Suchergebnisse

Abstract
Gender and ethnicity biases are pervasive across many societal domains including politics, employment, and medicine. Such biases will facilitate inequalities until they are revealed and mitigated at scale. To this end, over 1.8 million caregiver notes (502 million words) from a large US hospital were evaluated with natural language processing techniques in search of gender and ethnicity bias indicators. Consistent with nonlinguistic evidence of bias in medicine, physicians focused more on the emotions of women compared to men and focused more on the scientific and bodily diagnoses of men compared to women. Content patterns were relatively consistent across genders. Physicians also attended to fewer emotions for Black/African and Asian patients compared to White patients, and physicians demonstrated the greatest need to work through diagnoses for Black/African women compared to other patients. Content disparities were clearer across ethnicities, as physicians focused less on the pain of Black/African and Asian patients compared to White patients in their critical care notes. This research provides evidence of gender and ethnicity biases in medicine as communicated by physicians in the field and requires the critical examination of institutions that perpetuate bias in social systems.

Abstract
The trade-off between short-term success and long-term sustainability is a common subject of great importance both in the biological evolution of organisms and in the economic activities of human beings. In evolutionary biology, bet-hedging theories have described it as the trade-off between the (within-generation) arithmetic mean fitness and the (between-generation) geometric mean fitness of a genotype. Accordingly, bet-hedging strategies observed in various organisms are regarded as optimizing the geometric mean fitness. To increase the geometric mean fitness signifies to suppress the between-generation variance in the mean fitness. Thus, this view is consistent with mean-variance portfolio analysis in which the standard deviation of a portfolio is regarded as a measure of risk. In the present study, we provide yet another measure of long-term sustainability, which is based on minimization of the probability of extinction/bankruptcy that randomly varying population/asset size after a long time becomes less than a certain small value. We present results for representative examples to show that the present criterion gives a qualitatively similar but quantitatively different prediction from the traditional ones. In particular, we emphasize that maximizing survival probability (i.e. minimizing extinction probability) is equivalent neither to maximizing geometric mean fitness nor to minimizing variance in mean fitness, while these three are consistently related to each other.

Abstract
The acquisition of new hosts is a fundamental mechanism by which parasitic organisms expand their host range and perpetuate themselves on an evolutionary scale. Among pathogens, viruses, due to their speed of evolution, are particularly efficient in producing new emergence events. However, even though these phenomena are particularly important to the human species and therefore specifically studied, the processes of virus emergence in a new host species are very complex and difficult to comprehend in their entirety. In order to provide a structured framework for understanding emergence in a species (including humans), a comprehensive qualitative model is an indispensable cornerstone. This model explicitly describes all the stages necessary for a virus circulating in the wild to come to the crossing of the epidemic threshold. We have therefore developed a complete descriptive model explaining all the steps necessary for a virus circulating in host populations to emerge in a new species. This description of the parameters presiding over the emergence of a new virus allows us to understand their nature and importance in the emergence process.

Abstract
Containing the COVID-19 pandemic will confer global benefits that greatly exceed the costs but effective solutions require the redistribution of vaccines, technology, and other scarce resources from high-income to low-income countries. The United States has played a central role in coordinating responses to previous global health challenges, and its policy choices in the current pandemic will have a far-reaching impact on the rest of the world. Yet little is known about domestic support for international recovery efforts. We use a series of conjoint and persuasive messaging experiments, fielded on two national surveys of the US adult population (N = 5,965), to study mass support for international redistribution. We find clear evidence that the general population strongly supports allocating vaccines to own-country recipients before others. But despite this "vaccine nationalism," Americans are also willing to support the US government playing a major role in global pandemic recovery efforts, provided policymakers forge international agreements that ensure moderate domestic costs, burden-sharing with other countries, and priority for certain types of resources, such as domestically manufactured vaccines and patent buyouts. Finally, we test five different persuasive messaging strategies and find that emphasizing the relatively low costs and large economic benefits of global vaccination is the most promising means of increasing domestic support for international redistribution. Overall, our results demonstrate that policymakers can secure broad public support for costly international cooperation by crafting responses aligned with the economic interests of the United States.

