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Background Team leadership during medical emergencies like cardiac arrest resuscitation is cognitively demanding, especially for trainees. These cognitive processes remain poorly characterized due to measurement challenges. Using virtual reality simulation, this study aimed to elucidate and compare communication and cognitive processes-such as decision-making, cognitive load, perceived pitfalls, and strategies-between expert and novice code team leaders to inform strategies for accelerating proficiency development. Methods A simulation-based mixed methods approach was utilized within a single large academic medical center, involving twelve standardized virtual reality cardiac arrest simulations. These 10- to 15-minutes simulation sessions were performed by seven experts and five novices. Following the simulations, a cognitive task analysis was conducted using a cued-recall protocol to identify the challenges, decision-making processes, and cognitive load experienced across the seven stages of each simulation. Results The analysis revealed 250 unique cognitive processes. In terms of reasoning patterns, experts used inductive reasoning, while novices tended to use deductive reasoning, considering treatments before assessments. Experts also demonstrated earlier consideration of potential reversible causes of cardiac arrest. Regarding team communication, experts reported more critical communications, with no shared subthemes between groups. Experts identified more teamwork pitfalls, and suggested more strategies compared to novices. For cognitive load, experts reported lower median cognitive load (53) compared to novices (80) across all stages, with the exception of the initial presentation phase. Conclusions The identified patterns of expert performance — superior teamwork skills, inductive clinical reasoning, and distributed cognitive strategiesn — can inform training programs aimed at accelerating expertise development. 

Abstract Arboviruses transmitted mainly byAedes(Stegomyia)aegyptiandAe. albopictus, including dengue, chikungunya, and Zika viruses, and yellow fever virus in urban settings, pose an escalating global threat. Existing risk maps, often hampered by surveillance biases, may underestimate or misrepresent the true distribution of these diseases and do not incorporate epidemiological similarities despite shared vector species. We address this by generating new global environmental suitability maps forAedes-borne arboviruses using a multi-disease ecological niche model with a nested surveillance model fit to a dataset of over 21,000 occurrence points. This reveals a convergence in suitability around a common global distribution with recent spread of chikungunya and Zika closely aligning with areas suitable for dengue. We estimate that 5.66 (95% confidence interval 5.64-5.68) billion people live in areas suitable for dengue, chikungunya and Zika and 1.54 (1.53-1.54) billion people for yellow fever. We find large national and subnational differences in surveillance capabilities with higher income more accessible areas more likely to detect, diagnose and report viral diseases, which may have led to overestimation of risk in the United States and Europe. When combined with estimates of uncertainty, these suitability maps can be used by ministries of health to target limited surveillance and intervention resources in new strategies against these emerging threats. 

Variability of oxygen isotopes in environmental water is recorded in tooth enamel, providing a record of seasonal change, dietary variability, and mobility. Physiology dampens this variability, however, as oxygen passes from environmental sources into blood and forming teeth. We showcase two methods of high resolution, 2-dimensional enamel sampling, and conduct modeling, to report why and how environmental oxygen isotope variability is reduced in animal bodies and teeth. First, using two modern experimental sheep, we introduce a sampling method, die-saw dicing, that provides high-resolution physical samples (n = 109 and 111 sample locations per tooth) for use in conventional stable isotope and molecular measurement protocols. Second, we use an ion microprobe to sample innermost enamel in an experimental sheep (n = 156 measurements), and in a Pleistocene orangutan (n = 176 measurements). Synchrotron and conventional μCT scans reveal innermost enamel thicknesses averaging 18 and 21 μm in width. Experimental data in sheep show that compared to drinking water, oxygen isotope variability in blood is reduced to 70–90 %; inner and innermost enamel retain between 36 and 48 % of likely drinking water stable isotope range, but this recovery declines to 28–34 % in outer enamel. 2D isotope sampling suggests that declines in isotopic variability, and shifted isotopic oscillations throughout enamel, result from the angle of secretory hydroxyapatite deposition and its overprinting by maturation. This overprinting occurs at all locations including innermost enamel, and is greatest in outer enamel. These findings confirm that all regions of enamel undergo maturation to varying degrees and confirm that inner and innermost enamel preserve more environmental variability than other regions. We further show how the resolution of isotope sampling — not only the spatial resolution within teeth, but also the temporal resolution of water in the environment — impacts our estimate of how much variation teeth recover from the environment. We suggest inverse methods, or multiplication by standard factors determined by ecology, taxon, and sampling strategy, to reconstruct the full scale of seasonal environmental variability. We advocate for combined inverse modeling and high-resolution sampling informed by the spatiotemporal pattern of enamel formation, and at the inner or innermost enamel when possible, to recover seasonal records from teeth. 

