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Urological malignancy (UM) is among the leading threats to health care worldwide. Recent years have seen much investment in fundamental UM research, including mechanistic investigation, early diagnosis, immunotherapy, and nanomedicine. However, the results are not fully satisfactory. Bioprinted research models (BRMs) with programmed spatial structures and functions can serve as powerful research tools and are likely to disrupt traditional UM research paradigms. Herein, a comprehensive review of BRMs of UM is presented. It begins with a brief introduction and comparison of existing UM research models, emphasizing the advantages of BRMs, such as modeling real tissues and organs. Six kinds of mainstream bioprinting techniques used to fabricate such BRMs are summarized with examples. Thereafter, research advances in the applications of UM BRMs, such as culturing tumor spheroids and organoids, modeling cancer metastasis, mimicking the tumor microenvironment, constructing organ chips for drug screening, and isolating circulating tumor cells, are comprehensively discussed. At the end of this review, current challenges and future development directions of BRMs and UM are highlighted from the perspective of interdisciplinary science.

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Wallacea-the meeting point between the Asian and Australian fauna-is one of the world's largest centers of endemism. Twenty-three million years of complex geological history have given rise to a living laboratory for the study of evolution and biodiversity, highly vulnerable to anthropogenic pressures. In the present article, we review the historic and contemporary processes shaping Wallacea's biodiversity and explore ways to conserve its unique ecosystems. Although remoteness has spared many Wallacean islands from the severe overexploitation that characterizes many tropical regions, industrial-scale expansion of agriculture, mining, aquaculture and fisheries is damaging terrestrial and aquatic ecosystems, denuding endemics from communities, and threatening a long-term legacy of impoverished human populations. An impending biodiversity catastrophe demands collaborative actions to improve community-based management, minimize environmental impacts, monitor threatened species, and reduce wildlife trade. Securing a positive future for Wallacea's imperiled ecosystems requires a fundamental shift away from managing marine and terrestrial realms independently.

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Objectives: We measure the impacts of an intersectoral intervention tackling adolescent substance use implemented between 2017 and 2019 in a tri-border region of Brazil, Paraguay, and Argentina. Methods: The intervention involved 23 institutions from different sectors and 880 adolescents, equally split between randomly selected treatment and control classes across institutions. Treatment group students were involved in the co-development of activities to tackle substance use within their institutions. Both treatment and control group students benefited from the activities developed and implemented from the second year of the intervention. We use difference-in-differences models to measure the impacts of participation in the co-development of the activities on alcohol, tobacco, and cannabis consumption. Results: Adolescents involved in the co-development of activities are 8 pp less likely to consume tobacco and cannabis, and 13 pp less likely to consume alcohol (p < 0.01), compared to those who only participate in the activities. Among cannabis users, frequent consumption is also reduced by the intervention. Peer frequency of consumption is strongly associated with individual consumption. Conclusion: Co-development of activities by the subjects themselves can be key to decreasing substance use in this very crucial stage of life, especially if the institutions and the implementers are familiar with the area and subjects of the intervention.

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Because biodiversity loss has largely been attributed to human actions, people, particularly those in the Global South, are regularly depicted as threats to conservation. This context has facilitated rapid growth in green militarization, with fierce crackdowns against real or perceived environmental offenders. We designed an undergraduate course to assess student perspectives on biodiversity conservation and social justice and positioned those students to contribute to a human heritage-centered conservation (HHCC) initiative situated in Uganda. We evaluated changes in perspectives using pre- and postcourse surveys and reflection instruments. Although the students started the course prioritizing biodiversity conservation, even when it was costly to human well-being, by the end of the course, they were recognizing and remarking on the central importance of social justice within conservation. We present a framework for further integration of HHCC approaches into higher education courses so as to conserve the integrity of coupled human and natural systems globally.

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Data science is a newly-formed and, as yet, loosely-defined discipline that has nonetheless emerged as a critical component of successful scientific research. We seek to provide an understanding of the term "data science," particularly as it relates to public health; to identify ways that data science methods can strengthen public health research; to propose ways to strengthen education for public health data science; and to discuss issues in data science that may benefit from a public health perspective.