Abstract
Heterosis describes the phenomenon, whereby a hybrid population has higher fitness than an inbred population, which has previously been explained by either Mendelian dominance or overdominance under the general assumption of a simple genotype–phenotype relationship. However, recent studies have demonstrated that genes interact through a complex gene regulatory network (GRN). Furthermore, phenotypic variance is reportedly lower for heterozygotes, and the origin of such variance-related heterosis remains elusive. Therefore, a theoretical analysis linking heterosis to GRN evolution and stochastic gene expression dynamics is required. Here, we investigated heterosis related to fitness and phenotypic variance in a system with interacting genes by numerically evolving diploid GRNs. According to the results, the heterozygote population exhibited higher fitness than the homozygote population, indicating fitness-related heterosis resulting from evolution. In addition, the heterozygote population exhibited lower noise-related phenotypic variance in expression levels than the homozygous population, implying that the heterozygote population is more robust to noise. Furthermore, the distribution of the ratio of heterozygote phenotypic variance to homozygote phenotypic variance exhibited quantitative similarity with previous experimental results. By applying dominance and differential gene expression rather than only a single gene expression model, we confirmed the correlation between heterosis and differential gene expression. We explain our results by proposing that the convex high-fitness region is evolutionarily shaped in the genetic space to gain noise robustness under genetic mixing through sexual reproduction. These results provide new insights into the effects of GRNs on variance-related heterosis and differential gene expression.

Abstract
The effects of socioeconomic position (SEP) across life course accumulate and produce visible health inequalities between different socioeconomic groups. Yet, it is not well-understood how the experience of intergenerational income mobility between origin and destination SEP, per se, affects health outcomes. We use data from the National Longitudinal Study of Adolescent to Adult Health collected in the United States with the outcome measure of cardiometabolic risk (CMR) constructed from data on LDL Cholesterol, Glucose MG/DL, C-reactive protein, systolic and diastolic blood pressure, and resting heart rate. Intergenerational income mobility is estimated as the difference between Waves 1 and 5 income quintiles. Diagonal reference models are used to test if intergenerational income mobility, net of origin and destination income quintile effects, is associated with CMR. We find that individuals in the lowest and the highest income quintiles have, respectively, the highest and the lowest CMR; both origin and destination income quintiles are equally important; there are no significant overall income mobility effects for different gender and race/ethnicity groups, but downward income mobility has negative health implications for individuals with poor initial health. We conclude that downward income mobility can increase inequalities in CMR in the United States by worsening the health of those who had poor health before their mobility experiences.

Abstract
Data Science can be used to address racial health inequities. However, a wealth of scholarship has shown that there are many ethical challenges with using Data Science to address social problems. To develop a Data Science focused on racial health equity, we need the data, methods, application, and communication approaches to be antiracist and focused on serving minoritized groups that have long-standing worse health indicators than majority groups. In this perspective, we propose eight tenets that could shape a Data Science for Racial Health Equity research framework.

AbstractNeural, physiological, and behavioral signals synchronize between human subjects in a variety of settings. Multiple hypotheses have been proposed to explain this interpersonal synchrony, but there is no clarity under which conditions it arises, for which signals, or whether there is a common underlying mechanism. We hypothesized that cognitive processing of a shared stimulus is the source of synchrony between subjects, measured here as intersubject correlation (ISC). To test this, we presented informative videos to participants in an attentive and distracted condition and subsequently measured information recall. ISC was observed for electro-encephalography, gaze position, pupil size, and heart rate, but not respiration and head movements. The strength of correlation was co-modulated in the different signals, changed with attentional state, and predicted subsequent recall of information presented in the videos. There was robust within-subject coupling between brain, heart, and eyes, but not respiration or head movements. The results suggest that ISC is the result of effective cognitive processing, and thus emerges only for those signals that exhibit a robust brain–body connection. While physiological and behavioral fluctuations may be driven by multiple features of the stimulus, correlation with other individuals is co-modulated by the level of attentional engagement with the stimulus.

