The Master Observational Trial: A New Class of Master Protocol to Advance Precision Medicine.

This commentary introduces a new clinical trial construct, the Master Observational Trial (MOT), which hybridizes the power of molecularly based master interventional protocols with the breadth of real-world data. The MOT provides a clinical venue to allow molecular medicine to rapidly advance, answers questions that traditional interventional trials generally do not address, and seamlessly integrates with interventional trials in both diagnostic and therapeutic arenas. The result is a more comprehensive data collection ecosystem in precision medicine.

Rewards and dangers of regulatory innovation.

Adaptive evolution often involves structural variation affecting genes or cis-regulatory changes that engender novel and favorable gain-of-function gene regulation. Such mutation could result in a favorable dominant trait. At the same time, the gene product could be dosage sensitive if its change in concentration disrupts another trait. As a result, the mutant allele would display dosage-sensitive pleiotropy (DSP). By minimizing imbalance while conserving the favorable dominant effect, heterozygosity can increase fitness and result in heterosis. The properties of these alleles are consistent with evidence from multiple studies that indicate increased fitness of heterozygous regulatory mutations. DSP can help explain mysterious properties of heterosis as well as other effects of hybridization.

The impact of US-China tensions on US science: Evidence from the NIH investigations.

Amid the discourse on foreign influence investigations in research, this study examines the impact of NIH-initiated investigations starting in 2018 on U.S. scientists' productivity, focusing on those collaborating with Chinese peers. Using publication data from 2010 to 2021, we analyze over 113,000 scientists and find that investigations coincide with reduced productivity for those with China collaborations compared to those with other international collaborators, especially when accounting for publication impact. The decline is particularly pronounced in fields that received greater preinvestigation NIH funding and engaged more in U.S.-China collaborations. Indications of scientist migration and broader scientific progress implications also emerge. We also offer insights into the underlying mechanisms via qualitative interviews.

Promotional language and the adoption of innovative ideas in science.

How are the merits of innovative ideas communicated in science? Here, we conduct semantic analyses of grant application success with a focus on scientific promotional language, which may help to convey an innovative idea's originality and significance. Our analysis attempts to surmount the limitations of prior grant studies by examining the full text of tens of thousands of both funded and unfunded grants from three leading public and private funding agencies: the NIH, the NSF, and the Novo Nordisk Foundation, one of the world's largest private science funding foundations. We find a robust association between promotional language and the support and adoption of innovative ideas by funders and other scientists. First, a grant proposal's percentage of promotional language is associated with up to a doubling of the grant's probability of being funded. Second, a grant's promotional language reflects its intrinsic innovativeness. Third, the percentage of promotional language is predictive of the expected citation and productivity impact of publications that are supported by funded grants. Finally, a computer-assisted experiment that manipulates the promotional language in our data demonstrates how promotional language can communicate the merit of ideas through cognitive activation. With the incidence of promotional language in science steeply rising, and the pivotal role of grants in converting promising and aspirational ideas into solutions, our analysis provides empirical evidence that promotional language is associated with effectively communicating the merits of innovative scientific ideas.

Idea engines: Unifying innovation & obsolescence from markets & genetic evolution to science.

Innovation and obsolescence describe dynamics of ever-churning and adapting social and biological systems, concepts that encompass field-specific formulations. We formalize the connection with a reduced model of the dynamics of the "space of the possible" (e.g., technologies, mutations, theories) to which agents (e.g., firms, organisms, scientists) couple as they grow, die, and replicate. We predict three regimes: The space is finite, ever growing, or a Schumpeterian dystopia in which obsolescence drives the system to collapse. We reveal a critical boundary at which the space of the possible fluctuates dramatically in size, displaying recurrent periods of minimal and of veritable diversity. When the space is finite, corresponding to physically realizable systems, we find surprising structure. This structure predicts a taxonomy for the density of agents near and away from the innovative frontier that we compare with distributions of firm productivity, COVID diversity, and citation rates for scientific publications. Our minimal model derived from first principles aligns with empirical examples, implying a follow-the-leader dynamic in firm cost efficiency and biological evolution, whereas scientific progress reflects consensus that waits on old ideas to go obsolete. Our theory introduces a fresh and empirically testable framework for unifying innovation and obsolescence across fields.

An evolutionary innovation for mating facilitates ecological niche expansion and buffers species against climate change.