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While no one denies that science depends on epistemic values, many philosophers of science have wrestled with the appropriate role of non-epistemic values, such as social, ethical, and political values. Recently, philosophers of science have overwhelmingly accepted that non-epistemic values should play a legitimate role in science. The recent philosophical debate has shifted from the value-free ideal in science to questions about how science should incorporate non-epistemic values. This article engages with such questions through an exploration of the environmental sciences. These sciences are a mosaic of diverse fields characterized by interdisciplinarity, problem-orientation, policy-directedness, and ubiquitous non-epistemic values. This article addresses a frequently voiced concern about many environmental science practices: that they 'crowd out' or displace significant non-epistemic values by either (1) entailing some non-epistemic values, rather than others, or by (2) obscuring discussion of non-epistemic values altogether. With three detailed case studies - monetizing nature, nature-society dualism, and ecosystem health - we show that the alleged problem of crowding out emerges from active debates within the environmental sciences. In each case, critics charge that the scientific practice in question displaces non-epistemic values in at least one of the two senses distinguished above. We show that crowding out is neither necessary nor always harmful when it occurs. However, we do see these putative objections to the application of environmental science as teaching valuable lessons about what matters for successful environmental science, all things considered. Given the significant role that many environmental scientists see for non-epistemic values in their fields, we argue that these cases motivate lessons about the importance of value-flexibility (that practices can accommodate a plurality of non-epistemic values), transparency about value-based decisions that inform practice, and environmental pragmatism.

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Ecological and evolutionary processes govern the fitness, propagation, and interactions of organisms through space and time, and viruses are no exception. While coronavirus disease 2019 (COVID-19) research has primarily emphasized virological, clinical, and epidemiological perspectives, crucial aspects of the pandemic are fundamentally ecological or evolutionary. Here, we highlight five conceptual domains of ecology and evolution - invasion, consumer-resource interactions, spatial ecology, diversity, and adaptation - that illuminate (sometimes unexpectedly) the emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We describe the applications of these concepts across levels of biological organization and spatial scales, including within individual hosts, host populations, and multispecies communities. Together, these perspectives illustrate the integrative power of ecological and evolutionary ideas and highlight the benefits of interdisciplinary thinking for understanding emerging viruses.

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Resilient communities are less affected by, and recover faster from, natural disasters. To be resilient in rapidly changing contemporary environments subject to the effects of complex factors such as climate change and urbanization, communities must effectively and efficiently adapt to new conditions to minimize future risks. To develop resilience, the hazards to which the community is exposed and vulnerable (i.e., future hurricanes, subsidence, salt water intrusion) must be accurately assessed, the systems (i.e., natural, built, and social) must be well understood, and the community must be engaged in the proactive planning and priority setting process. An approach to building resilience that utilizes the adaptive capacity of planning highlights opportunities to work collaboratively across disciplines to incorporate models and data from different disciplines to reduce uncertainty. We present one interdisciplinary group's approach to addressing challenges to building resilience through proactive planning, including: (1) characterizing hazards more accurately; (2) improving understanding of the vulnerability of natural (e.g., climate and infrastructure) systems subject to hazards; and (3) capturing potential synergies from interactions between planning and policies that govern decisions about the design of human settlements in hazardous areas.

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The use of artificial intelligence (AI) in a variety of research fields is speeding up multiple digital revolutions, from shifting paradigms in healthcare, precision medicine and wearable sensing, to public services and education offered to the masses around the world, to future cities made optimally efficient by autonomous driving. When a revolution happens, the consequences are not obvious straight away, and to date, there is no uniformly adapted framework to guide AI research to ensure a sustainable societal transition. To answer this need, here we analyze three key challenges to interdisciplinary AI research, and deliver three broad conclusions: 1) future development of AI should not only impact other scientific domains but should also take inspiration and benefit from other fields of science, 2) AI research must be accompanied by decision explainability, dataset bias transparency as well as development of evaluation methodologies and creation of regulatory agencies to ensure responsibility, and 3) AI education should receive more attention, efforts and innovation from the educational and scientific communities. Our analysis is of interest not only to AI practitioners but also to other researchers and the general public as it offers ways to guide the emerging collaborations and interactions toward the most fruitful outcomes.

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Drivers of Late Quaternary megafaunal extinctions are relevant to modern conservation policy in a world of growing human population density, climate change, and faunal decline. Traditional debates tend toward global solutions, blaming either dramatic climate change or dispersals of Homo sapiens to new regions. Inherent limitations to archaeological and paleontological data sets often require reliance on scant, poorly resolved lines of evidence. However, recent developments in scientific technologies allow for more local, context-specific approaches. In the present article, we highlight how developments in five such methodologies (radiocarbon approaches, stable isotope analysis, ancient DNA, ancient proteomics, microscopy) have helped drive detailed analysis of specific megafaunal species, their particular ecological settings, and responses to new competitors or predators, climate change, and other external phenomena. The detailed case studies of faunal community composition, extinction chronologies, and demographic trends enabled by these methods examine megafaunal extinctions at scales appropriate for practical understanding of threats against particular species in their habitats today.