Abstract
How can behavioral insights best be leveraged to solve pressing policy challenges? Because research studies are typically designed to test the validity of a particular idea, surprisingly little is known about the relative efficacy of different approaches to changing behavior in any given policy context. We discuss megastudies as a research approach that can surmount this and other obstacles to developing optimal behaviorally informed policy interventions. We define a megastudy as "a massive field experiment in which many different treatments are tested synchronously in one large sample using a common, objectively measured outcome." We summarize this apples-to-apples approach to research and lay out recommendations, limitations, and promising future directions for scholars who might want to conduct or evaluate megastudies.

Abstract
There has been a sea change in the scientific world, advanced even more rapidly by the recent compounded public crises. Accelerated discovery, and impact from such discoveries have come from convergence approaches across disciplines, sectors, institutions, and the multiple communities seeking the common goal of innovations that transform. The classic simultaneous pursuit of fundamental understanding and application has been termed Pasteur's quadrant, where use-inspired basic research occurs. In the classic schematic developed by Donald Stokes, three quadrants represent research approaches using a 2D plane in which the vertical dimension represents the quest for understanding (basic research) and the horizontal dimension represents the consideration of use (applied research). The three outer quadrants are Bohr's (pure basic research), Edison's (pure applied research), and Pasteur's (use-inspired basic research). Viewing each of these axes as a continuum, we label the previously unnamed but contributory cell as the Innominate quadrant, where a nonzero amount of discovery and applied research also has value in generating scientific tools, novel processes or products that inform the other quadrants. More importantly, a reimagined Pasteur's quadrant schema shows a third dimension of Transformations over Time, occurring through a continuous fluid interchange among the quadrants. Transformative innovations may originate from any single quadrant. While work in Pasteur's quadrant has been shown to be highly productive, a dynamic fluid interchange among the quadrants is often involved and generates transformative advances at a faster rate. This should inform how we fund science, engineering, and medicine and educate the next generation of innovators.

Abstract
We report a biophysical mechanism, termed cryocampsis (Greek cryo-, cold, + campsis, bending), that helps northern shrubs bend downward under a snow load. Subfreezing temperatures substantially increase the downward bending of cantilever-loaded branches of these shrubs, while allowing them to recover their summer elevation after thawing and becoming unloaded. This is counterintuitive, because biological materials (including branches that show cryocampsis) generally become stiffer when frozen, so should flex less, rather than more, under a given bending load. Cryocampsis involves straining of the cell walls of a branch's xylem (wood), and depends upon the branch being hydrated. Among woody species tested, cryocampsis occurs in almost all Arctic, some boreal, only a few temperate and Mediterranean, and no tropical woody species that we have tested. It helps cold-winter climate shrubs reversibly get, and stay, below the snow surface, sheltering them from winter weather and predation hazards. This should be advantageous, because Arctic shrub bud winter mortality significantly increases if their shoots are forcibly kept above the snow surface. Our observations reveal a physically surprising behavior of biological materials at subfreezing temperatures, and a previously unrecognized mechanism of woody plant adaptation to cold-winter climates. We suggest that cryocampsis' mechanism involves the movement of water between cell wall matrix polymers and cell lumens during freezing, analogous to that of frost-heave in soils or rocks.