One of the drivers of life's diversification has been the emergence of "evolutionary innovations": The evolution of traits that grant access to underused ecological niches. Since ecological interactions can occur separately from mating, mating-related traits have not traditionally been considered factors in niche evolution. However, in order to persist in their environment, animals need to successfully mate just as much as they need to survive. Innovations that facilitate mating activity may therefore be an overlooked determinant of species' ecological limits. Here, we show that species' historical niches and responses to contemporary climate change are shaped by an innovation involved in mating-a waxy, ultra-violet-reflective pruinescence produced by male dragonflies. Physiological experiments in two species demonstrate that pruinescence reduces heating and water loss. Phylogenetic analyses show that pruinescence is gained after taxa begin adopting a thermohydrically stressful mating behavior. Further comparative analyses reveal that pruinose species are more likely to breed in exposed, open-canopy microhabitats. Biogeographic analyses uncover that pruinose species occupy warmer and drier regions in North America. Citizen-science observations of Pachydiplax longipennis suggest that the extent of pruinescence can be optimized to match the local conditions. Finally, temporal analyses indicate that pruinose species have been buffered against contemporary climate change. Overall, these historical and contemporary patterns show that successful mating can shape species' niche limits in the same way as growth and survival.

Coordination dynamics between fuel cell and battery technologies in the transition to clean cars.

Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry's transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry's markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms.

Modeling direct air carbon capture and storage in a 1.5 °C climate future using historical analogs.

Limiting the rise in global temperature to 1.5 °C will rely, in part, on technologies to remove CO2 from the atmosphere. However, many carbon dioxide removal (CDR) technologies are in the early stages of development, and there is limited data to inform predictions of their future adoption. Here, we present an approach to model adoption of early-stage technologies such as CDR and apply it to direct air carbon capture and storage (DACCS). Our approach combines empirical data on historical technology analogs and early adoption indicators to model a range of feasible growth pathways. We use these pathways as inputs to an integrated assessment model (the Global Change Analysis Model, GCAM) and evaluate their effects under an emissions policy to limit end-of-century temperature change to 1.5 °C. Adoption varies widely across analogs, which share different strategic similarities with DACCS. If DACCS growth mirrors high-growth analogs (e.g., solar photovoltaics), it can reach up to 4.9 GtCO2 removal by midcentury, compared to as low as 0.2 GtCO2 for low-growth analogs (e.g., natural gas pipelines). For these slower growing analogs, unabated fossil fuel generation in 2050 is reduced by 44% compared to high-growth analogs, with implications for energy investments and stranded assets. Residual emissions at the end of the century are also substantially lower (by up to 43% and 34% in transportation and industry) under lower DACCS scenarios. The large variation in growth rates observed for different analogs can also point to policy takeaways for enabling DACCS.

Resolution Pharmacology: Focus on Pro-Resolving Annexin A1 and Lipid Mediators for Therapeutic Innovation in Inflammation.

Chronic diseases that affect our society are made more complex by comorbidities and are poorly managed by the current pharmacology. While all present inflammatory etiopathogeneses, there is an unmet need for better clinical management of these diseases and their multiple symptoms. We discuss here an innovative approach based on the biology of the resolution of inflammation. Studying endogenous pro-resolving peptide and lipid mediators, how they are formed, and which target they interact with, can offer innovative options through augmenting the expression or function of pro-resolving pathways or mimicking their actions with novel targeted molecules. In all cases, resolution offers innovation for the treatment of the primary cause of a given disease and/or for the management of its comorbidities, ultimately improving patient quality of life. By implementing resolution pharmacology, we harness the whole physiology of inflammation, with the potential to bring a marked change in the management of inflammatory conditions.

A global initiative on addressing bioinformatics' grand challenges.

The Bioinformatics Grand Challenges Consortium (BGCC) is a collaborative effort to address the most pressing challenges in bioinformatics. Initially focusing on education and training, the consortium successfully defined seven key grand challenges and is actively developing actionable solutions for these challenges. Building on this foundation, the BGCC plans to broaden its focus to include additional grand challenges in emerging areas.

Evolutionary norm-breaking and extinction in the marine tropics.

Evolutionary innovations, defined as character states that transcend clade norms, are often studied in an exclusively phylogenetic context, but their distribution in time and space indicates that geography also influences the evolution of new ecological, morphological, and physiological traits. In an analysis of 99 fossillzable, norm-breaking innovations in tropical marine Neogene molluscan clades that arose uniquely in either (but not in both) the Indo-West Pacific (IWP) or Atlantic-East Pacific (AEP) realms, I show that there are far more innovations in the IWP (79%) than those in the AEP (21%). Most of the innovations are interpretable as defensive or competitive adaptations or as indicators of extreme habitat specialization. Although the innovations arose in taxonomically rich biotas, only 9% are associated with subclades comprising 10 or more species each, indicating that they contributed little to overall taxonomic richness. Compilations of extant species in 30 pantropical molluscan clades show that the IWP accounts for 71% of tropical shallow-water species, implying that the per-species incidence of norm-breaking innovations is higher there than in the AEP. Only 5% of innovations became extinct in the IWP as compared with 38% in the AEP, mirroring a similar difference in the magnitudes of Late Miocene and later taxonomic extinction in the two realms. These data imply that large-scale disruption strongly limits norm-breaking innovation. Opportunities for adaptive innovation are therefore likely to be few in today's heavily overexploited and disturbed biosphere.