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Finding better approaches to bridge field and laboratory primate research was identified as an important goal in a recent (2017) member survey of the American Society of Primatologists. Collaborative field-captive research was identified by >60% of respondents as somewhat or very underrepresented in the Society. In this introductory essay for a special section of American Journal of Primatology, I review commonalities and differences in the papers that were requested from field-captive primate collaborative teams. Each team approached important primate biology or welfare problems from different perspectives. The five commentaries in this section addressed how the collaborations began, scientific benefits that accrued, and insights or challenges that researchers faced in the collaboration. Despite the fact that the specific fields of inquiry were different (conservation genetics, chimpanzee captive welfare, environmental physiology, feeding biology, and reproductive physiology), the commentaries converged on the concept that an intentional, interdisciplinary approach, that included field observations and experiments informed by laboratory expertise, were essential to achieving innovative results.

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We develop a transdisciplinary deliberative model that moves beyond traditional scientific collaborations to include nonscientists in designing complexity-oriented research. We use the case of declining honey bee health as an exemplar of complex real-world problems requiring cross-disciplinary intervention. Honey bees are important pollinators of the fruits and vegetables we eat. In recent years, these insects have been dying at alarming rates. To prompt the reorientation of research toward the complex reality in which bees face multiple challenges, we came together as a group, including beekeepers, farmers, and scientists. Over a 2-year period, we deliberated about how to study the problem of honey bee deaths and conducted field experiments with bee colonies. We show trust and authority to be crucial factors shaping such collaborative research, and we offer a model for structuring collaboration that brings scientists and nonscientists together with the key objects and places of their shared concerns across time.

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Interdisciplinary research is increasingly called upon to find solutions to complex sustainability problems, yet co-creating usable knowledge can be challenging. This article offers broad lessons for conducting interdisciplinary science from the South Florida Water, Sustainability, and Climate Project (SFWSC), a 5-year project funded by the U.S. National Science Foundation (NSF). The goal was to develop a holistic decision-making framework to improve understanding of the complex natural-social system of South Florida water allocation and its threats from climate change, including sea level rise, using a water resources optimization model as an integration mechanism. The SFWSC project faced several challenges, including uncertainty with tasks, high task interdependence, and ensuring communication among geographically dispersed members. Our hypothesis was that adaptive techniques would help overcome these challenges and maintain scientific rigor as research evolved. By systematically evaluating the interdisciplinary management approach throughout the project, we learned that integration can be supported by a three-pronged approach: (1) Build a well-defined team and leadership structure for collaboration across geographic distance and disciplines, ensuring adequate coordination funding, encouraging cross-pollination, and allowing team structure to adapt; (2) intentionally design a process and structure for facilitating collaboration, creating mechanisms for routine analysis, and incorporating collaboration tools that foster communication; and (3) support integration within the scientific framework, by using a shared research output, and encouraging team members to adapt when facing unanticipated constraints. These lessons contribute to the international body of knowledge on interdisciplinary research and can assist teams attempting to develop sustainable solutions in complex natural-social systems.

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Sustainability challenges for nature and people are complex and interconnected, such that effective solutions require approaches and a common theory of change that bridge disparate disciplines and sectors. Causal chains offer promising approaches to achieving an integrated understanding of how actions affect ecosystems, the goods and services they provide, and ultimately, human well-being. Although causal chains and their variants are common tools across disciplines, their use remains highly inconsistent, limiting their ability to support and create a shared evidence base for joint actions. In this article, we present the foundational concepts and guidance of causal chains linking disciplines and sectors that do not often intersect to elucidate the effects of actions on ecosystems and society. We further discuss considerations for establishing and implementing causal chains, including nonlinearity, trade-offs and synergies, heterogeneity, scale, and confounding factors. Finally, we highlight the science, practice, and policy implications of causal chains to address real-world linked human-nature challenges.

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To a large extent, the pursuit of science takes place in universities. In this essay, I ask the following questions. Supposing there were no universities, and that all the knowledge mankind has ever collected and generated is somehow accessible, would we invent universities to make this knowledge available to address the problems humanity faces? What should those universities perform, and what role would science play in such universities? To look for answers to those questions, I consider the nature of the problems dealt with by science, the knowledge needed to address those problems, the gap between the two, the need for interdisciplinarity and the need to educate the leaders of the future, and finally, the boundaries of scientific knowledge.

