 27-isolate sets, each arranged as a 3 x 3 x 3 cube in which each 3 x 3 layer was defined as a 9-isolate SynCom, generating 45 SynComs in total. Screening under 100 mM NaCl identified SynCom DY1 (SCDY1) as a candidate salt stress-mitigating consortium. SCDY1 consisted of nine taxonomically diverse isolates and exhibited a multifunctional profile, including siderophore production, phosphate solubilization, carboxymethyl cellulose degradation, indole compound production, and growth under saline conditions. In Arabidopsis thaliana, SCDY1 promoted primary root elongation and biomass accumulation in a salinity-dependent manner, with the clearest effect under 120 mM NaCl, and at least a subset of constituent bacteria was recoverable from inoculated seedlings. RNA sequencing and targeted RT-qPCR indicated that SCDY1 modulated host gene expression under moderate salinity stress, with responsive genes associated with oxidative stress, water- and oxygen-related processes, phenylpropanoid biosynthesis, glutathione metabolism, and root epidermis-related processes. Root hair phenotyping further showed that SCDY1 enhanced root hair-related traits and shifted visible root hair formation closer to the root apex. These findings identify a quinoa-derived SynCom that improves plant performance under salinity stress and provide a practical, traceable framework for discovering beneficial microbial consortia from plant-associated bacterial collections. Scope statementThis manuscript fits the Research Topic "Harnessing Plant Microbiomes for Climate Resilience: From Ecological Insight to Synthetic Community Design" in Frontiers in Plant Science because it presents a traceable strategy for discovering functional synthetic microbial communities from a stress-adapted plant-associated bacterial collection. We developed a cube-based screening strategy using 135 quinoa-associated bacterial isolates and identified a nine-isolate synthetic microbial community, SCDY1, that promotes Arabidopsis growth under moderate salinity stress. The study integrates microbiological screening, characterization of plant growth-promoting traits, bacterial re-isolation, plant growth phenotyping, RNA-seq, RT-qPCR, and root hair phenotyping. These analyses link SCDY1 treatment to salinity-dependent growth promotion, recoverable bacterial members, stress- and redox-associated transcriptional changes, phenylpropanoid-related responses, and modulation of root epidermal phenotypes. By connecting a defined SynCom with host transcriptional and root epidermal responses, this work advances understanding of beneficial plant-microbe interactions under salt stress. The cube-based design also provides a practical and traceable framework for discovering functional SynComs from large plant-associated bacterial collections, which should be of interest to researchers studying plant symbiosis, microbiome engineering, abiotic stress tolerance, and sustainable crop improvement.

The basic reproduction number R0 confounds pathogen biology with adaptive human contact behavior. Earlier epidemiological--economic theory predicted a forward-looking behavioral contact response but could not test it in the absence of appropriate behavioral data. Using directly measured mobility as an observable proxy for contact, we (i) estimate the behavioral response function directly from data; (ii) show that the biology/behavior decomposition and hence the behavioral correction to R0 is not identified from an epidemic trajectory, the apparent constant-contact R0 being one endpoint of an observational-equivalence class that fits the factual curve identically yet diverges under counterfactual; and (iii) characterize that divergence ("what R0 deletes") as state-dependent, unimodal in counterfactual severity and vanishing when behavior saturates. We then show that, across US jurisdictions, the correction is empirically bounded because risk-responsiveness and behavioral non-saturation are confounded (r=-0.57, n=51): where behavior could compensate, it was already maximal, and where it was not maximal it did not respond. What R0 deletes is thus real and structurally characterizable yet empirically modest here, for reasons the framework itself supplies.