The effects of local interventions on global technological change through spillovers: A modeling framework and application to the road-freight sector.

To address global sustainability challenges, (public) policy interventions are needed to induce or accelerate technological change. While most policy interventions occur on the local level, their innovation effects can spill over to other jurisdictions, potentially having global impact. These spillovers can increase or reduce the incentive for interventions. Lacking to date are computational models that capture these spillover dynamics. Here, we devise a conceptual and methodological approach to quantify ex ante the effects of local demand-side interventions on global competition between incumbent and novel technologies. We introduce two factors that moderate global spillovers-relative size of selection environments and relative innovation potential of competing technologies. Our approach incorporates both factors in a techno-economic discrete choice model that evaluates technology competition over time through endogenized technological learning. We apply this modeling framework to the case of road freight. Different demand-pull interventions and shocks are modeled to assess spillover effects. In the case of road freight, electric vehicles experience growth in most application segments but can still be accelerated substantially through public policy intervention-spillovers occur if strong public interventions are introduced in large regions or in multiple combined regions under club policy interventions. These findings are discussed in the context of club policy interventions and a modeled geopolitical shock in China. A full sensitivity analysis of model input parameters and intervention or shock dynamics reveals high model robustness. Finally, we discuss the implications of the road-freight case study as it might inform the progress of other niche technologies in transitioning sectors.

The big business of sustainable food production and consumption: Exploring the transition to alternative proteins.

A widespread sense of the unsustainability of the food system has taken hold in recent years, leading to calls for fundamental change. The role of animal agriculture is central to many of these debates, leading to interest in the possibility of a "protein transition," whereby the production and consumption of animal-derived foods is replaced with plant-based substitutes or "alternative proteins." Despite the potential sustainability implications of this transition, the developmental trajectories and transformative potential of the associated technologies remain underexplored. This article sheds light on these dynamics by addressing two questions: 1) how have alternative protein innovations developed over the past three decades, and 2) what explains their more recent acceleration? To answer these questions, the article makes an empirical analysis of four alternative protein innovations, and the partial destabilization of the animal agriculture system between 1990 and 2021, guided by the multi-level perspective. The analysis highlights an intensification in corporate engagement with alternative protein development and diffusion. This intensification is judged to be consistent with the beginnings of a wider corporate reorientation, occurring alongside a rise in pressures on the animal agriculture system, notably an increasing scientific consensus and societal awareness of the links between climate change and meat-intensive diets. The paper demonstrates how differences in technological maturity across the niche innovations have resulted in potentially transformative pressures, which are consistent with an emerging sustainability transition, manifesting differently in terms of the extent of diffusion of the alternative protein niches.

Climate change framing and innovator attention: Evidence from an email field experiment.

Drawing the attention of innovators to climate change is important for green innovation. We report an email field experiment with MIT using messages about the impact of climate change to invite innovators (SBIR grantees) to apply to a technology competition. We vary our messages on the time frame and scale of the human cost of climate change across scientifically valid scenarios. Innovator attention (clicks) is sensitive to climate change messaging. These changes in clicks also predict higher application rates. The response varies by individual characteristics such as location-based exposure to climate change risks and whether innovators have climate-related innovations. Finally, using a structural model of innovator attention, we provide estimates of the implied discount rate of time and the elasticity of attention to lives at stake.

Faculty as catalysts for training new inventors: Differential outcomes for male and female PhD students.

STEM PhDs are a critical source of human capital in the economy, contributing to commercial as well as academic science. We examine whether STEM PhD students become new inventors (file their first patent) during their doctoral training at the top 25 U.S. universities (by patenting). We find that 4% of PhDs become new inventors. However, among PhDs of faculty who are themselves top (prolific) inventors, this figure rises to 23%. These faculty train 44% of all the new inventor PhDs by copatenting with their advisees. We also explore whether new inventor PhDs are equally distributed by gender. In our university sample, the female share of new inventors is 9% points (pp) lower than the female share of PhDs. Several channels contribute to this: First, female PhDs are less likely to be trained by top inventor advisors (TIs) than male PhDs. Second, they are less likely to be trained by (the larger number of) male top inventors: The estimated gap in the female % of PhDs between female and male TIs is 7 to 9 pp. Third, female PhDs (supervised by top inventors and especially by other faculty) have a lower probability of becoming new inventors relative to their male counterparts. Notably, we find that male and female top inventors have similar rates of transforming their female advisees into new inventors at 4 to 8 pp lower (17 to 26% lower rate) than for male advisees. The gap remains at 4 pp comparing students of the same advisor and controlling for thesis topic.