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Lars Sundstrom is Director of Enterprise and Translation at the West of England Academic Health Sciences Network [1] (UK), a Professor of Practice in Translational Medicine and Co-Director of the Elizabeth Blackwell Institute for Health Research at Bristol University [2] (UK), and an honorary Professor of Medicine at Cardiff University (UK). He has extensive experience in translational medicine and clinical neurosciences, holding positions at several eminent universities. He has also held executive and board-level positions at several SMEs, developing new therapeutics for neurological conditions and tools for drug discovery. He has also been an advisor to several UK and local government task forces and to the European Commission and the European Federation of Pharmaceutical Industry Associations. He was a founding member of the European Brain Council in Brussels, and set up the Severnside Alliance for Translational Research, developing a regional network partnership to link clinical and basic scientists. He was also involved in the creation of Health Research Wales.

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The sustainable use of forests constitutes one of the great challenges for the future due to forests' large spatial coverage, long-term planning horizons and inclusion of many ecosystem services. The mission of the Future Forests programme is to provide a scientifically robust knowledge base for sustainable governance and management of forests preparing for a future characterized by globalization and climate change. In this introduction to the Special Issue, we describe the interdisciplinary science approach developed in close collaboration with actors in the Future Forests programme, and discuss the potential impacts of this science on society. In addition, we introduce the 13 scientific articles and present results produced by the programme.

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Anciently introduced species can be confounded with native species because introduction pre-dates the first species inventories or because of the loss of the collective memory of the introductions. The term 'cryptogenic species' denotes species of unknown or unclear status (native versus non-native) in a given territory, and disciplinary approaches are often insufficient for solving their true status. Here, we follow an integrative, multidisciplinary approach to solve the status of a cryptogenic species, proposing that building on evidence from multiple disciplines can produce robust and clarifying insights. We undertook an exhaustive review of information on a putatively native crayfish (Austropotamobius italicus) in Spain. The reviewed information included taxonomy, genetics and phylogeography, history, archaeology, linguistics, biogeography, ecology, symbiotic organisms and even gastronomy and pharmacy. The knowledge produced by different scientific disciplines converges to indicate that A. italicus is a non-native species in Spain. Historical documents even identify the first introduction event: crayfish were shipped from Italy to Spain in 1588 as a diplomatic gift from Francesco I de' Medici to King Philip II of Spain. Previous discussions on the status of A. italicus focussed on inconclusive and often confusing genetic results and excluded the rich and clarifying evidence available from other approaches and disciplines. Interdisciplinarity is an often-invoked but rarely implemented practice in an academic environment that increasingly promotes narrow-focussed specialization. Our review shows that the integration of disciplines can surpass disciplinary approaches in solving scientific controversies. Our results have straightforward implications for strategies to conserve biological diversity in Spain and Europe, urging a debate on the appropriateness of devoting conservation efforts to non-native species.

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Multiinstitutional research collaborations now form the most rapid and productive project execution structures in the health sciences. Effective adoption of a multidisciplinary team research approach is widely accepted as one mechanism enabling rapid translation of new discoveries into interventions in human health. Although the impact of successful team-based approaches facilitating innovation has been well-documented, its utility for training a new generation of scientists has not been thoroughly investigated. We describe the characteristics of how multidisciplinary translational teams (MTTs) promote career development of translational research scholars through competency building, interprofessional integration, and team-based mentoring approaches. Exploratory longitudinal and outcome assessments from our experience show that MTT membership had a positive effect on the development of translational research competencies, as determined by a self-report survey of 32 scholars. We also observed that all trainees produced a large number of collaborative publications that appeared to be associated with their CTSA association and participation with MTTs. We conclude that the MTT model provides a unique training environment for translational and team-based learning activities, for investigators at early stages of career development.

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The importance of transdisciplinary collaboration is growing, though not much is known about how to measure collaboration patterns. The purpose of this paper is to present multiple ways of mapping and evaluating the growth of cross-disciplinary partnerships over time. Social network analysis was used to examine the impact of a Clinical and Translational Science Award (CTSA) on collaboration patterns. Grant submissions from 2007 through 2010 and publications from 2007 through 2011 of Institute of Clinical and Translational Sciences (ICTS) members were examined. A Cohort Model examining the first-year ICTS members demonstrated an overall increase in collaborations on grants and publications, as well as an increase in cross-discipline collaboration as compared to within-discipline. A Growth Model that included additional members over time demonstrated the same pattern for grant submissions, but a decrease in cross-discipline collaboration as compared to within-discipline collaboration for publications. ICTS members generally became more cross-disciplinary in their collaborations during the CTSA. The exception of publications for the Growth Model may be due to the time lag between funding and publication, as well as pressure for younger scientists to publish in their own fields. Network analysis serves as a valuable tool for evaluating changes in scientific collaboration.

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