Species distribution models (SDMs) increasingly inform conservation and biosecurity decisions in freshwater systems, where the reliability of its uncertainty estimates matters as much as its point predictions. Ensemble SDMs derive prediction intervals from across-replicate variance, but this variance captures systematic error only when replicates disagree about it, an assumption that fails when training data are contaminated with low-accuracy records, the norm in citizen-science datasets. Whether this failure is spatially uniform or concentrates in identifiable parts of a range is unknown. Using a panel of European freshwater crayfish spanning native headwater-associated species and invasive lowland colonizers, we show that contamination-induced calibration failure is strongly spatially structured: it concentrates at stream-network headwaters, the topological tops of the network, where upstream-aggregated predictors are structurally undefined, and scales with contamination severity, replicated across four species and both dominant ensemble protocols (replicate and consensus). The failure is driven by upward prediction bias, not by intervals failing to widen: contaminated ensembles overpredict suitability in headwaters, and because the bias is shared across ensemble members, the intervals do not flag it. This is a conservation-relevant blind spot, because headwaters are both refugia for threatened native crayfish and front lines for invasion; an SDM that silently overpredicts suitability there misdirects survey and management effort toward the segments where its predictions are least trustworthy. Standard leave-one-basin-out conformal calibration, the recommended panel-wide remedy, repairs marginal coverage but leaves headwaters undercovered, because a single calibration threshold is dominated by the abundant non-headwater segments. A group-conditional (Mondrian) variant, calibrating the two populations separately, restores reliable coverage in both at no extra cost and reallocates width where it is needed. We recommend network-position-stratified calibration as a default for ensemble SDMs in dendritic freshwater systems.

Objectives: Although HIV incidence has declined in some settings, the overall global burden of sexually transmitted infections remains a major public health concern. In the context of the World Health Organization's call for people-centred STI prevention and care, identifying the shared geographic pattern of multiple STIs using data-driven analysis may help detect vulnerable areas and inform integrated prevention strategies. Methods: We analysed country-level incidence counts from the Global Burden of Disease 2023 study for 204 countries and territories over 1990-2023. A Bayesian shared-component spatiotemporal model was fitted, decomposing each disease's log-rate into a shared spatial component (scaled intrinsic conditional autoregressive prior), disease-specific spatial deviations, disease-specific first-order random walk temporal effects, and five socioeconomic covariates, with a negative binomial likelihood to accommodate overdispersion. The shared spatial score - the posterior mean of the shared spatial component - was used as a continuous index of STI co-occurrence burden. Posterior exceedance probabilities quantified directional stability. External validity was assessed via Spearman correlation with the Socio-demographic Index and generalised estimating equation regression of HIV/AIDS mortality on the shared score. Results: The shared spatial score exhibited marked geographic heterogeneity. The five highest-scoring countries were Eswatini (2.25), Lesotho (2.13), Malawi (1.90), Mozambique (1.89), and South Africa (1.85), all in southern Africa. Fifty-seven countries had high directional stability (posterior exceedance probability >0.95), concentrated in sub-Saharan Africa and the Caribbean. The score correlated negatively with SDI (Spearman rho = -0.619, p = 6.4 x 10^-23) and positively with HIV/AIDS mortality (incidence rate ratio = 14.64 per standard deviation, 95% CI: 11.90-18.01). Prior sensitivity analysis confirmed near-perfect ranking stability (rho >= 0.9999). Conclusions: STI co-occurrence is geographically concentrated, with the highest shared burden in sub-Saharan Africa and persistently elevated shared spatial signals also observed in parts of mainland Southeast Asia and the Caribbean. The shared spatial score provides a data-driven tool for prioritising integrated STI screening and prevention resources across countries.