Superhuman artificial intelligence can improve human decision-making by increasing novelty.

How will superhuman artificial intelligence (AI) affect human decision-making? And what will be the mechanisms behind this effect? We address these questions in a domain where AI already exceeds human performance, analyzing more than 5.8 million move decisions made by professional Go players over the past 71 y (1950 to 2021). To address the first question, we use a superhuman AI program to estimate the quality of human decisions across time, generating 58 billion counterfactual game patterns and comparing the win rates of actual human decisions with those of counterfactual AI decisions. We find that humans began to make significantly better decisions following the advent of superhuman AI. We then examine human players' strategies across time and find that novel decisions (i.e., previously unobserved moves) occurred more frequently and became associated with higher decision quality after the advent of superhuman AI. Our findings suggest that the development of superhuman AI programs may have prompted human players to break away from traditional strategies and induced them to explore novel moves, which in turn may have improved their decision-making.

Sustainability transitions in consumption-production systems.

The need for faster and deeper transitions toward more sustainable development pathways is now widely recognized. How to meet that need has been at the center of a growing body of academic research and real-world policy implementation. This paper presents our perspective on some of the most powerful insights that have emerged from this ongoing work. In particular, we highlight insights on how sustainability transitions can be usefully conceptualized, how they come about and evolve, and how they can be shaped and guided through deliberate policy interventions. Throughout the paper, we also highlight some of the many how questions that remain unresolved and on which progress would be especially helpful for the pursuit of sustainable development. Our approach to these "how" questions on sustainability transitions draws on two strands of solution-driven research and policy advice: one emerging from studies of how human societies interact with nature and the other emerging from studies of how those societies interact with their technologies. Consumption-production systems have been a focus of extensive work in both strands. To help build bridges between them, we recently brought together a cross-section of relevant scholars for a PNAS Special Feature on "Sustainability transitions in consumption-production systems." Their contributions are summarized in a companion paper we have written to introduce the Special Feature [F. W. Geels, F. Kern, W. C. Clark, Proc. Natl. Acad. Sci. U.S.A. (2023)]. We draw on that work in the Perspective we present here as well as our reading of the relevant literatures.

Two-dimensional constrained chaos and industrial revolution cycles.

Since the 1760s, at least three industrial revolutions have occurred. To explain this phenomenon, we introduce two-dimensional (2D) constrained chaos. Using a model of innovation dynamics, we show that an industrial-revolution-like technology burst, driven by investment/saving motives for R&D activities, recurs about every one hundred years if the monopolistic use of a new technology lasts about 8 y.

Diverse origins of near-identical antifreeze proteins in unrelated fish lineages provide insights into evolutionary mechanisms of new gene birth and protein sequence convergence.

Determining the origins of novel genes and the mechanisms driving the emergence of new functions is challenging yet crucial for understanding evolutionary innovations. Recently evolved fish antifreeze proteins (AFPs) offer a unique opportunity to explore these processes, particularly the near-identical type I AFP (AFPI) found in four phylogenetically divergent fish taxa. This study tested the hypothesis of protein sequence convergence beyond functional convergence in three unrelated AFPI-bearing fish lineages. Through comprehensive comparative analyses of newly sequenced genomes of winter flounder and grubby sculpin, along with available high-quality genomes of cunner and 14 other related species, the study revealed that near-identical AFPI proteins originated from distinct genetic precursors in each lineage. Each lineage independently evolved a de novo coding region for the novel ice-binding protein while repurposing fragments from their respective ancestors into potential regulatory regions, representing partial de novo origination-a process that bridges de novo gene formation and the neofunctionalization of duplicated genes. The study supports existing models of new gene origination and introduces new ones: the Innovation-Amplification-Divergence (IAD) model, where novel changes precede gene duplication; the newly proposed Duplication-Degeneration-Divergence (DDD) model, which describes new functions arising from degenerated pseudogenes; and the DDD gene fission model, where each new sibling gene differentially degenerate and renovate distinct functional domains from their parental gene. These findings highlight the diverse evolutionary pathways through which a novel functional gene with convergent sequences at the protein level can evolve across divergent species, advancing our understanding of the mechanistic intricacies in new gene formation.

Translational success of fundamental virology: a VSV-vectored Ebola vaccine.

Ebola virus disease (EVD) caused by Ebola virus (EBOV) is a severe, often fatal, hemorrhagic disease. A critical component of the public health response to curb EVD epidemics is the use of a replication-competent, recombinant vesicular stomatitis virus (rVSV)-vectored Ebola vaccine, rVSVΔG-ZEBOV-GP (ERVEBO). In this Gem, we will discuss the past and ongoing development of rVSVΔG-ZEBOV-GP, highlighting the importance of basic science and the strength of public-private partnerships to translate fundamental virology into a licensed VSV-vectored Ebola vaccine.