AbstractThe properties of random Boolean networks have been investigated extensively as models of regulation in biological systems. However, the Boolean functions (BFs) specifying the associated logical update rules should not be expected to be random. In this contribution, we focus on biologically meaningful types of BFs, and perform a systematic study of their preponderance in a compilation of 2,687 functions extracted from published models. A surprising feature is that most of these BFs have odd "bias", that is they produce "on" outputs for a total number of input combinations that is odd. Upon further analysis, we are able to explain this observation, along with the enrichment of read-once functions (RoFs) and its nested canalyzing functions (NCFs) subset, in terms of 2 complexity measures: Boolean complexity based on string lengths in formal logic, which is yet unexplored in biological contexts, and the so-called average sensitivity. RoFs minimize Boolean complexity and all such functions have odd bias. Furthermore, NCFs minimize not only the Boolean complexity but also the average sensitivity. These results reveal the importance of minimum complexity in the regulatory logic of biological networks.

Abstract
Mutations in nonstructural protein 3 (nsp3) and nsp4 of SARS-CoV-2, presumably induced by the asthma drug ciclesonide (which also has anti-SARS-CoV-2 activity), were counted 5,851 cases in the GISAID EpiCoV genome database. Sporadic occurrence of mutants not linked to each other in the phylogenetic tree were identified at least 88 times; of which, 58 had one or more descendants in the same branch. Five of these had spread to more than 100 cases, and one had expanded to 4,748 cases, suggesting the mutations are frequent, selected in individual patients, and transmitted to form clusters of cases. Clinical trials of ciclesonide as a treatment for COVID-19 are the presumed cause of the frequent occurrence of mutations between 2020 June and 2021 November. In addition, because ciclesonide is a common treatment for asthma, it can drive mutations in asthmatics suffering from COVID-19. Ciclesonide-resistant mutations, which have unpredictable effects in humans, are likely to continue to emerge because SARS-CoV-2 remains prevalent globally.

Abstract
Bacterial community structure can change rapidly across short spatial and temporal scales as environmental conditions vary, but the mechanisms underlying those changes are still poorly understood. Here, we assessed how a lake microbial community assembles by following its reorganization from the main tributary, which, when flowing into the lake, first traverses an extensive macrophyte-dominated vegetated habitat, before reaching the open water. Environmental conditions in the vegetated habitat changed drastically compared to both river and lake waters and represented a strong environmental gradient for the incoming bacteria. We used amplicon sequencing of the 16S rRNA gene and transcript to reconstruct the shifts in relative abundance of individual taxa and link this to their pattern in activity (here assessed with RNA:DNA ratios). Our results indicate that major shifts in relative abundance were restricted mostly to rare taxa (<0.1% of relative abundance), which seemed more responsive to environmental changes. Dominant taxa (>1% of relative abundance), on the other hand, traversed the gradient mostly unchanged with relatively low and stable RNA:DNA ratios. We also identified a high level of local recruitment and a seedbank of taxa capable of activating/inactivating, but these were almost exclusively associated with the rare biosphere. Our results suggest a scenario where the lake community results from a reshuffling of the rank abundance structure within the incoming rare biosphere, driven by selection and growth, and that numerical dominance is not a synonym of activity, growth rate, or environmental selection, but rather reflect mass effects structuring these freshwater bacterial communities.

Abstract
Across the tree of life, female animals share biological characteristics that place them at risk for similar diseases and disorders. Greater awareness of these shared vulnerabilities can accelerate insight and innovation in women's health. We present a broadly comparative approach to female health that can inform issues ranging from mammary, ovarian, and endometrial cancer to preeclampsia, osteoporosis, and infertility. Our focus on female health highlights the interdependence of human, animal, and environmental health. As the boundaries between human and animal environments become blurred, female animals across species are exposed to increasingly similar environmental hazards. As such, the health of female animals has unprecedented relevance to the field of woman's health. Expanding surveillance of animal populations beyond zoonoses to include noncommunicable diseases can strengthen women's health prevention efforts as environmental factors are increasingly implicated in human mortality. The physiology of nonhuman females can also spark innovation in women's health. There is growing interest in those species of which the females appear to have a level of resistance to pathologies that claim millions of human lives every year. These physiologic adaptations highlight the importance of biodiversity to human health. Insights at the intersection of women's health and planetary health can be a rich source of innovations benefitting the health of all animals across the tree of life.