Background. In 2026, the Democratic Republic of the Congo (DRC) experienced the largest recorded outbreak of Ebola disease caused by Bundibugyo virus, with epidemiologically linked importations and secondary transmission in Uganda. This study analysed the publicly reported trajectory and assessed the risk of introduction and onward transmission in North Africa and Europe. Methods. Public surveillance reports from the World Health Organization (WHO), European Centre for Disease Prevention and Control (ECDC), Africa CDC, national ministries of health, and peer-reviewed sources were synthesised through 15-17 July 2026. Headline counts and crude case-fatality ratios were restricted to laboratory-confirmed cases. Average notification rates were calculated from cumulative DRC counts. Exact Poisson intervals used the Garwood method, and the June-July rate ratio was estimated on the log scale. Risk was assessed across introduction likelihood, conditional onward-transmission likelihood, impact, and confidence. Results. By 15 July, the DRC had reported 2,124 confirmed cases and 828 deaths (crude confirmed-case fatality ratio, 39.0%) across 46 health zones in five provinces. Uganda had reported 20 confirmed cases and two confirmed deaths: 15 imported infections and five secondary cases, with no documented community transmission. DRC notifications averaged 47.4 per day during 1-15 July versus 35.9 per day during 2-29 June (rate ratio 1.32; counting-model 95% interval 1.20-1.46). WHO reported that more than 80% of new cases were detected outside known contact lists, while 119 confirmed healthcare-worker infections and 36 deaths had occurred. Introduction likelihood was assessed as very low to low for North Africa and very low for the general European population; delayed recognition in routine healthcare was the principal scenario for limited secondary transmission. Interpretation. Available indicators were inconsistent with effective control in eastern DRC at the data cut-off. Public reporting-date series cannot separate transmission from changing ascertainment, but they showed no sustained decline. Preparedness in North Africa and Europe should prioritise complete exposure histories, rapid isolation, validated diagnostics, protected clinical care, and contact management rather than reliance on border screening. Keywords: Bundibugyo virus; Ebola disease; outbreak surveillance; rapid risk assessment; importation; North Africa; Europe; Algeria; International Health Regulations.

Background. The 2018-2020 Ebola virus disease outbreak in the Democratic Republic of the Congo (DRC) was the country's largest, and the second largest globally, amid armed conflict and community mistrust. Transmission heterogeneity (superspreading) is recognised in Ebola epidemics, but empirical estimates of its extent and determinants remain scarce for DRC outbreaks. We quantified transmission heterogeneity and its determinants during this outbreak. Methods. In this retrospective observational study, we reconstructed transmission chains for confirmed and probable cases (Aug 1, 2018, to June 25, 2020) using routinely collected Ministry of Health and Medecins Sans Frontieres surveillance data. We modelled the offspring distribution with a Bayesian negative binomial framework, correcting for incomplete contact tracing, to estimate the effective reproduction number (Reff), dispersion parameter (k), and proportion of cases responsible for 80% of transmission (prop80), overall, by subgroup, and over time. Individual-level determinants were assessed with a regression extension, adjusting for covariates. Findings. Among 3481 cases, 2008 transmission events linked 2402 (69%) individuals into 415 chains (median size 3, range 2-102). Overall Reff was 1.00 (95% CI 0.92-1.08) with k 0.29 (0.26-0.32); 17.8% of cases generated 80% of transmission. Overdispersion stayed stable despite fluctuating Reff. Non-isolation (IRR 1.79), death outside a treatment centre (IRR 4.34), and unfollowed contact status (IRR up to 4.48) predicted more secondary cases; vaccination cut transmission by about 60%. Interpretation. Epidemiological investigations linked 67.7% (2356/3481) of cases into 415 transmission chains (median size 3, range 2-102); linkage to a known infector fell to 10% during the November 2018-February 2019 period of peak insecurity. Transmission was heterogeneous overall, with dispersion parameter k of 0.29 (0.26-0.32), such that 17.8% (16.8-18.9) of cases generated 80% of onward transmission confirming superspreading as a stable, structural feature of Ebola dynamics. Critically, k remained stable throughout the outbreak, including during periods of elevated Reff, indicating that transmission surges reflected intensification of the same underlying process rather than new superspreading contexts, and that Reff alone is an insufficient summary of epidemic potential. Regression analyses identified predominantly modifiable determinants: cases not isolated in an Ebola treatment centre (IRR 1.79 [1.54-2.06]) or who died outside one (IRR 4.34 [3.47-5.31]) generated substantially more secondary cases, as did those registered as contacts but not followed up (IRR 3.01 [2.39-3.70]) or unregistered altogether (IRR 4.48 [3.67-5.38]) relative to actively followed-up contacts. Vaccination reduced onward transmission by 60-64% (IRR 0.36-0.40). These findings indicate that transmission was shaped less by gaps in epidemiological knowledge than by the operational reach of contact tracing, isolation, and vaccination delivery, particularly during periods of insecurity.