Abstract Climatic extremes have historically been seen as univariate; however, recent international reports have highlighted the potential for an increase in compound climate events (e.g., hot and dry events, recurrent flooding). Despite the projected increase in the frequency of compound climate events and the adoption of compound event terminology, few studies identify climate extremes as compound climate events and little evidence exists on the societal impacts of these compound climate events. This scoping review summarizes key findings and knowledge gaps in the current state of empirical studies that focus on the societal impacts of compound climate events. We identified 28 eligible studies published in four databases reporting on the societal impacts of compound climate events in four sectors: agriculture, public health, the built environment, and land use. Overall, we found the need for more research explicitly linking compound climate events to societal impacts, particularly across multiple compound climate events, rather than single case study events. We also noted several key findings, including changes in agricultural productivity, loss of habitat, increased fire risk, poor mental health outcomes, decreased health care access, and destruction of homes and infrastructure from these events. Additional research is needed both globally and locally to understand the implications of compound climate events across different geographic regions and populations to ensure responsive adaptation policies in a compound climate event framework. 

Abstract Interactions among humans, livestock, and wildlife within disturbed ecosystems, such as those impacted by climate change, can facilitate pathogen spillover transmission and increase disease emergence risks. The study of future climate change impacts on the distribution of free-ranging bats is therefore relevant for forecasting potential disease burden. This study used current and future climate data and historic occurrence locations of the vampire bat speciesDesmodus rotundus, a reservoir of the rabies virus to assess the potential impacts of climate change on disease reservoir distribution. Analyses included a comprehensive comparison of different climate change periods, carbon emission scenarios, and global circulation models (GCMs) on final model outputs. Models revealed that, although climatic scenarios and GCMs used have a significant influence on model outputs, there was a consistent signal of range expansion across the future climates analyzed. Areas suitable forD. rotundusrange expansion include the southern United States and south-central portions of Argentina and Chile. Certain areas in the Amazon Rainforest, which currently rests at the geographic center ofD. rotundus’ range, may become climatically unsuitable for this species within the context of niche conservatism. While the impacts of rabies virus transmitted byD. rotunduson livestock are well known, an expansion ofD. rotundusinto novel areas may impact new mammalian species and livestock with unexpected consequences. Some areas in the Americas may benefit from an assessment of their preparedness to deal with an expectedD. rotundusrange expansion. 

Shifts in agricultural land use over the past 200 years have led to a loss of nearly 50% of existing wetlands in the USA, and agricultural activities contribute up to 65% of the nutrients that reach the Mississippi River Basin, directly contributing to biological disasters such as the hypoxic Gulf of Mexico “Dead” Zone. Federal efforts to construct and restore wetland habitats have been employed to mitigate the detrimental effects of eutrophication, with an emphasis on the restoration of ecosystem services such as nutrient cycling and retention. Soil microbial assemblages drive biogeochemical cycles and offer a unique and sensitive framework for the accurate evaluation, restoration, and management of ecosystem services. The purpose of this study was to elucidate patterns of soil bacteria within and among wetlands by developing diversity profiles from high-throughput sequencing data, link functional gene copy number of nitrogen cycling genes to measured nutrient flux rates collected from flow-through incubation cores, and predict nutrient flux using microbial assemblage composition. Soil microbial assemblages showed fine-scale turnover in soil cores collected across the topsoil horizon (0–5 cm; top vs bottom partitions) and were structured by restoration practices on the easements (tree planting, shallow water, remnant forest). Connections between soil assemblage composition, functional gene copy number, and nutrient flux rates show the potential for soil bacterial assemblages to be used as bioindicators for nutrient cycling on the landscape. In addition, the predictive accuracy of flux rates was improved when implementing deep learning models that paired connected samples across time.