An epidemic's expected course is determined by the magnitude and timing of a typical person's infectiousness --- captured, in turn, by the basic reproduction number and the generation-time distribution. These fundamental, population-average quantities can mask individual-level variation that shapes how an epidemic actually unfolds: for example, individual variation in the magnitude of infectiousness (overdispersion) creates superspreading, a key feature of the SARS-CoV-1 and SARS-CoV-2 epidemics. However, the impact of individual variation in infectiousness timing is less well understood. Here, we demonstrate that individual infectiousness timing varies substantially and to different degrees across pathogens. For some common pathogens, including influenza, measles, and SARS-CoV-2, infectiousness is "bursty", or highly concentrated and variably-timed across individuals: for example, the window of appreciable infectiousness for SARS-CoV-2 may last for roughly a day, vs. the 9--12 days usually quoted. We show that bursty infectiousness creates superspreading without inherent superspreaders, makes epidemic timing more variable, amplifies the time-sensitivity of common interventions, and complicates inference of key epidemiological parameters. Together with the reproduction number, the generation-time distribution, and overdispersion, burstiness completes a family of basic parameters that govern how epidemics unfold.

Background. The 2026 Bundibugyo virus disease (BVD) epidemic in the Democratic Republic of the Congo (DRC) was declared on 15 May 2026 and determined a public health emergency of international concern on 17 May 2026. Public surveillance reporting consists of cumulative counts by report date; no line list with symptom-onset dates is available. Widely circulated characterisations - that this is the fastest-growing Ebola outbreak on record, that reported cases are doubling every 22 days, and that the case fatality ratio (CFR) is 37.5% - rest on these aggregates. We examined what the published data actually support. Methods. We assembled twelve published anchor points from 15 May to 13 July 2026 from WHO, WHO AFRO, NICD and the DRC National Institute of Public Health; one was recovered by back-calculation and checked against the directly reported subsequent total. We computed mean daily incidence between anchors and the within-interval death-to-case ratio. We reconstructed symptom-onset dates by Richardson-Lucy deconvolution with right-truncation correction under assumed onset-to-report delays with means of 5, 7 and 9 days, estimated the instantaneous reproduction number using the Cori method, and computed three CFR estimators: crude, resolved-case and outcome-delay-adjusted. Provincial CFRs used exact binomial intervals. Results. Confirmed cases plateaued at 40-52 per day for eighteen days, from 25 June to 13 July. Over the same period, the within-interval death-to-case ratio rose from 0.28 to 0.58. Reconstructed Rt was 1.28, with a 95% credible interval of 1.15-1.41, on 7 July, having fallen from approximately 2.9 in mid-May. Growth on the reconstructed onset curve corresponded to a doubling time of approximately 90 days, compared with 22 days computed from cumulative counts. CFR estimates were 37.5% for the crude estimator, 50.2% for the outcome-delay-adjusted estimator and 67.3% for the resolved-case estimator. Crude provincial CFR was 34.9% with a 95% confidence interval of 32.7-37.1 in Ituri, 58.2% with a 95% confidence interval of 50.7-65.5 in North Kivu, and 81.0% with a 95% confidence interval of 58.1-94.6 in newly affected provinces. Conclusions. A flat case count accompanied by a rising death-to-case ratio is difficult to reconcile with a transmission plateau and is consistent with saturated case detection. Reported case counts appear to have substantially decoupled from transmission and cannot presently distinguish control from detection failure. Doubling times computed from cumulative totals are artefacts. Test volume and positivity by health zone are the critical missing denominators.

In noisy environments, visible speech articulations improve listening comprehension. The benefit derives from several sources, including articulatory timing and shape. Recent research has shown that visual cortex encodes a categorical representation of articulatory features and that visual speech can benefit both acoustic and phonetic feature processing separately. The present study advances the hypothesis that the shape of the articulators specifically influences the categorization of auditory speech in terms of its phonetic features. We tested this by linearly modeling electroencephalographic responses to natural, continuous speech (in noise) in terms of the acoustic and articulatory features of the speech. We compared the performance of these models in conditions where the speech was accompanied by a natural video of the speaker with their mouth visible, and a video where their mouth was covered by a dynamic ellipse obscuring articulatory shape but preserving dynamics. The dynamic mask reduced comprehension, neural processing of phonetic features, the associated multisensory benefits, and indices of visual-only linguistic processing over occipital scalp. Our findings support substantial visual involvement in speech comprehension, derived largely from the shape of the articulators. They also corroborate several proposals involving audiovisual speech processing hierarchy and the nature of the information contained in visible speech. HighlightsO_LIVisual speech provides at least two forms of information to enhance acoustic speech processing: redundant temporal dynamics and complementary articulatory information C_LIO_LICovering the mouth with a dynamic mask preserves horizontal and vertical lip movement information, but largely removes articulatory detail C_LIO_LIVisual speech with a mask preserves some general multisensory benefits but removes visual linguistic information and its ability to enhance auditory processing at the level of phonetic features. C_LI

Green algae must continuously balance resource availability to maintain photosynthetic performance. The O2:CO2 ratio is a key determinant of their metabolic mode. Under hyperoxia or low CO2, many algae induce a carbon concentrating mechanism (CCM). In the model green alga Chlamydomonas reinhardtii, the CCM relies on a pyrenoid, a specialized microcompartment that elevates CO2 around rubisco. While ambient CO2 acclimation is well-studied, responses to hyperoxia remain poorly understood, despite its frequent occurrence in nature under high light. Using controlled bioreactors, we exposed two diverse Chlamydomonas ecotypes, CC1009 and CC2343, to 95% oxygen to analyze time-dependent, genome-wide transcriptomic and phenotypic changes. Both ecotypes induced CCM genes, but they exhibited distinct molecular and physiological phenotypes. The tolerant ecotype (CC1009) successfully adapted, developing a functional CCM with a structured starch sheath. Conversely, the sensitive ecotype (CC2343) suffered growth arrest and formed malformed pyrenoids. Transcriptomics revealed that CC1009 initiated a rapid initial response, upregulating chloroplast proteostasis and downregulating nucleotide metabolism. CC2343 showed a massive, delayed transcriptional response, downregulating genes coding for photosystems and tetrapyrrole biosynthesis. This unbiased transcriptomic approach identifies key candidate genes driving algal acclimation to hyperoxic stress in natural, high-light environments.

Differences in physical features and disease prevalence between men and women are examples of sexual dimorphisms. However, sex differences can manifest not only in trait means but also in how strongly risk factors are linked to diseases (e. g. BMI to cardiovascular disease), a question heavily under-researched. To fill this gap, we set out to identify sex differences in phenotype correlations (rP) and decompose them into genetic (rG) and environmental (rE) contributions. Our analysis revealed 250 trait pairs with significant sex-different phenotypic correlations in the UK Biobank. Overall, we observed a predominance of environmental contributions to sex-different effects: 182 trait pairs (73%) exhibited exclusively sex-different rE, while 68 (27%) showed sex differences in both rE and rG, and no trait pair was affected solely by sex-specific rG. For example, we detected sex-different environmental correlation between C-reactive protein and BMI (rE(men) = 0.07 vs rE(women) = 0.25), but no sex-difference in genetic correlation. On the contrary, glycated haemoglobin and LDL cholesterol showed genetic correlation only in women (rG(women) = 0.17; 95% CI = [0.1, 0.23]), but environmental correlation only in men (rE(men) = -0.18; 95% CI = [-0.19, -0.16]). Some of the observed sex differences - including those involving testosterone, SHBG, urate, waist-hip ratio, and triglycerides - may reflect underlying sex-specific genetic architectures, as evidenced by low between-sex genetic correlations. In conclusion, environmental factors are the predominant contributors to sex differences in phenotypic correlations between complex traits, with modest detectable contributions from sex-specific genetic architectures. Recognising these patterns can inform the development of more effective, sex-informed interventions.